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Proc Natl Acad Sci U S A. 2000 October 24; 97(22): 12127–12131. | PMCID: PMC17305 |
Copyright © 2000, The National Academy of Sciences Developmental Biology Parameters of self-organization in
Hydra aggregates Ulrich Technau,*† Christoph Cramer von Laue,† Fabian Rentzsch,† Susanne Luft,† Bert Hobmayer,† Hans R. Bode,‡ and Thomas W. Holstein*† †Department of Molecular Cell Biology, Darmstadt University of Technology, Schnittspahnstr. 10, 64287 Darmstadt, Germany; and ‡Department of Developmental and Cell Biology and Developmental Biology Center, University of California, Irvine, CA 92697 Received June 13, 2000; Accepted August 28, 2000. Self-organization has been demonstrated in a variety of systems
ranging from chemical-molecular to ecosystem levels, and evidence is
accumulating that it is also fundamental for animal development. Yet,
self-organization can be approached experimentally in only a few animal
systems. Cells isolated from the simple metazoan Hydra
can aggregate and form a complete animal by self-organization. By using
this experimental system, we found that clusters of 5–15 epithelial
cells are necessary and sufficient to form de novo
head-organizing centers in an aggregate. Such organizers presumably
arise by a community effect from a small number of cells that express
the conserved HyBra1 and HyWnt genes.
These local sources then act to pattern and instruct the surrounding
cells as well as generate a field of lateral inhibition that ranges up
to 1,000 μm. We propose that conserved patterning systems in higher
animals originate from extremely robust and flexible molecular
self-organizing systems that were selected for during early metazoan
evolution. Animal development is
commonly explained in terms of hierarchical genetic cascades that begin
with an initial asymmetry based on either maternal or external cues. In
Drosophila, for instance, complex cellular interactions
during oogenesis eventually lead to the local deposition of maternal
messages in the oocyte that determine the body axes ( 1, 2). In the
Xenopus embryo, a pre-established animal-vegetal asymmetry
in the egg and sperm entry point determine the location of the
anterior-posterior and the dorsoventral axes by locally initiating
genetic cascades that lead to the formation of the future organizer ( 3,
4). Less clear is how an organizer is set up in tissue without inherent
asymmetry or external cues. Only a few animal systems are amenable to the experimental analysis of
self-organization during development ( 5– 7). The simple metazoan
Hydra is particularly useful in this context, because its
body plan and any positional information can be completely destroyed
and re-established in dissociation-reaggregation studies.
Hydra consists of a single axis with a head and foot at
either end of a tubular body column. The axial pattern of the animal is
maintained by a gradient of head formation competence,
commonly referred to as the head activation gradient ( 8), or source
density gradient ( 9). The term gradient of head formation
competence, or more simply gradient of head competence, is in line with
current terminology and will be used in this work. (The term head
activation will be used for the actual process of head formation.) This
head competence gradient reflects the ability of tissue of the body
column to form a head either on bisection leading to head regeneration
at the apical end of the lower half, or on transplantation of a piece
of the body column to the body column of a second animal. The gradient
is maximal near the head decreasing down the body column and is a
relatively stable property of the body column ( 8). Head formation in
the body column is prevented by a head inhibition gradient, produced in
the head and transmitted to the body column ( 10). Tissue in which the head competence gradient has been destroyed can be
generated by dissociating Hydra into a suspension of single
cells and subsequently centrifuging them into a pellet, or aggregate.
In these aggregates, new heads appear after 2–3 days and proceed to
organize surrounding tissue into complete polyps ( 11– 16). Previous
work has shown that development of new heads and feet in aggregates
occurs by true de novo pattern formation starting from
nearly homogeneous conditions ( 12, 13). Because cells with different
levels of head competence are randomly distributed throughout the
aggregate, it is commonly assumed that head formation will occur where,
by chance, cells with higher levels of head competence happen to be
near one another. In such centers, termed activation centers, head
activation is initiated, and they act as classical organizers that are
able to recruit and instruct surrounding cells to participate in
formation of the head as well as the whole axis. Here we show that
de novo formation of activation centers minimally requires a
cluster of 5–15 epithelial cells in which head activation is taking
place. Molecular analysis shows that the conserved patterning genes
HyBra1 and HyWnt are expressed in locally
restricted areas corresponding to such clusters. Animal Culture. Polyps of the Basel strain of Hydra vulgaris were used for
all experiments. Animals were maintained as described ( 12) in mass
cultures, fed daily, and starved for 24 h before use in
experiments. Formation of Aggregates Containing Clusters of Vitally Labeled
Cells. Animals were vitally labeled with FITC- or rhodamine-labeled beads
(1-μm FITC-labeled or polychromatic Fluoresbrite plain microspheres;
Polysciences) as described ( 12). About 50% of the epithelial cells
were labeled with this procedure. To obtain cells with an elevated
level of head activation, 300 labeled animals were decapitated and
allowed to regenerate for 12 h. Regenerating tips, which are known
to be undergoing head activation ( 8), were isolated and dissociated
into a cell suspension by using dissociation medium as described ( 11).
