- Email: [email protected]
Growth: A Model for Establishing Cell Size and Shape
Current Biology
Dispatches external synaptic inhibition also enables wakefulness (Figure 1B). Such external control of the sleep–wake balance might impart greater flexibility in the integration of the multiple physiological variables in sleep–wake control. For example, why does a sleeping hungry mammal wake up more easily than a well-fed mouse? Such conditions could involve hypothalamic control of the VLPO area. Thus, this paper is the first to demonstrate that a synaptic inhibition of the VLPO area can efficiently turn-off the off-switch to promote arousal. Many new and stimulating questions are raised by the work of Venner et al. [1]. First, which are the physiological conditions that drive the LH-VLPO projection? Where in the hierarchy of sleep–wake control lies this projection, in particular also with respect to other non-REM sleep promoting areas [13,14]? What about REM sleep control [19]? What are the neuronal and molecular identities of the VLPO neurons that are targeted by LH-GABAergic neurons? The power of chemogenetic tools to address these question becomes very clear in this landmark study. Trans-synaptic tracing and molecular profiling, combined with sleep manipulation, will help bring further advances in the genetic and circuit dissection of the VLPO. These results will provide clues to more specific pharmacological and behavioral sleep therapies. REFERENCES 1. Venner, A., Anaclet, C., Broadhurst, R.Y., Saper, C.B., and Fuller, P.M. (2016). A novel population of wake-promoting GABAergic neurons in the ventral lateral hypothalamus. Curr. Biol. 26, 2137–2143. 2. Brown, R.E., Basheer, R., McKenna, J.T., Strecker, R.E., and McCarley, R.W. (2012). Control of sleep and wakefulness. Physiol. Rev. 92, 1087–1187. 3. Saper, C.B., Fuller, P.M., Pedersen, N.P., Lu, J., and Scammell, T.E. (2010). Sleep state switching. Neuron 68, 1023–1042. 4. Luppi, P.H., Peyron, C., and Fort, P. (2016). Not a single but multiple populations of GABAergic neurons control sleep. Sleep Med. Rev. http://dx.doi.org/10.1016/j.smrv.2016. 03.002. 5. Adamantidis, A.R., Zhang, F., Aravanis, A.M., Deisseroth, K., and de Lecea, L. (2007). Neural substrates of awakening probed with optogenetic control of hypocretin neurons. Nature 450, 420–424. 6. Carter, M.E., Yizhar, O., Chikahisa, S., Nguyen, H., Adamantidis, A., Nishino, S., Deisseroth,
K., and de Lecea, L. (2010). Tuning arousal with optogenetic modulation of locus coeruleus neurons. Nat. Neurosci. 13, 1526– 1533. 7. Szymusiak, R., and McGinty, D. (2008). Hypothalamic regulation of sleep and arousal. Ann. N.Y. Acad. Sci. 1129, 275–286. 8. Szymusiak, R., Alam, N., Steininger, T.L., and McGinty, D. (1998). Sleep-waking discharge patterns of ventrolateral preoptic/anterior hypothalamic neurons in rats. Brain Res. 803, 178–188. 9. Modirrousta, M., Mainville, L., and Jones, B.E. (2004). Gabaergic neurons with a2-adrenergic receptors in basal forebrain and preoptic area express c-Fos during sleep. Neuroscience 129, 803–810. 10. Lu, J., Greco, M.A., Shiromani, P., and Saper, C.B. (2000). Effect of lesions of the ventrolateral preoptic nucleus on NREM and REM sleep. J. Neurosci. 20, 3830–3842. 11. Boulant, J.A. (2000). Role of the preopticanterior hypothalamus in thermoregulation and fever. Clin. Inf. Dis. 31 (Suppl 5 ), S157– S161. 12. Dulac, C., O’Connell, L.A., and Wu, Z. (2014). Neural control of maternal and paternal behaviors. Science 345, 765–770. 13. Zhang, Z., Ferretti, V., Gu¨ntan, I., Moro, A., Steinberg, E.A., Ye, Z., Zecharia, A.Y., Yu, X., Vyssotski, A.L., Brickley, S.G., et al. (2015). Neuronal ensembles sufficient for recovery sleep and the sedative actions of a2 adrenergic agonists. Nat. Neurosci. 18, 553–561.
