Solute exchange through gap junctions lessens the adverse effects of inactivating mutations in metabolite-handling genes
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Evaluation Summary:
This work shows that spontaneous mutations in cancer cells affecting metabolic pathways do not necessarily result in functional defects, as affected cells may be able to be rescued by gap junction-mediated exchange of metabolites. This is verified in three specific examples, although some of the "quantitative" methods of measuring gap junctional coupling are actually only qualitative in nature. In addition, more experiments are needed to address the effect of Cx31 and Cx43 KD. This paper is of potential interest to a broad readership in cancer biology as well as colleagues studying metabolic pathways.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)
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Abstract
Growth of cancer cells in vitro can be attenuated by genetically inactivating selected metabolic pathways. However, loss-of-function mutations in metabolic pathways are not negatively selected in human cancers, indicating that these genes are not essential in vivo. We hypothesize that spontaneous mutations in ‘metabolic genes’ will not necessarily produce functional defects because mutation-bearing cells may be rescued by metabolite exchange with neighboring wild-type cells via gap junctions. Using fluorescent substances to probe intercellular diffusion, we show that colorectal cancer (CRC) cells are coupled by gap junctions assembled from connexins, particularly Cx26. Cells with genetically inactivated components of pH regulation ( SLC9A1 ), glycolysis ( ALDOA ), or mitochondrial respiration ( NDUFS1 ) could be rescued through access to functional proteins in co-cultured wild-type cells. The effect of diffusive coupling was also observed in co-culture xenografts. Rescue was largely dependent on solute exchange via Cx26 channels, a uniformly and constitutively expressed isoform in CRCs. Due to diffusive coupling, the emergent phenotype is less heterogenous than its genotype, and thus an individual cell should not be considered as the unit under selection, at least for metabolite-handling processes. Our findings can explain why certain loss-of-function mutations in genes ascribed as ‘essential’ do not influence the growth of human cancers.
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Author Response
REVIEWER #1 (PUBLIC REVIEW):
The study by Monterisi et al. reports that loss-of-function mutations in metabolic pathways do not necessarily have a negative impact on cancer growth. The authors suggest that small solutes transferred via gap junction channels formed between wild-type cells and cells express mutants defective in metabolic pathways rescue the metabolic-deficient cancer cells. Through the examination of multiple human cell lines with several advanced means to determine gap junction coupling, Cx26 was identified as a major connexin molecule involved in medicating gap junction coupling between colorectal cancer (CRC) cells. The gene mutations of three metabolic gene mutations were investigated for major metabolic function of the cell, pH regulation, glycolysis and mitochondrial function.
Strengths: The …
Author Response
REVIEWER #1 (PUBLIC REVIEW):
The study by Monterisi et al. reports that loss-of-function mutations in metabolic pathways do not necessarily have a negative impact on cancer growth. The authors suggest that small solutes transferred via gap junction channels formed between wild-type cells and cells express mutants defective in metabolic pathways rescue the metabolic-deficient cancer cells. Through the examination of multiple human cell lines with several advanced means to determine gap junction coupling, Cx26 was identified as a major connexin molecule involved in medicating gap junction coupling between colorectal cancer (CRC) cells. The gene mutations of three metabolic gene mutations were investigated for major metabolic function of the cell, pH regulation, glycolysis and mitochondrial function.
Strengths: The paper tests a new hypothesis that the mutations that inactivate key metabolic pathways do not incur functional deficits in cancer cells expressing the mutants due to their gap junction coupling to wild type cells.
From microarray data they identified multiple connexins expressed in various CRC cells. Several advanced analyses were used to assess gap junction coupling in CRC cells including fluorescence recovery after photobleaching (FRAP). The extent of permeability at steady state was evaluated using CellTracker dyes and coupling coefficients were determined. They also used flow-cytometry to study dye transfer, which will provide a quantitative, dynamic means for study cell coupling. The data showed that knocking down Cx26 could greatly reduce diffusive exchange in most of the CRC cells tested.
