Louis Du Plessis

Last Name

Du Plessis

First Name

Louis

ORCID

0000-0003-0352-6289

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09490 - Stadler, Tanja / Stadler, Tanja

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Publications 1 - 10 of 66

A depauperate immune repertoire precedes evolution of sociality in bees
Barribeau, Seth M.; Sadd, Ben M.; Du Plessis, Louis; et al. (2015)
Genome Biology
Background Sociality has many rewards, but can also be dangerous, as high population density and low genetic diversity, common in social insects, is ideal for parasite transmission. Despite this risk, honeybees and other sequenced social insects have far fewer canonical immune genes relative to solitary insects. Social protection from infection, including behavioral responses, may explain this depauperate immune repertoire. Here, based on full genome sequences, we describe the immune repertoire of two ecologically and commercially important bumblebee species that diverged approximately 18 million years ago, the North American Bombus impatiens and European Bombus terrestris. Results We find that the immune systems of these bumblebees, two species of honeybee, and a solitary leafcutting bee, are strikingly similar. Transcriptional assays confirm the expression of many of these genes in an immunological context and more strongly in young queens than males, affirming Bateman’s principle of greater investment in female immunity. We find evidence of positive selection in genes encoding antiviral responses, components of the Toll and JAK/STAT pathways, and serine protease inhibitors in both social and solitary bees. Finally, we detect many genes across pathways that differ in selection between bumblebees and honeybees, or between the social and solitary clades. Conclusions The similarity in immune complement across a gradient of sociality suggests that a reduced immune repertoire predates the evolution of sociality in bees. The differences in selection on immune genes likely reflect divergent pressures exerted by parasites across social contexts.
Disruption of seasonal influenza circulation and evolution during the 2009 H1N1 and COVID-19 pandemics in Southeastern Asia
Chen, Zhiyuan; Tsui, Joseph L.-H.; Cai, Jun; et al. (2025)
Nature Communications
East, South, and Southeast Asia (together referred to as Southeastern Asia hereafter) have been recognized as critical areas fuelling the global circulation of seasonal influenza. However, the seasonal influenza migration network within Southeastern Asia remains unclear, including how pandemic-related disruptions altered this network. We leveraged genetic, epidemiological, and airline travel data between 2007-2023 to characterise the dispersal patterns of influenza A/H3N2 and B/Victoria viruses both out of and within Southeastern Asia, including during perturbations by the 2009 A/H1N1 and COVID-19 pandemics. During the COVID-19 pandemic, consistent autumn-winter movement waves from Southeastern Asia to temperate regions were interrupted for both subtype/lineages, however the A/H1N1 pandemic only disrupted A/H3N2 spread. We find a higher persistence of A/H3N2 than B/Victoria circulation in Southeastern Asia and identify distinct pandemic-related disruptions in A/H3N2 antigenic evolution between two pandemics, compared to interpandemic levels; similar patterns are observed in B/Victoria using genetic distance. The internal movement structure within Southeastern Asia markedly diverged during the COVID-19 pandemic season, and to a lesser extent, during the 2009 A/H1N1 pandemic season. Our findings provide insights into the heterogeneous impact of two distinct pandemic-related disruptions on influenza circulation, which can help anticipate the effects of future pandemics and potential mitigation strategies on influenza dynamics.
Zoonotic hepatitis E virus spreads through environmental routes in pig herds–A phylodynamic analysis
Meester , Marina; Valenzuela Agüí, Cecilia; Tobias , Tijs J.; et al. (2025)
PLoS Pathogens
Worldwide, many pig farms are affected by hepatitis E virus (HEV) genotype 3, a zoonotic virus that causes hepatitis in humans. People can become infected after eating contaminated pork, making HEV control in pig farms crucial for public health. However, knowledge of HEV transmission dynamics and control options within farms is limited. Our findings reveal that HEV persists in the farm environment, enabling transmission between pigs separated in space and time. We investigated HEV transmission on two Dutch finishing farms for nine months in 2022. In both farms, samples from three compartments (confined rooms), holding 12 pens with pigs each, were collected and tested weekly across three batches (consecutively housed groups of pigs). Additionally, at least one sample per HEV-positive pen was sequenced per batch, retrieving 89 near-complete sequences. We integrated epidemiological data on duration and timing of infection with phylogenetic data to quantify transmission. We observed phylogenetic clustering of pens per