14. Anaclet, C., Ferrari, L., Arrigoni, E., Bass, C.E., Saper, C.B., Lu, J., and Fuller, P.M. (2014). The GABAergic parafacial zone is a medullary slow wave sleep-promoting center. Nat. Neurosci. 17, 1217–1224. 15. Hassani, O.K., Henny, P., Lee, M.G., and Jones, B.E. (2010). GABAergic neurons intermingled with orexin and MCH neurons in the lateral hypothalamus discharge maximally during sleep. Eur. J. Neurosci. 32, 448–457. 16. Koyama, Y., Takahashi, K., Kodama, T., and Kayama, Y. (2003). State-dependent activity of neurons in the perifornical hypothalamic area during sleep and waking. Neuroscience 119, 1209–1219. 17. Gervasoni, D., Peyron, C., Rampon, C., Barbagli, B., Chouvet, G., Urbain, N., Fort, P., and Luppi, P.H. (2000). Role and origin of the GABAergic innervation of dorsal raphe serotonergic neurons. J. Neurosci. 20, 4217– 4225. 18. Herrera, C.G., Cadavieco, M.C., Jego, S., Ponomarenko, A., Korotkova, T., and Adamantidis, A. (2016). Hypothalamic feedforward inhibition of thalamocortical network controls arousal and consciousness. Nat. Neurosci. 19, 290–298. 19. Sapin, E., Be´rod, A., Le´ger, L., Herman, P.A., Luppi, P.H., and Peyron, C. (2010). A very large number of GABAergic neurons are activated in the tuberal hypothalamus during paradoxical (REM) sleep hypersomnia. PLoS One 5, e11766.
Growth: A Model for Establishing Cell Size and Shape Yee-Hung Mark Chan Department of Biology, San Francisco State University, 1600 Holloway Ave., San Francisco, CA 94132, USA Correspondence: [email protected] http://dx.doi.org/10.1016/j.cub.2016.06.067
New experiments reveal that the relative growth between cell surface area and volume are key determinants of the shape and size of rodlike bacteria. These results are synthesized into a relative-growth model that applies to questions ranging from morphogenesis to cellcycle timing. Cells exhibit an amazing diversity of morphologies, ranging from the compact, clean geometries of diatoms to the extended, branching trees of neurons. The morphology of these cells
reflects their function, and so it is crucial to discover how cells determine their shapes and sizes [1–3]. Many bacterial cells, including Caulobacter crescentus and Escherichia coli, maintain a rod-like
Current Biology 26, R756–R777, August 22, 2016 ª 2016 Elsevier Ltd. R767
Current Biology
Dispatches Surface area to volume ratio A Elongation
Decreases
B Septation
Increases
+ C Fosfomycin treatment or rich-medium shift
Decreases
D Early phase of chloramphenicol treatment
Increases
Current Biology
Figure 1. Cell growth impacts the surface area to volume ratio (SA/V). (A) As rod-like cells grow by elongation, the SA/V decreases. (B) During septation, two new cell caps are constructed, leading to an increase in the SA/V. (C) Under fosfomycin treatment and shifts to rich media, volume-growth rate and surface-area growth rate change, leading to an increase in the SA/V, and cells adjust their size accordingly. (D) In an early stage of chloramphenicol treatment, cells shrink, thus leading to a decrease in the SA/V.