The study focused on three metabolic genes, Na+/H+ exchanger NHE1, a regulator of intracellular pH, a glycolytic gene, ALDOA and mitochondrial respiration gene, NDUFS1. These genes were knocked out in the selected CRC cells highly expressing these genes. The co-culture studies were well executed with fluorescence-markers distinguishing the WT and knockout cells and well-defined readouts such as intracellular pH, media pH, glucose/lactate levels and mitochondrial O2 consumption and glycolytic acid.
The experiments in general were well designed and conducted, and the data supported the conclusions. The paper is also logically written and figures were well presented providing clear graphic illustrations.
Thank you for recognising the strengths and novelty of our findings.
Weaknesses: Although the hypothesis is innovative, no clear justification is provided that illustrates the scenario representing the clinical situation. The remaining questions include: What kind of somatic mutations in cancer cells has little impact on their growth and progression?
We have now added in vivo data (Fig 8) and revised the Introduction and Discussion to address this point. Briefly, the broader clinical relevance our findings relates to the notion of essential genes and their negative selection. We show that connexin-dependent coupling can rescue a genetic deficiency, provided the mutation-carrying cell can access wild-type neighbours for the missing function. This rescue effect is limited to processes that handle solutes that can pass via connexin channels, i.e. metabolic processes. As such, sporadic loss-of-function mutations in “essential genes” may not produce a functional deficit in human cancers. We demonstrate rescue extensively in vitro, and now in a xenograft model.
We argue that our work can explain why certain metabolic genes are essential in vitro, but not in vivo. In monolayers of mutated cells, diffusion across gap junctions cannot rescue the mutant phenotype, because there is no wild-type cell available to supply the missing function. In contrast, mutations in vivo will arise sporadically and wild-type cells are typically available to couple onto the mutation-bearing cell, providing it with functional rescue. Thus, only in the former case would the lethality of essential genes emerge.
Indeed, many notable studies have found genes of various metabolic pathways to be essential for growth in vitro. Such genes would be expected to undergo negative selection in vivo, but this is exceedingly rare according to multiple observations. By demonstrating metabolic rescue in co-cultures (i.e. a setting closer to the tumour) and (now) in xenografts, our work provides an explanation for this apparent paradox. Indeed, cells such as NDUFS1-negative SW1222 grow very, very slowly in culture compared to wild-type cells and require regular media changes to keep pH alkaline. However, coupling onto wild-type cells can rescue knock-out cells in vitro and in vivo. We argue that this finding explains why loss-of-function mutations in NDUFS1 (and similar genes) do not undergo negative selection in human tumours (despite in vitro predictions).
The three proteins selected for this study were chosen to represent very distinct types of solute-handling processes. We illustrate our point in a (new) summary figure in Fig 8.
What types of WT cells, within the tumour cells or with neighbouring normal cells? Whether the current experimental design closely recapitulates the scenario in vivo?
Indeed, we find that stromal fibroblasts may also support cancer cells via gap junctions, as this is essentially the same concept (i.e. coupling onto a cell with wild-type genes). However, we feel that expanding our present submission to fibroblasts would make the volume of data exceeding large. Also, the methods we use for fibroblasts are different, and require a full manuscript on its own. For example, there is the issue of how to control for the radically different growth rates of fibroblasts and cancer cells. We chose co-cultures of WT and genetically altered CRC cells so that the co-cultures are of the same background, with just one element changing (i.e. the metabolite-handling gene). This makes our data easy to interpret, and thus strengthens our case. Our in vitro experiments were performed on monolayers, where cells can make contacts in 2D. In vivo, these contacts will spread in all dimensions, thus connectivity is likely to be even more significant. If anything, monolayers probably under-estimate the importance of connectivity, but this preparation is more accessible for studying cell-to-cell communication.
We recognise the importance of adding in vivo data to firm our conclusions. To that end, we have analysed xenografts established from co-cultures of wild-type DLD1 and NDUFS1-KO SW1112 cells on one flank of a mouse, and Cx26-KO DLD1 and NDUFS1-KO SW1112 cells on the other flank. This experiment tested whether Cx26-dependent connections between mitochondrially-defective NDUFS1 KO SW1222 cells and respiring DLD1 cells (on left flank only) are able to stimulate growth of the former (GFP-tagged). Indeed, NDUFS1-deficient cells grew faster when rescued by Cx26-expressing DLD1 cells. In contrast, their growth decelerated when DLD1 cells were Cx26-negative. We include these experiments and their controls in Fig 8.