Clusters of cells formed by swirling the cell suspension (4 ×
10 6 cells/ml) on a rotary shaker for 30 min at
10°C. The resulting suspension of cell clusters was size-fractionated
on a 5% Percoll (Amersham Pharmacia) per dissociation medium column.
The number of cells per cluster in each fraction was determined with a
compound microscope. Cluster sizes of 60 ± 12 μm (10–25
cells), 90 ± 20 μm (40–60 cells), and 120 ± 31 μm
(70–180 cells) were chosen for analysis. Cell clusters consisted
primarily of endodermal and ectodermal epithelial cells with
occasionally a few interstitial cells adhering to the periphery. To
examine the possibility that dissociated cells were undergoing cell
death, cell suspensions were stained with 4′,6-diamidino-2-phenylindole
dihydrochloride and analyzed for signs of chromatin fragmentation ( 17).
Within the time frame of the experiment, single cells, which make up
80–90% of the cell suspension used for aggregation, showed completely
normal nuclear morphology and no indication of apoptosis. To form aggregates containing clusters of labeled cells, the heads and
feet of 300 budless polyps were removed, and the tissue was dissociated
into cells. Then, statistically 1–2 labeled clusters of a specific
size were added to an aliquot of the cell suspension and aggregates
were formed. In addition to the labeled clusters, these aggregates
contained 4,300 ± 500 unlabeled epithelial cells. During the
development of the aggregates, the fraction of clusters found within
developing heads was determined. In Situ Hybridization. Aggregates containing 8,000–10,000 epithelial cells were formed and
allowed to develop. In situ hybridization analysis was
performed as described ( 18) with slight modifications. RNA probes were
prepared by amplifying directly from plasmids by PCR. They were used at
a concentration of about 0.05 ng/μl. Statistical Analysis. Statistical significance was calculated by using the log likelihood
ratio test ( G test) based on calculated probabilities of
binomial distributions of observed frequencies ( 19). The null
hypothesis was rejected at the 95% confidence limit. Curve fitting was
done by using igor pro 3.3 software (WaveMetrics,
Lake Oswego, OR). A Cluster of a Small Number of Cells from Head-Regenerating Tips
Acts as an Organizer. A crucial parameter of self-organization is the minimum number of cells
that are necessary for the formation of a head activation center, or
organizer. One approach to this question is to add clusters of
different numbers of labeled cells undergoing head activation to an
aggregate, and determine the minimum cluster size that is capable of
inducing a head (Fig. ) (see
Materials and Methods). Both control aggregates without
clusters and aggregates with clusters formed a total of two heads (Fig.
B and C). When
labeled cell clusters were added to the carrier cell suspension, about
half were found in a developing head (Fig. A and
C). This was true for all three cluster sizes (Fig.
D). The effect was even more pronounced when the carrier
tissue consisted of the lower four-fifths of the body column. In this
case, two-thirds of the 90- and 120-μm clusters were in developing
heads (Fig. D). Because the clusters contained only
0.2–4% of the cells in an aggregate, the high frequency of the
appearance of the clusters in developing heads was not random. Instead,
the results suggest that the cell clusters are involved in head
induction.
In contrast, when 5–15 labeled single cells (each ≈ 30 μm in
diameter) derived from regenerating tips were added to the cell
suspension, virtually none were later found in developing heads (Fig.
D). Similarly, when clusters were formed from cells of the
body column that have a lower level of head competence, they were
localized in developing heads at a low level (2–10%; Fig.