shape as they grow. Classically, their growth has been described by a simple model in which cells increase in length while maintaining a constant width [4,5]. This model was supported by functional studies of structural proteins like MreB, the bacterial actin orthologue, which provides a mechanistic link between elongation and width control [6]. Other experiments demonstrate that cell length and width don’t provide the full story [7,8]. For example, strains harboring mutations in mreB show irregular cell widths, but nevertheless still maintain their surface area to volume ratio (SA/V) near wild-type levels. In a new study published recently in Cell, Harris and Theriot [9] developed
and tested a quantitative model in which they hypothesize that the relative growth between a bacterium’s cell-wall surface and its cytoplasmic volume is the primary determinant of cell size and shape. Growth is intimately related to shape [10]. During growth, cells expand their surface by adding new material to the cell wall and membrane [11]. Simultaneously, synthesis of new cytoplasmic content increases the cell’s volume. Harris and Theriot [9] make the intuitive hypothesis that growth of the cell wall and cytoplasm must then be coupled to each other in some way based on the biosynthetic capacity of a cell. In this context,
R768 Current Biology 26, R756–R777, August 22, 2016
the relationship between surfacearea growth and volume growth is intimately related to cell size (Figure 1A,B). Different growth rates define the average cell SA/V, and cell length and width can be adjusted to tune the cell’s shape to match this SA/V. Harris and Theriot [9] set out to understand how the growth of rodlike bacteria impacts their shape. In their manuscript, they propose a relative-growth model in which bacterial volume (cytoplasm) and surface area (cell wall) increase at rates directly proportionally to bacterial volume (V), with proportionality constants a and b, respectively; i.e. volume growth rate = aV, and surfacearea growth rate = bV. Therefore, the relative growth rates of these two parameters would define the steadystate SA/V = b=a. To test the predictions of this model, the authors hypothesized that applying drugs and conditions that impact cell wall or overall cell growth would result in 0 0 perturbed a and b . Consequently, after perturbation, the cell population 0 0 should approach a new SA/V = b =a , reflected in changes to cell length and width. The authors tested three conditions that shift a and b in different ways. Fosfomycin was used to selectively attenuate cell wall growth rates with relatively little effect on overall cytoplasmic growth rates 0 0 (a ya and b < b). Cells shifted from nutrient-poor medium into nutrient-rich medium increase both cell wall and cytoplasmic growth rates, as was expected with greater nutrient 0 0 availability (a > a and b > b). The ribosome inhibitor, chloramphenicol, was used to reduce the biosynthetic capacity of the cell, and this antibiotic led to more complex evolutions of a and b. In each of these cases, the authors found that steady-state and dynamic measurements of cell size and growth confirm the quantitative predictions of the relative-growth model. Under all these conditions, cells adopted a new SA/V by changing their average length and width to match the new a and b parameters (Figure 1C,D). The changes in SA/V followed characteristic exponential
Current Biology
Dispatches decays with time constants equal to a. Furthermore, independent derivations of a and b were all found to be consistent with one another. Taken together, these findings show that a key cellular response to changes in growth is to establish a new SA/V. These experiments also provided a way to test how cell growth impacts cell size. In the case of fosfomycin exposure and shifts to rich medium, cells became longer and wider despite differing effects of these conditions on cell-wall and cytoplasm synthesis. When exposed to chloramphenicol, the cells show two phases; cells first shrink, and then become larger in size. Strikingly, steady-state cell size becomes larger when overall cell growth rate increases (shift to rich medium) or when it decreases (antibiotic exposure). Therefore, cell size is not a simple outcome of increased growth rate. Instead, cell size varies with the predicted changes in SA/V under these conditions, an observation that is consistent in the context of the relative-growth model. Thus, the authors provide further evidence that SA/V is a primary determinant of cell size and shape. In a population of cells, the average SA/V is defined by the relative growth rates of these parameters. However, cell populations are made up of individual cells, in which SA/V is expected to change depending on specific events that occur during the cell cycle. In particular, the process of septation will increase SA/V, as new cell wall is constructed to divide an existing cell into two (Figure 1B). Further, the timing of septation determines the average cell length, which has a strong impact on a cell’s SA/V. Where does the new cell-wall material come from, and how is the timing of septation determined? The authors propose answers to both of these questions based on the relative-growth model. To do so, they make a distinction between the rate of synthesis of cell-wall material and the rate of its incorporation. While synthesis is assumed to remain proportional to cell volume at all times, the amount of cell-wall material incorporated may change during the cell cycle. Indeed, measurements on single cells reveal that the cell wall is
