Orchestrated immune responses of Bos indicus versus Bos taurus cattle towards vector-borne pathogens such as bluetongue virus differ significantly affecting disease outcomes

Orchestrated immune responses of Bos indicus versus Bos taurus cattle towards vector-borne pathogens such as bluetongue virus differ significantly affecting disease outcomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Orchestrated immune responses of Bos indicus versus Bos taurus cattle towards vector-borne pathogens such as bluetongue virus differ significantly affecting disease outcomes Thomas Démoulins, Thatcha Yimthin, Jing Zhang, Alexander Leonard, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7748972/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Communications Biology → Version 1 posted You are reading this latest preprint version Abstract Cattle are the mammalian species with most global biomass, encompass the two subspecies Bos taurus and Bos indicus , which are phenotypically distinguishable and have distinct genetic backgrounds as a result of their different evolutionary trajectories. We used fresh primary bovine blood cells to characterize and dissect host-pathogen interactions, hypothesizing that Bos taurus and Bos indicus cattle exhibit different immune responses towards vector-borne diseases (VBDs) impacting the clinical disease outcome. We tested Schmallenberg virus (SBV) and Bluetongue virus (BTV), examples of vector-borne pathogens responsible for recent European disease outbreaks, driven by increased vector activity linked to rising temperatures. Bos taurus cattle showed a moderate ex vivo response towards SBV compared to BTV, which indicates a fine-tuning of the immune response depending on vector-borne virus. The most striking finding was the differential immune response towards BTV: broad and over-exuberant in Bos taurus , mainly antiviral in Bos indicus . Moreover, fever-like temperature, a classical clinical sign of disease, reduced the capacity of most immune cell subsets to respond to the pathogens tested. Overall, our findings of different immune responses are in line with other studies that suggest different susceptibilities of the Bos indicus versus Bos taurus towards major pathogens like bovine tuberculosis. Biological sciences/Immunology/Infectious diseases/Viral infection Biological sciences/Immunology/Antimicrobial responses Vector-borne diseases Bos indicus Bos taurus RNA vector-borne viruses Disease susceptibility Ex vivo immune response Bluetongue virus Schmallenberg virus genetic background Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 INTRODUCTION Global food security is one of the most pressing issues for humanity, and agricultural production is critical for achieving this. However, global food security – tightly linked to trade, human health and livelihoods – is seriously threatened by vector-borne diseases (VBDs), some of which specifically affect livestock production ( 1 , 2 ). Many of these VBDs are co-endemic, and it is estimated that more than half the world’s population live in areas where two or more VBDs are present ( 3 ). Despite the obvious need to intensify efforts to prevent and control VBDs, climate change is worsening the overall situation by changing vector endemicities and exacerbating the transmission and spread of VBDs. Among VBD pathogens, the arboviruses Schmallenberg virus (SBV) and bluetongue virus (BTV) affect predominantly ruminants, causing major animal welfare issues and great economic losses. Both are transmitted by Culicoides biting midges and emerged recently in Europe ( 4 – 6 ). SBV is an orthobunyavirus identified during the initial outbreak in 2011 in Germany that spread rapidly in surrounding countries ( 7 ). Infection in adult cattle typically causes transient fever, diarrhea, and reduced milk production. In pregnant females, it may lead to abortions or severe congenital malformations in the offspring ( 5 ). BTV is an orbivirus marked by regular outbreaks in Europe since 2006, while the most recent cases occurred in 2023–2024, when serotype 3 was found in the Netherlands and spread rapidly through Northern Europe, including Switzerland ( 8 , 9 ). The global expansion of the vector due to climate change has facilitated the emergence of different viral serotypes, with 29 that have been identified through phylogenetic studies, sequencing data and cross-neutralization assays ( 10 , 11 ). Infection in adult cattle is characterized by fever, edema, hyperemia, hemorrhages, cyanosis and lameness, sometimes leading to the death of the infected animals ( 6 , 12 ) Livestock contributes nearly 40 percent of total agricultural output in developed countries and 20 percent in low-and-middle-income countries, supporting the livelihoods of at least 1.3 billion livestock-depending people worldwide. About 8,000 and 10,000 years ago Bos indicus (zebu) and Bos taurus (taurine) cattle subspecies, respectively, were domesticated from humped and humpless populations of the now extinct aurochs progenitor Bos primigenus that diverged about 30,000 years ago ( 13 ). Bos indicus have their origin in the tropical climate of the Indus Valley in what is now considered Pakistan, while Bos taurus originate from the Fertile Crescent now the Middle East ( 14 – 17 ). That period of domestication encountered robust hydroclimate variability, leading to drier and less hospitable zones such as Indus Valley, in which the increased stress fostered the evolution of new and multifaceted adaptive strategies that increased the resilience of ancient populations ( 18 ). Indeed, it is well-accepted that Bos indicus have higher heat resistance, can sustain poor nutrition, and show increased resistance to a number of pathogenic parasites such as babesiosis ( 19 ), ticks ( 20 ), and nematodes ( 21 ) compared to Bos taurus cattle. Recently we reported for the first time that Bos indicus cattle kept in Switzerland are less colonized by bacterial hoof pathogens ( 22 ) compared to taurine cattle. VBDs such as East Coast fever caused by Theileria parva affect Bos taurus cattle more than Bos indicus cattle ( 23 , 24 ). The co-evolution of Bos indicus cattle with tropical vector borne pathogens likely resulted in orchestrated immune responses controlling the pathogens, although this remains to be proved. This work aimed to test our working hypothesis that the immune response towards vector-borne pathogens such as SBV and BTV differs significantly between the two cattle subspecies Bos indicus and Bos taurus which is likely to affect the disease outcome. Moreover, we were interested in measuring the effect of fever-like temperature on immune cells to modulate the antiviral immune response, as well as immune cell interaction with SBV and BTV. In line with the 3R principles, we used an ex vivo laboratory platform employing primary blood cells of outbred animals to investigate bovine-pathogen interactions ( 25 , 26 ). Overall, we confirmed our working hypothesis and our findings provide a unique comparative approach between the immune responses of Bos taurus and Bos indicus cattle. The presented ex vivo platform will foster further research to understand disease tolerance and susceptibility in cattle, assisting selection procedures to develop resistant livestock breeds. RESULTS Previous exposure towards vector-borne viruses The cows (N Bos taurus =16, N Bos indicus =16) enrolled in the study had no prior clinical reports of BTV or SBV-related disease. They were healthy, randomly selected, bled and later tested for their seroprevalence towards BTV and SBV. Serological analysis unequivocally confirmed the absence of previous exposure to BTV in all animals, with the exception of one Bos indicus animal ( Additional file 1 ). Nevertheless, we did not discard this animal from analysis for two key reasons: i) we considered that immune cells derived from this animal might behave as outliers, in which case this would potentially highlight the accuracy and sensitivity of our ex vivo platform; ii) we considered that the inclusion of this specimen would not likely compromise any statistical outcomes, given that the study was conducted with robust sample size of eight animals per group. Different serological results were obtained for SBV, since serum samples from the majority of animals showed SBV-positive antibodies indicating previous encounter with this pathogen. Specifically, 14 out of 16 Bos taurus (87.5%); 13 out of 16 Bos indicus animals (81.2%) exhibited optical densities in the diagnostic assay referring to > 60% of those quantified in the positive control ( Additional file 1 ). These high frequencies were expected, given the geographical distribution of the virus and published data on its prevalence ( 27 ). Determination of the kinship relationship and physiological state of the cattle enrolled in the study The kinship relationship of herds of Bos taurus and Bos indicus animals enrolled in the study were reported recently ( 22 , 25 ). Thus, animals enrolled in the project are largely outbred and genetic heterogeneous, supporting the external reproducibility of our findings. Additionally, we aligned the RNA sequencing reads of all samples against the taurine reference sequence to identify and genotype variants. As described previously for variants called from RNA sequencing ( 28 ), the rather uneven alignment coverage with coverage spikes in highly expressed genes identifies substantially less variants than DNA sequencing data. More variants were called in indicine than taurine samples as expected given their higher divergence from the taurine reference sequence. A PCA conducted with a subset of 362 k variants with high genotyping rate across all samples grouped the samples into two distinct clusters representing taurine and indicine subspecies ( Additional file 2 ). Then, we investigated the concentrations of different metabolic parameters and enzyme activities related to energy metabolism in blood serums, this to ensure that no animal displayed unphysiological concentrations of free fatty acids, beta-hydroxybutyrate or glucose levels that could have impacted the immune system. Effectively, results were within the reference values of the respective physiological status, i.e. gravidity and lactation ( Additional file 3 ). Immune cell subset representation in the peripheral blood of Bos indicus and Bos taurus cattle All the stimulations performed in this study were done on blood cells isolated the same day and prepared within 4–5 hours after collection. The transport of the freshly collected blood to the laboratory was done at 20–25°C. The workflow and experimental design are summarized in Fig. 1 . Three main parameters were investigated throughout the study, namely comparison of Bos taurus versus Bos indicus cattle, vector-borne viruses BTV versus SBV, and influence of physiological temperature (38.5°C) versus fever-like temperature (41.0°C). Following the validation study conducted in Bos taurus , it was essential to confirm that the previously designed FCM antibody combinations (i.e., [Antigen presenting cells], [T cells] and [B cells, NK cells]) were applicable to Bos indicus cattle. This was successfully demonstrated, as witnessed by the clear delineation of all immune cell subsets, as well as the strong signal intensity of maturation / activation markers. A representative example of gating strategy is shown in Additional file 4 . We subsequently tested whether Bos taurus and Bos indicus exhibited comparable representation of individual immune cell subsets. At physiological temperature (38.5°C), analysis of unstimulated samples revealed a striking observation: 10 out of 13 investigated cell subsets showed different counts between the two genetic backgrounds. The three subsets comparable were cDC1s, CD8 + T cells and NK cells. Notably, except for non-classical monocytes and γδ T cells, which were significantly enriched in Bos indicus , all subsets showed a noticeable decrease compared to Bos taurus (Fig. 2 A). Those clear differences reinforced the hypothesis that Bos indicus and Bos taurus cattle are likely to exhibit distinct ex vivo responses towards VBD pathogens. Under fever-like temperature (41.0°C), the same results were overall obtained, except for non-classical monocytes and pDC subsets, that were no longer significantly different ( Additional file 5 ). Viral titers in the supernatant of stimulated primary blood cells We optimized the protocols for propagating and harvesting BTV (serotype 8 from 2008) and SBV (serotype 3 from 2011), using ultimately the BHK-21 cell line ( Additional file 6 ). This allowed us to achieve sufficient virus titers for subsequent infection of bovine PBMCs. We first tested BTV or SBV replication when exposed to primary blood cells of Bos taurus and Bos indicus at a high MOI = 0.05. For BTV, the PBMCs of both cattle subspecies promoted high and comparable titers at physiological temperature, that were slightly affected by fever-like temperature conditions (trend for Bos taurus , significant for Bos indicus ) (Fig. 2 B, left panel). Exposure to SBV led to smaller titers, with substantial divergence between Bos taurus and Bos indicus (Fig. 2 B, right panel). Indeed, PBMCs from Bos taurus were more efficient in controlling growth of SBV when compared to Bos indicus , regardless of physiological or fever-like temperatures (TCID50/ml = 1.1 × 10 2 and 5.2 × 10 2 , respectively; p < 0.01). Therefore, BTV and SBV proved to replicate differently in bovine primary blood cells; moreover, the difference measured for SBV titers between both cattle indicated distinct host-pathogen interactions, with potential consequences on disease outcome. Then, the impact of vector-borne viruses on PBMCs was roughly investigated with t-SNE algorithm (visualization of high dimensional data in a 2-D representation). Clearly, blue islands that came from samples stimulated with BTV were observable in both Bos taurus and Bos indicus , indicating that this virus at a MOI = 0.05 induces high changes of the blood cell phenotypic parameters. In comparison, orange areas who are specific to SBV stimulation were mostly stacked with areas of unstimulated samples. Nevertheless, a few orange islands were visible in Bos indicus , showing that SBV has a detectable impact on bovine blood cells (Fig. 2 C). From this, it was clear that BTV and SBV interact differently with host immune cells. Ex vivo response towards vector-borne viruses at bovine body temperature, 38.5°C We assessed the responsiveness of Bos taurus derived PBMCs to both VBD pathogens in a pilot experiment, to determine optimal MOIs (MOI = 0.05 (high), MOI = 0.005 (low)) and time points (t = 24 h and 48 h), consistent with numerous published studies. Overall, the responses of Bos taurus versus Bos indicus derived PBMCs differed significantly in their reactions to both BTV and SBV, underlining the importance of having a clear delineation of immune cell subsets for in-depth investigations (Figs. 3 and 4 ). For instance, non-classical monocytes from Bos indicus showed a clear MHC-II upregulation following exposure to BTV, whereas in Bos taurus this subset exhibited enhanced expression levels of CD25 and CCR7 (Fig. 3 A). When the same analysis was done to evaluate response to SBV, non-classical monocytes from both cattle subspecies displayed no clear activation markers, except for a slight increase in CCR7 in Bos indicus (Fig. 4 A). Overall, these findings suggest that both bovine genetic backgrounds had different non-classical monocyte counts, but also that their biological effector functions may differ. More generally, all individual immune cell types demonstrated significant differences in the magnitude of their responses, with most cases showing reactions to both viruses (including classical monocytes, non-classical monocytes, pDCs, CD21 high B cells). In some cases, responses were observed only towards BTV (in cDC1s, cDC2s, CD4 + T cells, CD8 + T cells, γδ T cells, CD20 + B cells, CD21 low B cells and NK cells) or only towards SBV (intermediate monocytes) (Figs. 3 B-D and 4 B-D). Clearly, our study supports our hypothesis that immune responses of cattle with markedly different genetic background to VBDs differ, underscoring the relevance of breed-specific immunological studies in understanding disease susceptibility and disease outcome. Induction of cytokine secretion at bovine body temperature, 38.5°C Next, we aimed to confirm the distinct magnitude of cytokine production by PBMCs in response to vector-borne viruses. Upon stimulation with BTV, the most noticeable result in Bos taurus consisted of massive levels of a set of pro-inflammatory cytokines, namely IL-1α, IL-1β, IL-6, MIP-1α (= CCL3), MIP-1β (= CCL4), and TNF-α, as well as pro-Th1 (IFN-γ) and pro-Th17 (IL-17). Additionally, as published previously for Mycoplasmopsis bovis ( M. bovis ) stimulation ( 25 ), the anti-inflammatory IL-10 paralleled this induction. Bos indicus exhibited a similar trend in cytokine induction with a clear reduction in overall cytokine levels as compared to Bos taurus , as illustrated in Fig. 5 A (upper part, heat map depicting all individual animals; lower part, radar plot showing the mean of all animals). Of note, even if the cytokine induction profiles were quite superimposable between 24 h and 48 h, the full detection of IFN-γ required the latter time point. This is