Limits...
Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation.

Chiang M, Cinquin A, Paz A, Meeds E, Price CA, Welling M, Cinquin O - BMC Biol. (2015)

Bottom Line: Computational simulations of mutation accumulation characterize a tradeoff between fast development and low mutation accumulation, and show that slow-cycling stem cells allow for an advantageous compromise to be reached.Experimental measurements of cell cycle lengths derived using a new, quantitative technique are consistent with these predictions.Our findings shed light both on design principles that underlie the role of stem cells in delaying aging and on evolutionary forces that shape stem-cell gene regulatory networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Developmental & Cell Biology, University of California, Irvine, California, USA.

ABSTRACT

Background: Stem cells are thought to play a critical role in minimizing the accumulation of mutations, but it is not clear which strategies they follow to fulfill that performance objective. Slow cycling of stem cells provides a simple strategy that can minimize cell pedigree depth and thereby minimize the accumulation of replication-dependent mutations. Although the power of this strategy was recognized early on, a quantitative assessment of whether and how it is employed by biological systems is missing.

Results: Here we address this problem using a simple self-renewing organ - the C. elegans gonad - whose overall organization is shared with many self-renewing organs. Computational simulations of mutation accumulation characterize a tradeoff between fast development and low mutation accumulation, and show that slow-cycling stem cells allow for an advantageous compromise to be reached. This compromise is such that worm germ-line stem cells should cycle more slowly than their differentiating counterparts, but only by a modest amount. Experimental measurements of cell cycle lengths derived using a new, quantitative technique are consistent with these predictions.

Conclusions: Our findings shed light both on design principles that underlie the role of stem cells in delaying aging and on evolutionary forces that shape stem-cell gene regulatory networks.

No MeSH data available.


Related in: MedlinePlus

Simulation setup. Agent-based simulations used to characterize the dependence of pedigree depth on the spatiotemporal profile of cell cycle lengths comprised control of cell cycle length by position along the distal–proximal axis, cell movement through the mitotic and meiotic zones, and eventual differentiation or apoptosis. The spatial domain of the MZ was defined by a lattice of positions that could be occupied by at most one cell at a time. The lattice was rectangular (with length and width that were either predetermined or that were set by parameters over which optimization was performed), or had a shape defined from experimental measurements. The lattice was seeded with a single primordial cell located at the distal end. As this cell divided, its descendants filled the MZ first width-wise and then length-wise, with daughter cells being pushed laterally or proximally as cells behind them (i.e. more distal to them) divided. To mimic the cone-like structure of the gonad, cells at either end of a given row could be displaced in a way that they wrapped around to the other end of the same row (a, red arrow). Once daughter cells were pushed beyond the last MZ row, they exited the mitotic cell cycle and differentiated by entering the meiotic zone. The meiotic zone was modeled as a first-in-first-out queue, with cells entering at the distal end as they left the MZ, and exiting at the proximal end as they underwent apoptosis or matured as an oocyte. The length of the mitotic cell cycle was modeled as a linear gradient, controlled at the distal end of the MZ and at its proximal end by two parameters with value greater than 2.8 h (b, double-ended arrows; some cell cycle fit simulations allowed for a third, more proximal control point shown with a dashed line; see “Results”). Depending on the kind of simulation, cell length values at the control points were allowed to change at various developmental stages (see Table 1); in this case, the cell cycle length was linearly interpolated along the time axis in addition to the space axis.
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Fig6: Simulation setup. Agent-based simulations used to characterize the dependence of pedigree depth on the spatiotemporal profile of cell cycle lengths comprised control of cell cycle length by position along the distal–proximal axis, cell movement through the mitotic and meiotic zones, and eventual differentiation or apoptosis. The spatial domain of the MZ was defined by a lattice of positions that could be occupied by at most one cell at a time. The lattice was rectangular (with length and width that were either predetermined or that were set by parameters over which optimization was performed), or had a shape defined from experimental measurements. The lattice was seeded with a single primordial cell located at the distal end. As this cell divided, its descendants filled the MZ first width-wise and then length-wise, with daughter cells being pushed laterally or proximally as cells behind them (i.e. more distal to them) divided. To mimic the cone-like structure of the gonad, cells at either end of a given row could be displaced in a way that they wrapped around to the other end of the same row (a, red arrow). Once daughter cells were pushed beyond the last MZ row, they exited the mitotic cell cycle and differentiated by entering the meiotic zone. The meiotic zone was modeled as a first-in-first-out queue, with cells entering at the distal end as they left the MZ, and exiting at the proximal end as they underwent apoptosis or matured as an oocyte. The length of the mitotic cell cycle was modeled as a linear gradient, controlled at the distal end of the MZ and at its proximal end by two parameters with value greater than 2.8 h (b, double-ended arrows; some cell cycle fit simulations allowed for a third, more proximal control point shown with a dashed line; see “Results”). Depending on the kind of simulation, cell length values at the control points were allowed to change at various developmental stages (see Table 1); in this case, the cell cycle length was linearly interpolated along the time axis in addition to the space axis.