incorporated relatively slowly during elongation and relatively quickly during septation (Figure 1A,B). Based on their model, the authors hypothesize that during elongation an excess of cell-wall material is synthesized but not incorporated. This excess material forms a ‘reservoir’ that can fulfill the increased demand for cell-wall incorporation during septation. This scenario raises the intriguing possibility that excess cell-wall synthesis provides a way for the cell to time cell division in a manner that is related to proposed ‘adder’ mechanisms [12]. Consistent with this possibility, the authors calculate that division is triggered when the cell has accumulated enough excess cell wall to construct the two new hemispherical caps during septation. The relative-growth model is a powerful framework to understand many observations regarding bacterial growth, shape, and size regulation. Harris and Theriot [9] convincingly show that cells primarily adjust their SA/V to compensate for changes in growth. But, for any value of SA/V, there are multiple shapes and sizes that can satisfy that constraint — so how do cells choose from within this solution space? Structural proteins such as MreB may place additional shape constraints that must be fulfilled during cell growth, forcing the cell to elongate and preventing bulging in the middle. Can these or other regulatory proteins sense changes in growth rates and redirect growth to modulate or preserve cell shape accordingly [13]? What are the functional consequences of this regulation [14]? It would also be interesting to consider whether the relative-growth model applies to cells with more complex shapes. How well can relative surface-area growth and volume growth describe more complex shapes of diatoms, neurons and other cells? What additional mechanisms are necessary to achieve these shapes? Such questions are key to understanding processes like polarization and asymmetric division, in which the cell makes local decisions regarding whether growth will occur. Loss of symmetry may require that the relative growth rates of cell surface and volume vary depending on location, implying the need for
subcellular sensing of size [15]. The answers will shed light on our understanding of the morphogenesis not just of cells, but of biological structures spanning all size scales, including organelles, organs, and organisms. REFERENCES 1. Marshall, W.F., Young, K.D., Swaffer, M., Wood, E., Nurse, P., Kimura, A., Frankel, J., Wallingford, J., Walbot, V., Qu, X., et al. (2012). What determines cell size? BMC Biol. 10, 101. 2. Young, K.D. (2006). The selective value of bacterial shape. Microbiol. Mol. Biol. Rev. 70, 660–703. 3. Koch, A.L. (1996). What size should a bacterium be? A question of scale. Annu. Rev. Microbiol. 50, 317–348. 4. Marr, A.G., Harvey, R.J., and Trentini, W.C. (1966). Growth and division of Escherichia coli. J. Bacteriol. 91, 2388–2389. 5. Cullum, J., and Vicente, M. (1978). Cell growth and length distribution in Escherichia coli. J. Bacteriol. 134, 330–337. 6. Figge, R.M., Divakaruni, A.V., and Gober, J.W. (2004). MreB, the cell shape-determining bacterial actin homologue, co-ordinates cell wall morphogenesis in Caulobacter crescentus. Mol. Microbiol. 51, 1321–1332. 7. Schaechter, M., MaalØe, O., and Kjeldgaard, N.O. (1958). Dependency on medium and temperature of cell size and chemical composition during balanced growth of Salmonella typhimurium. Microbiology 19, 592–606. 8. Trueba, F.J. (1982). On the precision and accuracy achieved by Escherichia coli. Arch. Microbiol. 131, 55–59. 9. Harris, L.K., and Theriot, J.A. (2016). Relative rates of surface and volume synthesis set bacterial cell size. Cell 165, 1479–1492. 10. Chan, Y.-H.M., and Marshall, W.F. (2010). Scaling properties of cell and organelle size. Organogenesis 6, 88–96. 11. Daniel, R.A., and Errington, J. (2003). Control of cell morphogenesis in bacteria: two distinct ways to make a rod-shaped cell. Cell 113, 767–776. 12. Taheri-Araghi, S., Bradde, S., Sauls, J.T., Hill, N.S., Levin, P.A., Paulsson, J., Vergassola, M., and Jun, S. (2015). Cell-size control and homeostasis in bacteria. Curr. Biol. 25, 385–391. 13. Jones, L.J.F., Carballido-Lo´pez, R., and Errington, J. (2001). Control of cell shape in bacteria: helical, actin-like filaments in Bacillus subtilis. Cell 104, 913–922. 14. Young, K.D. (2007). Bacterial morphology: why have different shapes? Curr. Opin. Microbiol. 10, 596–600. 15. Chan, Y.-H.M., and Marshall, W.F. (2012). How cells know the size of their organelles. Science 337, 1186–1189.
