Mathias Franz

Profiling of Arabidopsis Secondary Metabolites by Capillary Liquid Chromatography Coupled to Electrospray Ionization Quadrupole Time-of-Flight Mass Spectrometry

Large-scale metabolic profiling is expected to develop into an integral part of functional genomics and systems biology. The metabolome of a cell or an organism is chemically highly complex. Therefore, comprehensive biochemical phenotyping requires a multitude of analytical techniques. Here, we describe a profiling approach that combines separation by capillary liquid chromatography with the high resolution, high sensitivity, and high mass accuracy of quadrupole time-of-flight mass spectrometry. About 2,000 different mass signals can be detected in extracts of Arabidopsis roots and leaves. Many of these originate from Arabidopsis secondary metabolites. Detection based on retention times and exact masses is robust and reproducible. The dynamic range is sufficient for the quantification of metabolites. Assessment of the reproducibility of the analysis showed that biological variability exceeds technical variability. Tools were optimized or established for the automatic data deconvolution and data processing. Subtle differences between samples can be detected as tested with the chalcone synthase deficient tt4 mutant. The accuracy of time-of-flight mass analysis allows to calculate elemental compositions and to tentatively identify metabolites. In-source fragmentation and tandem mass spectrometry can be used to gain structural information. This approach has the potential to significantly contribute to establishing the metabolome of Arabidopsis and other model systems. The principles of separation and mass analysis of this technique, together with its sensitivity and resolving power, greatly expand the range of metabolic profiling.

Network-based diffusion analysis: a new method for detecting social learning

Social learning has been documented in a wide diversity of animals. In free-living animals, however, it has been difficult to discern whether animals learn socially by observing other group members or asocially by acquiring a new behaviour independently. We addressed this challenge by developing network-based diffusion analysis (NBDA), which analyses the spread of traits through animal groups and takes into account that social network structure directs social learning opportunities. NBDA fits agent-based models of social and asocial learning to the observed data using maximum-likelihood estimation. The underlying learning mechanism can then be identified using model selection based on the Akaike information criterion. We tested our method with artificially created learning data that are based on a real-world co-feeding network of macaques. NBDA is better able to discriminate between social and asocial learning in comparison with diffusion curve analysis, the main method that was previously applied in this context. NBDA thus offers a new, more reliable statistical test of learning mechanisms. In addition, it can be used to address a wide range of questions related to social learning, such as identifying behavioural strategies used by animals when deciding whom to copy.

Social enhancement can create adaptive, arbitrary and maladaptive cultural traditions

Many animals are known to learn socially, i.e. they are able to acquire new behaviours by using information from other individuals. Researchers distinguish between a number of different social-learning mechanisms such as imitation and social enhancement. Social enhancement is a simple form of social learning that is among the most widespread in animals. However, unlike imitation, it is debated whether social enhancement can create cultural traditions. Based on a recent study on capuchin monkeys, we developed an agent-based model to test the hypotheses that (i) social enhancement can create and maintain stable traditions and (ii) social enhancement can create cultural conformity. Our results supported both hypotheses. A key factor that led to the creation of cultural conformity and traditions was the repeated interaction of individual reinforcement and social enhancement learning. This result emphasizes that the emergence of cultural conformity does not necessarily require cognitively complex mechanisms such as ‘copying the majority’ or group norms. In addition, we observed that social enhancement can create learning dynamics similar to a ‘copy when uncertain’ learning strategy. Results from additional analyses also point to situations that should favour the evolution of learning mechanisms more sophisticated than social enhancement.

Stable heterosexual associations in a promiscuous primate

Close associations between adult males and females are rare among group-living, nonmonogamous mammals but may mark the transition from life in promiscuous bisexual groups to groups of pairs or pair living. Although heterosexual friendships have been described in baboons, these are short-term affairs serving as protection against infanticide and thus tightly linked to the presence of vulnerable infants. Long-term association may be adaptive in situations of low male monopolization potential where it pays to invest in a particular female partner instead of spreading the effort among many females. Using long-term data, we investigated maleefemale and maleeinfant associations in wild Assamese macaques, Macaca assamensis. Group-wide and individual maleefemale associations were stable for at least 2 or 3 years. Association during the mating season but not before the mating season predicted male mating success, lending support to the ‘friends with benefits’ but not the ‘mating effort’ hypothesis. Mating success in turn predicted maleefemale association at birth as well as maleeinfant association before weaning. In support of the ‘paternal care hypothesis’ paternity was an independent predictor of maleeinfant association beyond weaning age, creating potential for true paternal care. We thus postulate that particular demographic and life history circumstances may favour maleefemale friendships by creating a positive feedback between maleefemaleeinfant associations driven by paternal care and maleefemale associations promoted by increased mating access to drive the evolution of long-term maleefemale bonds.