compartment in both farms. In farm A, some sequences from different compartments and different batches also clustered, suggesting transmission between pigs housed separately. In farm B, only one compartment became HEV-positive during one batch. Within that compartment, between-pen transmission was efficient, with an effective reproduction number (Re) of 3.6 (95% HPD interval 1.3–6.7). The other compartments and batch may have remained HEV-negative thanks to stringent biosecurity measures applied on that farm. In farm A, the Re’s for transmission between pens within and across compartments were not significantly above 1, yet all sampled pens became positive in all batches. A combination of transmission routes, in conjunction with persistence of HEV in the environment, is required to explain why all pens tested positive. These findings show not only how HEV effectively spreads without pigs sharing housing, yet also that reduction of HEV’s zoonotic risk may be achieved by improved biosecurity within farms.
Characterizing Co-Circulating Respiratory Virus Genomic Diversity in Switzerland with Hybrid-Capture Sequencing and Phylogenetic Reconstructions: Insights into the 2023/24 Season
Bürki, Charlyne; Carrara, Matteo; Fahrni, Lea; et al. (2025)
bioRxiv
Respiratory viruses circulate yearly with strain-specific patterns. Although SARS-CoV-2 and Influenza A/B genomic surveillance is well-developed, most respiratory viruses are unevenly monitored, lacking geographical diversity to capture wider population dynamics. Consequently, insights into respiratory virus evolution are limited. We investigated the genetic diversity of these viruses within one country. During the 2023/24 season, we conducted whole-genome sequencing of 1129 clinical samples using a hybrid-capture protocol. These samples were pre-tested by real-time PCR panels throughout Switzerland. Leveraging publicly-available full-length genomes, we constructed background datasets representative of geographical diversity and built phylogenies for all viruses with more than 40 new high-quality genomes from this study. We detected 981 viruses and recovered 461 high-quality genomes, including 18 co-infections, from 437 PCR-positive and 6 PCR-negative samples. All viruses detected by PCR were also detected by sequencing in 56% of samples. The four most prevalent viruses were Influenza A/H1N1, SARS-CoV-2, RSV-A, and HPIV-3, and their seasonal spread was consistent with wastewater monitoring and influenza-like illness reports. Swiss viral genomes were representative of the global genomic diversity, with evidence for multiple introductions into Switzerland, and we identified putative Swiss clusters. In this proof-of-concept study, we focus on 3 viruses (Influenza A/H1N1, RSV-A/B, and HPIV-3), and we demonstrate the streamlined implementation of a broad respiratory virus genomic surveillance workflow with an off-the-shelf protocol and publicly-available software. In addition, we highlight additional evolutionary insights that can only be derived from genomic surveillance. Going forward, this dataset will be a useful resource for future investigations into respiratory viral genomic diversity.
Impact of the tree prior on estimating clock rates during epidemic outbreaks
Möller, Simon; Du Plessis, Louis; Stadler, Tanja (2018)
Proceedings of the National Academy of Sciences of the United States of America
Bayesian phylogenetics aims at estimating phylogenetic trees together with evolutionary and population dynamic parameters based on genetic sequences. It has been noted that the clock rate, one of the evolutionary parameters, decreases with an increase in the sampling period of sequences. In particular, clock rates of epidemic outbreaks are often estimated to be higher compared with the long-term clock rate. Purifying selection has been suggested as a biological factor that contributes to this phenomenon, since it purges slightly deleterious mutations from a population over time. However, other factors such as methodological biases may also play a role and make a biological interpretation of results difficult. In this paper, we identify methodological biases originating from the choice of tree prior, that is, the model specifying epidemiological dynamics. With a simulation study we demonstrate that a misspecification of the tree prior can upwardly bias the inferred clock rate and that the interplay of the different models involved in the inference can be complex and nonintuitive. We also show that the choice of tree prior can influence the inference of clock rate on real-world Ebola virus (EBOV) datasets. While commonly used tree priors result in very high clock-rate estimates for sequences from the initial phase of the epidemic in Sierra Leone, tree priors allowing for population structure lead to estimates agreeing with the long-term rate for EBOV.
Taming the BEAST - A Community Teaching Material Resource for BEAST 2
Barido-Sottani, Joëlle; Bošková, Veronika; Du Plessis, Louis; et al. (2018)
Systematic Biology