Current Biology 26, R756–R777, August 22, 2016 R769
Dispatches external synaptic inhibition also enables wakefulness (Figure 1B). Such external control of the sleep–wake balance might impart greater flexibility in the integration of the multiple physiological variables in sleep–wake control. For example, why does a sleeping hungry mammal wake up more easily than a well-fed mouse? Such conditions could involve hypothalamic control of the VLPO area. Thus, this paper is the first to demonstrate that a synaptic inhibition of the VLPO area can efficiently turn-off the off-switch to promote arousal. Many new and stimulating questions are raised by the work of Venner et al. [1]. First, which are the physiological conditions that drive the LH-VLPO projection? Where in the hierarchy of sleep–wake control lies this projection, in particular also with respect to other non-REM sleep promoting areas [13,14]? What about REM sleep control [19]? What are the neuronal and molecular identities of the VLPO neurons that are targeted by LH-GABAergic neurons? The power of chemogenetic tools to address these question becomes very clear in this landmark study. Trans-synaptic tracing and molecular profiling, combined with sleep manipulation, will help bring further advances in the genetic and circuit dissection of the VLPO. These results will provide clues to more specific pharmacological and behavioral sleep therapies. REFERENCES 1. Venner, A., Anaclet, C., Broadhurst, R.Y., Saper, C.B., and Fuller, P.M. (2016). A novel population of wake-promoting GABAergic neurons in the ventral lateral hypothalamus. Curr. Biol. 26, 2137–2143. 2. Brown, R.E., Basheer, R., McKenna, J.T., Strecker, R.E., and McCarley, R.W. (2012). Control of sleep and wakefulness. Physiol. Rev. 92, 1087–1187. 3. Saper, C.B., Fuller, P.M., Pedersen, N.P., Lu, J., and Scammell, T.E. (2010). Sleep state switching. Neuron 68, 1023–1042. 4. Luppi, P.H., Peyron, C., and Fort, P. (2016). Not a single but multiple populations of GABAergic neurons control sleep. Sleep Med. Rev. http://dx.doi.org/10.1016/j.smrv.2016. 03.002. 5. Adamantidis, A.R., Zhang, F., Aravanis, A.M., Deisseroth, K., and de Lecea, L. (2007). Neural substrates of awakening probed with optogenetic control of hypocretin neurons. Nature 450, 420–424. 6. Carter, M.E., Yizhar, O., Chikahisa, S., Nguyen, H., Adamantidis, A., Nishino, S., Deisseroth,
K., and de Lecea, L. (2010). Tuning arousal with optogenetic modulation of locus coeruleus neurons. Nat. Neurosci. 13, 1526– 1533. 7. Szymusiak, R., and McGinty, D. (2008). Hypothalamic regulation of sleep and arousal. Ann. N.Y. Acad. Sci. 1129, 275–286. 8. Szymusiak, R., Alam, N., Steininger, T.L., and McGinty, D. (1998). Sleep-waking discharge patterns of ventrolateral preoptic/anterior hypothalamic neurons in rats. Brain Res. 803, 178–188. 9. Modirrousta, M., Mainville, L., and Jones, B.E. (2004). Gabaergic neurons with a2-adrenergic receptors in basal forebrain and preoptic area express c-Fos during sleep. Neuroscience 129, 803–810. 10. Lu, J., Greco, M.A., Shiromani, P., and Saper, C.B. (2000). Effect of lesions of the ventrolateral preoptic nucleus on NREM and REM sleep. J. Neurosci. 20, 3830–3842. 11. Boulant, J.A. (2000). Role of the preopticanterior hypothalamus in thermoregulation and fever. Clin. Inf. Dis. 31 (Suppl 5 ), S157– S161. 12. Dulac, C., O’Connell, L.A., and Wu, Z. (2014). Neural control of maternal and paternal behaviors. Science 345, 765–770. 13. Zhang, Z., Ferretti, V., Gu¨ntan, I., Moro, A., Steinberg, E.A., Ye, Z., Zecharia, A.Y., Yu, X., Vyssotski, A.L., Brickley, S.G., et al. (2015). Neuronal ensembles sufficient for recovery sleep and the sedative actions of a2 adrenergic agonists. Nat. Neurosci. 18, 553–561.