why focusing on 48 h rather than 24 h offered the most exhaustive picture of cytokine release by blood cells ( Additional File 7 ). The above results obtained for BTV proved to be markedly robust compared to those observed for SBV, which were, at best, moderate (Fig. 5 B). Specifically, in Bos taurus , most cytokines were moderately induced (IFN-γ, IL-1, IL-6, etc.). Nevertheless, the immune response against SBV was still notable, revealing clear differences when comparing Bos indicus and Bos taurus . Notably, IFN-γ and IL-17 levels were enhanced in Bos taurus , while MCP-1 and VEGF-A levels were enhanced in Bos indicus . Finally, when the impact of both vector-borne viruses on PBMCs was compared for a given cattle subspecies, it was clear that BTV was a more potent inducer of cytokines / chemokines than SBV for Bos taurus , as well as for Bos indicus (Figs. 5 C and 5 D) (upper part, heat map depicting all individual animals; lower part, radar plot showing the mean of all animals). This, combined with previous results obtained by FCM, demonstrated that BTV and SBV have a divergent effect on cattle primary blood cells. Ex vivo response towards vector-borne viruses at fever-like temperature, 41°C Assessment moved on to influence of fever, typical clinical signs of severe disease caused by BTV or SBV, by raising the question of how stimulation at 41°C (high fever temperature) would influence the magnitude of PBMC response. Results illustrated in Fig. 6 A showed a negative impact in Bos taurus of the rise from 38.5°C to 41.0°C on the capacity of monocytes, T-cell and B-cell subsets, as well as NK cells, to respond to BTV, as witnessed by CD25 down-regulation. Of note, DCs kept their full capacity to upregulate CD25, as previously reported following exposure to the bacterial pathogen M. bovis ( 25 ). When the same analysis was applied to blood cells isolated from Bos indicus , the results proved to be moderate in comparison, but still noticeable for numerous subsets (classical monocytes, CD4 + , CD8 + and γδ T cells, CD21 high B cells and NK cells). Again, we failed to detect any decrease of CD25 for DC subsets at fever-like temperature, but the opposite for most animals (i.e., cDC2 subset) (Fig. 6 A). In conclusion, regardless of cattle subspecies being considered, we obtained a significant reduction of maturation / activation parameters upon interaction with BTV, virus for which we obtained the stronger response under physiological temperature. Then, the responsiveness to SBV was tested at fever-like temperature (Fig. 6 B). As expected, an overall reduction of immune subsets to maturate and activate happened to a lesser extent, but still noticeable. Indeed, febrile temperatures influenced moderately – but significantly – the lower upregulation of CD25 following exposure to SBV (negative effects on classical monocytes, cDC2s and CD21 low B cells for Bos taurus ; negative effects on cDC2s, CD4 + and γδ T cells, and CD21 low B cells for Bos indicus ). Altogether, these findings implied that under fever-like temperature conditions, bovine immune responses to SBV are impaired, possibly preventing efficient clearance. Induction of cytokine secretion at fever-like temperature, 41°C Next, we assessed cytokine secretions at 41°C (Figs. 6 C-F). When the values obtained with fever-like temperatures (41°C) were normalized to that obtained with normal bovine body temperature (38.5°C), no consistent influence was noted for unstimulated samples from Bos taurus and Bos indicus (“No virus”, mostly white pattern). In contrast, a very strong reduction was calculated for all induced cytokines produced in response to BTV, particularly clear for Bos taurus (dark blue color patterns) (Fig. 6 C), and to a lesser extent for Bos indicus (blue color patterns) (Fig. 6 D), confirming that fever-like condition attenuates PBMCs capacity to respond to BTV. The decrease of cytokine levels following SBV exposure was more difficult to quantify due to the low ex vivo response inherent to this virus; nevertheless, in line with results related to activation / maturation markers, we could still detect a negative influence for some cytokines, as witnessed by the blue color patterns visualized in Bos taurus (ie., IFN-γ, IL-17 and IP-10) (Fig. 6 E) and Bos indicus (ie., IFN-γ and IL-6) (Fig. 6 F). Finally, although 48 h is the more informative time point to get a full picture of the cytokine secretion profile, it is worth noting that the negative impact of fever-like temperature was easily found at earlier time point ( Additional file 8 ). Collectively, these results highlighted the detrimental impact of fever-like temperature on PBMC’s capacity to respond to vector-borne viruses, regardless of the cattle subspecies: optimal at normal body temperature, attenuated at febrile temperature. Correlation between multiplex immunoassay and of RNA-Sequencing analysis The relevance of subspecies-specific immunological studies in understanding disease susceptibility and resistance was implemented with a procedure of higher complexity: identification of thousands of DEGs. First, GC content of raw reads showed a normal distribution across samples, with percentage range of 40.1%-51.8%. Moreover, a range of 77.1–95.6% of reads trimmed aligned to the respective reference genomes. Among the aligned sequence reads, 70.7–95.3% of reads were assigned to gene features, with total assigned reads ranging from 36.3-85.3M. Then, we ensured that RNA-Seq analysis corroborates cytokine secretion levels obtained by multiplex immunoassay. Indeed, the induction quantified from the two independent readouts proved to strongly correlate at physiological temperature at both 24 and 48 h, but not anymore at fever-like temperature where we showed above that the bovine ex vivo response is impeded ( Additional File 9 ). Again, the magnitude of cytokine response under BTV stimulation was enhanced in Bos taurus compared to Bos indicus , particularly for IFN-γ, IL-1β and IL-12β. We then selected manually a relevant set of interferon-stimulated genes (ISGs): surprisingly, most of ISGs were more upregulated in cells derived from Bos indicus (i.e., RSAD2 , MX1 , MX2 and ISG15 ), indicating that this cattle subspecies responds to viral infections by mounting a balanced and effective immune response, whereas Bos taurus tend to poorly control their anti-BTV response, characterized by a subsequent “cytokine storm”. We then examined whether the better controlled response in Bos indicus could be attributed to increased levels of regulatory immune components (i.e., FOXP3 , LAG3 , etc.); however, comparable values were found between the two cattle subspecies, ruling out this possible explanation ( Additional File 10 ). Transcriptomic profiles of PBMCs derived from Bos taurus in response to vector-borne viruses at body temperature, 38.5°C Next, we compared the entire transcriptomic profiles of Bos taurus primary blood cells exposed to VBD viruses to unstimulated cells. Based on the first two principal components following a PCA of all genes, samples did not cluster significantly differently when stimulated with SBV, in contrast to the effects observed for BTV ( Additional File 11 ). For BTV, we found 2,275 DEGs to be significantly downregulated after stimulation, whereas 1,712 DEGs were significantly upregulated (Fig. 7 A). Venn diagrams were generated to assess the DEGs overlap between stimulation by the two vector-borne viruses; interestingly, only 260 genes were commonly found, suggesting different recognition mechanisms between BTV and SBV (Fig. 7 B). A volcano plot pointed out that the transcripts that were most significantly induced in response to BTV were involved in a broad range of functions (including pro-inflammatory activity, with IL12RB2 ), while the response towards SBV was most restricted to genes involved in regulation of the immune response ( TGFB , PILRA , CD163 ) (Fig. 7 C). To better understand the potential roles of host responses to Culicoides -borne viruses, the biological functions of DEGs were subjected to Gene Ontology (GO) enrichment. Of note, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was not considered, due to species-specific database limitations and gene annotation mismatches between Bos taurus and Bos indicus . With GO analysis, BTV infection induced a broad immune response, with significant enrichment of antiviral responses (Type I interferon receptor binding), but also Cellular and Humoral responses, Cytokine and Chemokine activity, as well as NK cell activation involved in immune response (Fig. 7 D). For SBV, when those DEGs were analyzed based on GO, then the three most significantly enriched GO terms were Transmembrane signaling receptor activity, Carbohydrate binding and Sialic acid binding (Fig. 7 E). This, combined with the previous phenotypic results, provides an unprecedented in-depth characterization of Bos taurus circulating blood cell response to vector-borne viruses. Transcriptomic profiles of PBMCs derived from Bos indicus in response to vector-borne viruses at body temperature, 38.5°C Afterwards, we investigated RNA-Seq data derived from Bos indicus animals, where the magnitude of the response towards BTV was found attenuated in terms of phenotypic readouts (multiparameter FCM and multiplex immunoassay). Nevertheless, PCA still revealed clear clustering in response to BTV stimulation, whereas samples stimulated with SBV failed to cluster away from unstimulated samples ( Additional File 11 ). The total number of DEGs induced by BTV was 1,991 (1,137 downregulated and 854 upregulated), which was less than what was observed for Bos taurus . Exposure to SBV led to a noticeable change of transcriptomic profiles compared to unstimulated PBMCs (628 downregulated and 311 upregulated). Venn diagrams were generated, showing that only 227 genes were commonly found in the response to both vector-borne viruses, suggesting also this time different recognition pathways between BTV and SBV in Bos indicus (Figs. 7 F-G). A volcano plot pointed out that the transcripts that were most significantly induced in response to BTV or SBV were involved in a broad range of functions, albeit with no clear involvement in the immune response (Fig. 7 H). The biological functions were then examined using GO enrichment analysis: this confirmed that the pathways associated with immune responses were mainly antiviral responses. Strikingly, the most enriched GO terms were a G protein-coupled receptor activity and Olfactory receptor activity (Fig. 7 I). Altogether, those results provided a new insight into the specific set of genes triggered in BTV-well adapted cattle subspecies, with clear distinctions compared to naive Bos taurus animals. Finally, GO analysis for stimulation with SBV highlighted that the enriched GO terms were unrelated to immune stimulation nor antiviral responses: Sialic acid binding, Chemoattractant activity and Collagen binding (Fig. 7 J). As for BTV, this strongly suggests that Bos taurus and Bos indicus are prone to combat SBV infection with qualitatively and quantitatively distinct immune responses. Likely, this influences the difference of disease susceptibility between the two cattle subspecies. Recent Bluetongue virus outbreak in Northern Europe By the time of this study was conducted, a novel BTV outbreak occurred in Switzerland (September 2024 – January 2025, serotype 3), affecting numerous farms, including the one from which our blood samples were collected. Interestingly, this farm cohoused Bos indicus (n = 20) and Bos taurus (n = 19) (Aubrac breed) animals, giving us the unique opportunity to investigate the link between clinical data and serological prevalence in both cattle subspecies. We found that animals of this farm seroconverted and hence were infected, with antibodies directed against BTV found in all animals but one Bos indicus . However, none of the adults belonging to Bos indicus cattle subspecies were reported to show clinical signs (despite 2 neonatal calves having fatal disease), whereas the Bos taurus group showed five adult cows with pronounced clinical signs, demonstrating unequivocal higher susceptibility for the Bos taurus animals. DISCUSSION The two genetically distinct subspecies of cattle, Bos indicus and Bos taurus , arose from independent domestication events 8,000 and 10,000 years ago, respectively. As a result, the subspecies display substantial phenotypic and tissue-specific gene expression differences ( 12 , 29 ). Moreover, indicine and taurine cattle breeds show epigenetic divergence across immune cell types ( 17 ). Among others, Bos indicus are known for decades to be more resistant to emerging animal diseases compared to Bos taurus due to a longer period of adaptation ( 12 , 19 – 22 ). In the specific case of BTV, a study monitored infections in > 500 indigenous Bos indicus animals in western Kenya, from birth to death or 12 months of age. The results showed a very high prevalence (∼ 0.95), with heterogeneous serotypes and long viral persistence, but stinkingly no overt clinical signs in any cattle ( 30 ). The present study aimed to compare innate and adaptive immune responses of both cattle subspecies, by assessing their ex vivo responses to VBD pathogens recently emerged in Europe due to global warming. We took advantage of the fact that Switzerland houses around hundred Bos indicus cattle, that are kept under similar production systems and infection pressure. Although we only enrolled female animals due to availability, we do not assume that male animals show markedly different immune responses. Identifying the mechanisms responsible for controlling specific pathogens in cattle represents an essential step in developing predictive phenotypic markers and foster efficient vaccine development. We focused our analysis on primary blood cells rather than performing in vivo challenge experiments. This way we followed the 3Rs principles and used protocols that can be implemented in other labs besides being economic in terms of costs. It is important to consider that following the bite of an infected vector, many VBD viruses replicates shortly in endothelial cells before spreading to peripheral tissues via the blood stream ( 31 – 34 ). It is also known that ovine CD4 + and WC1 + γδ T cells, as well as bovine CD4 + , CD8 + , and WC1 + γδ T cells, can be productively infected by BTV ( 33 ). Besides, the prolonged presence of BTV in circulation has been reported following infection ( 35 ), associated with acute immunosuppression and substantial lymphopenia, enabling BTV to evade the host immune response ( 36 ). For all these reasons, we evaluated the specific interactions of vector-borne viruses with host PBMCs, that furthermore offer the advantage to comprise most immune cell subsets that cooperate to mount efficient innate and adaptive immune response. Genetic analysis of Swiss zebu indicates high genomic diversity and clear separation from taurine cattle ( Additional File 2 , ( 22 )). Furthermore, the relatively high genetic diversity of Swiss zebu, particularly when compared to Holstein, suggests that inbreeding remains low despite their small population size in Switzerland, supporting external reproducibility of the present findings ( 37 ). However, a potential drawback in the comparison of both cattle subspecies is the poor evaluation of the impact of usage differences: Bos taurus are normally subjected to greater metabolic stress due to their dairy use that can impact the immune system, whereas Bos indicus are mainly used for beef production. In the present study, we ruled out this potential bias by showing that all enrolled animals displayed physiological concentrations of free fatty acids, beta-hydroxybutyrate or glucose levels with no indication of metabolic stress ( Additional File 3 ). We started our immunological comparison with the investigation of possible qualitative and/or quantitative differences in frequencies of different immune cell subsets in the two cattle subspecies tested. Available data on such frequencies to date are rather sparse and inconsistent, mainly due to restricted use of antibodies that impeded proper delineation. In a study done more than a decade ago, Bos indicus animals were reported to have higher percentage of CD4 + T cells, while Bos taurus animals had relatively higher percentages of macrophage-type cells (monocytes and MHCII-expressing cells) in their circulation ( 38 ); this conflicts somehow with our findings employing up-to-date 12-color panels in the FCM analysis. In a more recent study, overrepresentation of γδ T cells was reported in Bos indicus ( 39 ), which is in line with our data. Altogether, our study showed clear differences in the frequencies of different immune cell subsets, correlating with genetic background. Corroborating this statement, we found a clear distinctive phenotype and anti-BTV response for monocytes derived from Bos indicus animals: classical monocytes had a phenotype reminiscent of migratory subset (CCR7 upregulation), whereas non-classical monocytes acted like “hyper presenting cells”, as witnessed by the high MHC-II upregulation. Finally, it is worth noting that the stimulation of bovine PBMCs by vector-borne viruses required to extend cell culture for 48 h, implying modulation of cell surface proteins on subsets like DCs or monocytes ( Additional File 4 ); indeed, it