SONNE – International

Abstract Since the development of DNA microarrays and later RNA bulk sequencing, testing with statistically independent samples has been the standard method for detecting genes with different transcription patterns. Single-cell assays challenge these assumptions because individual cells are statistically dependent, and all proposed methodologies present mathematical limitations or computational bottlenecks that prevent a seamless integration of data from many cells and patients simultaneously. In this work, we solve this crucial limitation by introducing a Bayesian framework that retrieves the independence structure at the level of individual patients, separating differences across individuals from actual transcriptional differences. Leveraging multi-GPU and variational inference, our approach excels across different experimental designs and scales to analyse over 10 million cells. This framework enables single-cell differential expression analysis that can finally integrate datasets from large clinical cohorts, atlas projects, or drug-response screens with thousands of samples and millions of cells.

Fusarium head blight (FHB), caused by Fusarium graminearum, poses a significant threat to wheat production in Ethiopia, causing yield losses of up to 30–70

HIV-1 escape from neutralizing antibodies, even in the presence of strong host immunity, is associated with variations in envelope proteins that drive antigenic diversification. The virus exploits the error-prone nature of reverse transcriptase, generating substantial genetic diversity that facilitates immune evasion. In this context, while monospecific antibody responses against invading pathogens are well characterized, the functional relevance of multispecific or cross-reactive antibodies in limiting viral escape remains poorly understood. Interestingly, the immune system often produces cross-reactive antibodies, with an anticipated role in neutralizing point mutations in HIV surface proteins by cross-reacting with mutants and tolerating them. In light of this paradox, we investigated immune evasion in the context of observed antibody cross-reactivity by screening single-chain variable fragment (scFv) antibodies against several crucial HIV-1 gp41 epitopes using a phage display library. Selected cross-reactive scFvs were biochemically characterized for binding affinity and their ability to recognize envelope protein and its mutants expressed on the cell surface. High-affinity cross-reactive scFvs showed physiologically relevant affinities for peptide epitopes, their analogs, and the native HIV-1 gp41 protein. We determined the crystal structure of a high-affinity, cross-reactive scFv DE94, and gained insights into the molecular interactions of scFv antibodies with peptide epitopes and their natural mutants using molecular docking studies. This analysis provides mechanistic insight into antibody multispecificity and could contribute to the development of therapeutics against immune-evading pathogens and pave the way for innovative strategies to combat viral infections, including emerging global threats.

African trypanosomiasis is a neglected tropical disease transmitted by tsetse flies ( Glossin a spp.) in sub-Saharan Africa. The fly’s saliva carries parasitic unicellular trypanosomes, such as Trypanosoma brucei , leading to infections in humans, domestic animals, and wildlife. Tsetse flies feed on a broad spectrum of hosts, including humans, elephants, buffaloes, rhinos, hippos, turtles and monitor lizards. To understand how the insects can penetrate such diverse skin types, we detailed the anatomical structures involved in tsetse blood feeding, their mechanical properties and the forces exerted by the fly during probing. We found that the tsetse fly’s feeding apparatus does not rely on exceptionally unique structures or extraordinary forces. Instead, the tsetse fly has evolved subtle yet highly efficient adaptations, which include a labellum equipped with arrays of small teeth. When combined with a robust retraction movement of the proboscis, these structures create lesions on various types of skin, thus facilitating blood pool feeding on a broad host spectrum.

Climate change is expected to heighten the risk of epidemics and outbreaks of coffee leaf rust (CLR), caused by the obligate parasite Hemileia vastatrix, as reported in the literature. While knowledge is available on rising temperatures’ effects on CLR epidemiological processes, fewer studies have explored combined temperature-atmospheric carbon dioxide (CO 2 ) impacts, with contrasting findings on CLR incidence and severity. CLR epidemics are multifactorial, and controlled-condition experiments targeting individual components help anticipate pathogen behavior under future climates. Urediniospore germination, a time-efficient indicator, enables exploration of pathogen responses across diverse temperature-CO 2 combinations, providing insights into CLR epidemiological shifts. We investigated H. vastatrix urediniospore germination under varying combinations of temperature and atmospheric CO 2 in controlled conditions (in phytotrons), testing thirty combinations of temperatures (16°C to 32°C), and atmospheric CO 2 concentrations (181 to 707 ppm). The fitted generalized linear model with a binomial distribution within an augmented design framework to our data was robust (pseudo-R²=0.78) and revealed that germination probability followed a quadratic pattern as a function of varying atmospheric CO 2 , with optima dependent on both CO 2 and temperature. Urediniospore germination probabilities are optimized (pmax) below the current CO 2 (424 ppm) at 24°C (pmax=0.45) and 28°C (pmax=0.43), and above 424 ppm at 16°C (pmax=0.34) and 32°C (pmax=0.35). This indicates that elevated CO 2 can partly compensate for less suitable temperatures while reducing germination within the current optimal range. Overall, our results highlight a trade-off in which rising CO 2 reshapes, rather than uniformly increases, infection opportunities under climate change, providing new data for future risk models.