14. Anaclet, C., Ferrari, L., Arrigoni, E., Bass, C.E., Saper, C.B., Lu, J., and Fuller, P.M. (2014). The GABAergic parafacial zone is a medullary slow wave sleep-promoting center. Nat. Neurosci. 17, 1217–1224. 15. Hassani, O.K., Henny, P., Lee, M.G., and Jones, B.E. (2010). GABAergic neurons intermingled with orexin and MCH neurons in the lateral hypothalamus discharge maximally during sleep. Eur. J. Neurosci. 32, 448–457. 16. Koyama, Y., Takahashi, K., Kodama, T., and Kayama, Y. (2003). State-dependent activity of neurons in the perifornical hypothalamic area during sleep and waking. Neuroscience 119, 1209–1219. 17. Gervasoni, D., Peyron, C., Rampon, C., Barbagli, B., Chouvet, G., Urbain, N., Fort, P., and Luppi, P.H. (2000). Role and origin of the GABAergic innervation of dorsal raphe serotonergic neurons. J. Neurosci. 20, 4217– 4225. 18. Herrera, C.G., Cadavieco, M.C., Jego, S., Ponomarenko, A., Korotkova, T., and Adamantidis, A. (2016). Hypothalamic feedforward inhibition of thalamocortical network controls arousal and consciousness. Nat. Neurosci. 19, 290–298. 19. Sapin, E., Be´rod, A., Le´ger, L., Herman, P.A., Luppi, P.H., and Peyron, C. (2010). A very large number of GABAergic neurons are activated in the tuberal hypothalamus during paradoxical (REM) sleep hypersomnia. PLoS One 5, e11766.
Growth: A Model for Establishing Cell Size and Shape Yee-Hung Mark Chan Department of Biology, San Francisco State University, 1600 Holloway Ave., San Francisco, CA 94132, USA Correspondence: [email protected] http://dx.doi.org/10.1016/j.cub.2016.06.067
New experiments reveal that the relative growth between cell surface area and volume are key determinants of the shape and size of rodlike bacteria. These results are synthesized into a relative-growth model that applies to questions ranging from morphogenesis to cellcycle timing. Cells exhibit an amazing diversity of morphologies, ranging from the compact, clean geometries of diatoms to the extended, branching trees of neurons. The morphology of these cells
reflects their function, and so it is crucial to discover how cells determine their shapes and sizes [1–3]. Many bacterial cells, including Caulobacter crescentus and Escherichia coli, maintain a rod-like
Current Biology 26, R756–R777, August 22, 2016 ª 2016 Elsevier Ltd. R767
Current Biology
Dispatches Surface area to volume ratio A Elongation
Decreases
B Septation
Increases
+ C Fosfomycin treatment or rich-medium shift
Decreases
D Early phase of chloramphenicol treatment
Increases
Current Biology
Figure 1. Cell growth impacts the surface area to volume ratio (SA/V). (A) As rod-like cells grow by elongation, the SA/V decreases. (B) During septation, two new cell caps are constructed, leading to an increase in the SA/V. (C) Under fosfomycin treatment and shifts to rich media, volume-growth rate and surface-area growth rate change, leading to an increase in the SA/V, and cells adjust their size accordingly. (D) In an early stage of chloramphenicol treatment, cells shrink, thus leading to a decrease in the SA/V.