Phylogenetics and phylodynamics are central topics in modern evolutionary biology. Phylogenetic methods reconstruct the evolutionary relationships among organisms, whereas phylodynamic approaches reveal the underlying diversification processes that lead to the observed relationships. These two fields have many practical applications in disciplines as diverse as epidemiology, developmental biology, palaeontology, ecology, and linguistics. The combination of increasingly large genetic data sets and increases in computing power is facilitating the development of more sophisticated phylogenetic and phylodynamic methods. Big data sets allow us to answer complex questions. However, since the required analyses are highly specific to the particular data set and question, a black-box method is not sufficient anymore. Instead, biologists are required to be actively involved with modeling decisions during data analysis. The modular design of the Bayesian phylogenetic software package BEAST 2 enables, and in fact enforces, this involvement. At the same time, the modular design enables computational biology groups to develop new methods at a rapid rate. A thorough understanding of the models and algorithms used by inference software is a critical prerequisite for successful hypothesis formulation and assessment. In particular, there is a need for more readily available resources aimed at helping interested scientists equip themselves with the skills to confidently use cutting-edge phylogenetic analysis software. These resources will also benefit researchers who do not have access to similar courses or training at their home institutions. Here, we introduce the “Taming the Beast” (https://taming-the-beast.github.io/) resource, which was developed as part of a workshop series bearing the same name, to facilitate the usage of the Bayesian phylogenetic software package BEAST 2.
Investigations into the relationship between evolutionary rate variation, protein structure and codon usage
Du Plessis, Louis (2011)
BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis
Bouckaert, Remco; Vaughan, Timothy G.; Barido-Sottani, Joëlle; et al. (2019)
PLoS Computational Biology
Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.
Analysis of hyperspectral data with diffusion maps and Fuzzy ART
Xu, Rui; Du Plessis, Louis; Damelin, Steven; et al. (2009)
Proceedings of the 2009 International Joint Conference on Neural Network Conference (IJCNN 2009)
The genomes of Crithidia bombi and C. expoeki, common parasites of bumblebees
Schmid-Hempel, Paul; Aebi, Markus; Barribeau, Seth; et al. (2018)
PLoS ONE
Trypanosomatids (Trypanosomatidae, Kinetoplastida) are flagellated protozoa containing many parasites of medical or agricultural importance. Among those, Crithidia bombi and C. expoeki, are common parasites in bumble bees around the world, and phylogenetically close to Leishmania and Leptomonas. They have a simple and direct life cycle with one host, and partially castrate the founding queens greatly reducing their fitness. Here, we report the nuclear genome sequences of one clone of each species, extracted from a field-collected infection. Using a combination of Roche 454 FLX Titanium, Pacific Biosciences PacBio RS, and Illumina GA2 instruments for C. bombi, and PacBio for C. expoeki, we could produce high-quality and well resolved sequences. We find that these genomes are around 32 and 34 MB, with 7,808 and 7,851 annotated genes for C. bombi and C. expoeki, respectively—which is somewhat less than reported from other trypanosomatids, with few introns, and organized in polycistronic units. A large fraction of genes received plausible functional support in comparison primarily with Leishmania and Trypanosoma. Comparing the annotated genes of the two species with those of six other trypanosomatids (C. fasciculata, L. pyrrhocoris, L. seymouri, B. ayalai, L. major, and T. brucei) shows similar gene repertoires and many orthologs. Similar to other trypanosomatids, we also find signs of concerted evolution in genes putatively involved in the interaction with the host, a high degree of synteny between C. bombi and C. expoeki, and considerable overlap with several other species in the set. A total of 86 orthologous gene groups show signatures of positive selection in the branch leading to the two Crithidia under study, mostly of unknown function. As an example, we examined the initiating glycosylation pathway of surface components in C. bombi, finding it deviates from most other eukaryotes and also from other kinetoplastids, which may indicate rapid evolution in the extracellular matrix that is involved in interactions with the host. Bumble bees are important pollinators and Crithidia-infections are suspected to cause substantial selection pressure on their host populations. These newly sequenced genomes provide tools that should help better understand host-parasite interactions in these pollinator pathogens.

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Louis Du Plessis

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