Mentions: What is the optimal compromise between minimization of mutation accumulation and early production of differentiated cells, and what is the resulting optimal stem-cell cycling speed? The answers to these questions depend on the relative costs of mutation accumulation and of delaying the production of differentiated cells. We tackle this problem within the context of the C. elegans hermaphroditic gonadal arm, which over the reproductive lifetime of an individual produces ~3000 cells that differentiate by entering meiosis. Cells leaving the MZ ensure compensation of germ-cell loss to apoptosis and gametogenesis, maintaining gonadal arm cell numbers at a rough steady state of ~1000 during adulthood (Fig. 1). Only 220 meiotic cells give rise to gametes on average; others contribute to oocyte growth by streaming cytoplasmic content [40] and can undergo apoptosis. The germ-line mutation rate is low (3 × 10−9 to 10–8 per site per generation [31, 32]) and timing of reproduction is critical to worm fitness [41]. Therefore, both minimization of mutation accumulation and early production of differentiated cells are important performance objectives for the worm germ line. We first sought to establish whether the MZ’s tubular organization can efficaciously minimize pedigree depth when combined with a cell cycle gradient. The minimal average pedigree depth of the ~3000 germ cells produced over the lifetime of a gonadal arm is log2(3000) = 11.55. This minimal value can only be reached by keeping all cells in a cycling state until the time the population number reaches its final value; the body of a young adult C. elegans hermaphrodite could most likely not fit such a high number of germ cells. We thus asked whether average pedigree depth of differentiated cells can be minimized to a value close to its theoretical minimum even with an MZ of limited size. We used the simulations outlined in Box 1 and detailed in “Methods.” The length of the mitotic cell cycle was modeled as a linear gradient, varying from 2.8 h at the proximal edge of the mitotic zone to a value at the distal end that was free to vary above a minimum of 2.8 h (2.8 h is the shortest cycle length we observed experimentally during germ-line development; Fig. 3a and experimental results detailed in the following). The value at the distal end was allowed to vary between each of four ranges of developmental stages (pre-L4 larval stages, L4 stage, L4 + 1 day i.e. first day of adulthood, and L4 + 3 days); however, the MZ length and width did not vary between developmental stages. Thus, this simulation had six free parameters: MZ width and length (sampled such that total MZ cell number was no more than 2000), and distal cell cycle length for each developmental stage. These six parameters were optimized as described in “Methods” to minimize pedigree depth of the first 3000 differentiated cells. The minimal pedigree depth, achieved with an MZ comprising 359 cells, was 11.74 (Table 1, optimization 1; full optimization results are given in Additional file 1: Table S1); this is close to the theoretical minimum of 11.55.Box 1


Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation.