shape as they grow. Classically, their growth has been described by a simple model in which cells increase in length while maintaining a constant width [4,5]. This model was supported by functional studies of structural proteins like MreB, the bacterial actin orthologue, which provides a mechanistic link between elongation and width control [6]. Other experiments demonstrate that cell length and width don’t provide the full story [7,8]. For example, strains harboring mutations in mreB show irregular cell widths, but nevertheless still maintain their surface area to volume ratio (SA/V) near wild-type levels. In a new study published recently in Cell, Harris and Theriot [9] developed
and tested a quantitative model in which they hypothesize that the relative growth between a bacterium’s cell-wall surface and its cytoplasmic volume is the primary determinant of cell size and shape. Growth is intimately related to shape [10]. During growth, cells expand their surface by adding new material to the cell wall and membrane [11]. Simultaneously, synthesis of new cytoplasmic content increases the cell’s volume. Harris and Theriot [9] make the intuitive hypothesis that growth of the cell wall and cytoplasm must then be coupled to each other in some way based on the biosynthetic capacity of a cell. In this context,
R768 Current Biology 26, R756–R777, August 22, 2016
the relationship between surfacearea growth and volume growth is intimately related to cell size (Figure 1A,B). Different growth rates define the average cell SA/V, and cell length and width can be adjusted to tune the cell’s shape to match this SA/V. Harris and Theriot [9] set out to understand how the growth of rodlike bacteria impacts their shape. In their manuscript, they propose a relative-growth model in which bacterial volume (cytoplasm) and surface area (cell wall) increase at rates directly proportionally to bacterial volume (V), with proportionality constants a and b, respectively; i.e. volume growth rate = aV, and surfacearea growth rate = bV. Therefore, the relative growth rates of these two parameters would define the steadystate SA/V = b=a. To test the predictions of this model, the authors hypothesized that applying drugs and conditions that impact cell wall or overall cell growth would result in 0 0 perturbed a and b . Consequently, after perturbation, the cell population 0 0 should approach a new SA/V = b =a , reflected in changes to cell length and width. The authors tested three conditions that shift a and b in different ways. Fosfomycin was used to selectively attenuate cell wall growth rates with relatively little effect on overall cytoplasmic growth rates 0 0 (a ya and b < b). Cells shifted from nutrient-poor medium into nutrient-rich medium increase both cell wall and cytoplasmic growth rates, as was expected with greater nutrient 0 0 availability (a > a and b > b). The ribosome inhibitor, chloramphenicol, was used to reduce the biosynthetic capacity of the cell, and this antibiotic led to more complex evolutions of a and b. In each of these cases, the authors found that steady-state and dynamic measurements of cell size and growth confirm the quantitative predictions of the relative-growth model. Under all these conditions, cells adopted a new SA/V by changing their average length and width to match the new a and b parameters (Figure 1C,D). The changes in SA/V followed characteristic exponential
Current Biology
Dispatches decays with time constants equal to a. Furthermore, independent derivations of a and b were all found to be consistent with one another. Taken together, these findings show that a key cellular response to changes in growth is to establish a new SA/V. These experiments also provided a way to test how cell growth impacts cell size. In the case of fosfomycin exposure and shifts to rich medium, cells became longer and wider despite differing effects of these conditions on cell-wall and cytoplasm synthesis. When exposed to chloramphenicol, the cells show two phases; cells first shrink, and then become larger in size. Strikingly, steady-state cell size becomes larger when overall cell growth rate increases (shift to rich medium) or when it decreases (antibiotic exposure). Therefore, cell size is not a simple outcome of increased growth rate. Instead, cell size varies with the predicted changes in SA/V under these conditions, an observation that is consistent in the context of the relative-growth model. Thus, the authors provide further evidence that SA/V is a primary determinant of cell size and shape. In a population of cells, the average SA/V is defined by the relative growth rates of these parameters. However, cell populations are made up of individual cells, in which SA/V is expected to change depending on specific events that occur during the cell cycle. In particular, the process of septation will increase SA/V, as new cell wall is constructed to divide an existing cell into two (Figure 1B). Further, the timing of septation determines the average cell length, which has a strong impact on a cell’s SA/V. Where does the new cell-wall material come from, and how is the timing of septation determined? The authors propose answers to both of these questions based on the relative-growth model. To do so, they make a distinction between the rate of synthesis of cell-wall material and the rate of its incorporation. While synthesis is assumed to remain proportional to cell volume at all times, the amount of cell-wall material incorporated may change during the cell cycle. Indeed, measurements on single cells reveal that the cell wall is