The readouts for co-culturing for glycolytic ALDOA and NDUFS1 knockout are only cell mass, without determining the more relevant markers, glucose/lactate and mitochondrial O2 consumption and glycolytic acid production.
Our readouts are two-fold: total biomass and the size of the genetically altered compartment of co-cultures (GFP). We can therefore follow the relative growth of KO cells, which is essential for describing their growth (dis)advantage. We appreciate other markers are informative. Indeed, we characterised KO and WT cells in terms of O2 consumption and acid production in Fig 7. However, it would not be possible to measure glucose consumption selectively in GFP-positive KO cells of a co-culture, as the assays available for this measure ensemble rates for the entire population of cells (e.g. in a single well). Nonetheless, we believe that biomass as a readout is highly relevant to cancer, and we hope the reviewer concurs with us.
The study needs to include cells without functional gap junctions like the characterized negative control RKO cells.
This is an excellent suggestion, and we have added data for RKO cells to several figures. As expected, these do not form a syncytium and cannot rescue genetic defects in co-cultured cells. New data are shown in Fig 3G-H, Fig 6-supp2 and Fig 7H, adding to existing RKO controls in Fig 2A/B. Briefly, RKO cells do not exchange CellTracker dyes in monolayers (Fig 3F/G), cannot rescue cells that are ALDOA-deficient (Fig 6-supp2), and cannot rescue NDUFS1-deficient cells (Fig 7H). We also added Cx26-KO DLD1 cells to the CellTracker experiments in Fig 3.
REVIEWER #2 (PUBLIC REVIEW):
This paper is a logical extension of the 50 year-old concept of the "bystander effect" in tumours, wherein the effects of anti-tumour chemotherapeutics extend beyond the cells that take them up due to spread through gap junctions to adjacent cells. In this case, however, the authors have creatively realized that the reverse might also occur, and that tumour cells with otherwise fatal mutations in essential metabolic pathways can be rescued by their neighbours through passage of the missing metabolites through gap junctions. This can explain why mutations in other critical pathways, such as protein synthesis and transporters, are selected against in rapidly growing tumours, but others in equally critical pathways of glycolysis, electron transport, etc. are not, despite these genes having been demonstrated to be essential in in vitro KO studies (where all cells in the plate have the critical gene knocked out). A series of elegant experiments are used to test this proposal in several colorectal cancer (CRC) cell lines using three examples - pH regulation (defective Na+/H+ exchanger NHE1), glycolysis (defective Aldolase A (ALDOA)) and oxidative phosphorylation (defective Complex 1 - NDUFS1).
Thank you for these positive comments. We have added key references to the bystander effect in the Introduction, and explain how our findings build on these milestones.
The authors first determine the levels of different Cx proteins expressed in each cell line, and determine that for most Cx26 and 31 are dominant, although come lines have a subset of cells with high Cx43 expression. They then use Cell Tracker Green to pre-label cells and use FRAP as a means to measure how well the cell population is coupled. This is a useful measurement but is significantly over-interpreted by the authors as a "permeability" in uM/min. This is not really a permeability, which requires knowledge of the concentration gradient of the permeant species, relative cell volumes, etc. Rather it is a rate of fluorescent recovery that is presumably correlated with, but not quantitatively related to, levels of coupling.
Thank you for this comment. We would like to explain why we believe our FRAP experiments are able to estimate permeability in units of um/s. The rate of recovery of a solute in a cell following its “destruction” (here, photobleaching) is given as follows:
dCcell/dt = p⋅P(Ccell-Csurround) … [1]
Where subscripts ‘cell’ and ‘surround’ refer to the cell and its neighbours. P is the permeability of the barrier between these two compartments, and p is the ratio of the surface area of the barrier (i.e. membrane) to volume of the bleached cell. Within a “bleached” cell, we measure fluorescence.