is known that those antigen presenting cells tend to differentiate or die ex vivo , requiring some caution before extrapolating our results to what occurs in vivo ( 40 ). BTV affects wild and domestic ruminants, with cattle being natural reservoirs due to persistence in the blood of some animals for relatively long periods, facilitating horizontal transmission by Culicoides ( 35 ). Since dsRNA is detected by toll-like receptors (TLR) 3 and retinoic acid inducible gene (RIG-1)-like family receptors ( 41 ), it was expected to observe triggering of the production of interferon and other pro-inflammatory cytokines to activate an antiviral response to combat the infection. This was effectively the case, where a clear type I antiviral response was detected in both cattle subspecies (RNA-Seq analysis, Additional File 10 and Fig. 7 ). Clearly, anti BTV response in Bos taurus specimen was accompanied by the secretion of a large panel of cytokine / chemokine, whereas Bos indicus ex vivo response was mainly restricted to antiviral immune components. This broader response in Bos taurus animals could be attributed to monocytes or B cells, involved in the sensing of the infection, given that their transcriptome was previously shown to have viral recognition and sensing of the infection signatures at early timepoints ( 42 ). This assumption was not obvious in the present study for monocytes – notably because of the aforementioned differences in terms of phenotype and functions in both cattle subspecies. In contrast, CD21 high B cells showed a clear over-activation in Bos taurus compared to Bos indicus specimens (CD25 induction: 5.4 and 2.6, respectively, Fig. 3 D), making this subset a potential contributor to the excessive immune response. Nevertheless, a particular observation implied that monocytes play a key role in fighting BTV infection in Bos indicus animals which is not surprising. Indeed, an outlier animal exhibited a very strong response to BTV (i.e., CD25 and CCR7 upregulation on classical monocytes; MHC-II on non-classical monocytes, IFN-γ secretion). Remarkably, this specific animal had BTV-specific antibodies in its serum indicating previous encounter with BTV. Interestingly, a few reports have described in ruminants the capacity of monocytes and macrophages to be trained and have memory-like traits such as persistent hyperactivation for several months ( 43 , 44 ), which was likely to be the case in our study. Finally, besides a key role of monocytes in early interaction with BTV, our study points out some immune specificity of Bos indicus , possibly a result of the selection pressure with tropical vector-borne pathogens in the Indus Valley that resulted in better adaptation of their immune system to combat efficiently tropical vector borne diseases. A likely explanation of disease susceptibility in Bos taurus subspecies would be that the high magnitude of the ex vivo response led to over-exuberant immune response in vivo , responsible for inflammation of the mucous membranes. Indeed, dampening of the immune response by regulatory mechanisms is necessary to prevent collateral damage and severe disease course, even if this impairs pathogen clearance ( 45 ). In line with this, previous transcriptomic analysis of in vitro BTV infection of ovine and caprine PBMCs, two particularly susceptible animal species, have shown activation of genes belonging to PRR and cytokine/chemokine signaling pathways, similarly to what we detected in Bos taurus subspecies ( 46 ). Moreover, another study pointed out the key role played by CD4 + , CD8 + and γδ T cells in susceptibility versus resistance to BTV disease ( 47 ). Loss of CD4 + T cells was found to exacerbate the disease, making this subset a potential key player in disease resistance; indeed, we found CD4 + T cells more activated in Bos indicus. In contrast, loss of CD8 + T cell subset was shown to be associated with lower clinical scores and higher survival; herein, this potential disease contributor was effectively more activated in Bos taurus (Fig. 3 C). Finally, WC1 + γδ T cells were reported to be protective against BTV; considering that this subset is over-represented in Bos indicus at steady state gives another likely explanation why zebu cattle are more resistant (Fig. 2 A). An alternative possibility would be that the enhanced expression of ISGs reported in susceptible animals induce a faster host cell protein synthesis shutoff, resulting in a premature downregulation of antiviral proteins required for BTV clearance ( 48 ). This is not in line with our observation related to “cytokine storm” in cells derived from Bos taurus animals (Fig. 5 , Additional File 6 and 10) . SBV was detected for the first time in November 2011 in plasma samples collected from cows displaying fever and diarrhea ( 7 ). Unlike BTV, SBV is now endemic in Europe and particularly in Switzerland. It can infect a broader range than only domestic livestock, with specific antibodies witnessing previous exposures detected in free-ranging wild and exotic ruminants, pointing out the reasons why some species are more susceptible to disease ( 49 – 51 ). Importantly, SBV specific antibodies are known to persist at least 12–24 months in cattle after natural infection ( 52 ), which explained the high prevalence found in our study. Also, one might argue that the moderate effects observed with SBV were due to a low MOI used in our assays, but very low dose of virus are sufficient for animal challenge (10 3 -2.10 3 TCID50), with no gain in using enhanced viral load ( 52 ). Moreover, the percentage of infected cells in vitro , such as of primary fibroblast, is also very low (∼ 30%) with high dose of SBV (MOI = 5) ( 53 ), giving a solid explanation why we had moderate readouts in our phenotypic approach compared to BTV. Finally, the low ex vivo response measured herein can be attributed to strong interference of SBV with the IFN pathway. Indeed, previous studies emphasized the role of nonstructural (NS) protein in shutting down the immune response of the host, and NS removal was shown to favor the restoration of an antiviral response a set of antiviral genes ( 53 , 54 ). Another study showed that shutting down genes of the host innate response was mainly due to Mx inhibition ( 55 ), although this was not clearly seen in the present study ( Additional File 10 ). Nevertheless, despite the overall low responses, our results suggest that Bos indicus blood cells interact more with SBV than the ones derived from Bos taurus animals, with more DEGs, even if most of functions involved were not related to immune responses. Finally, we only investigated host responses at 48 h p.i., while other time points might have identified other DEGs. Another major finding of the present study was the detrimental impact of fever-like temperature on ex vivo responses towards vector-borne viruses. Fever is a clinical hallmark of infection, which in turn is associated with a negative impact on the clinical disease outcome ( 42 ). Overall, our data showed clearly a reduced capacity of cells – with the exception of some DC subsets – to respond to vector-borne viruses, confirming our previous observation with M. bovis , another important bovine pathogen ( 25 ). Despite fever like temperature is a common physiological characteristic of immune responses, it is still poorly understood in terms of impact on immune cells that have to fight infection and mediate inflammation. Herein, the most striking observation under fever-like temperature was the strongly reduced capacity to rapidly produce IFN-γ (Fig. 9 G). Given the crucial role that this cytokine plays in promoting both innate and adaptive immunity against intracellular pathogens ( 56 ), this contributed to the attenuation of the ex vivo responses towards BTV, and to a lesser extent SBV. Interestingly, a recent study also showed that febrile temperatures selectively affect the metabolism of a variety of T cell types – reported to be productively infected by BTV ( 33 ) –, driving to their apoptosis ( 57 ). Consequently, this could lead to less favorable conditions for viral replication, leading to lower viral titers and attenuation of associated ex vivo responses. Conclusive remarks The fine deciphering of host immune responses of the different cattle subspecies towards vector-borne viruses highlighted distinct immune responses triggered by the two subspecies. These immune responses are likely to correlate with a differential control of the pathogen. This paves the road for better understanding of better control and resistance towards infections with tropical VBD by Bos indicus . Our platform has great prospects for screening different cattle breeds for their immune responses towards pathogens to identify resistant breeds that can be further tested and enrolled in breeding programmes and to understand immunity that can be elicited by rational vaccines. MATERIALS AND METHODS Ethics statement The collection of bovine blood was performed in compliance with the Swiss animal protection law (TSchG SR 455; TSchV SR 455.1; TVV SR 455.163) under the cantonal license BE55/2022. The application was reviewed by the cantonal committee on animal experiments of the cantons of Bern, Fribourg and Solothurn, Switzerland, and approved by the veterinary authority of the canton of Bern (Amt für Landwirtschaft und Natur LANAT, Veterinärdienst VeD, Bern, Switzerland). Selection of cattle used for the study Switzerland is home to > 100 Bos indicus cattle besides the many Bos taurus subspecies. We took advantage of the presence of both cattle subspecies for sampling, since the infection pressure and livestock production systems are similar and allow a side-by-side analysis. Serological screening of previous exposure towards Bluetongue and Schmallenberg viruses At the time of enrollment in this study, animals had no previous reports of Bluetongue or Schmallenberg virus-related disease. Previous exposure towards both pathogens was investigated serologically on all animals using the Bluetongue Virus Antibody Test Kit, cELISA v2 (VRMD, VRMD Inc, Pullman, WA) and ID Screen Schmallenberg virus Indirect Multi-species kit (Innovative Diagnostic, France). Serum from venous blood to be tested was collected from the animals using standard methods employing vacutainer serum tubes (Becton Dickinson). Measurement of metabolic blood parameters Concentrations of different metabolic parameters and enzyme activities related to energy metabolism were analysed in blood serum. Analysis was carried out using an autoanalyzer (Cobas Pure c303) and commercially available assays validated for bovines. Variant calling from RNA sequencing data Total RNA was isolated from bovine blood cells using the TRIzol reagent and sequenced using next generation sequencing (see below). Paired-end RNA sequencing reads were aligned to the Bos taurus taurus reference sequence (ARS-UCD2.0, GCA_002263795.4) and RefSeq (release 106) annotation using the splice-aware aligner STAR (v2.7.11b) ( 58 ). We used SAMtools (v1.21) ( 59 ) for collating alignments by name, marking duplicates, and coordinate sorting. Variants were called from the aligned bam files using DeepVariant (v1.5) ( 60 ) using the “--split_skip_reads” and the v1.4 RNA checkpoint model. All samples were merged using GLnexus (v1.4.1) ( 61 ). We used plink (v1.90) ( 62 ) to create binary files containing 6,509,257 autosomal variants of which we retained 362,134 that had minor allele frequency greater than 0.01 and were genotyped in at least 90% of the 156 samples. Principal component analysis (PCA) was conducted with plink, and hierarchical clustering was performed with the hclust function in R. Virus propagation and titration A German BTV serotype 8 from 2008 (isolate: BTV-8_D/07_1) and a SBV serotype 3 (isolate: BH80/11 − 4) ( 7 ) were kindly provided by Gert Zimmer from the Swiss Institute of Virology and Immunology (IVI). Baby hamster kidney (BHK) 21 cells were obtained from the IVI and grown in Glasgow’s minimal essential medium (GMEM; Life Technologies) supplemented with 10% fetal bovine serum (FBS). BHK-21 cells were expanded to propagate both viruses. For the stock production, frozen BTV-8 and SBV were recovered from storage, thawed for 1–2 min at 37°C, and added to the cells, at a multiplicity of infection (MOI) = 0.01 in a total volume of 30 mL per flask. After 48 h, the cytopathogenic effect (CPE) reached approximately 80% (cell rounding and extensive cellular monolayer disruption), so that the cultures were frozen at -70˚C, to disrupt the BHK-21 cells and release the virus. The freeze-thaw cycle was done twice, after what cell debris were sedimented by centrifugation at 250 × g and 4°C for 10 min, and the supernatants were aliquoted and frozen at -70°C until further use in the next few months. Infectious virus titers were determined on BHK-21 cells and were calculated according to the Spearman-Kärber method and expressed as 50% tissue culture infectious doses per mL (TCID50/mL). Isolation of bovine peripheral blood mononuclear cells (PBMCs) Blood from Bos taurus cows (n = 16, Holstein Friesian breed, aged 1–3 years) was collected at the Agroscope research facility in Posieux, Switzerland. The donor cattle enrolled in the study belonged to a herd not mingling with other animals outside the facility. Blood of Bos indicus cows (n = 16, Zebu breed, aged 1–14 years) was collected in two farms in the cantons of Bern and Solothurn. 30–50 mL of blood was obtained by jugular vein puncture ( Bos taurus ) or tail vein puncture ( Bos indicus ) into vacutainer EDTA tubes (Becton Dickinson). For PBMC isolation, blood was first centrifuged at 1,000 × g for 20 min. Then the buffy coat was collected and diluted with PBS containing 1 mM UltraPure™ EDTA (Invitrogen) to a ratio of 1 to 1 before being layered onto Ficoll Paque (1.077 g/mL; GE Healthcare Europe GmbH). After centrifugation (800 × g for 25 min), PBMCs were collected and washed twice with cold PBS containing 1 mM EDTA (Invitrogen) (350 × g for 10 min). If needed, erythrocytes were lysed by resuspending the pellet with 1–2 mL of H2O and washed immediately with 48 mL of cold PBS containing 1 mM EDTA and centrifuged (350 × g for 10 min). A final washing step was done at 250 × g for 10 min to remove platelets. Stimulation of bovine PBMCs Blood cell stimulation employed flat-bottom 6-well plates (TPP, Switzerland). Per well, 5 × 10 6 cells were cultured in 3 mL Dulbecco’s modified Eagle’s medium (DMEM) (Life Technologies) supplemented with 10% FBS (Life Technologies). Importantly, all tests were run either at 38.5°C (bovine body temperature) or at 41.0°C (high fever temperature). Stimulation with BTV or SBV was done at a MOI = 0.05 (high MOI) or 0.005 (low MOI), for 48 h, based on preliminary experiments. At 24 h and 44 h post infection (p.i.), 50–100 µl of cell culture supernatant was collected and frozen at -20°C for subsequent cytokine secretion measurement using a bead based multiplex immunoassay (see below). At 44 h p.i., Brefeldin A (10 µg/mL) (ThermoFisher) was added to the medium to block cytokine secretion; incubation was extended for another 4 h, to allow the de novo cytokine synthesis measurement employing flow cytometry (FCM) intracellular staining. Multiparameter flow cytometry (FCM) assay Application of multiparameter FCM assay has been described elsewhere ( 25 ), apart from very few changes of antibodies and fluorophores: in house conjugation of CD3 employed Zenon Alexa Fluor 568 labelling kit (instead of Alexa Fluor 532 Antibody Labeling Kit), CD45RO (clone IL-A116) replaced CD44. Otherwise, combination staining and gating strategies remained unchanged, analyzing monocytes (classical, intermediate and non-classical), cDCs (cDC1s and cDC2s), pDCs, γδ T cells, NK cells, CD4 + and CD8 + T cells, and B cells. For the acquisitions, cells from the whole samples were accumulated. For the fold-change analysis of activation / maturation marker following stimulation, the mean fluorescence intensity (MFI) measured in stimulated sample for a given cow was normalized to the MFI measured in unstimulated sample from that same animal. For the counts of immune cell subtypes, we calculated the percentage of total events: ratio [number of events in the gated cell subtype] to [number of all events, excepting cell aggregates and debris]. This readout was preferred to absolute counts because PBMC enumeration was performed under the light microscope with Trypan blue exclusion, raising the possibility of human factors introducing bias and irrelevant disparity between samples. In contrast, the percentage of total events is an accurate and unbiased picture that reflects what is found in the peripheral blood ( 63 ). FCM acquisitions were performed on a Cytek Aurora (Cytek Biosciences) using the SpectroFlo software with autofluorescence extraction, and further analyzed with FlowJo 10.9.0 (TreeStar). Multiplex bead-based immunoassay The commercial MILLIPLEX Bovine Cytokine/Chemokine Magnetic Bead Panel 1 - Immunology Multiplex (Merck) employed here has been described elsewhere ( 25 ). Of note, chemokines are named in the figures with their “historical names”, which adhere to the names used in the manufacturer’s manual. However, the recent nomenclature states that the new names for the chemokines are CCL3 (C-C motif ligand 3), CXCL10 (C-X-C motif ligand 10), CCL2, and