Experimental Babesia rossi infection induces hemolytic, metabolic, and viral response pathways in the canine host

Background

Babesia rossi is a leading cause of morbidity and mortality among the canine population of sub-Saharan Africa, but pathogenesis remains poorly understood. Previous studies of B. rossi infection were derived from clinical cases, in which neither the onset of infection nor the infectious inoculum was known. Here, we performed controlled B. rossi inoculations in canines and evaluated disease progression through clinical tests and whole blood transcriptomic profiling.

Results

Two subjects were administered a low inoculum (10⁴ parasites) while three received a high (10⁸ parasites). Subjects were monitored for 8 consecutive days; anti-parasite treatment with diminazene aceturate was administered on day 4. Blood was drawn prior to inoculation as well as every experimental day for assessment of clinical parameters and transcriptomic profiles. The model recapitulated natural disease manifestations including anemia, acidosis, inflammation and behavioral changes. Rate of disease onset and clinical severity were proportional to the inoculum. To analyze the temporal dynamics of the transcriptomic host response, we sequenced mRNA extracted from whole blood drawn on days 0, 1, 3, 4, 6, and 8. Differential gene expression, hierarchical clustering, and pathway enrichment analyses identified genes and pathways involved in response to hemolysis, metabolic changes, and several arms of the immune response including innate immunity, adaptive immunity, and response to viral infection.

Conclusions

This work comprehensively characterizes the clinical and transcriptomic progression of B. rossi infection in canines, thus establishing a large mammalian model of severe hemoprotozoal disease to facilitate the study of host-parasite biology and in which to test novel anti-disease therapeutics. The knowledge gained from the study of B. rossi in canines will not only improve our understanding of this emerging infectious disease threat in domestic dogs, but also provide insight into the pathobiology of human diseases caused by Babesia and Plasmodium species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07889-4.

Dense time-course gene expression profiling of the Drosophila melanogaster innate immune response

BACKGROUND

Immune responses need to be initiated rapidly, and maintained as needed, to prevent establishment and growth of infections. At the same time, resources need to be balanced with other physiological processes. On the level of transcription, studies have shown that this balancing act is reflected in tight control of the initiation kinetics and shutdown dynamics of specific immune genes.

RESULTS

To investigate genome-wide expression dynamics and trade-offs after infection at a high temporal resolution, we performed an RNA-seq time course on D. melanogaster with 20 time points post Imd stimulation. A combination of methods, including spline fitting, cluster analysis, and Granger causality inference, allowed detailed dissection of expression profiles, lead-lag interactions, and functional annotation of genes through guilt-by-association. We identified Imd-responsive genes and co-expressed, less well characterized genes, with an immediate-early response and sustained up-regulation up to 5 days after stimulation. In contrast, stress response and Toll-responsive genes, among which were Bomanins, demonstrated early and transient responses. We further observed a strong trade-off with metabolic genes, which strikingly recovered to pre-infection levels before the immune response was fully resolved.

CONCLUSIONS

This high-dimensional dataset enabled the comprehensive study of immune response dynamics through the parallel application of multiple temporal data analysis methods. The well annotated data set should also serve as a useful resource for further investigation of the D. melanogaster innate immune response, and for the development of methods for analysis of a post-stress transcriptional response time-series at whole-genome scale.