Since fluorescence (F) is proportional to concentration (C), we can substitute:
C = α⋅F
where α is a constant of proportionality. Thus, the rate of recovery (L.H.S. of equation [1]) becomes:
dC/dt = d(α⋅F)/dt = α⋅dF/dt … [2]
And the R.H.S. of equation [1] is re-written as: P⋅(Ccell-Csurround) = P⋅(α⋅Fcell-α⋅Fsurround) = α⋅P⋅ (Fcell-Fsurround) … [3]
Putting [2] and [3] together,
dFcell/dt = p⋅P⋅(Fcell-Fsurround)
Prior to photobleaching, there are no (net) gradients, thus initial Fcell and Fsurround are equal.
Thus, we can re-write the equation in terms of normalized fluorescence (f=F/F0):
dfcell/dt = p⋅P⋅(fcell-fsurround)
P can therefore be expressed as:
P = dfcell/dt / (p⋅ (fcell-fsurround))
Here, dfcell/dt is measured from the fluorescence recovery time course and fcell-fsurround is measured experimentally (in fact, bleaching in the cell is set to 50%, thus this takes the value of 0.5 by default). We can approximate the monolayer as a network of cuboidal cells. The cell’s volume is thus ‘area’ times ‘height’, and the cell’s surface (at which it contacts its neighbors) is the ‘cell’s perimeter’ times ‘height’. Thus, for the bleached cell,
p = perimeter × height / area × height = perimeter / area.
The perimeter and area can be measured from the acquired fluorescence images. Thus, we can describe permeability using data obtained from image stacks. We appreciate that this method makes certain geometrical approximations, but we believe these are not unreasonable. We explain the assumptions and calculations in Appendix 1. More information about the method is published by us in https://pubmed.ncbi.nlm.nih.gov/28368405/. Of course, we accept that these calculations are less accurate than, say, electrical conductance measurements, and to that end, we added a note of caution to the main text.
This fluorescent recovery is shown to be sensitive to siRNA KO of Cx expression, but strangely its reduction is only correlated with KD of Cx26 in the 5 cell lines examined. KD of Cx43 (in LOVO cells) and Cx31 in all 5 cell lines had no effect or in some cases seemed to increase the rate of recovery (DLD1 and SNU1235). This is a notable finding, yet the authors choose to completely ignore it and continue with Cx26 KDs in studies of specific metabolite transfers. Some discussion should be included as to why KD pf these Cxs has no effect or causes an apparent increase in coupling of the cells.
The effectiveness of GJB2 knockdown in ablating ensemble connectivity is most likely a reflection that Cx26 is likely the dominant conductance inherited from the parent epithelium. Other isoforms are expressed, but in most CRCs cells, these do not produce major coupling, as GJB2 knockdown was sufficient to uncouple many CRCs. These observations justify our choice of connexin for studying metabolic rescue functionally. These findings are also consistent with the good correlation between ensemble connectivity and GJB2 levels.
Our data show a trend that GJB3 (Cx31) KD in DLD1 and SNU1235 cells and of GJA1 (Cx43) KD in LOVO cells produce an increase in coupling. However, when analysed by hierarchical (nested) analysis, these effects are not statistically significant, and for that reason we did not elaborate on these trends in the original submission. The apparent increase in conductivity in cells treated with GJA1 or GJB3 siRNA could reflect a compensatory response to the ablation of a specific message, closer contacts between cells allowing Cx26 to strengthen its connections, or a shift away from heterotypic channels involving Cx26 and Cx31/Cx43, towards homotypic Cx26. We did not see any consistent change in the intimacy of cell-cell contacts. We now performed western blots for connexins to probe for compensatory changes (see Fig 2-supp1). In comparison to wild-type cells, expression of Cx31 was not changed by GJB2 (Cx26) or GJA1 (Cx43) knockdown in DLD1 cells. GJB2 KO DLD1 cells did not induce expression of the other major isoform, Cx43. Also, in DLD1 cells, KD of GJB3 or GJA1 did not substantially change Cx26 levels. Similarly, KD of GJB3 did not affect Cx43 levels. In GJA1-high C10 cells, KD of GJB3 did not alter Cx43 levels, although a small decrease was observed with GJB2 KD on Cx43. Also in C10 cells, KD of GJB2 and GJA1 did not induce an increase in Cx31 levels.
