Demographic analysis reveals gradual senescence in the flatworm Macrostomum lignano
© Mouton et al; licensee BioMed Central Ltd. 2009
Received: 9 March 2009
Accepted: 30 July 2009
Published: 30 July 2009
Free-living flatworms ("Turbellaria") are appropriate model organisms to gain better insight into the role of stem cells in ageing and rejuvenation. Ageing research in flatworms is, however, still scarce. This is partly due to culture difficulties and the lack of a complete set of demographic data, including parameters such as median lifespan and age-specific mortality rate. In this paper, we report on the first flatworm survival analysis. We used the species Macrostomum lignano, which is an emerging model for studying the reciprocal influence between stem cells, ageing and rejuvenation. This species has a median lifespan of 205 ± 13 days (average ± standard deviation [SD]) and a 90th percentile lifespan of 373 ± 32 days. The maximum lifespan, however, is more than 745 days, and the average survival curve is characterised by a long tail because a small number of individuals lives twice as long as 90% of the population. Similar to earlier observations in a wide range of animals, in M. lignano the age-specific mortality rate increases exponentially, but levels off at the oldest ages. To compare the senescence of M. lignano with that of other ageing models, we determined the mortality rate doubling time, which is 0.20 ± 0.02 years. As a result, we can conclude that M. lignano shows gradual senescence at a rate similar to the vertebrate ageing models Rattus norvegicus and Mus musculus. We argue that M. lignano is a suitable model for ageing and rejuvenation research, and especially for the role of stem cells in these processes, due to its accessible stem cell system and regeneration capacity, and the possibility of combining stem cell studies with demographic analyses.
Flatworms have been an object of ageing studies since Child's initial investigations [1, 2]. Researchers tended to focus on the role of stem cells and cell renewal during ageing, and the causal effect of regeneration and starvation on rejuvenation [2–4]. Despite these fascinating themes, the extent of flatworm ageing research remained limited in comparison to that of other model organisms such as Caenorhabditis elegans, Drosophila melanogaster and rodents. The lack of detailed demographic data partly accounts for this, as the only available data are the maximum lifespans of several species. These data, however, include many discrepancies due to non-specified or non-standardised culture conditions or culture problems such as the presence of fungal and bacterial contaminations [3, 4]. Without a basic set of demographic data, the most fundamental question – at which age can an individual be considered old? – remains unanswered. As a result, it is hard to draw any conclusions about, for example, old-age regeneration capacity or the rate of cell renewal as a function of age. Previously published data about these issues are often contradictory or ambiguous and there is still little known about senescence, rejuvenation and the causes of death in flatworms [3, 4]. This demonstrates that establishing a survival curve, median lifespan and 90th percentile lifespan is a prerequisite for the experimental design of ageing studies and should be the first step in initiating ageing research with a new model organism. Emerging ageing models are often first described demographically, after which detailed studies follow, stemming from these initial descriptions [5, 6]. Because lifespan parameters indicate when individuals can be considered young or old, they allow for choosing age groups to study biomarkers as a function of age and for experiments in which young and old worms are studied comparatively. Furthermore, the survival curve indicates what proportion of the initial cohort is alive at a certain age. Therefore, it can be used to calculate how large an initial culture set-up is needed to retain individuals at a desired age to give the experiment enough statistical power. Besides lifespan parameters, data about the age-related changes in mortality rate provide a basic measure for the rate of senescence , and can be used to study rejuvenation by experimental manipulation, such as regeneration and caloric restriction.
In this manuscript, the first flatworm survival curve and demographic dataset are presented. We used Macrostomum lignano (Rhabditophora, Platyhelminthes), which is a new model for stem cell biology, development, regeneration and the study of sexual selection [8–13], as well as an emerging model for ageing and rejuvenation research, and especially for the role of stem cells in these processes . Egger et al. suggested that, in M. lignano, repeated regeneration induces a lifespan extension and possible rejuvenation [8, 9, 11], because individuals were cut up to 59 times over a period of 26.5 months and were still able to regenerate . The demographic data in this manuscript can be used to design experiments in which mortality rate parameters are used to conclude whether repeated regeneration slows down the ageing process or induces an actual rejuvenation in comparison to uncut individuals of M. lignano.
Lifespan data of Macrostomum lignano in three replicate cohorts (1–3).
Median lifespan (days)
90th percentile (days)
Maximum lifespan (days)
more than 745
Parameters of the Gompertz fit.
(0.0006 – 0.0016)
(0.0089 – 0.0136)
(0.0008 – 0.0021)
(0.0067 – 0.0112)
(0.0007 – 0.0020)
(0.0075 – 0.0125)
Parameters of the Logistic fit.
