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  • Section: Animal Science ; Topics: Agricultural sciences, Applied biological sciences, Applied mathematics

    From data on gross activity to the characterization of animal behaviour: which metrics for which purposes?

    10.24072/pcjournal.489 - Peer Community Journal, Volume 4 (2024), article no. e105.

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    The behaviour of an animal is closely linked to its internal state. Various metrics can be calculated from activity data. Complex patterns of activity within or between individuals, such as cyclic patterns and synchrony, can inform on the biological functioning, the health status, or the welfare of an animal. These patterns are now available thanks to sensors that continuously monitor the activity of individual animals over long periods. Data processing and calculations, however, should be clarified and harmonised across studies for the results to be comparable. We present metrics describing activity patterns, we discuss their significance, relevance and limitations for behavioural and welfare studies, and we detail how they can be calculated. Four groups of metrics are distinguished: metrics related to overall activity (e.g., time spent in each activity per unit of time), metrics related to fluctuations around mean activity, metrics related to the cyclicity of activity, and metrics related to the synchrony between animals. Metrics may take statistical approaches (e.g., average and variance) or modelling approaches (e.g., Fourier Transform). Examples are taken essentially from cattle for who individual activity sensors are easily available at present. The calculations, however, can be applied to other species and can be performed on data obtained from sensors as well as visual observations. The present methodological article will help researchers to obtain the most benefit from activity data and will support the decision of which metric can be used to address a given purpose.

  • Section: Network Science ; Topics: Ecology, Environmental sciences, Computer sciences

    A single changing hypernetwork to represent (social-)ecological dynamics

    10.24072/pcjournal.482 - Peer Community Journal, Volume 4 (2024), article no. e104.

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    To understand and manage (social-)ecological systems, we need an intuitive and rigorous way to represent them. Recent ecological studies propose to represent interaction networks into modular graphs, multiplexes and higher-order interactions. Along these lines, we argue here that non-dyadic (non-pairwise) interactions are common in ecology and environmental sciences, necessitating fresh concepts and tools for handling them. In addition, such interaction networks often change sharply, due to appearing and disappearing species and components. We illustrate in a simple example that any ecosystem can be represented by a single hypergraph, here called the ecosystem hypernetwork. Moreover, we highlight that any ecosystem hypernetwork exhibits a changing topology summarizing its long term dynamics (e.g., species extinction/invasion, pollutant or human arrival/migration). Qualitative and discrete-event models developed in computer science appear suitable for modeling hypergraph (topological) dynamics. Hypernetworks thus also provide a conceptual foundation for theoretical as well as more applied studies in ecology (at large), as they form the qualitative backbone of ever-changing ecosystems.

  • Wild and domestic ungulates can be infected with the same species of gastrointestinal parasitic nematodes. These parasites have free-living stages in the environment that contribute to the ease of transmission among different host species. In addition, gastrointestinal nematodes have developed resistance to anthelmintics which is now considered a major problem for the livestock sector. In a context where wild and domestic ungulates share the same pastures, the maintenance and circulation of resistant gastrointestinal nematodes between species have rarely been explored. In the European Alps, domestic sheep are driven to high-altitude summer pastures and live in sympatry with wild ungulates for several months each year. In this study, we investigated the nemabiome of domestic sheep and Alpine ibex, Capra ibex, in three different areas of the French Alps to evaluate parasite circulation between the two host species. The Alpine ibex is a protected mountain ungulate that is phylogenetically related to sheep and hosts nematode species common to sheep. Using internal transcribed spacer 2 (ITS-2) nemabiome metabarcoding, we found sheep and ibex share similar gastrointestinal nematodes, except for a few species such as Marshallagia marshalli and Trichostrongylus axei. This suggests that the long-term co-occurrence of sheep and ibex on mountain pastures has promoted the exchange of gastrointestinal nematodes between the two hosts. Based on the sequencing of the isotype 1 of the beta tubulin gene, associated with benzimidazole resistance, we found resistant nematodes in all sheep flocks and in all ibex populations. Our results demonstrated that ibex can host and shed resistant strains before transhumant sheep arrive on pastures, and thus could act as a refuge or even contribute to maintaining resistant gastrointestinal nematodes. The relative role of ibex in the maintenance and circulation of resistant strains in sheep remain to be determined.

  • Section: Mathematical & Computational Biology ; Topics: Biophysics and computational biology, Microbiology, Systems biology

    In silico identification of switching nodes in metabolic networks

    10.24072/pcjournal.480 - Peer Community Journal, Volume 4 (2024), article no. e102.

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    Cells modulate their metabolism according to environmental conditions. A major challenge to better understand metabolic regulation is to identify, from the hundreds or thousands of molecules, the key metabolites where the re-orientation of fluxes occurs. Here, a method called ISIS (for In Silico Identification of Switches) is proposed to locate these nodes in a metabolic network, based on the analysis of a set of flux vectors (obtained e.g. by parsimonious flux balance analysis with different inputs). A metabolite is considered as a switch if the fluxes at this point are redirected in a different way when conditions change. The soundness of ISIS is shown with four case studies, using both core and genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae and the diatom Phaeodactylum tricornutum. Through these examples, we show that ISIS can identify hot-spots where fluxes are reoriented. Additionally, switch metabolites are deeply involved in post-translational modification of proteins, showing their importance in cellular regulation. In P. tricornutum, we show that Erythrose 4-phosphate is an important switch metabolite for mixotrophy suggesting the importance of this metabolite in the non-oxidative pentose phosphate pathway to orchestrate the flux variations between glycolysis, the Calvin cycle and the oxidative pentose phosphate pathway when the trophic mode changes. Finally, a comparison between ISIS and reporter metabolites identified with transcriptomic data confirms the key role of metabolites such as L-glutamate or L-aspartate in the yeast response to nitrogen input variation. Overall, ISIS opens up new possibilities for studying cellular metabolism and regulation, as well as potentially for developing metabolic engineering.

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