We agree that complex interactions between connexin genes are possible, but we feel that a molecular study of Cx gene regulation would fall outside the scope of the present manuscript. Our findings point to a prominent role of Cx26 in metabolic rescue, and to strengthen this point, we show that Cx26-negative cells that express other connexins (e.g. C10 cells or NCIH747 cells) cannot rescue ALDOA-deficient counterparts or NDUFS1-KO SW1222 cells (new data in Fig 6 and 7). We share the Reviewer’s enthusiasm about the interplay between connexins and will endeavour to study this further in the near future.
Rather than just focus on acute transfer of dye between cells, the authors develop a system using 50/50 mixes of cells labelled with two junctionally permeant dyes and measured the degree of mixing at equilibrium (48 hours). This is presented as a "coupling coefficient", but how it is calculated, and its significance is not well described, and does not correlate with the historical use of this term in the literature. Nonetheless, the studies do seem to demonstrate a good degree of equilibration, although it would have been informative to determine of the cells that do not exchange dyes express Connexins. To document that this equilibration requires gap junctions, the authors employ low density cultures, which significantly decrease dye exchange. However, in at least one cell line (SW1222) dye exchange is only reduced by <50%, indicating a very high background to this assay. This is not addressed.
Thank you for these comments. We agree that our description of the method was inadequate, and we have added the necessary information in Appendix 1. We have also added information about actual confluency and restructured the figure. We also added new data for RKO cells and DLD1-Cx26 KO cells, i.e. two negative controls (Fig 3H). We pondered about the best name for describing the numerical output of the method, and concluded that “coupling coefficient” is reasonable (provided we improve our description of it) because it is dimensionless, and like many coefficients has a finite range (here, zero to one). With further explanation, we hope this terminology is acceptable. The issue with SW1222 cells is that both low- and high-seeding densities produce clusters of cells. Even though overall cell numbers were different in high and low seeded cultures, actual connectivity within “islands” of cells remained high, hence their similar coupling coefficients (see Fig 3E). Indeed, this CRC line is unusual in this behaviour, so we only present data from the higher density.
The most compelling part of the study is the use of reporters to directly demonstrate a role of Cx26 coupling of cells to rescue cells with mutations of the three genes mentioned above when mixed with normal neighbours. This case was most convincing in the cases of ALDOA and NDUFS1, with the data for the pH regulation requiring more explanation for full understanding of the data shown (e.g. Figs 7 G and H).
Thank you for this comment. Studies of pHi regulation provide a unique opportunity to obtain single-cell resolution (unlike e.g. glycolytic assays). We took advantage of this, and therefore the figure on pHi presents a greater depth of analysis. Nonetheless, we agree the pH data need further explanation. We have expanded the text, and also added a bar plot of data on day 7, which now provides a clearer illustration of the rescue effect. This form of presentation was also adopted for ALDOA and NDUFS1 experiments in the subsequent figures.
Overall, the study does a credible job of demonstrating that Cx26 coupling of CRC cells serves to rescue cells with mutations in critically necessary metabolic pathways, presumably due to transfer of metabolites from surrounding wt cells. However, some of the results indicate this is not a simple process where all connexins behave similarly, and some effort should be made to investigate if Cx31 and 43, which do not seem to play the same roles in maintaining cell coupling as Cx26, also play any role in such metabolic rescue.
Thank you for this comment. We have addressed this by selecting three additional cell lines for study: RKO – a cell line with no major Cx expression; C10 – a cell line that expresses Cx43, but very low levels of Cx26; NCIH747 – a cell line that expresses Cx31, but low levels of Cx26. These additional experiments cover lines that are GJB2 (Cx26)-low/negative to test whether metabolic rescue is best achieved with Cx26. Our new data show that these cells are unable to rescue metabolic defects (new data provided in Fig 6H/I, Fig 7H, and Fig 6-supp2). These findings strengthen our case for a major role of Cx26, at least in CRC networks. Indeed, recent analyses by Robert Gatenby and colleagues have shown that mutations in GJB2 (Cx26) are exceedingly rare in cancer (a property not shown for other connexins genes). This is interpreted to mean that Cx26 plays a particularly prominent role, ostensibly for metabolic rescue.