incorporated relatively slowly during elongation and relatively quickly during septation (Figure 1A,B). Based on their model, the authors hypothesize that during elongation an excess of cell-wall material is synthesized but not incorporated. This excess material forms a ‘reservoir’ that can fulfill the increased demand for cell-wall incorporation during septation. This scenario raises the intriguing possibility that excess cell-wall synthesis provides a way for the cell to time cell division in a manner that is related to proposed ‘adder’ mechanisms [12]. Consistent with this possibility, the authors calculate that division is triggered when the cell has accumulated enough excess cell wall to construct the two new hemispherical caps during septation. The relative-growth model is a powerful framework to understand many observations regarding bacterial growth, shape, and size regulation. Harris and Theriot [9] convincingly show that cells primarily adjust their SA/V to compensate for changes in growth. But, for any value of SA/V, there are multiple shapes and sizes that can satisfy that constraint — so how do cells choose from within this solution space? Structural proteins such as MreB may place additional shape constraints that must be fulfilled during cell growth, forcing the cell to elongate and preventing bulging in the middle. Can these or other regulatory proteins sense changes in growth rates and redirect growth to modulate or preserve cell shape accordingly [13]? What are the functional consequences of this regulation [14]? It would also be interesting to consider whether the relative-growth model applies to cells with more complex shapes. How well can relative surface-area growth and volume growth describe more complex shapes of diatoms, neurons and other cells? What additional mechanisms are necessary to achieve these shapes? Such questions are key to understanding processes like polarization and asymmetric division, in which the cell makes local decisions regarding whether growth will occur. Loss of symmetry may require that the relative growth rates of cell surface and volume vary depending on location, implying the need for
subcellular sensing of size [15]. The answers will shed light on our understanding of the morphogenesis not just of cells, but of biological structures spanning all size scales, including organelles, organs, and organisms. REFERENCES 1. Marshall, W.F., Young, K.D., Swaffer, M., Wood, E., Nurse, P., Kimura, A., Frankel, J., Wallingford, J., Walbot, V., Qu, X., et al. (2012). What determines cell size? BMC Biol. 10, 101. 2. Young, K.D. (2006). The selective value of bacterial shape. Microbiol. Mol. Biol. Rev. 70, 660–703. 3. Koch, A.L. (1996). What size should a bacterium be? A question of scale. Annu. Rev. Microbiol. 50, 317–348. 4. Marr, A.G., Harvey, R.J., and Trentini, W.C. (1966). Growth and division of Escherichia coli. J. Bacteriol. 91, 2388–2389. 5. Cullum, J., and Vicente, M. (1978). Cell growth and length distribution in Escherichia coli. J. Bacteriol. 134, 330–337. 6. Figge, R.M., Divakaruni, A.V., and Gober, J.W. (2004). MreB, the cell shape-determining bacterial actin homologue, co-ordinates cell wall morphogenesis in Caulobacter crescentus. Mol. Microbiol. 51, 1321–1332. 7. Schaechter, M., MaalØe, O., and Kjeldgaard, N.O. (1958). Dependency on medium and temperature of cell size and chemical composition during balanced growth of Salmonella typhimurium. Microbiology 19, 592–606. 8. Trueba, F.J. (1982). On the precision and accuracy achieved by Escherichia coli. Arch. Microbiol. 131, 55–59. 9. Harris, L.K., and Theriot, J.A. (2016). Relative rates of surface and volume synthesis set bacterial cell size. Cell 165, 1479–1492. 10. Chan, Y.-H.M., and Marshall, W.F. (2010). Scaling properties of cell and organelle size. Organogenesis 6, 88–96. 11. Daniel, R.A., and Errington, J. (2003). Control of cell morphogenesis in bacteria: two distinct ways to make a rod-shaped cell. Cell 113, 767–776. 12. Taheri-Araghi, S., Bradde, S., Sauls, J.T., Hill, N.S., Levin, P.A., Paulsson, J., Vergassola, M., and Jun, S. (2015). Cell-size control and homeostasis in bacteria. Curr. Biol. 25, 385–391. 13. Jones, L.J.F., Carballido-Lo´pez, R., and Errington, J. (2001). Control of cell shape in bacteria: helical, actin-like filaments in Bacillus subtilis. Cell 104, 913–922. 14. Young, K.D. (2007). Bacterial morphology: why have different shapes? Curr. Opin. Microbiol. 10, 596–600. 15. Chan, Y.-H.M., and Marshall, W.F. (2012). How cells know the size of their organelles. Science 337, 1186–1189.
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