Chiang M, Cinquin A, Paz A, Meeds E, Price CA, Welling M, Cinquin O - BMC Biol. (2015)

Simulation setup. Agent-based simulations used to characterize the dependence of pedigree depth on the spatiotemporal profile of cell cycle lengths comprised control of cell cycle length by position along the distal–proximal axis, cell movement through the mitotic and meiotic zones, and eventual differentiation or apoptosis. The spatial domain of the MZ was defined by a lattice of positions that could be occupied by at most one cell at a time. The lattice was rectangular (with length and width that were either predetermined or that were set by parameters over which optimization was performed), or had a shape defined from experimental measurements. The lattice was seeded with a single primordial cell located at the distal end. As this cell divided, its descendants filled the MZ first width-wise and then length-wise, with daughter cells being pushed laterally or proximally as cells behind them (i.e. more distal to them) divided. To mimic the cone-like structure of the gonad, cells at either end of a given row could be displaced in a way that they wrapped around to the other end of the same row (a, red arrow). Once daughter cells were pushed beyond the last MZ row, they exited the mitotic cell cycle and differentiated by entering the meiotic zone. The meiotic zone was modeled as a first-in-first-out queue, with cells entering at the distal end as they left the MZ, and exiting at the proximal end as they underwent apoptosis or matured as an oocyte. The length of the mitotic cell cycle was modeled as a linear gradient, controlled at the distal end of the MZ and at its proximal end by two parameters with value greater than 2.8 h (b, double-ended arrows; some cell cycle fit simulations allowed for a third, more proximal control point shown with a dashed line; see “Results”). Depending on the kind of simulation, cell length values at the control points were allowed to change at various developmental stages (see Table 1); in this case, the cell cycle length was linearly interpolated along the time axis in addition to the space axis.
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Related In: Results  -  Collection

License 1 - License 2
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getmorefigures.php?uid=PMC4538916&req=5