REVIEWER #3 (PUBLIC REVIEW):
Strengths of the study include that it appears to be a careful and well thought out set of experiments. The analysis and treatment of multiplexed data is also sophisticated. For the most part, the work is clearly and logically described, as well as well illustrated. In general, the authors achieved their experimental goals, and the methods while not entirely new, do provide new twists and augmentations that should be useful to the field. A general weakness is that this is not entirely a new story. Instead, it is a variant of one of the oldest concepts in the field of gap junction biology i.e. "Metabolic cooperation". The term "Metabolic cooperation" (i.e., as mediated by gap junctions) was not mentioned by the authors, but it is a long-established and foundational concept in the field. Indeed, in a classic paper by Gilula and colleagues published in 1972, the experimental approach used was similar to that of the study in hand. These earlier authors showed how transformed cell lines with deficiencies in hypoxanthine metabolism can be "rescued" by "metabolic cooperation" in co-culture with metabolically competent cells via passing a gap junctional permeant molecule. This and other relevant papers were not cited. More importantly, the extant literature places the onus on the authors to explain and convince reviewers why this study is more than an incremental step.
We apologise for not quoting these important and classical references. We have now added these works to our reference list (quoted in Introduction). At the time of these seminal discoveries, Loewenstein and colleagues made a case that connexins are absent in cancer, and this belief persisted for many decades. More recently, the role of gap junctions in cancers has garnered attention. With new gene manipulations (e.g. CRISPR/Cas9) and imaging techniques and improved xenografting, it is now possible to precisely study the impact of GJ on cancer metabolism. Moreover, we have a wide panel of cancer cell lines to study, and identify the prominent role of Cx26. We highlight that our study is the first to offer a mechanistic explanation for the absence of negative selection in cancer, a phenomenon which was not known in the 1970s. To strengthen our novelty, we now add in vivo data to Fig 8 that confirm in vitro findings.
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Evaluation Summary:
This work shows that spontaneous mutations in cancer cells affecting metabolic pathways do not necessarily result in functional defects, as affected cells may be able to be rescued by gap junction-mediated exchange of metabolites. This is verified in three specific examples, although some of the "quantitative" methods of measuring gap junctional coupling are actually only qualitative in nature. In addition, more experiments are needed to address the effect of Cx31 and Cx43 KD. This paper is of potential interest to a broad readership in cancer biology as well as colleagues studying metabolic pathways.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their …
Evaluation Summary:
This work shows that spontaneous mutations in cancer cells affecting metabolic pathways do not necessarily result in functional defects, as affected cells may be able to be rescued by gap junction-mediated exchange of metabolites. This is verified in three specific examples, although some of the "quantitative" methods of measuring gap junctional coupling are actually only qualitative in nature. In addition, more experiments are needed to address the effect of Cx31 and Cx43 KD. This paper is of potential interest to a broad readership in cancer biology as well as colleagues studying metabolic pathways.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)
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Reviewer #1 (Public Review):
The study by Monerisi et al. reports that loss-of-function mutations in metabolic pathways do not necessarily have a negative impact on cancer growth. The authors suggest that small solutes transferred via gap junction channels formed between wild-type cells and cells express mutants defective in metabolic pathways rescue the metabolic-deficient cancer cells. Through the examination of multiple human cell lines with several advanced means to determine gap junction coupling, Cx26 was identified as a major connexin molecule involved in medicating gap junction coupling between colorectal cancer (CRC) cells. The gene mutations of three metabolic gene mutations were investigated for major metabolic function of the cell, pH regulation, glycolysis and mitochondrial function.
Strengths:
The paper tests a new …
Reviewer #1 (Public Review):
The study by Monerisi et al. reports that loss-of-function mutations in metabolic pathways do not necessarily have a negative impact on cancer growth. The authors suggest that small solutes transferred via gap junction channels formed between wild-type cells and cells express mutants defective in metabolic pathways rescue the metabolic-deficient cancer cells. Through the examination of multiple human cell lines with several advanced means to determine gap junction coupling, Cx26 was identified as a major connexin molecule involved in medicating gap junction coupling between colorectal cancer (CRC) cells. The gene mutations of three metabolic gene mutations were investigated for major metabolic function of the cell, pH regulation, glycolysis and mitochondrial function.