Self-organizing dominance hierarchies in a wild primate population.

Linear dominance hierarchies, which are common in social animals, can profoundly influence access to limited resources, reproductive opportunities and health. In spite of their importance, the mechanisms that govern the dynamics of such hierarchies remain unclear. Two hypotheses explain how linear hierarchies might emerge and change over time. The ‘prior attributes hypothesis’ posits that individual differences in fighting ability directly determine dominance ranks. By contrast, the ‘social dynamics hypothesis’ posits that dominance ranks emerge from social self-organization dynamics such as winner and loser effects. While the prior attributes hypothesis is well supported in the literature, current support for the social dynamics hypothesis is limited to experimental studies that artificially eliminate or minimize individual differences in fighting abilities. Here, we present the first evidence supporting the social dynamics hypothesis in a wild population. Specifically, we test for winner and loser effects on male hierarchy dynamics in wild baboons, using a novel statistical approach based on the Elo rating method for cardinal rank assignment, which enables the detection of winner and loser effects in uncontrolled group settings. Our results demonstrate (i) the presence of winner and loser effects, and (ii) that individual susceptibility to such effects may have a genetic basis. Taken together, our results show that both social self-organization dynamics and prior attributes can combine to influence hierarchy dynamics even when agonistic interactions are strongly influenced by differences in individual attributes. We hypothesize that, despite variation in individual attributes, winner and loser effects exist (i) because these effects could be particularly beneficial when fighting abilities in other group members change over time, and (ii) because the coevolution of prior attributes and winner and loser effects maintains a balance of both effects.

Rapid evolution of social learning

Culture is widely thought to be beneficial when social learning is less costly than individual learning and thus may explain the enormous ecological success of humans. Rogers (1988. Does biology constrain culture. Am. Anthropol. 90: 819–831) contradicted this common view by showing that the evolution of social learning does not necessarily increase the net benefits of learned behaviours in a variable environment. Using simulation experiments, we re‐analysed extensions of Rogers’ model after relaxing the assumption that genetic evolution is much slower than cultural evolution. Our results show that this assumption is crucial for Rogers’ finding. For many parameter settings, genetic and cultural evolution occur on the same time scale, and feedback effects between genetic and cultural dynamics increase the net benefits. Thus, by avoiding the costs of individual learning, social learning can increase ecological success. Furthermore, we found that rapid evolution can limit the evolution of complex social learning strategies, which have been proposed to be widespread in animals.

Investigating the Impact of Observation Errors on the Statistical Performance of Network-based Diffusion Analysis

Experiments in captivity have provided evidence for social learning, but it remains challenging to demonstrate social learning in the wild. Recently, we developed network-based diffusion analysis (NBDA; 2009) as a new approach to inferring social learning from observational data. NBDA fits alternative models of asocial and social learning to the diffusion of a behavior through time, where the potential for social learning is related to a social network. Here, we investigate the performance of NBDA in relation to variation in group size, network heterogeneity, observer sampling errors, and duration of trait diffusion. We find that observation errors, when severe enough, can lead to increased Type I error rates in detecting social learning. However, elevated Type I error rates can be prevented by coding the observed times of trait acquisition into larger time units. Collectively, our results provide further guidance to applying NBDA and demonstrate that the method is more robust to sampling error than initially expected. Supplemental materials for this article may be downloaded from http://lb.psychonomic-journals.org/content/supplemental.

How feeding competition determines female chimpanzee gregariousness and ranging in the Taï National Park, Côte d'Ivoire.

Socioecological theory suggests that feeding competition shapes female social relationships. Chimpanzees (Pan troglodytes) live in fission–fusion societies that allow them to react flexibly to increased feeding competition by forming smaller foraging parties when food is scarce. In chimpanzees at Gombe and Kibale, female dominance rank can crucially influence feeding competition and reproductive success as high‐ranking females monopolize core areas of relatively high quality, are more gregarious, and have higher body mass and reproductive success than low‐ranking females. Chimpanzee females in Taï National Park do not monopolize core areas; they use the entire territory as do the males of their community and are highly gregarious. Although female chimpanzees in Taï generally exhibit a linear dominance hierarchy benefits of high rank are currently not well understood. We used a multivariate analysis of long‐term data from two Taï chimpanzee communities to test whether high‐ranking females (1) increase gregariousness and (2) minimize their travel costs. We found that high‐ranking females were more gregarious than low‐rankers only when food was scarce. During periods of food scarcity, high rank allowed females to enjoy benefits of gregariousness, while low‐ranking females strongly decreased their gregariousness. High‐ranking females traveled more than low‐ranking females, suggesting that low‐rankers might follow a strategy to minimize energy expenditure. Our results suggest that, in contrast to other chimpanzee populations and depending on the prevailing ecological conditions, female chimpanzees at Taï respond differently to varying levels of feeding competition. Care needs to be taken before generalizing results found in any one chimpanzee population to the species level. Am. J. Primatol. 73:305–313, 2011.