D, open symbols), reflecting a statistical chance of being
incorporated into a new head. A straightforward interpretation of these
results is that clusters containing as few as 5–15 cells undergoing
head activation, which corresponds to a cluster of 40–60 μm in
diameter, have the capacity to act as a head-organizing center in an
aggregate. The fact that a minimal number of cells undergoing head
activation is necessary and sufficient to act as a head organizer
suggests that a community effect ( 20) between these cells might be
involved in the creation of an organizer. Models based on reaction-diffusion mechanisms provide an explanation
for the self-organization of an organizer ( 9, 21– 25). These models
assume a short-ranging activator and a long-ranging inhibitor. Because
the production of the inhibitor is stimulated by the autocatalytic
activator, they both have their maximum in the same location. In a
field of virtually identical cells, random fluctuations in the
activator concentrations are amplified by the autocatalysis of the
activator leading to the generation of a stable pattern of local
activation and lateral inhibition that functions as a prepattern for
axial differentiation. The small cell clusters that were introduced in
the experiment give a measure of the minimal requirements these random
fluctuations have to meet to act as new organizers. Besides the minimal organizer size, the range of the activator, which
is the mean distance a molecule can travel between its production and
disappearance ( 26), is of crucial importance for self-organization
models. The range of the activator can be tentatively deduced as
follows. The model predicts that fluctuations (i.e., clusters) smaller
than the activator range will not be amplified because they lose
activator too rapidly to the environment by diffusion. In contrast,
cluster sizes that are similar to the activator range will amplify
quite well, whereas clusters larger than the activator range will not
have any further advantage in inducing heads. Thus, the rate of
activation increase of an activation center, or cluster, is expected to
reach a maximum once the cluster size is larger than the range of
activation. This rate is crucial for the decision whether or not an
activation center will be amplified or will decay. Accordingly, the
activation range is probably not much larger than the size of a cluster
(more precisely its radius) capable of inducing the formation of a
head, which would be about 45 μm for a 90-μm cluster (about 2–3
epithelial cell diameters). Clusters of Cells in Which Head Activation Occurs Inhibit the
Formation of Heads Within Their Vicinity. The second central component of a reaction-diffusion mechanism is the
inhibitor that is produced by the activation center and transmitted to
the surrounding tissue to prevent the initiation of another activation
center. To obtain direct evidence concerning the presence and dimension
of an inhibitory field, the following experiment was performed. A
120-μm cell cluster labeled red and a 60-μm cell cluster labeled
green, both derived from regenerating tissue undergoing head
activation, were added to carrier tissue and allowed to develop as
usual. The larger clusters were found significantly more often in heads
than were the smaller clusters (90% vs. 50%; Fig.
A and B;
P < 0.01). This suggests that the larger cluster
exerted an inhibitory influence on the smaller cluster. The failure or
success of a 60-μm cluster to form a head was tightly correlated with
its distance from the nearest head. About 50% of the 60-μm clusters
were not involved in head formation at a distance of 600 μm,
whereas essentially all were in heads at 1,000 μm (Fig.
C). This indicates an effective range for the inhibition of
about 800–900 μm.
A characteristic of a reaction-diffusion mechanism is that the range of
inhibition is much greater than that of activation. The results
obtained here are consistent with that condition. The range of
activation, as deduced from the size of cell clusters able to induce
head formation, is about 45 μm. In comparison, the range of
inhibition (800–900 μm) is easily 20 times longer. These results are
consistent with calculations based on a reaction-diffusion mechanism.
In their pioneering paper, Gierer and Meinhardt ( 22) assume a 15-fold
difference in diffusion constants between activator and inhibitor.
Later, MacWilliams ( 8), to account for a variety of Hydra
transplantation phenomena, assumed an even greater difference
leading to a very small activated and large inhibited area in a
proportion-regulating version of the Gierer-Meinhardt model. In comparison, intact polyps can reach a size of about 2,000–4,000
μm before they start forming a second head during bud formation at a
distance of about 2,000 μm from the adult head. Whereas this is
beyond the inhibition range as determined in our aggregate assay, it is
explained by the shallow gradient of the head competence, which reaches
quite low levels at this distance from the head. At very low levels of
head competence, the autocatalysis is less efficient and head
activation less likely to occur, even at lowest levels of inhibition.