CCL4 for MIP-1α, IP-10, MCP-1 and MIP-1β, respectively. RNA isolation, library preparation and sequencing For RNA sequencing, total RNA from 156 samples was extracted from cultured PBMCs using TRIzol reagent (ThermoFisher). In short, 2 × 10 6 cells were lysed with 1 mL of TRIzol reagent and kept at -70°C until the RNA was handed over to the sequencing facility for analysis. The RNA quantification, library preparation and sequencing were conducted by Novogene (Novogene Co., Ltd., Munich, Germany). In summary, the quantity and quality of the total RNA sample was evaluated by Nanodrop and Agilent 5400. Messenger RNA (mRNA) was purified from total RNA using poly-T oligo-attached magnetic beads. Following fragmentation, the first-strand cDNA was synthesized using random hexamer primers followed by the second-strand cDNA synthesis. Library preparation involved end repair, A-tailing, adapter ligation, size selection, amplification, and purification. The library quality was assessed using Qubit for quantification, real-time PCR for amplification verification, and a bioanalyzer for size distribution analysis. Quantified libraries were pooled and paired-end sequenced on the NovaSeq X Plus platform (Illumina, San Diego, CA, USA) based on effective library concentration and desired data volume. Bioinformatic analysis of RNA-seq data RNA-seq data analysis was carried out on the servers of the Linux Cluster of the Interfaculty Bioinformatics Unit at the University of Bern. Sequence quality was first assessed with FastQC (Available at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc (version 0.12.1)). Adapter sequences were removed and reads with a Phred base quality threshold below 15 (Q < 15) or shorter than 15 bp were filtered out using fastp ( 64 ) (version 0.22.0). High-quality reads were mapped to the Bos taurus and Bos indicus reference genomes (ARS-UCD2.0 GCF_002263795.3 and UOA_Brahman_1 GCF_003369695.1, respectively) using STAR ( 58 ) (version 2.7.11b). FeatureCounts ( 65 ) (version 2.0.6) was employed to quantify the number of reads assigned to each gene. Read quality and alignment was generated with MultiQC ( 66 ) (version 1.22.2). Two samples were removed from downstream analysis due to low mapping rates. Differential gene expression analysis between experimental groups was conducted using the Bioconductor DESeq2 package ( 67 ). All analyses were carried out in R (version 4.4). Raw read counts were normalized and rlog-transformed across all samples for exploratory data analysis using PCA and hierarchical clustering. For unbiased analysis, stimulated samples of each subset were compared to corresponding control samples. Differentially expressed genes (DEGs) were identified based on an adjusted p value threshold of 0.05 and an absolute log 2 fold change greater than 1. Functional enrichment analysis of all DEGs were accomplished on the basis of the gene ontology (GO) database using DAVID (Database for Annotation, Visualization and Integrated Discovery) ( 68 , 69 ). Statistical analysis Statistical analysis was done using the GraphPad Prism 8 software (GraphPad software, La Jolla, CA, USA). To determine differences between groups, paired t tests, non-parametric paired Wilcoxon tests or one-way repeated measure ANOVA followed by Geisser-Greenhouse correction were used, as appropriate. Associations were tested using the Spearman rank correlation test. A p value < 0.05 was considered statistically significant (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001). Declarations Acknowledgments We thank Stephanie Talker, James Prendergast and Olivier Hanotte for useful discussion and the Swiss Zebu farmers for their collaboration; Bernd Hoffmannfor supplying the viruses. We are grateful to the previous and current Jores lab members not listed as authors for lively discussions and assistance. Data availability “Mapping assemblies”, i.e., called variants after mapping reads to the bovine reference genome version ARS-UCD1.3 (GCF_002263795.2) (Holstein = PRJEB66341; Zebu; PRJEB67281). RNA sequencing data have been deposited in the European Nucleotide Archive (ENA) and can be retrieved from Bioproject PRJEB96282. Accession numbers for the raw data are available in Additional File 12 . Ethics statement The collection of ruminant blood was performed in compliance with the Swiss animal protection law (TSchG SR 455; TSchV SR 455.1; TVV SR 455.163) under the cantonal license BE55/2022. 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1","display":"","copyAsset":false,"role":"figure","size":382841,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow chart depicting the experimental set-up. \u003c/strong\u003eBlood sampling, peripheral blood mononuclear cell (PBMC) isolation and incubation, to final readouts consisting of either multiplex immunoassays (Milliplex), flow cytometry (FCM) or RNA Sequencing (RNA-Seq). Each symbol represents an individual animal.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/4c9124c29ce8d23ed4f9fbec.png"},{"id":94369760,"identity":"1f7e4f32-f26c-47c6-8ca0-61de09a7a3bb","added_by":"auto","created_at":"2025-10-27 13:19:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":794642,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCapacity of vector-borne viruses to replicate in primary blood cells of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBos taurus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBos indicus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Comparison of immune cell subset counts between \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e in peripheral blood. Violin plots show all animals enrolled in the study. Cattle subspecies were compared using two-tailed Mann–Whitney U. A p value \u0026lt; 0.05 was considered statistically significant (* p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001, **** p \u0026lt; 0.0001). (\u003cstrong\u003eB\u003c/strong\u003e) Virus titer detected in supernatant from infected primary blood cells. PBMCs from 8 individual animals per group were stimulated for 48 h with BTV or SBV, MOI = 0.05. Supernatants were collected and the virus titer were determined using a TCID50 assay with BHK-21 cells. Data are presented as the mean ± SEM of the virus titer from 8 individual animal per group. Each symbol represents an individual animal. Statistics employed non-parametric paired Wilcoxon tests (38.5 °C versus 41.0 °C) or Mann–Whitney U-tests (\u003cem\u003eBos taurus\u003c/em\u003e or \u003cem\u003eBos indicus\u003c/em\u003e). Stars indicate significance levels. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001. (\u003cstrong\u003eC\u003c/strong\u003e) The live primary blood cells from 8 animals were merged to create a single t-SNE map with the signal strength of all phenotypic markers for the 3 combination staining: “APCs”, “T cells” and “B cells, NK cells”. Blue islands came from samples stimulated with BTV, whereas orange areas are specific to SBV stimulation. The t-SNE algorithm used perplexity value of 30 and 1000 iterations. Grey zones: unstimulated cells; Blue zones: BTV-stimulated cells; Orange zones: SBV-stimulated cells. APCs: Antigen Presenting Cells.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/9f4e58cdef4d0265860c1b7c.png"},{"id":94369597,"identity":"19edff8f-ed40-41f3-be66-9bdd36c576e9","added_by":"auto","created_at":"2025-10-27 13:18:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":707768,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEx vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e response towards Bluetongue virus at bovine body temperature, 38.5 °C. \u003c/strong\u003ePBMCs from 8 individual animals per group, whatever \u003cem\u003eBos taurus\u003c/em\u003e or \u003cem\u003eBos indicus\u003c/em\u003e, were either let for 48 h unstimulated (reference points for the assay), stimulated with Bluetongue virus (“BTV”, blue color). The fold changes analysis of activation / maturation markers was determined by FCM with FlowJo. Cells from the individual \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e-like cattle are represented by separate symbols; for stimulated samples, mean fluorescence intensity (MFI) values are normalized to that obtained with the reference point from the same animal. Results obtained for Monocyte (\u003cstrong\u003eA\u003c/strong\u003e), Dendritic cell (\u003cstrong\u003eB\u003c/strong\u003e), T-cell (\u003cstrong\u003eC\u003c/strong\u003e), B-cell and NK-cell (\u003cstrong\u003eD\u003c/strong\u003e) subsets. On the left side are provided representative contour plots overlaying signal obtained in unstimulated blood cells (black) with the signal obtained in cells exposed to BTV (blue). On the right side are shown graphs displaying all individual animals. Blue triangle backgrounds indicate a significant difference or a clear trend between both cattle subspecies. “High” indicates a MOI = 0.05, whereas “Low” indicates a MOI=0.005. Experimental conditions were compared using Mann–Whitney U-tests paired t tests. Stars indicate significance levels. *, p\u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/b9a6dafe98e910f4bdc45fbe.png"},{"id":94369686,"identity":"e417531e-db0a-4bbb-a4e7-c16cb6e4538c","added_by":"auto","created_at":"2025-10-27 13:18:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":646745,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEx vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e response towards Schmallenberg virus at bovine body temperature, 38.5 °C. \u003c/strong\u003ePBMCs from 8 individual animals per group, whatever \u003cem\u003eBos taurus\u003c/em\u003e or \u003cem\u003eBos indicus\u003c/em\u003e, were either let for 48 h unstimulated (reference points for the assay), stimulated with Bluetongue virus (“SBV”, orange color). The fold changes analysis of activation / maturation markers was determined by FCM with FlowJo. Cells from the individual \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e cattle are represented by separate symbols; for stimulated samples, mean fluorescence intensity (MFI) values are normalized to that obtained with the reference point from the same animal. Results obtained for Monocyte (\u003cstrong\u003eA\u003c/strong\u003e), Dendritic cell (\u003cstrong\u003eB\u003c/strong\u003e), T-cell (\u003cstrong\u003eC\u003c/strong\u003e), B-cell and NK-cell (\u003cstrong\u003eD\u003c/strong\u003e) subsets. On the left side are provided representative contour plots overlaying signal obtained in unstimulated blood cells (black) with the signal obtained in cells exposed to BTV (orange). On the right side are shown graphs displaying all individual animals. Orange triangle backgrounds indicate a significant difference or a clear trend between both cattle subspecies. “High” indicates a MOI = 0.05, whereas “Low” indicates a MOI = 0.005. Experimental conditions were compared using Mann–Whitney U-tests paired t tests. Stars indicate significance levels. *, p\u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/a755b6d11ccec6ad7f1b77dd.png"},{"id":94369679,"identity":"eb34753a-b699-4c62-9891-277c3c26dfc1","added_by":"auto","created_at":"2025-10-27 13:18:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":358844,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInduction of cytokine secretion at bovine body temperature, 38.5 °C. \u003c/strong\u003ePBMCs from 8 individual animals per group were either unstimulated or stimulated with BTV or SBV for 48 h. Interbreed comparison for BTV (\u003cstrong\u003eA\u003c/strong\u003e) and SBV (\u003cstrong\u003eB\u003c/strong\u003e). Vector-borne virus comparison for \u003cem\u003eBos taurus\u003c/em\u003e (\u003cstrong\u003eC\u003c/strong\u003e) and \u003cem\u003eBos indicus\u003c/em\u003e (\u003cstrong\u003eD\u003c/strong\u003e). Stimulations were run at ruminant body temperature (38.5 °C). Upper panel: a single measurement was done per sample tested, and each symbol represents an individual cow. Heat map shows log2-fold changes in concentration of 15 Cytokines/chemokines. For a given cytokine / chemokine, normalization was as follows: [concentration for a given animal] / [average concentration of reference points]. Lower panel: Radar plots showing the mean of 8 animals of log2-fold changes in concentration. Experimental conditions were compared using Mann–Whitney U-tests (\u003cstrong\u003eA\u003c/strong\u003e, \u003cstrong\u003eB\u003c/strong\u003e) or non-parametric paired Wilcoxon tests (\u003cstrong\u003eC\u003c/strong\u003e, \u003cstrong\u003eD\u003c/strong\u003e). Stars indicate significance levels. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/52350480b4602adb0fb15a01.png"},{"id":94369602,"identity":"7ea055cb-f55d-4b08-b9e2-9c159691131a","added_by":"auto","created_at":"2025-10-27 13:18:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":644421,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEx vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e response towards vector-borne viruses at fever-like temperature, 41 °C.\u003c/strong\u003e PBMCs from 8 individual animals per group were either incubated for 48 h at 38.5 °C (Physiological temperature, either unstimulated (reference points for the assay) or stimulated with vector-borne viruses) or 41.0 °C (fever-like temperature, either unstimulated or stimulated with vector-borne viruses). The fold changes analysis of activation / maturation markers was determined by FCM with FlowJo. Cells from the individual cows are represented by separate symbols; for stimulated samples, mean fluorescence intensity (MFI) values are normalized to that obtained with the reference point from the same animal. (\u003cstrong\u003eA\u003c/strong\u003e) Influence of fever-like temperature on primary blood cell stimulation by BTV.\u003cstrong\u003e (B) \u003c/strong\u003eAs in\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) but with SBV.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eC-F\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eInfluence of fever-like temperature on induction of cytokines by primary blood cells exposed to vector-borne viruses. Cytokine / chemokine secretion in supernatants of PBMC cultures, using multiplex immunoassay. Upper panel: A single measurement was done per sample tested, and each symbol represents an individual cow. For a given cytokine/chemokine, normalization was as follows: log [(concentration for a given animal at 41 °C / average concentration of reference points at 38.5 °C) ¸ (concentration for the same animal at 38 °C / average concentration of reference points at 38.5 °C)]. Lower panel: Radar plots showing the mean of 8 animals of log2-fold changes in concentration. Experimental conditions were compared using non-parametric paired Wilcoxon tests. Stars indicate significance levels. *, p \u0026lt; 0.05; **, p\u0026lt; 0.01; ***, p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/8a62bf008ea166d3a577e989.png"},{"id":94369854,"identity":"a8f2279d-c903-473d-be49-1b3572cc20b9","added_by":"auto","created_at":"2025-10-27 13:20:10","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":956655,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic profiles of primary blood cells in response to vector-borne viruses. \u003c/strong\u003ePBMCs from 8 individual animals per group were either incubated for 48 h at 38.5 °C (Physiological temperature, either unstimulated (reference points for the assay) or stimulated with vector-borne virus.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eA-E\u003c/strong\u003e) Cells derived from \u003cem\u003eBos taurus\u003c/em\u003e animals.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Number of differentially expressed genes (DEGs) in BTV or SBV stimulated PBMCS, over unstimulated cells from same animals at 48 h.\u0026nbsp;(\u003cstrong\u003eB\u003c/strong\u003e) Venn diagram indicating the number of unique and common DEGs following blood cell stimulation by either BTV or SBV. (\u003cstrong\u003eC\u003c/strong\u003e) Volcano plots highlighting the most significantly upregulated DEGs when stimulated with either BTV or SBV. Cut-off of DEGs based on absolute log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;fold change ≥ 1 (x\u0026nbsp;axis) and adjusted\u0026nbsp;p\u0026nbsp;\u0026lt; 0.05 (y\u0026nbsp;axis). Blue: upregulated genes ≥ 2-fold change following BTV stimulation; orange: upregulated genes ≥ 2-fold change following SBV stimulation; light grey corresponding to genes showing no expression change. (\u003cstrong\u003eD\u003c/strong\u003e) Top 15 enriched GO terms (Molecular function and Biological process) in response to BTV displayed by –log\u003csub\u003e10\u003c/sub\u003e\u0026nbsp;p values. (\u003cstrong\u003eE\u003c/strong\u003e) Top 15 enriched GO terms (Molecular function and Biological process) in response to SBV displayed by –log\u003csub\u003e10\u003c/sub\u003e\u0026nbsp;p values. (\u003cstrong\u003eF\u003c/strong\u003e-\u003cstrong\u003eJ\u003c/strong\u003e) As in (\u003cstrong\u003eA\u003c/strong\u003e-\u003cstrong\u003eE\u003c/strong\u003e), but with cells derived from \u003cem\u003eBos indicus\u003c/em\u003e animals.