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

In silico identification of switching nodes in metabolic networks

Mairet, Francis

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.
Section: Evolutionary Biology ; Topics: Evolution, Genetics/genomics, Population biology

The impact of social complexity on the efficacy of natural selection in termites

Roux, Camille; Ha, Alice; Weyna, Arthur; Lode, Morgan; Romiguier, Jonathan

10.24072/pcjournal.476 - Peer Community Journal, Volume 4 (2024), article no. e101.
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In eusocial species, reproduction is monopolized by a few reproductive individuals.From the perspective of population genetics, this implies that the effective population size (Ne) of these organisms is likely to be smaller compared to solitary species, as has been proposed in the literature for eusocial hymenoptera. In this study, we investigate the genomic consequences of eusociality in termites (Isoptera) on two different timescales. First, by analyzing transcriptome data from 66 Blattodea species, we focus on the ratio of non-synonymous to synonymous mutations d_N/d_S as a marker of natural selection efficiency and effective population size. Our results demonstrate an elevated d_N/d_S ratio in termites compared to other members of Blattodea, further generalizing the idea that convergent evolution toward eusociality strongly reduces the effective population size and the genome-wide efficiency of natural selection. Then, by comparing 68 termite transcriptomes, we show that this decrease in natural selection efficiency is even more pronounced in termites displaying high levels of social complexity. This study contributes to understanding the complex interplay between social structures and natural selection patterns, highlighting the genetic footprint of eusociality in shaping the evolution of termites.
Section: Ecotoxicology & Environmental Chemistry ; Topics: Agricultural sciences, Ecology, Statistics

Identifying pesticide mixtures at country-wide scale

Cairo, Milena; Monnet, Anne-Christine; Robin, Stéphane; Porcher, Emmanuelle; Fontaine, Colin

10.24072/pcjournal.472 - Peer Community Journal, Volume 4 (2024), article no. e100.
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Wild organisms are likely exposed to complex mixtures of pesticides owing to the large diversity of substances on the market and the broad range agricultural practices. The consequences of such exposure are still poorly understood, first because of potentially strong synergistic effects, making cocktails effects not predictable from the effects of single compounds, but also because little is known about the actual exposure of organisms to pesticide mixtures in nature. We aimed to identify the number and composition of pesticide mixtures potentially occurring in French farmland, using a database of pesticide purchases in postcodes. We developed a statistical method based on a model-based clustering (mixture model) to cluster postcodes according to the identity, purchase probability and quantity of 279 active substances. We found that the 5,642 French postcodes can be clustered into a small number of postcode groups (ca. 20), characterized by a specific pattern of pesticide purchases, i.e. pesticide mixtures. Substances defining mixtures can be sorted into “core” substances highly probable in most postcode groups and “discriminating” substances, which are specific to and highly probable in some postcode groups only, thus playing a key role in the identity of pesticide mixtures. We found 12 core substances: two insecticides (deltamethrin and lambda-cyhalothrin), six herbicides (glyphosate, diflufenican, fluroxypyr, MCPA, 2,4-d, triclopyr) and four fungicides (fludioxonil, tebuconazole, difenoconazole, thiram). The number of discriminating substances per postcode group ranged from 2 to 74. These differences in substance purchases seemed related to differences in crop composition but also potentially to regional effects. Overall, our analyses return (1) sets of molecules that are likely to be part of the same pesticide mixtures, for which synergetic effects should be investigated further and (2) areas within which biodiversity might be exposed to similar mixture composition. This information will hopefully be of interest for future ecotoxicological studies to characterise the actual impacts of pesticide cocktails on biodiversity in the field.
Section: Genomics ; Topics: Agricultural sciences, Genetics/genomics, Population biology

Trends in genome diversity of small populations under a conservation program: a case study of two French chicken breeds

Bortoluzzi, Chiara; Restoux, Gwendal; Rouger, Romuald; Desnoues, Benoit; Petitjean, Florence; Bosse, Mirte; Tixier-Boichard, Michèle

10.24072/pcjournal.474 - Peer Community Journal, Volume 4 (2024), article no. e99.
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Livestock biodiversity is declining globally at rates unprecedented in human history. Of all avian species, chickens are among the most affected ones because many local breeds have a small effective population size that makes them more susceptible to demographic and genetic stochasticity. The maintenance of genetic diversity and control over genetic drift and inbreeding by conservation programs are fundamental to ensure the long-term survival and adaptive potential of a breed. However, while the benefits of a conservation program are well understood, they are often overlooked. We here used temporal whole-genome sequencing data to assess the effects of a conservation program on the genetic diversity (Δπ), deleterious variation (ΔL), and inbreeding (ΔF) of two local French chicken breeds, the Barbezieux and Gasconne. We showed that when the conservation program is consistent over time and does not undergo any major organisational changes (i.e., Barbezieux), the loss of genetic diversity is limited. This was true for both pedigree and genomic inbreeding but also for the genetic load estimated from functionally important genome-wide variants. However, when a conservation program is interrupted or re-initiated from scratch (i.e., Gasconne), the loss of genetic diversity can hardly be limited as a result of the bottleneck effect associated with the re-sampling. Our results reinforce the imperative to establish and sustain existing conservation programs that aim to keep populations with a relatively small effective population size from the brink of extinction. Moreover, we conclude by encouraging the use of molecular data to more effectively monitor inbreeding at the genome level while improving fitness by tracking protein-coding and non-coding deleterious variants.

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The network image was drawn by Martin Grandjean: A force-based network visualization CC BY-SA