In fact, Meinhardt ( 9) showed by modeling that the generation and
maintenance of the graded competence is the critical factor for
maintaining a single organizing region even when the length of the
animal appears to exceed the range of the inhibition. Consistent with
this view is that treatment with diacylglycerol ( 27),
which raises the head competence gradient, results in the formation of
ectopic heads along the body column. Production of Head Inhibition Is Not Tightly Coupled with an
Increase in Head Activation. If the increase in lateral inhibition were tightly linked to the
increase in activation, the spacing should be equal and more or less
regular under all conditions, i.e., irrespective of the average level
of head competence in the aggregate. We tested this prediction by
analyzing aggregates made from tissue of either the apical halves (with
a high level of head competence) or the basal halves (with a low level
of head competence) of the body column. Several parameters indicated
that the prediction was not met. Aggregates made from apical tissue
formed more heads than did aggregates derived from basal tissue despite
the fact that basal aggregates were 1.5 times larger on average (Table
1). This is also reflected in the average
area per head, which is >4 times larger for heads in basal
aggregates compared with those in apical aggregates. Were the increase
in lateral inhibition closely coordinated with the increase in head
activation, one would expect a similar average area per head.
| Table 1Spacing of head formation in aggregates from apical and
basal tissue |
More significant is the highly irregular spacing of heads formed in
apical tissue. Were the increase in lateral inhibition tightly linked
to the increase in activation, one would expect the spacing between
heads to be quite regular. Instead, the minimal distance in basal
aggregates is twice as large as that in apical aggregates (Table 1).
Perhaps the clearest measure of this greater irregularity of spacing of
heads in apical tissue aggregates is the variance index (SD per mean
value). Were heads spaced with perfect regularity, this index would
have a value of zero. Instead, the variance index is four times higher
in the apical aggregates than in basal tissue aggregates, indicating a
much higher degree of irregularity in apical aggregates (Table 1). These results suggest that the increase in inhibition is not tightly
linked to the increase in activation, leading to a less rigid spacing
in tissue with a high level of head competence. This is of particular
relevance for the flexibility and robustness of the system, because it
allows pattern formation to occur in a broad range of initial
conditions. A similar conclusion concerning the increase in inhibition
was drawn by MacWilliams ( 8) on the basis of transplantation
experiments. Two Hypostome Markers Indicating Cluster Behavior Reflect Organizer
Formation Accurately. Finally, we wished to gain information about early molecular patterning
events in the generation of self-organizing centers. To this end, we
examined the expression pattern of two early head genes,
HyBra1, a Hydra homologue of the T-box gene
Brachyury ( 28), and HyWnt, a homologue of
Wnt/Wg genes encoding signaling molecules ( 29). In intact
polyps, these two genes have overlapping expression patterns in the
head. Both are expressed very early during head regeneration, as well
as during bud formation, the asexual form of reproduction of
Hydra. In developing aggregates, the two layers, ectoderm
and endoderm, have formed by 24 h ( 12). At this time,
HyBra1 and HyWnt are first expressed almost
simultaneously in small spots comprising only a few endodermal cells
(Fig. A and B).
By 96 h, the HyBra1 and HyWnt spots have
enlarged to their final size in future hypostomes (Fig.
A). Interestingly, the size of the HyWnt
spots are 50–60 μm, which corresponds to the minimal cluster size
that acts as an organizer (Fig. D), whereas the
HyBra1 spots (150–200 μm) are similar in size to the
large clusters that can induce a head. Quantitative analysis shows that
all spots eventually develop into heads about 2 days later (Fig.
B).
Subsequent to the early expression of these point-source
genes, several other genes that are initially expressed uniformly
throughout the aggregate become restricted to domains where new heads
are being formed. Examples for this type of domain-restriction
behavior are HyTCF and Hyβ-catenin, two
other genes in the Wnt pathway ( 29), and the homeobox genes
Cnox3 and msx (H.R.B., unpublished results).