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/e6c718ba322480af93572111.png"},{"id":94369662,"identity":"ba926094-f4fc-493f-9c9f-1470405b290e","added_by":"auto","created_at":"2025-10-27 13:18:30","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":847295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFever-like temperature mediates changes of transcriptomic profiles in response to vector-borne viruses. \u003c/strong\u003ePBMCs from 8 individual animals per group were stimulated with vector-borne virus for 48 h either at 38.5 °C (normal bovine body temperature) or 41.0 °C (fever-like temperature). (\u003cstrong\u003eA\u003c/strong\u003e-\u003cstrong\u003eE\u003c/strong\u003e) Results obtained from PBMCs stimulated with BTV. (\u003cstrong\u003eA\u003c/strong\u003e) Number of DEGs in BTV stimulated PBMCS, over unstimulated cells from same animals at 48 h.\u0026nbsp;(\u003cstrong\u003eB\u003c/strong\u003e) Venn diagram showing the indicating the number of unique and common DEGs at 38.5°C or 41.0°C, following blood cell stimulation by BTV. (\u003cstrong\u003eC\u003c/strong\u003e) Volcano plots highlighting the most significantly regulated DEGs when stimulated with BTV at either 38.5 °C or 41.0 °C. Cut-off of differentially expressed genes (DEGs) based on absolute log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;fold change ≥ 1 (x\u0026nbsp;axis) and adjusted\u0026nbsp;p\u0026nbsp;\u0026lt; 0.05 (y\u0026nbsp;axis). Dark grey: upregulated genes ≥ 2-fold change following BTV stimulation at 38.5 °C; green: upregulated genes ≥ 2-fold change following BTV stimulation at 41.0 °C; light grey corresponding to genes showing no expression change. (\u003cstrong\u003eD\u003c/strong\u003e) Top enriched GO terms (Molecular function and Biology) calculated in cells derived from \u003cem\u003eBos taurus\u003c/em\u003e in response to BTV, at either 38.5 °C or 41.0 °C, displayed by –log\u003csub\u003e10\u003c/sub\u003e\u0026nbsp;p values. (\u003cstrong\u003eE\u003c/strong\u003e) Top enriched GO terms (Molecular function and Biology) calculated in cells derived from \u003cem\u003eBos indicus\u003c/em\u003e in response to BTV, at either 38.5 °C or 41.0 °C, displayed by –log\u003csub\u003e10\u003c/sub\u003e\u0026nbsp;p values. (\u003cstrong\u003eF\u003c/strong\u003e-\u003cstrong\u003eJ\u003c/strong\u003e) As in (\u003cstrong\u003eA\u003c/strong\u003e-\u003cstrong\u003eE\u003c/strong\u003e), but with cells stimulated with SBV.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/2ea73937b924a30b8016d106.png"},{"id":94369749,"identity":"391519c4-4e6e-4cb3-b931-6d5286a1d944","added_by":"auto","created_at":"2025-10-27 13:19:12","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":377356,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEarly transcriptomic profiles in response to Bluetongue virus.\u003c/strong\u003e PBMCs from 8 individual \u003cem\u003eBos taurus\u003c/em\u003e animals were incubated for 24 or 48 h, either at 38.5 °C or 41.0 °C.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Number of differentially expressed genes (DEGs) in BTV stimulated PBMCs at 38.5 °C, over unstimulated cells from same animals at 24 or 48 h.\u0026nbsp;(\u003cstrong\u003eB\u003c/strong\u003e) Venn diagram indicating the number of unique and common DEGs following blood cell stimulation by either BTV at 24 or 48 h (38.5 °C). (\u003cstrong\u003eC\u003c/strong\u003e) Number of DEGs in BTV stimulated PBMCs at 41.0 °C, over unstimulated cells from same animals at 24 or 48 h.\u0026nbsp;(\u003cstrong\u003eD\u003c/strong\u003e) Venn diagram indicating the number of unique and common DEGs following blood cell stimulation by either BTV at 24 or 48 h (41.0 °C). (\u003cstrong\u003eE-F\u003c/strong\u003e) Volcano plots highlighting the most significantly up- / down-regulated DEGs when stimulated with BTV at 48 h versus 24 h, at 38.5 °C (\u003cstrong\u003eE\u003c/strong\u003e) and 41.0 °C (\u003cstrong\u003eF\u003c/strong\u003e). Cut-off of DEGs based on absolute log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;fold change ≥ 1 (x\u0026nbsp;axis) and adjusted\u0026nbsp;p\u0026nbsp;\u0026lt; 0.05 (y\u0026nbsp;axis). Light grey corresponding to genes showing no expression change. (\u003cstrong\u003eG-I\u003c/strong\u003e) Expression heatmap of manually selected genes induced by BTV in cells derived from \u003cem\u003eBos taurus\u003c/em\u003e animals. (\u003cstrong\u003eG\u003c/strong\u003e) Cytokines / Chemokines, (\u003cstrong\u003eH\u003c/strong\u003e) Interferon-Stimulated Genes and (\u003cstrong\u003eI\u003c/strong\u003e) Regulatory Immune Components.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/1f56e6aa06adc446088cbc5c.png"},{"id":107972411,"identity":"a82a6515-e3f2-462e-894a-2edfa7b84ae2","added_by":"auto","created_at":"2026-04-28 07:07:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6106535,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7748972/v1/26e797c5-6eca-4deb-8e84-ea51c984b7a4.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Orchestrated immune responses of Bos indicus versus Bos taurus cattle towards vector-borne pathogens such as bluetongue virus differ significantly affecting disease outcomes","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eGlobal food security is one of the most pressing issues for humanity, and agricultural production is critical for achieving this. However, global food security \u0026ndash; tightly linked to trade, human health and livelihoods \u0026ndash; is seriously threatened by vector-borne diseases (VBDs), some of which specifically affect livestock production (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Many of these VBDs are co-endemic, and it is estimated that more than half the world\u0026rsquo;s population live in areas where two or more VBDs are present (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Despite the obvious need to intensify efforts to prevent and control VBDs, climate change is worsening the overall situation by changing vector endemicities and exacerbating the transmission and spread of VBDs.\u003c/p\u003e\u003cp\u003eAmong VBD pathogens, the arboviruses Schmallenberg virus (SBV) and bluetongue virus (BTV) affect predominantly ruminants, causing major animal welfare issues and great economic losses. Both are transmitted by \u003cem\u003eCulicoides\u003c/em\u003e biting midges and emerged recently in Europe (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). SBV is an orthobunyavirus identified during the initial outbreak in 2011 in Germany that spread rapidly in surrounding countries (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Infection in adult cattle typically causes transient fever, diarrhea, and reduced milk production. In pregnant females, it may lead to abortions or severe congenital malformations in the offspring (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). BTV is an orbivirus marked by regular outbreaks in Europe since 2006, while the most recent cases occurred in 2023\u0026ndash;2024, when serotype 3 was found in the Netherlands and spread rapidly through Northern Europe, including Switzerland (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The global expansion of the vector due to climate change has facilitated the emergence of different viral serotypes, with 29 that have been identified through phylogenetic studies, sequencing data and cross-neutralization assays (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Infection in adult cattle is characterized by fever, edema, hyperemia, hemorrhages, cyanosis and lameness, sometimes leading to the death of the infected animals (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eLivestock contributes nearly 40 percent of total agricultural output in developed countries and 20 percent in low-and-middle-income countries, supporting the livelihoods of at least 1.3\u0026nbsp;billion livestock-depending people worldwide. About 8,000 and 10,000 years ago \u003cem\u003eBos indicus\u003c/em\u003e (zebu) and \u003cem\u003eBos taurus\u003c/em\u003e (taurine) cattle subspecies, respectively, were domesticated from humped and humpless populations of the now extinct aurochs progenitor \u003cem\u003eBos primigenus\u003c/em\u003e that diverged about 30,000 years ago (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). \u003cem\u003eBos indicus\u003c/em\u003e have their origin in the tropical climate of the Indus Valley in what is now considered Pakistan, while \u003cem\u003eBos taurus\u003c/em\u003e originate from the Fertile Crescent now the Middle East (\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). That period of domestication encountered robust hydroclimate variability, leading to drier and less hospitable zones such as Indus Valley, in which the increased stress fostered the evolution of new and multifaceted adaptive strategies that increased the resilience of ancient populations (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Indeed, it is well-accepted that \u003cem\u003eBos indicus\u003c/em\u003e have higher heat resistance, can sustain poor nutrition, and show increased resistance to a number of pathogenic parasites such as babesiosis (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), ticks (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), and nematodes (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) compared to \u003cem\u003eBos taurus\u003c/em\u003e cattle. Recently we reported for the first time that \u003cem\u003eBos indicus\u003c/em\u003e cattle kept in Switzerland are less colonized by bacterial hoof pathogens (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) compared to taurine cattle. VBDs such as East Coast fever caused by \u003cem\u003eTheileria parva\u003c/em\u003e affect \u003cem\u003eBos taurus\u003c/em\u003e cattle more than \u003cem\u003eBos indicus\u003c/em\u003e cattle (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The co-evolution of \u003cem\u003eBos indicus\u003c/em\u003e cattle with tropical vector borne pathogens likely resulted in orchestrated immune responses controlling the pathogens, although this remains to be proved.\u003c/p\u003e\u003cp\u003eThis work aimed to test our working hypothesis that the immune response towards vector-borne pathogens such as SBV and BTV differs significantly between the two cattle subspecies \u003cem\u003eBos indicus\u003c/em\u003e and \u003cem\u003eBos taurus\u003c/em\u003e which is likely to affect the disease outcome. Moreover, we were interested in measuring the effect of fever-like temperature on immune cells to modulate the antiviral immune response, as well as immune cell interaction with SBV and BTV. In line with the 3R principles, we used an \u003cem\u003eex vivo\u003c/em\u003e laboratory platform employing primary blood cells of outbred animals to investigate bovine-pathogen interactions (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Overall, we confirmed our working hypothesis and our findings provide a unique comparative approach between the immune responses of \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e cattle. The presented \u003cem\u003eex vivo\u003c/em\u003e platform will foster further research to understand disease tolerance and susceptibility in cattle, assisting selection procedures to develop resistant livestock breeds.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePrevious exposure towards vector-borne viruses\u003c/h2\u003e\u003cp\u003eThe cows (N\u003csub\u003e\u003cem\u003eBos taurus\u003c/em\u003e\u003c/sub\u003e=16, N\u003csub\u003e\u003cem\u003eBos indicus\u003c/em\u003e\u003c/sub\u003e=16) enrolled in the study had no prior clinical reports of BTV or SBV-related disease. They were healthy, randomly selected, bled and later tested for their seroprevalence towards BTV and SBV. Serological analysis unequivocally confirmed the absence of previous exposure to BTV in all animals, with the exception of one \u003cem\u003eBos indicus\u003c/em\u003e animal (\u003cb\u003eAdditional file 1\u003c/b\u003e). Nevertheless, we did not discard this animal from analysis for two key reasons: i) we considered that immune cells derived from this animal might behave as outliers, in which case this would potentially highlight the accuracy and sensitivity of our \u003cem\u003eex vivo\u003c/em\u003e platform; ii) we considered that the inclusion of this specimen would not likely compromise any statistical outcomes, given that the study was conducted with robust sample size of eight animals per group.\u003c/p\u003e\u003cp\u003eDifferent serological results were obtained for SBV, since serum samples from the majority of animals showed SBV-positive antibodies indicating previous encounter with this pathogen. Specifically, 14 out of 16 \u003cem\u003eBos taurus\u003c/em\u003e (87.5%); 13 out of 16 \u003cem\u003eBos indicus\u003c/em\u003e animals (81.2%) exhibited optical densities in the diagnostic assay referring to \u0026gt;\u0026thinsp;60% of those quantified in the positive control (\u003cb\u003eAdditional file 1\u003c/b\u003e). These high frequencies were expected, given the geographical distribution of the virus and published data on its prevalence (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDetermination of the kinship relationship and physiological state of the cattle enrolled in the study\u003c/h3\u003e\n\u003cp\u003eThe kinship relationship of herds of \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e animals enrolled in the study were reported recently (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Thus, animals enrolled in the project are largely outbred and genetic heterogeneous, supporting the external reproducibility of our findings.\u003c/p\u003e\u003cp\u003eAdditionally, we aligned the RNA sequencing reads of all samples against the taurine reference sequence to identify and genotype variants. As described previously for variants called from RNA sequencing (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), the rather uneven alignment coverage with coverage spikes in highly expressed genes identifies substantially less variants than DNA sequencing data. More variants were called in indicine than taurine samples as expected given their higher divergence from the taurine reference sequence. A PCA conducted with a subset of 362 k variants with high genotyping rate across all samples grouped the samples into two distinct clusters representing taurine and indicine subspecies (\u003cb\u003eAdditional file 2\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eThen, we investigated the concentrations of different metabolic parameters and enzyme activities related to energy metabolism in blood serums, this to ensure that no animal displayed unphysiological concentrations of free fatty acids, beta-hydroxybutyrate or glucose levels that could have impacted the immune system. Effectively, results were within the reference values of the respective physiological status, i.e. gravidity and lactation (\u003cb\u003eAdditional file 3\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eImmune cell subset representation in the peripheral blood of\u003c/b\u003e \u003cb\u003eBos indicus\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eBos taurus\u003c/b\u003e \u003cb\u003ecattle\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll the stimulations performed in this study were done on blood cells isolated the same day and prepared within 4\u0026ndash;5 hours after collection. The transport of the freshly collected blood to the laboratory was done at 20\u0026ndash;25\u0026deg;C. The workflow and experimental design are summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Three main parameters were investigated throughout the study, namely comparison of \u003cem\u003eBos taurus\u003c/em\u003e versus \u003cem\u003eBos indicus\u003c/em\u003e cattle, vector-borne viruses BTV versus SBV, and influence of physiological temperature (38.5\u0026deg;C) versus fever-like temperature (41.0\u0026deg;C).\u003c/p\u003e\u003cp\u003eFollowing the validation study conducted in \u003cem\u003eBos taurus\u003c/em\u003e, it was essential to confirm that the previously designed FCM antibody combinations (i.e., [Antigen presenting cells], [T cells] and [B cells, NK cells]) were applicable to \u003cem\u003eBos indicus\u003c/em\u003e cattle. This was successfully demonstrated, as witnessed by the clear delineation of all immune cell subsets, as well as the strong signal intensity of maturation / activation markers. A representative example of gating strategy is shown in \u003cb\u003eAdditional file 4\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eWe subsequently tested whether \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e exhibited comparable representation of individual immune cell subsets. At physiological temperature (38.5\u0026deg;C), analysis of unstimulated samples revealed a striking observation: 10 out of 13 investigated cell subsets showed different counts between the two genetic backgrounds. The three subsets comparable were cDC1s, CD8\u003csup\u003e+\u003c/sup\u003e T cells and NK cells. Notably, except for non-classical monocytes and γδ T cells, which were significantly enriched in \u003cem\u003eBos indicus\u003c/em\u003e, all subsets showed a noticeable decrease compared to \u003cem\u003eBos taurus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Those clear differences reinforced the hypothesis that \u003cem\u003eBos indicus\u003c/em\u003e and \u003cem\u003eBos taurus\u003c/em\u003e cattle are likely to exhibit distinct \u003cem\u003eex vivo\u003c/em\u003e responses towards VBD pathogens. Under fever-like temperature (41.0\u0026deg;C), the same results were overall obtained, except for non-classical monocytes and pDC subsets, that were no longer significantly different (\u003cb\u003eAdditional file 5\u003c/b\u003e).