Capillary HPLC Coupled to Electrospray Ionization Quadrupole Time-of-flight Mass Spectrometry

Metabolite profiling in the pre-metabolomics era of the early 1970s to the late 1990s as well as the pioneering metabolomics projects since the late 1990s have been predominantly GC-MS based. GC-MS techniques are robust and well-established.Many primarymetabolites (e. g. organic acids, sugars, amino acids, sugar alcohols) can easily be derivatized and are therefore amenable to GC-MS analysis. Also, spectral databases and deconvolution algorithms are available, which help extracting meaningful information. Early on, however, it was obvious that no single analytical technique would be sufficient to achieve comprehensive coverage of the metabolome (Sumner et al. 2003). As stated from the beginning and reiterated since, the chemical diversity of metabolites makes it virtually impossible to detect all compound classes in one “catch” (Goodacre et al. 2004; Dunn et al. 2005). That is why already the first reports describing GC-MS-based metabolomics platforms emphasized the need to develop complementing LC-MSplatforms (Roessner et al. 2000). LC-MS covers in principle a much wider mass range and should allow one to target many compound classes not detectable by GC-MS. Furthermore, there is usually no need for derivatization and LC-MS offers superior options to elucidate unknown metabolites structurally. Particular fractions can easily be collected for NMR analysis and metabolites/molecular ions can be further analyzed by tandem-MS or even MSn. Hampering the adoption of LC-MS approaches for metabolomics, however, was the fact that LC-MS has only rather recently (i. e. in the 1990s) developed into a routine technology (Niessen 1999a). One might argue that the need for LC-MS-based profiling is even more pressing in plant science. A highly rich and diverse secondary metabolism is a hallmark of plant biology. Lacking the ability to avoid or to retreat from unfavorable conditions or potential foes, plants have evolved an enormous metabolic plasticity, which allows them to respond dynamically to environmental changes through the synthesis and/or degradation of particular compounds. This is complemented by the accumulation of various pre-formed defenses against microbial attack and other threats (Dixon 2001). Furthermore, many so-called secondary metabolites also apparently play major roles in primary developmental processes and as signaling molecules. Flavonoids

Rapid evolution of cooperation in group-living animals

BackgroundIt is often assumed that evolution takes place on very large timescales. Countering this assumption, rapid evolutionary dynamics are increasingly documented in biological systems, e.g. in the context of predator–prey interactions, species coexistence and invasion. It has also been shown that rapid evolution can facilitate the evolution of cooperation. In this context often evolutionary dynamics influence population dynamics, but in spatial models rapid evolutionary dynamics also emerge with constant population sizes. Currently it is not clear how well these spatial models apply to species in which individuals are not embedded in fixed spatial structures. To address this issue we employ an agent-based model of group living individuals. We investigate how positive assortment between cooperators and defectors and pay-off differences between cooperators and defectors depend on the occurrence of evolutionary dynamics.ResultsWe find that positive assortment and pay-off differences between cooperators and defectors differ when comparing scenarios with and without selection, which indicates that rapid evolutionary dynamics are occurring in the selection scenarios. Specifically, rapid evolution occurs because changes in positive assortment feed back on evolutionary dynamics, which crucially impacts the evolution of cooperation. At high frequencies of cooperators these feedback dynamics increase positive assortment facilitating the evolution of cooperation. In contrast, at low frequencies of cooperators rapid evolutionary dynamics lead to a decrease in assortment, which acts against the evolution of cooperation. The contrasting dynamics at low and high frequencies of cooperators create positive frequency-dependent selection.ConclusionsRapid evolutionary dynamics can influence the evolution of cooperation in group-living species and lead to positive frequency-dependent selection even if population size and maximum group-size are not affected by evolutionary dynamics. Rapid evolutionary dynamics can emerge in this case because sufficiently strong selective pressures allow evolutionary and demographic dynamics, and consequently also feedback between assortment and evolution, to occur on the same timescale. In particular, emerging positive frequency-dependent selection could be an important explanation for differences in cooperative behaviors among different species with similar population structures such as humans and chimpanzees.