Strengths:
The paper tests a new hypothesis that the mutations that inactivate key metabolic pathways do not incur functional deficits in cancer cells expressing the mutants due to their gap junction coupling to wild type cells.
From microarray data they identified multiple connexins expressed in various CRC cells. Several advanced analyses were used to assess gap junction coupling in CRC cells including fluorescence recovery after photobleaching (FRAP). The extent of permeability at steady state was evaluated using CellTracker dyes and coupling coefficients were determined. They also used flow-cytometry to study dye transfer, which will provide a quantitative, dynamic means for study cell coupling. The data showed that knocking down Cx26 could greatly reduce diffusive exchange in most of the CRC cells tested.
The study focused on three metabolic genes, Na+/H+ exchanger NHE1, a regulator of intracellular pH, a glycolytic gene, ALDOA and mitochondrial respiration gene, NDUFS1. These genes were knocked out in the selected CRC cells highly expressing these genes. The co-culture studies were well executed with fluorescence-markers distinguishing the WT and knockout cells and well-defined readouts such as intracellular pH, media pH, glucose/lactate levels and mitochondrial O2 consumption and glycolytic acid.
The experiments in general were well designed and conducted, and the data supported the conclusions. The paper is also logically written and figures were well presented providing clear graphic illustrations.
Weaknesses:
Although the hypothesis is innovative, no clear justification is provided that illustrates the scenario representing the clinical situation. The remaining questions include: What kind of somatic mutations in cancer cells has little impact on their growth and progression? What types of WT cells, within the tumor cells or with neighboring normal cells? Whether the current experimental design closely recapitulates the scenario in vivo?
The readouts for co-culturing for glycolytic ALDOA and NDUFS1 knockout are only cell mass, without determining the more relevant markers, glucose/lactate and mitochondrial O2 consumption and glycolytic acid production.
The study needs to include cells without functional gap junctions like the characterized negative control RKO cells. -
Reviewer #2 (Public Review):
This paper is a logical extension of the 50 year-old concept of the "bystander effect" in tumors, wherein the effects of anti-tumor chemotherapeutics extend beyond the cells that take them up due to spread through gap junctions to adjacent cells. In this case, however, the authors have creatively realized that the reverse might also occur, and that tumor cells with otherwise fatal mutations in essential metabolic pathways can be rescued by their neighbors through passage of the missing metabolites through gap junctions. This can explain why mutations in other critical pathways, such as protein synthesis and transporters, are selected against in rapidly growing tumors, but others in equally critical pathways of glycolysis, electron transport, etc. are not, despite these genes having been demonstrated to be …
Reviewer #2 (Public Review):
This paper is a logical extension of the 50 year-old concept of the "bystander effect" in tumors, wherein the effects of anti-tumor chemotherapeutics extend beyond the cells that take them up due to spread through gap junctions to adjacent cells. In this case, however, the authors have creatively realized that the reverse might also occur, and that tumor cells with otherwise fatal mutations in essential metabolic pathways can be rescued by their neighbors through passage of the missing metabolites through gap junctions. This can explain why mutations in other critical pathways, such as protein synthesis and transporters, are selected against in rapidly growing tumors, but others in equally critical pathways of glycolysis, electron transport, etc. are not, despite these genes having been demonstrated to be essential in in vitro KO studies (where all cells in the plate have the critical gene knocked-out). A series of elegant experiments are used to test this proposal in several colorectal cancer (CRC) cell lines using three examples - pH regulation (defective Na+/H+ exchanger NHE1), glycolysis (defective Aldolase A (ALDOA)) and oxidative phosphorylation (defective Complex 1 - NDUFS1).