\u003c/p\u003e\n\u003ch3\u003eViral titers in the supernatant of stimulated primary blood cells\u003c/h3\u003e\n\u003cp\u003eWe optimized the protocols for propagating and harvesting BTV (serotype 8 from 2008) and SBV (serotype 3 from 2011), using ultimately the BHK-21 cell line (\u003cb\u003eAdditional file 6\u003c/b\u003e). This allowed us to achieve sufficient virus titers for subsequent infection of bovine PBMCs. We first tested BTV or SBV replication when exposed to primary blood cells of \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e at a high MOI\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eFor BTV, the PBMCs of both cattle subspecies promoted high and comparable titers at physiological temperature, that were slightly affected by fever-like temperature conditions (trend for \u003cem\u003eBos taurus\u003c/em\u003e, significant for \u003cem\u003eBos indicus\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, left panel).\u003c/p\u003e\u003cp\u003eExposure to SBV led to smaller titers, with substantial divergence between \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, right panel). Indeed, PBMCs from \u003cem\u003eBos taurus\u003c/em\u003e were more efficient in controlling growth of SBV when compared to \u003cem\u003eBos indicus\u003c/em\u003e, regardless of physiological or fever-like temperatures (TCID50/ml\u0026thinsp;=\u0026thinsp;1.1 \u0026times; 10\u003csup\u003e2\u003c/sup\u003e and 5.2 \u0026times; 10\u003csup\u003e2\u003c/sup\u003e, respectively; p \u0026lt; 0.01). Therefore, BTV and SBV proved to replicate differently in bovine primary blood cells; moreover, the difference measured for SBV titers between both cattle indicated distinct host-pathogen interactions, with potential consequences on disease outcome.\u003c/p\u003e\u003cp\u003eThen, the impact of vector-borne viruses on PBMCs was roughly investigated with t-SNE algorithm (visualization of high dimensional data in a 2-D representation). Clearly, blue islands that came from samples stimulated with BTV were observable in both \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e, indicating that this virus at a MOI\u0026thinsp;=\u0026thinsp;0.05 induces high changes of the blood cell phenotypic parameters. In comparison, orange areas who are specific to SBV stimulation were mostly stacked with areas of unstimulated samples. Nevertheless, a few orange islands were visible in \u003cem\u003eBos indicus\u003c/em\u003e, showing that SBV has a detectable impact on bovine blood cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). From this, it was clear that BTV and SBV interact differently with host immune cells.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEx vivo\u003c/b\u003e \u003cb\u003eresponse towards vector-borne viruses at bovine body temperature, 38.5\u0026deg;C\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe assessed the responsiveness of \u003cem\u003eBos taurus\u003c/em\u003e derived PBMCs to both VBD pathogens in a pilot experiment, to determine optimal MOIs (MOI\u0026thinsp;=\u0026thinsp;0.05 (high), MOI\u0026thinsp;=\u0026thinsp;0.005 (low)) and time points (t\u0026thinsp;=\u0026thinsp;24 h and 48 h), consistent with numerous published studies.\u003c/p\u003e\u003cp\u003eOverall, the responses of \u003cem\u003eBos taurus\u003c/em\u003e versus \u003cem\u003eBos indicus\u003c/em\u003e derived PBMCs differed significantly in their reactions to both BTV and SBV, underlining the importance of having a clear delineation of immune cell subsets for in-depth investigations (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For instance, non-classical monocytes from \u003cem\u003eBos indicus\u003c/em\u003e showed a clear MHC-II upregulation following exposure to BTV, whereas in \u003cem\u003eBos taurus\u003c/em\u003e this subset exhibited enhanced expression levels of CD25 and CCR7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). When the same analysis was done to evaluate response to SBV, non-classical monocytes from both cattle subspecies displayed no clear activation markers, except for a slight increase in CCR7 in \u003cem\u003eBos indicus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Overall, these findings suggest that both bovine genetic backgrounds had different non-classical monocyte counts, but also that their biological effector functions may differ.\u003c/p\u003e\u003cp\u003eMore generally, all individual immune cell types demonstrated significant differences in the magnitude of their responses, with most cases showing reactions to both viruses (including classical monocytes, non-classical monocytes, pDCs, CD21\u003csup\u003ehigh\u003c/sup\u003e B cells). In some cases, responses were observed only towards BTV (in cDC1s, cDC2s, CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells, γδ T cells, CD20\u003csup\u003e+\u003c/sup\u003e B cells, CD21\u003csup\u003elow\u003c/sup\u003e B cells and NK cells) or only towards SBV (intermediate monocytes) (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-D and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-D). Clearly, our study supports our hypothesis that immune responses of cattle with markedly different genetic background to VBDs differ, underscoring the relevance of breed-specific immunological studies in understanding disease susceptibility and disease outcome.\u003c/p\u003e\n\u003ch3\u003eInduction of cytokine secretion at bovine body temperature, 38.5°C\u003c/h3\u003e\n\u003cp\u003eNext, we aimed to confirm the distinct magnitude of cytokine production by PBMCs in response to vector-borne viruses. Upon stimulation with BTV, the most noticeable result in \u003cem\u003eBos taurus\u003c/em\u003e consisted of massive levels of a set of pro-inflammatory cytokines, namely IL-1α, IL-1β, IL-6, MIP-1α (=\u0026thinsp;CCL3), MIP-1β (=\u0026thinsp;CCL4), and TNF-α, as well as pro-Th1 (IFN-γ) and pro-Th17 (IL-17). Additionally, as published previously for \u003cem\u003eMycoplasmopsis bovis\u003c/em\u003e (\u003cem\u003eM. bovis\u003c/em\u003e) stimulation (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), the anti-inflammatory IL-10 paralleled this induction. \u003cem\u003eBos indicus\u003c/em\u003e exhibited a similar trend in cytokine induction with a clear reduction in overall cytokine levels as compared to \u003cem\u003eBos taurus\u003c/em\u003e, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA (upper part, heat map depicting all individual animals; lower part, radar plot showing the mean of all animals). Of note, even if the cytokine induction profiles were quite superimposable between 24 h and 48 h, the full detection of IFN-γ required the latter time point. This is why focusing on 48 h rather than 24 h offered the most exhaustive picture of cytokine release by blood cells (\u003cb\u003eAdditional File 7\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eThe above results obtained for BTV proved to be markedly robust compared to those observed for SBV, which were, at best, moderate (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Specifically, in \u003cem\u003eBos taurus\u003c/em\u003e, most cytokines were moderately induced (IFN-γ, IL-1, IL-6, etc.). Nevertheless, the immune response against SBV was still notable, revealing clear differences when comparing \u003cem\u003eBos indicus\u003c/em\u003e and \u003cem\u003eBos taurus\u003c/em\u003e. Notably, IFN-γ and IL-17 levels were enhanced in \u003cem\u003eBos taurus\u003c/em\u003e, while MCP-1 and VEGF-A levels were enhanced in \u003cem\u003eBos indicus\u003c/em\u003e. Finally, when the impact of both vector-borne viruses on PBMCs was compared for a given cattle subspecies, it was clear that BTV was a more potent inducer of cytokines / chemokines than SBV for \u003cem\u003eBos taurus\u003c/em\u003e, as well as for \u003cem\u003eBos indicus\u003c/em\u003e (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) (upper part, heat map depicting all individual animals; lower part, radar plot showing the mean of all animals). This, combined with previous results obtained by FCM, demonstrated that BTV and SBV have a divergent effect on cattle primary blood cells.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEx vivo\u003c/b\u003e \u003cb\u003eresponse towards vector-borne viruses at fever-like temperature, 41\u0026deg;C\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAssessment moved on to influence of fever, typical clinical signs of severe disease caused by BTV or SBV, by raising the question of how stimulation at 41\u0026deg;C (high fever temperature) would influence the magnitude of PBMC response. Results illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA showed a negative impact in \u003cem\u003eBos taurus\u003c/em\u003e of the rise from 38.5\u0026deg;C to 41.0\u0026deg;C on the capacity of monocytes, T-cell and B-cell subsets, as well as NK cells, to respond to BTV, as witnessed by CD25 down-regulation. Of note, DCs kept their full capacity to upregulate CD25, as previously reported following exposure to the bacterial pathogen \u003cem\u003eM. bovis\u003c/em\u003e (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). When the same analysis was applied to blood cells isolated from \u003cem\u003eBos indicus\u003c/em\u003e, the results proved to be moderate in comparison, but still noticeable for numerous subsets (classical monocytes, CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e and γδ T cells, CD21\u003csup\u003ehigh\u003c/sup\u003e B cells and NK cells). Again, we failed to detect any decrease of CD25 for DC subsets at fever-like temperature, but the opposite for most animals (i.e., cDC2 subset) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). In conclusion, regardless of cattle subspecies being considered, we obtained a significant reduction of maturation / activation parameters upon interaction with BTV, virus for which we obtained the stronger response under physiological temperature.\u003c/p\u003e\u003cp\u003eThen, the responsiveness to SBV was tested at fever-like temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). As expected, an overall reduction of immune subsets to maturate and activate happened to a lesser extent, but still noticeable. Indeed, febrile temperatures influenced moderately \u0026ndash; but significantly \u0026ndash; the lower upregulation of CD25 following exposure to SBV (negative effects on classical monocytes, cDC2s and CD21\u003csup\u003elow\u003c/sup\u003e B cells for \u003cem\u003eBos taurus\u003c/em\u003e; negative effects on cDC2s, CD4\u003csup\u003e+\u003c/sup\u003e and γδ T cells, and CD21\u003csup\u003elow\u003c/sup\u003e B cells for \u003cem\u003eBos indicus\u003c/em\u003e). Altogether, these findings implied that under fever-like temperature conditions, bovine immune responses to SBV are impaired, possibly preventing efficient clearance.\u003c/p\u003e\n\u003ch3\u003eInduction of cytokine secretion at fever-like temperature, 41°C\u003c/h3\u003e\n\u003cp\u003eNext, we assessed cytokine secretions at 41\u0026deg;C (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC-F). When the values obtained with fever-like temperatures (41\u0026deg;C) were normalized to that obtained with normal bovine body temperature (38.5\u0026deg;C), no consistent influence was noted for unstimulated samples from \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e (\u0026ldquo;No virus\u0026rdquo;, mostly white pattern). In contrast, a very strong reduction was calculated for all induced cytokines produced in response to BTV, particularly clear for \u003cem\u003eBos taurus\u003c/em\u003e (dark blue color patterns) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), and to a lesser extent for \u003cem\u003eBos indicus\u003c/em\u003e (blue color patterns) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD), confirming that fever-like condition attenuates PBMCs capacity to respond to BTV.\u003c/p\u003e\u003cp\u003eThe decrease of cytokine levels following SBV exposure was more difficult to quantify due to the low \u003cem\u003eex vivo\u003c/em\u003e response inherent to this virus; nevertheless, in line with results related to activation / maturation markers, we could still detect a negative influence for some cytokines, as witnessed by the blue color patterns visualized in \u003cem\u003eBos taurus\u003c/em\u003e (ie., IFN-γ, IL-17 and IP-10) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE) and \u003cem\u003eBos indicus\u003c/em\u003e (ie., IFN-γ and IL-6) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Finally, although 48 h is the more informative time point to get a full picture of the cytokine secretion profile, it is worth noting that the negative impact of fever-like temperature was easily found at earlier time point (\u003cb\u003eAdditional file 8\u003c/b\u003e). Collectively, these results highlighted the detrimental impact of fever-like temperature on PBMC\u0026rsquo;s capacity to respond to vector-borne viruses, regardless of the cattle subspecies: optimal at normal body temperature, attenuated at febrile temperature.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCorrelation between multiplex immunoassay and of RNA-Sequencing analysis\u003c/h2\u003e\u003cp\u003eThe relevance of subspecies-specific immunological studies in understanding disease susceptibility and resistance was implemented with a procedure of higher complexity: identification of thousands of DEGs. First, GC content of raw reads showed a normal distribution across samples, with percentage range of 40.1%-51.8%. Moreover, a range of 77.1\u0026ndash;95.6% of reads trimmed aligned to the respective reference genomes. Among the aligned sequence reads, 70.7\u0026ndash;95.3% of reads were assigned to gene features, with total assigned reads ranging from 36.3-85.3M.\u003c/p\u003e\u003cp\u003eThen, we ensured that RNA-Seq analysis corroborates cytokine secretion levels obtained by multiplex immunoassay. Indeed, the induction quantified from the two independent readouts proved to strongly correlate at physiological temperature at both 24 and 48 h, but not anymore at fever-like temperature where we showed above that the bovine \u003cem\u003eex vivo\u003c/em\u003e response is impeded (\u003cb\u003eAdditional File 9\u003c/b\u003e). Again, the magnitude of cytokine response under BTV stimulation was enhanced in \u003cem\u003eBos taurus\u003c/em\u003e compared to \u003cem\u003eBos indicus\u003c/em\u003e, particularly for IFN-γ, IL-1β and IL-12β. We then selected manually a relevant set of interferon-stimulated genes (ISGs): surprisingly, most of ISGs were more upregulated in cells derived from \u003cem\u003eBos indicus\u003c/em\u003e (i.e., \u003cem\u003eRSAD2\u003c/em\u003e, \u003cem\u003eMX1\u003c/em\u003e, \u003cem\u003eMX2\u003c/em\u003e and \u003cem\u003eISG15\u003c/em\u003e), indicating that this cattle subspecies responds to viral infections by mounting a balanced and effective immune response, whereas \u003cem\u003eBos taurus\u003c/em\u003e tend to poorly control their anti-BTV response, characterized by a subsequent \u0026ldquo;cytokine storm\u0026rdquo;. We then examined whether the better controlled response in \u003cem\u003eBos indicus\u003c/em\u003e could be attributed to increased levels of regulatory immune components (i.e., \u003cem\u003eFOXP3\u003c/em\u003e, \u003cem\u003eLAG3\u003c/em\u003e, etc.); however, comparable values were found between the two cattle subspecies, ruling out this possible explanation (\u003cb\u003eAdditional File 10\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomic profiles of PBMCs derived from\u003c/b\u003e \u003cb\u003eBos taurus\u003c/b\u003e \u003cb\u003ein response to vector-borne viruses at body temperature, 38.5\u0026deg;C\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNext, we compared the entire transcriptomic profiles of \u003cem\u003eBos taurus\u003c/em\u003e primary blood cells exposed to VBD viruses to unstimulated cells. Based on the first two principal components following a PCA of all genes, samples did not cluster significantly differently when stimulated with SBV, in contrast to the effects observed for BTV (\u003cb\u003eAdditional File 11\u003c/b\u003e). For BTV, we found 2,275 DEGs to be significantly downregulated after stimulation, whereas 1,712 DEGs were significantly upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Venn diagrams were generated to assess the DEGs overlap between stimulation by the two vector-borne viruses; interestingly, only 260 genes were commonly found, suggesting different recognition mechanisms between BTV and SBV (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). A volcano plot pointed out that the transcripts that were most significantly induced in response to BTV were involved in a broad range of functions (including pro-inflammatory activity, with \u003cem\u003eIL12RB2\u003c/em\u003e), while the response towards SBV was most restricted to genes involved in regulation of the immune response (\u003cem\u003eTGFB\u003c/em\u003e, \u003cem\u003ePILRA\u003c/em\u003e, \u003cem\u003eCD163\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eTo better understand the potential roles of host responses to \u003cem\u003eCulicoides\u003c/em\u003e-borne viruses, the biological functions of DEGs were subjected to Gene Ontology (GO) enrichment. Of note, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was not considered, due to species-specific database limitations and gene annotation mismatches between \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e. With GO analysis, BTV infection induced a broad immune response, with significant enrichment of antiviral responses (Type I interferon receptor binding), but also Cellular and Humoral responses, Cytokine and Chemokine activity, as well as NK cell activation involved in immune response (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eFor SBV, when those DEGs were analyzed based on GO, then the three most significantly enriched GO terms were Transmembrane signaling receptor activity, Carbohydrate binding and Sialic acid binding (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). This, combined with the previous phenotypic results, provides an unprecedented in-depth characterization of \u003cem\u003eBos taurus\u003c/em\u003e circulating blood cell response to vector-borne viruses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomic profiles of PBMCs derived from\u003c/b\u003e \u003cb\u003eBos indicus\u003c/b\u003e \u003cb\u003ein response to vector-borne viruses at body temperature, 38.5\u0026deg;C\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfterwards, we investigated RNA-Seq data derived from \u003cem\u003eBos indicus\u003c/em\u003e animals, where the magnitude of the response towards BTV was found attenuated in terms of phenotypic readouts (multiparameter FCM and multiplex immunoassay). Nevertheless, PCA still revealed clear clustering in response to BTV stimulation, whereas samples stimulated with SBV failed to cluster away from unstimulated samples (\u003cb\u003eAdditional File 11\u003c/b\u003e). The total number of DEGs induced by BTV was 1,991 (1,137 downregulated and 854 upregulated), which was less than what was observed for \u003cem\u003eBos taurus\u003c/em\u003e. Exposure to SBV led to a noticeable change of transcriptomic profiles compared to unstimulated PBMCs (628 downregulated and 311 upregulated). Venn diagrams were generated, showing that only 227 genes were commonly found in the response to both vector-borne viruses, suggesting also this time different recognition pathways between BTV and SBV in \u003cem\u003eBos indicus\u003c/em\u003e (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF-G). A volcano plot pointed out that the transcripts that were most significantly induced in response to BTV or SBV were involved in a broad range of functions, albeit with no clear involvement in the immune response (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003eThe biological functions were then examined using GO enrichment analysis: this confirmed that the pathways associated with immune responses were mainly antiviral responses. Strikingly, the most enriched GO terms were a G protein-coupled receptor activity and Olfactory receptor activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eI). Altogether, those results provided a new insight into the specific set of genes triggered in BTV-well adapted cattle subspecies, with clear distinctions compared to naive \u003cem\u003eBos taurus\u003c/em\u003e animals.\u003c/p\u003e\u003cp\u003eFinally, GO analysis for stimulation with SBV highlighted that the enriched GO terms were unrelated to immune stimulation nor antiviral responses: Sialic acid binding, Chemoattractant activity and Collagen binding (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eJ). As for BTV, this strongly suggests that \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e are prone to combat SBV infection with qualitatively and quantitatively distinct immune responses. Likely, this influences the difference of disease susceptibility between the two cattle subspecies.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eRecent Bluetongue virus outbreak in Northern Europe\u003c/h3\u003e\n\u003cp\u003eBy the time of this study was conducted, a novel BTV outbreak occurred in Switzerland (September 2024 \u0026ndash; January 2025, serotype 3), affecting numerous farms, including the one from which our blood samples were collected. Interestingly, this farm cohoused \u003cem\u003eBos indicus\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;20) and \u003cem\u003eBos taurus\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;19) (Aubrac breed) animals, giving us the unique opportunity to investigate the link between clinical data and serological prevalence in both cattle subspecies. We found that animals of this farm seroconverted and hence were infected, with antibodies directed against BTV found in all animals but one \u003cem\u003eBos indicus\u003c/em\u003e. However, none of the adults belonging to \u003cem\u003eBos indicus\u003c/em\u003e cattle subspecies were reported to show clinical signs (despite 2 neonatal calves having fatal disease), whereas the \u003cem\u003eBos taurus\u003c/em\u003e group showed five adult cows with pronounced clinical signs, demonstrating unequivocal higher susceptibility for the \u003cem\u003eBos taurus\u003c/em\u003e animals.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe two genetically distinct subspecies of cattle, \u003cem\u003eBos indicus\u003c/em\u003e and \u003cem\u003eBos taurus\u003c/em\u003e, arose from independent domestication events 8,000 and 10,000 years ago, respectively. As a result, the subspecies display substantial phenotypic and tissue-specific gene expression differences (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Moreover, indicine and taurine cattle breeds show epigenetic divergence across immune cell types (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Among others, \u003cem\u003eBos indicus\u003c/em\u003e are known for decades to be more resistant to emerging animal diseases compared to \u003cem\u003eBos taurus\u003c/em\u003e due to a longer period of adaptation (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In the specific case of BTV, a study monitored infections in \u0026gt;\u0026thinsp;500 indigenous \u003cem\u003eBos indicus\u003c/em\u003e animals in western Kenya, from birth to death or 12 months of age. The results showed a very high prevalence (\u0026sim; 0.95), with heterogeneous serotypes and long viral persistence, but stinkingly no overt clinical signs in any cattle (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The present study aimed to compare innate and adaptive immune responses of both cattle subspecies, by assessing their \u003cem\u003eex vivo\u003c/em\u003e responses to VBD pathogens recently emerged in Europe due to global warming. We took advantage of the fact that Switzerland houses around hundred \u003cem\u003eBos indicus\u003c/em\u003e cattle, that are kept under similar production systems and infection pressure. Although we only enrolled female animals due to availability, we do not assume that male animals show markedly different immune responses. Identifying the mechanisms responsible for controlling specific pathogens in cattle represents an essential step in developing predictive phenotypic markers and foster efficient vaccine development.\u003c/p\u003e\u003cp\u003eWe focused our analysis on primary blood cells rather than performing \u003cem\u003ein vivo\u003c/em\u003e challenge experiments. This way we followed the 3Rs principles and used protocols that can be implemented in other labs besides being economic in terms of costs. It is important to consider that following the bite of an infected vector, many VBD viruses replicates shortly in endothelial cells before spreading to peripheral tissues via the blood stream (\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). It is also known that ovine CD4\u003csup\u003e+\u003c/sup\u003e and WC1\u003csup\u003e+\u003c/sup\u003e γδ T cells, as well as bovine CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e, and WC1\u003csup\u003e+\u003c/sup\u003e γδ T cells, can be productively infected by BTV (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Besides, the prolonged presence of BTV in circulation has been reported following infection (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), associated with acute immunosuppression and substantial lymphopenia, enabling BTV to evade the host immune response (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). For all these reasons, we evaluated the specific interactions of vector-borne viruses with host PBMCs, that furthermore offer the advantage to comprise most immune cell subsets that cooperate to mount efficient innate and adaptive immune response.\u003c/p\u003e\u003cp\u003eGenetic analysis of Swiss zebu indicates high genomic diversity and clear separation from taurine cattle (\u003cb\u003eAdditional File 2\u003c/b\u003e, (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)). Furthermore, the relatively high genetic diversity of Swiss zebu, particularly when compared to Holstein, suggests that inbreeding remains low despite their small population size in Switzerland, supporting external reproducibility of the present findings (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). However, a potential drawback in the comparison of both cattle subspecies is the poor evaluation of the impact of usage differences: \u003cem\u003eBos taurus\u003c/em\u003e are normally subjected to greater metabolic stress due to their dairy use that can impact the immune system, whereas \u003cem\u003eBos indicus\u003c/em\u003e are mainly used for beef production. In the present study, we ruled out this potential bias by showing that all enrolled animals displayed physiological concentrations of free fatty acids, beta-hydroxybutyrate or glucose levels with no indication of metabolic stress (\u003cb\u003eAdditional File 3\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eWe started our immunological comparison with the investigation of possible qualitative and/or quantitative differences in frequencies of different immune cell subsets in the two cattle subspecies tested. Available data on such frequencies to date are rather sparse and inconsistent, mainly due to restricted use of antibodies that impeded proper delineation. In a study done more than a decade ago, \u003cem\u003eBos indicus\u003c/em\u003e animals were reported to have higher percentage of CD4\u003csup\u003e+\u003c/sup\u003e T cells, while \u003cem\u003eBos taurus\u003c/em\u003e animals had relatively higher percentages of macrophage-type cells (monocytes and MHCII-expressing cells) in their circulation (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e); this conflicts somehow with our findings employing up-to-date 12-color panels in the FCM analysis. In a more recent study, overrepresentation of γδ T cells was reported in \u003cem\u003eBos indicus\u003c/em\u003e (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), which is in line with our data. Altogether, our study showed clear differences in the frequencies of different immune cell subsets, correlating with genetic background. Corroborating this statement, we found a clear distinctive phenotype and anti-BTV response for monocytes derived from \u003cem\u003eBos indicus\u003c/em\u003e animals: classical monocytes had a phenotype reminiscent of migratory subset (CCR7 upregulation), whereas non-classical monocytes acted like \u0026ldquo;hyper presenting cells\u0026rdquo;, as witnessed by the high MHC-II upregulation. Finally, it is worth noting that the stimulation of bovine PBMCs by vector-borne viruses required to extend cell culture for 48 h, implying modulation of cell surface proteins on subsets like DCs or monocytes (\u003cb\u003eAdditional File 4\u003c/b\u003e); indeed, it is known that those antigen presenting cells tend to differentiate or die \u003cem\u003eex vivo\u003c/em\u003e, requiring some caution before extrapolating our results to what occurs \u003cem\u003ein vivo\u003c/em\u003e (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBTV affects wild and domestic ruminants, with cattle being natural reservoirs due to persistence in the blood of some animals for relatively long periods, facilitating horizontal transmission by \u003cem\u003eCulicoides\u003c/em\u003e (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Since dsRNA is detected by toll-like receptors (TLR) 3 and retinoic acid inducible gene (RIG-1)-like family receptors (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), it was expected to observe triggering of the production of interferon and other pro-inflammatory cytokines to activate an antiviral response to combat the infection. This was effectively the case, where a clear type I antiviral response was detected in both cattle subspecies (RNA-Seq analysis, \u003cb\u003eAdditional File 10\u003c/b\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Clearly, anti BTV response in \u003cem\u003eBos taurus\u003c/em\u003e specimen was accompanied by the secretion of a large panel of cytokine / chemokine, whereas \u003cem\u003eBos indicus ex vivo\u003c/em\u003e response was mainly restricted to antiviral immune components. This broader response in \u003cem\u003eBos taurus\u003c/em\u003e animals could be attributed to monocytes or B cells, involved in the sensing of the infection, given that their transcriptome was previously shown to have viral recognition and sensing of the infection signatures at early timepoints (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). This assumption was not obvious in the present study for monocytes \u0026ndash; notably because of the aforementioned differences in terms of phenotype and functions in both cattle subspecies. In contrast, CD21\u003csup\u003ehigh\u003c/sup\u003e B cells showed a clear over-activation in \u003cem\u003eBos taurus\u003c/em\u003e compared to \u003cem\u003eBos indicus\u003c/em\u003e specimens (CD25 induction: 5.4 and 2.6, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD), making this subset a potential contributor to the excessive immune response.\u003c/p\u003e\u003cp\u003eNevertheless, a particular observation implied that monocytes play a key role in fighting BTV infection in \u003cem\u003eBos indicus\u003c/em\u003e animals which is not surprising. Indeed, an outlier animal exhibited a very strong response to BTV (i.e., CD25 and CCR7 upregulation on classical monocytes; MHC-II on non-classical monocytes, IFN-γ secretion). Remarkably, this specific animal had BTV-specific antibodies in its serum indicating previous encounter with BTV. Interestingly, a few reports have described in ruminants the capacity of monocytes and macrophages to be trained and have memory-like traits such as persistent hyperactivation for several months (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), which was likely to be the case in our study. Finally, besides a key role of monocytes in early interaction with BTV, our study points out some immune specificity of \u003cem\u003eBos indicus\u003c/em\u003e, possibly a result of the selection pressure with tropical vector-borne pathogens in the Indus Valley that resulted in better adaptation of their immune system to combat efficiently tropical vector borne diseases.\u003c/p\u003e\u003cp\u003eA likely explanation of disease susceptibility in \u003cem\u003eBos taurus\u003c/em\u003e subspecies would be that the high magnitude of the \u003cem\u003eex vivo\u003c/em\u003e response led to over-exuberant immune response \u003cem\u003ein vivo\u003c/em\u003e, responsible for inflammation of the mucous membranes. Indeed, dampening of the immune response by regulatory mechanisms is necessary to prevent collateral damage and severe disease course, even if this impairs pathogen clearance (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). In line with this, previous transcriptomic analysis of \u003cem\u003ein vitro\u003c/em\u003e BTV infection of ovine and caprine PBMCs, two particularly susceptible animal species, have shown activation of genes belonging to PRR and cytokine/chemokine signaling pathways, similarly to what we detected in \u003cem\u003eBos taurus\u003c/em\u003e subspecies (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Moreover, another study pointed out the key role played by CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e and γδ T cells in susceptibility versus resistance to BTV disease (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Loss of CD4\u003csup\u003e+\u003c/sup\u003e T cells was found to exacerbate the disease, making this subset a potential key player in disease resistance; indeed, we found CD4\u003csup\u003e+\u003c/sup\u003e T cells more activated in \u003cem\u003eBos indicus.