(0.0001 – 0.0009)
(0.0162 – 0.0418)
(1.1507 – 4.7650)
(0.0010 – 0.0020)
(0.0054 – 0.0085)
(0.0000 – 0.0000)
(0.0004 – 0.0020)
(0.0079 – 0.0266)
(0.5170 – 3.6739)
(0.0002 – 0.0016)
(0.0103 – 0.0333)
(0.7049 – 4.4350)
Likelihood ratio test.
The short lifespan in comparison to other gradually ageing models and the ease of culturing makes M. lignano a suitable ageing model, but the major advantage is the presence of a very accessible stem cell system. The stem cells can be visualised and quantified in vivo, and also manipulated in several ways. Stem cells can be arrested in mitosis or in S-phase by adding colchicine or hydroxyurea respectively to the medium, or eliminated through irradiation. In contrast, the proliferation rate can also be increased by injuring the individual, which induces regeneration [11, 24–28]. Furthermore, this manuscript demonstrates that it is possible to perform demographic analyses, which are necessary to draw reliable conclusions when stem cells are studied at different ages. Because the accessible stem cell population of M. lignano can be combined with demographic studies, this species has the potential to play a key role in obtaining a better understanding of stem cell biology in tissue homeostasis, ageing, and even rejuvenation.
M. lignano is a free-living, hermaphrodite flatworm with a five-day embryonic development and a generation time of about 2–3 weeks . M. lignano was first found in 1995 in Lignano, Italy, resulting in the first lab cultures. Afterwards, it was resampled several times, and cultures have been established in several labs. [10, 11]. The species and its natural habitat is described in detail by Ladurner et al. [10, 11].
In the lab, M. lignano is easily cultured in f/2, a nutrient-enriched artificial seawater medium at a salinity of 32‰ , and incubated at 20°C with a 60% relative humidity and a 13 h:11 h light: dark cycle . Individuals are fed ad libitum with the diatom Nitzschia curvilineata, which is grown under identical conditions as the worms and can be obtained from the culture collection of algae (SAG) at the University of Göttingen (strain 48.91, http://sagdb.uni-goettingen.de) .
Survival was followed in three replicate cultures consisting of 100 individuals each. To initiate the replicates, one-day-old juveniles were put in separate wells of a 12-well plate and, by maintaining the worms individually, reproduction and hence a mixture of individuals of different ages could be avoided. About every 30 days, individuals were put into new 12-well plates with new culture medium and diatoms to maintain ad libitum food resources. The number of survivors was counted about every 10 days. As in demographic studies of other model organisms [31, 32], animals that died due to age-independent injury (for example rupture in C. elegans) were censored to ensure that the analysis reflects the natural lifespan. In M. lignano, age-independent death can be caused by infection with Thraustochytrium caudivorum . This can be recognised by the characteristic dissolution of the tail plate . In previous ageing cultures, it was observed at different ages (ranging from three weeks old to the oldest individuals in culture), which allowed us to conclude that it is age-independent. In the meantime, we were able to establish parasite-free cultures by optimising the working procedures and using the Triton treatment presented by Schärer et al. . Kaplan-Meier survival curves were constructed (for completeness, non-censored survival curves are also given in additional file 1), and the median lifespan (50% mortality), 90th percentile lifespan (90% mortality), and maximum lifespan were determined.
Characterising senescence was done by calculating the age-specific mortality rate and determining the mortality parameters of both the Gompertz and the Logistic model. The equations of these models are y(t) = A0eGt and respectively . Identifying which demographic model best fits the data and determining the mortality parameters was done by using WinModest software. This software uses the maximum likelihood method, which is based on the age distribution of deaths. The method provides better parameter estimates that are more consistent and less influenced by technical aspects of the experimental design such as sample size than those of other methods [17, 18]. The WinModest software is very straightforward in use and is made freely available by Dr. Pletcher . To determine the parameters of the Logistic model, we used the complete survival dataset of the three replicates. Because the Gompertz model describes the exponential increase in mortality rates, we used the dataset until Day 367. We chose this subset because at Day 367 the average 90th percentile was reached, and after this day there is an obvious deceleration of the increasing mortality rate. The MRDT was calculated using the formula MRDT = ln(2)/G [7, 20].
We want to thank S.D. Pletcher for his useful suggestions concerning the use of WinModest. We also want to thank W. Govaerts and A.L. Kheibarshekan for helping us to get more insight into the mathematics of model fitting. S. Mouton, M. Willems, and P. Back received funding from the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen).
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