The authors first determine the levels of different Cx proteins expressed in each cell line, and determine that for most Cx26 and 31 are dominant, although come lines have a subset of cells with high Cx43 expression. They then use Cell Tracker Green to pre-label cells and use FRAP as a means to measure how well the cell population is coupled. This is a useful measurement but is significantly over-interpreted by the authors as a "permeability" in uM/min. This is not really a permeability, which requires knowledge of the concentration gradient of the permeant species, relative cell volumes, etc. Rather it is a rate of fluorescent recovery that is presumably correlated with, but not quantitatively related to, levels of coupling.
This fluorescent recovery is shown to be sensitive to siRNA KO of Cx expression, but strangely its reduction is only correlated with KD of Cx26 in the 5 cell lines examined. KD of Cx43 (in LOVO cells) and Cx31 in all 5 cell lines had no effect or in some cases seemed to increase the rate of recovery (DLD1 and SNU1235). This is a notable finding, yet the authors choose to completely ignore it and continue with Cx26 KDs in studies of specific metabolite transfers. Some discussion should be included as to why KD pf these Cxs has no effect or causes an apparent increase in coupling of the cells.
Rather than just focus on acute transfer of dye between cells, the authors develop a system using 50/50 mixes of cells labeled with two junctionally permeant dyes and measured the degree of mixing at equilibrium (48 hours). This is presented as a "coupling coefficient", but how it is calculated, and its significance is not well described, and does not correlate with the historical use of this term in the literature. Nonetheless, the studies do seem to demonstrate a good degree of equilibration, although it would have been informative to determine of the cells that do not exchange dyes express Connexins. To document that this equilibration requires gap junctions, the authors employ low density cultures, which significantly decrease dye exchange. However, in at least one cell line (SW1222) dye exchange is only reduced by <50%, indicating a very high background to this assay. This is not addressed.
The most compelling part of the study is the use of reporters to directly demonstrate a role of Cx26 coupling of cells to rescue cells with mutations of the three genes mentioned above when mixed with normal neighbors. This case was most convincing in the cases of ALDOA and NDUFS1, with the data for the pH regulation requiring more explanation for full understanding of the data shown (e.g. Figs 7 G and H).
Overall, the study does a credible job of demonstrating that Cx26 coupling of CRC cells serves to rescue cells with mutations in critically necessary metabolic pathways, presumably due to transfer of metabolites from surrounding wt cells. However, some of the results indicate this is not a simple process where all connexins behave similarly, and some effort should be made to investigate if Cx31 and 43, which do not seem to play the same roles in maintaining cell coupling as Cx26, also play any role in such metabolic rescue.
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Reviewer #3 (Public Review):
Strengths of the study include that it appears to be a careful and well thought out set of experiments. The analysis and treatment of multiplexed data is also sophisticated. For the most part, the work is clearly and logically described, as well as well illustrated. In general, the authors achieved their experimental goals, and the methods while not entirely new, do provide new twists and augmentations that should be useful to the field. A general weakness is that this is not entirely a new story. Instead, it is a variant of one of the oldest concepts in the field of gap junction biology i.e. "Metabolic cooperation". The term "Metabolic cooperation" (i.e., as mediated by gap junctions) was not mentioned by the authors, but it is a long-established and foundational concept in the field. Indeed, in a classic …
Reviewer #3 (Public Review):
Strengths of the study include that it appears to be a careful and well thought out set of experiments. The analysis and treatment of multiplexed data is also sophisticated. For the most part, the work is clearly and logically described, as well as well illustrated. In general, the authors achieved their experimental goals, and the methods while not entirely new, do provide new twists and augmentations that should be useful to the field. A general weakness is that this is not entirely a new story. Instead, it is a variant of one of the oldest concepts in the field of gap junction biology i.e. "Metabolic cooperation". The term "Metabolic cooperation" (i.e., as mediated by gap junctions) was not mentioned by the authors, but it is a long-established and foundational concept in the field. Indeed, in a classic paper by Gilula and colleagues published in 1972, the experimental approach used was similar to that of the study in hand. These earlier authors showed how transformed cell lines with deficiencies in hypoxanthine metabolism can be "rescued" by "metabolic cooperation" in co-culture with metabolically competent cells via passing a gap junctional permeant molecule. This and other relevant papers were not cited. More importantly, the extant literature places the onus on the authors to explain and convince reviewers why this study is more than an incremental step.
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