Fig6: Simulation setup. Agent-based simulations used to characterize the dependence of pedigree depth on the spatiotemporal profile of cell cycle lengths comprised control of cell cycle length by position along the distal–proximal axis, cell movement through the mitotic and meiotic zones, and eventual differentiation or apoptosis. The spatial domain of the MZ was defined by a lattice of positions that could be occupied by at most one cell at a time. The lattice was rectangular (with length and width that were either predetermined or that were set by parameters over which optimization was performed), or had a shape defined from experimental measurements. The lattice was seeded with a single primordial cell located at the distal end. As this cell divided, its descendants filled the MZ first width-wise and then length-wise, with daughter cells being pushed laterally or proximally as cells behind them (i.e. more distal to them) divided. To mimic the cone-like structure of the gonad, cells at either end of a given row could be displaced in a way that they wrapped around to the other end of the same row (a, red arrow). Once daughter cells were pushed beyond the last MZ row, they exited the mitotic cell cycle and differentiated by entering the meiotic zone. The meiotic zone was modeled as a first-in-first-out queue, with cells entering at the distal end as they left the MZ, and exiting at the proximal end as they underwent apoptosis or matured as an oocyte. The length of the mitotic cell cycle was modeled as a linear gradient, controlled at the distal end of the MZ and at its proximal end by two parameters with value greater than 2.8 h (b, double-ended arrows; some cell cycle fit simulations allowed for a third, more proximal control point shown with a dashed line; see “Results”). Depending on the kind of simulation, cell length values at the control points were allowed to change at various developmental stages (see Table 1); in this case, the cell cycle length was linearly interpolated along the time axis in addition to the space axis.
Mentions: What is the optimal compromise between minimization of mutation accumulation and early production of differentiated cells, and what is the resulting optimal stem-cell cycling speed? The answers to these questions depend on the relative costs of mutation accumulation and of delaying the production of differentiated cells. We tackle this problem within the context of the C. elegans hermaphroditic gonadal arm, which over the reproductive lifetime of an individual produces ~3000 cells that differentiate by entering meiosis. Cells leaving the MZ ensure compensation of germ-cell loss to apoptosis and gametogenesis, maintaining gonadal arm cell numbers at a rough steady state of ~1000 during adulthood (Fig. 1). Only 220 meiotic cells give rise to gametes on average; others contribute to oocyte growth by streaming cytoplasmic content [40] and can undergo apoptosis. The germ-line mutation rate is low (3 × 10−9 to 10–8 per site per generation [31, 32]) and timing of reproduction is critical to worm fitness [41]. Therefore, both minimization of mutation accumulation and early production of differentiated cells are important performance objectives for the worm germ line. We first sought to establish whether the MZ’s tubular organization can efficaciously minimize pedigree depth when combined with a cell cycle gradient. The minimal average pedigree depth of the ~3000 germ cells produced over the lifetime of a gonadal arm is log2(3000) = 11.55. This minimal value can only be reached by keeping all cells in a cycling state until the time the population number reaches its final value; the body of a young adult C. elegans hermaphrodite could most likely not fit such a high number of germ cells. We thus asked whether average pedigree depth of differentiated cells can be minimized to a value close to its theoretical minimum even with an MZ of limited size. We used the simulations outlined in Box 1 and detailed in “Methods.” The length of the mitotic cell cycle was modeled as a linear gradient, varying from 2.8 h at the proximal edge of the mitotic zone to a value at the distal end that was free to vary above a minimum of 2.8 h (2.8 h is the shortest cycle length we observed experimentally during germ-line development; Fig. 3a and experimental results detailed in the following). The value at the distal end was allowed to vary between each of four ranges of developmental stages (pre-L4 larval stages, L4 stage, L4 + 1 day i.e. first day of adulthood, and L4 + 3 days); however, the MZ length and width did not vary between developmental stages. Thus, this simulation had six free parameters: MZ width and length (sampled such that total MZ cell number was no more than 2000), and distal cell cycle length for each developmental stage. These six parameters were optimized as described in “Methods” to minimize pedigree depth of the first 3000 differentiated cells. The minimal pedigree depth, achieved with an MZ comprising 359 cells, was 11.74 (Table 1, optimization 1; full optimization results are given in Additional file 1: Table S1); this is close to the theoretical minimum of 11.55.Box 1

Bottom Line: Computational simulations of mutation accumulation characterize a tradeoff between fast development and low mutation accumulation, and show that slow-cycling stem cells allow for an advantageous compromise to be reached.Experimental measurements of cell cycle lengths derived using a new, quantitative technique are consistent with these predictions.Our findings shed light both on design principles that underlie the role of stem cells in delaying aging and on evolutionary forces that shape stem-cell gene regulatory networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Developmental & Cell Biology, University of California, Irvine, California, USA.

ABSTRACT

Background: Stem cells are thought to play a critical role in minimizing the accumulation of mutations, but it is not clear which strategies they follow to fulfill that performance objective. Slow cycling of stem cells provides a simple strategy that can minimize cell pedigree depth and thereby minimize the accumulation of replication-dependent mutations. Although the power of this strategy was recognized early on, a quantitative assessment of whether and how it is employed by biological systems is missing.

Results: Here we address this problem using a simple self-renewing organ - the C. elegans gonad - whose overall organization is shared with many self-renewing organs. Computational simulations of mutation accumulation characterize a tradeoff between fast development and low mutation accumulation, and show that slow-cycling stem cells allow for an advantageous compromise to be reached. This compromise is such that worm germ-line stem cells should cycle more slowly than their differentiating counterparts, but only by a modest amount. Experimental measurements of cell cycle lengths derived using a new, quantitative technique are consistent with these predictions.

Conclusions: Our findings shed light both on design principles that underlie the role of stem cells in delaying aging and on evolutionary forces that shape stem-cell gene regulatory networks.

No MeSH data available.


Related in: MedlinePlus