Thus, the results described above involving both the experiments with
clusters of cells as well as those using molecular markers support the
idea that the definition of point sources precedes the establishment of
domains in the initially symmetrical environment of an aggregate. We have shown that very small clusters of epithelial cells
expressing the conserved HyBra1 and HyWnt genes
act as head organizers during de novo pattern formation in
Hydra aggregates. Members of the T-box gene family and Wnt
pathway play crucial roles in the patterning of all higher animals ( 30,
31). The expression of these genes in the self-organization of
head-organizing centers in aggregates of Hydra, a
representative of one of the oldest metazoan phyla, strongly indicates
the antiquity of these patterning systems ( 29, 32, 33). This
pattern-forming system is able to generate complete structures (whole
organisms) starting from a broad range of initial conditions. We
therefore propose that during early metazoan evolution, an extremely
robust and flexible self-organization system involving these molecular
interactions was selected for, which became conserved during the
evolution of higher animals. We thank Patrick Lemaire for critical comments on the
manuscript. This work was supported by a postdoctoral European
Molecular Biology Organization long-term fellowship and Deutsche
Forschungsgemeinschaft Grants Te 311/1–2 to U.T. and SFB 474-B1 to
B.H. and T.W.H, and National Science Foundation Grants IBN-9723660 and
IBN-9904757 to H.R.B. 1. Ray R P, Schüpbach T. Genes Dev. 1997;10:1711–1723. [PubMed] 2. St. Johnston D, Nüsslein-Volhard C. Cell. 1992;68:201–219. [PubMed] 3. Moon R T, Kimelman D. BioEssays. 1998;20:536–545. [PubMed] 4. Harland R, Gerhart J. Annu Rev Cell Dev Biol. 1997;13:611–667. [PubMed] 5. Psychoyos D, Stern C D. Development (Cambridge, UK). 1996;122:3263–3273. [PubMed] 6. Yuan S, Schoenwolf G C. Development (Cambridge, UK). 1998;125:201–213. [PubMed] 7. Bernacki S H, McClay D R. J Exp Zool. 1989;251:203–216. [PubMed] 8. MacWilliams H K. Dev Biol. 1983;96:239–257. [PubMed] 9. Meinhardt H. Dev Biol. 1993;157:321–333. [PubMed] 10. MacWilliams H K. Dev Biol. 1983;96:217–238. [PubMed] 11. Gierer A, Berking S, Bode H R, David C N, Flick K M, Hansmann G, Schaller H, Trenkner E. Nat New Biol. 1972;239:98–101. [PubMed] 12. Technau U, Holstein T W. Dev Biol. 1992;151:117–127. [PubMed] 13. Sato M, Tashiro H, Oikawa A, Sawada Y. Dev Biol. 1992;151:111–116. [PubMed] 14. Lee P-C, Javois L. Dev Biol. 1993;157:10–18. [PubMed] 15. Sato M, Bode H R, Sawada Y. Dev Biol. 1990;141:412–420. [PubMed] 16. Sato M, Sawada Y. Dev Biol. 1989;133:119–127. [PubMed] 17. Cikala M, Wilm B, Hobmayer E, Böttger A, David C N. Curr Biol. 1999;9:959–962. [PubMed] 18. Grens A, Mason E, Marsh J L, Bode H R. Development (Cambridge, UK). 1995;121:4027–4035. [PubMed] 19. Sokal R R, Rohlf F J. Biometry. 3rd Ed. New York: Freeman; 1995. pp. 1–685. 20. Gurdon J, Lemaire P, Kato K. Cell. 1993;75:831–834. [PubMed] 21. Turing A. Philos Trans R Soc London B. 1952;237:37–72. 22. Gierer A, Meinhardt H. Kybernetik. 1972;12:30–39. [PubMed] 23. Meinhardt H. Models of Biological Pattern Formation. London: Academic; 1982. 24. Kauffman S. The Origin of Order. London: Oxford Univ. Press; 1993. 25. Harrison L G. Kinetic Theory of Living Pattern. New York: Cambridge Univ. Press; 1993. 26. Meinhardt H, Gierer A. BioEssays. 2000;22:753–760. [PubMed] 27. Müller W A. Development (Cambridge, UK.). 1989;105:309–316. 28. Technau U, Bode H R. Development (Cambridge, UK). 1999;126:999–1010. [PubMed] 29. Hobmayer B, Rentzsch F, Kuhn K, Happel C M, Cramer von Laue C, Snyder P, Rothbächer U, Holstein T W. Nature (London). 2000;407:186–189. [PubMed] 30. Smith J. Trends Genet. 1999;15:154–159. [PubMed] 31. Cadigan K M, Nusse R. Genes Dev. 1997;11:3286–3305. [PubMed] 32. Bode H, Martinez D, Shenk M A, Smith K, Steele R, Technau U. Biol Bull (Woods Hole, MA). 1999;195:408–410. [PubMed] 33. Galliot B, Miller D. Trends Genet. 2000;16:1–5. [PubMed]
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