\u003c/em\u003e In contrast, loss of CD8\u003csup\u003e+\u003c/sup\u003e T cell subset was shown to be associated with lower clinical scores and higher survival; herein, this potential disease contributor was effectively more activated in \u003cem\u003eBos taurus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Finally, WC1\u003csup\u003e+\u003c/sup\u003e γδ T cells were reported to be protective against BTV; considering that this subset is over-represented in \u003cem\u003eBos indicus\u003c/em\u003e at steady state gives another likely explanation why zebu cattle are more resistant (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). An alternative possibility would be that the enhanced expression of ISGs reported in susceptible animals induce a faster host cell protein synthesis shutoff, resulting in a premature downregulation of antiviral proteins required for BTV clearance (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). This is not in line with our observation related to \u0026ldquo;cytokine storm\u0026rdquo; in cells derived from \u003cem\u003eBos taurus\u003c/em\u003e animals (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cb\u003eAdditional File 6\u003c/b\u003e and \u003cb\u003e10)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eSBV was detected for the first time in November 2011 in plasma samples collected from cows displaying fever and diarrhea (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Unlike BTV, SBV is now endemic in Europe and particularly in Switzerland. It can infect a broader range than only domestic livestock, with specific antibodies witnessing previous exposures detected in free-ranging wild and exotic ruminants, pointing out the reasons why some species are more susceptible to disease (\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Importantly, SBV specific antibodies are known to persist at least 12\u0026ndash;24 months in cattle after natural infection (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), which explained the high prevalence found in our study. Also, one might argue that the moderate effects observed with SBV were due to a low MOI used in our assays, but very low dose of virus are sufficient for animal challenge (10\u003csup\u003e3\u003c/sup\u003e-2.10\u003csup\u003e3\u003c/sup\u003e TCID50), with no gain in using enhanced viral load (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Moreover, the percentage of infected cells \u003cem\u003ein vitro\u003c/em\u003e, such as of primary fibroblast, is also very low (\u0026sim; 30%) with high dose of SBV (MOI\u0026thinsp;=\u0026thinsp;5) (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e), giving a solid explanation why we had moderate readouts in our phenotypic approach compared to BTV. Finally, the low \u003cem\u003eex vivo\u003c/em\u003e response measured herein can be attributed to strong interference of SBV with the IFN pathway. Indeed, previous studies emphasized the role of nonstructural (NS) protein in shutting down the immune response of the host, and NS removal was shown to favor the restoration of an antiviral response a set of antiviral genes (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Another study showed that shutting down genes of the host innate response was mainly due to Mx inhibition (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e), although this was not clearly seen in the present study (\u003cb\u003eAdditional File 10\u003c/b\u003e). Nevertheless, despite the overall low responses, our results suggest that \u003cem\u003eBos indicus\u003c/em\u003e blood cells interact more with SBV than the ones derived from \u003cem\u003eBos taurus\u003c/em\u003e animals, with more DEGs, even if most of functions involved were not related to immune responses. Finally, we only investigated host responses at 48 h p.i., while other time points might have identified other DEGs.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAnother major finding of the present study was the detrimental impact of fever-like temperature on \u003cem\u003eex vivo\u003c/em\u003e responses towards vector-borne viruses. Fever is a clinical hallmark of infection, which in turn is associated with a negative impact on the clinical disease outcome (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Overall, our data showed clearly a reduced capacity of cells \u0026ndash; with the exception of some DC subsets \u0026ndash; to respond to vector-borne viruses, confirming our previous observation with \u003cem\u003eM. bovis\u003c/em\u003e, another important bovine pathogen (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Despite fever like temperature is a common physiological characteristic of immune responses, it is still poorly understood in terms of impact on immune cells that have to fight infection and mediate inflammation. Herein, the most striking observation under fever-like temperature was the strongly reduced capacity to rapidly produce IFN-γ (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eG). Given the crucial role that this cytokine plays in promoting both innate and adaptive immunity against intracellular pathogens (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e), this contributed to the attenuation of the \u003cem\u003eex vivo\u003c/em\u003e responses towards BTV, and to a lesser extent SBV. Interestingly, a recent study also showed that febrile temperatures selectively affect the metabolism of a variety of T cell types \u0026ndash; reported to be productively infected by BTV (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) \u0026ndash;, driving to their apoptosis (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Consequently, this could lead to less favorable conditions for viral replication, leading to lower viral titers and attenuation of associated \u003cem\u003eex vivo\u003c/em\u003e responses.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eConclusive remarks\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe fine deciphering of host immune responses of the different cattle subspecies towards vector-borne viruses highlighted distinct immune responses triggered by the two subspecies. These immune responses are likely to correlate with a differential control of the pathogen. This paves the road for better understanding of better control and resistance towards infections with tropical VBD by \u003cem\u003eBos indicus\u003c/em\u003e. Our platform has great prospects for screening different cattle breeds for their immune responses towards pathogens to identify resistant breeds that can be further tested and enrolled in breeding programmes and to understand immunity that can be elicited by rational vaccines.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eEthics statement\u003c/h2\u003e\u003cp\u003eThe collection of bovine blood was performed in compliance with the Swiss animal protection law (TSchG SR 455; TSchV SR 455.1; TVV SR 455.163) under the cantonal license BE55/2022. The application was reviewed by the cantonal committee on animal experiments of the cantons of Bern, Fribourg and Solothurn, Switzerland, and approved by the veterinary authority of the canton of Bern (Amt f\u0026uuml;r Landwirtschaft und Natur LANAT, Veterin\u0026auml;rdienst VeD, Bern, Switzerland).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eSelection of cattle used for the study\u003c/h2\u003e\u003cp\u003eSwitzerland is home to \u0026gt;\u0026thinsp;100 \u003cem\u003eBos indicus\u003c/em\u003e cattle besides the many \u003cem\u003eBos taurus\u003c/em\u003e subspecies. We took advantage of the presence of both cattle subspecies for sampling, since the infection pressure and livestock production systems are similar and allow a side-by-side analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eSerological screening of previous exposure towards Bluetongue and Schmallenberg viruses\u003c/h2\u003e\u003cp\u003eAt the time of enrollment in this study, animals had no previous reports of Bluetongue or Schmallenberg virus-related disease. Previous exposure towards both pathogens was investigated serologically on all animals using the Bluetongue Virus Antibody Test Kit, cELISA v2 (VRMD, VRMD Inc, Pullman, WA) and ID Screen Schmallenberg virus Indirect Multi-species kit (Innovative Diagnostic, France). Serum from venous blood to be tested was collected from the animals using standard methods employing vacutainer serum tubes (Becton Dickinson).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eMeasurement of metabolic blood parameters\u003c/h2\u003e\u003cp\u003eConcentrations of different metabolic parameters and enzyme activities related to energy metabolism were analysed in blood serum. Analysis was carried out using an autoanalyzer (Cobas Pure c303) and commercially available assays validated for bovines.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eVariant calling from RNA sequencing data\u003c/h2\u003e\u003cp\u003eTotal RNA was isolated from bovine blood cells using the TRIzol reagent and sequenced using next generation sequencing (see below). Paired-end RNA sequencing reads were aligned to the \u003cem\u003eBos taurus taurus\u003c/em\u003e reference sequence (ARS-UCD2.0, GCA_002263795.4) and RefSeq (release 106) annotation using the splice-aware aligner STAR (v2.7.11b) (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). We used SAMtools (v1.21) (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e) for collating alignments by name, marking duplicates, and coordinate sorting. Variants were called from the aligned bam files using DeepVariant (v1.5) (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e) using the \u0026ldquo;--split_skip_reads\u0026rdquo; and the v1.4 RNA checkpoint model. All samples were merged using GLnexus (v1.4.1) (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). We used plink (v1.90) (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e) to create binary files containing 6,509,257 autosomal variants of which we retained 362,134 that had minor allele frequency greater than 0.01 and were genotyped in at least 90% of the 156 samples. Principal component analysis (PCA) was conducted with plink, and hierarchical clustering was performed with the hclust function in R.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eVirus propagation and titration\u003c/h2\u003e\u003cp\u003eA German BTV serotype 8 from 2008 (isolate: BTV-8_D/07_1) and a SBV serotype 3 (isolate: BH80/11\u0026thinsp;\u0026minus;\u0026thinsp;4) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) were kindly provided by Gert Zimmer from the Swiss Institute of Virology and Immunology (IVI). Baby hamster kidney (BHK) 21 cells were obtained from the IVI and grown in Glasgow\u0026rsquo;s minimal essential medium (GMEM; Life Technologies) supplemented with 10% fetal bovine serum (FBS). BHK-21 cells were expanded to propagate both viruses. For the stock production, frozen BTV-8 and SBV were recovered from storage, thawed for 1\u0026ndash;2 min at 37\u0026deg;C, and added to the cells, at a multiplicity of infection (MOI)\u0026thinsp;=\u0026thinsp;0.01 in a total volume of 30 mL per flask. After 48 h, the cytopathogenic effect (CPE) reached approximately 80% (cell rounding and extensive cellular monolayer disruption), so that the cultures were frozen at -70˚C, to disrupt the BHK-21 cells and release the virus. The freeze-thaw cycle was done twice, after what cell debris were sedimented by centrifugation at 250 \u0026times; \u003cem\u003eg\u003c/em\u003e and 4\u0026deg;C for 10 min, and the supernatants were aliquoted and frozen at -70\u0026deg;C until further use in the next few months. Infectious virus titers were determined on BHK-21 cells and were calculated according to the Spearman-K\u0026auml;rber method and expressed as 50% tissue culture infectious doses per mL (TCID50/mL).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eIsolation of bovine peripheral blood mononuclear cells (PBMCs)\u003c/h2\u003e\u003cp\u003eBlood from \u003cem\u003eBos taurus\u003c/em\u003e cows (n\u0026thinsp;=\u0026thinsp;16, Holstein Friesian breed, aged 1\u0026ndash;3 years) was collected at the Agroscope research facility in Posieux, Switzerland. The donor cattle enrolled in the study belonged to a herd not mingling with other animals outside the facility. Blood of \u003cem\u003eBos indicus\u003c/em\u003e cows (n\u0026thinsp;=\u0026thinsp;16, Zebu breed, aged 1\u0026ndash;14 years) was collected in two farms in the cantons of Bern and Solothurn.\u003c/p\u003e\u003cp\u003e30\u0026ndash;50 mL of blood was obtained by jugular vein puncture (\u003cem\u003eBos taurus\u003c/em\u003e) or tail vein puncture (\u003cem\u003eBos indicus\u003c/em\u003e) into vacutainer EDTA tubes (Becton Dickinson). For PBMC isolation, blood was first centrifuged at 1,000 \u0026times; g for 20 min. Then the buffy coat was collected and diluted with PBS containing 1 mM UltraPure\u0026trade; EDTA (Invitrogen) to a ratio of 1 to 1 before being layered onto Ficoll Paque (1.077 g/mL; GE Healthcare Europe GmbH). After centrifugation (800 \u0026times; g for 25 min), PBMCs were collected and washed twice with cold PBS containing 1 mM EDTA (Invitrogen) (350 \u0026times; g for 10 min). If needed, erythrocytes were lysed by resuspending the pellet with 1\u0026ndash;2 mL of H2O and washed immediately with 48 mL of cold PBS containing 1 mM EDTA and centrifuged (350 \u0026times; g for 10 min). A final washing step was done at 250 \u0026times; g for 10 min to remove platelets.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eStimulation of bovine PBMCs\u003c/h2\u003e\u003cp\u003eBlood cell stimulation employed flat-bottom 6-well plates (TPP, Switzerland). Per well, 5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells were cultured in 3 mL Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium (DMEM) (Life Technologies) supplemented with 10% FBS (Life Technologies). Importantly, all tests were run either at 38.5\u0026deg;C (bovine body temperature) or at 41.0\u0026deg;C (high fever temperature).\u003c/p\u003e\u003cp\u003eStimulation with BTV or SBV was done at a MOI\u0026thinsp;=\u0026thinsp;0.05 (high MOI) or 0.005 (low MOI), for 48 h, based on preliminary experiments.\u003c/p\u003e\u003cp\u003eAt 24 h and 44 h post infection (p.i.), 50\u0026ndash;100 \u0026micro;l of cell culture supernatant was collected and frozen at -20\u0026deg;C for subsequent cytokine secretion measurement using a bead based multiplex immunoassay (see below). At 44 h p.i., Brefeldin A (10 \u0026micro;g/mL) (ThermoFisher) was added to the medium to block cytokine secretion; incubation was extended for another 4 h, to allow the \u003cem\u003ede novo\u003c/em\u003e cytokine synthesis measurement employing flow cytometry (FCM) intracellular staining.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eMultiparameter flow cytometry (FCM) assay\u003c/h2\u003e\u003cp\u003eApplication of multiparameter FCM assay has been described elsewhere (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), apart from very few changes of antibodies and fluorophores: in house conjugation of CD3 employed Zenon Alexa Fluor 568 labelling kit (instead of Alexa Fluor 532 Antibody Labeling Kit), CD45RO (clone IL-A116) replaced CD44. Otherwise, combination staining and gating strategies remained unchanged, analyzing monocytes (classical, intermediate and non-classical), cDCs (cDC1s and cDC2s), pDCs, γδ T cells, NK cells, CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, and B cells.\u003c/p\u003e\u003cp\u003eFor the acquisitions, cells from the whole samples were accumulated.\u003c/p\u003e\u003cp\u003eFor the fold-change analysis of activation / maturation marker following stimulation, the mean fluorescence intensity (MFI) measured in stimulated sample for a given cow was normalized to the MFI measured in unstimulated sample from that same animal.\u003c/p\u003e\u003cp\u003eFor the counts of immune cell subtypes, we calculated the percentage of total events: ratio [number of events in the gated cell subtype] to [number of all events, excepting cell aggregates and debris]. This readout was preferred to absolute counts because PBMC enumeration was performed under the light microscope with Trypan blue exclusion, raising the possibility of human factors introducing bias and irrelevant disparity between samples. In contrast, the percentage of total events is an accurate and unbiased picture that reflects what is found in the peripheral blood (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFCM acquisitions were performed on a Cytek Aurora (Cytek Biosciences) using the SpectroFlo software with autofluorescence extraction, and further analyzed with FlowJo 10.9.0 (TreeStar).\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eMultiplex bead-based immunoassay\u003c/h2\u003e\u003cp\u003eThe commercial MILLIPLEX Bovine Cytokine/Chemokine Magnetic Bead Panel 1 - Immunology Multiplex (Merck) employed here has been described elsewhere (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Of note, chemokines are named in the figures with their \u0026ldquo;historical names\u0026rdquo;, which adhere to the names used in the manufacturer\u0026rsquo;s manual. However, the recent nomenclature states that the new names for the chemokines are CCL3 (C-C motif ligand 3), CXCL10 (C-X-C motif ligand 10), CCL2, and CCL4 for MIP-1α, IP-10, MCP-1 and MIP-1β, respectively.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eRNA isolation, library preparation and sequencing\u003c/h2\u003e\u003cp\u003eFor RNA sequencing, total RNA from 156 samples was extracted from cultured PBMCs using TRIzol reagent (ThermoFisher). In short, 2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells were lysed with 1 mL of TRIzol reagent and kept at -70\u0026deg;C until the RNA was handed over to the sequencing facility for analysis.\u003c/p\u003e\u003cp\u003eThe RNA quantification, library preparation and sequencing were conducted by Novogene (Novogene Co., Ltd., Munich, Germany). In summary, the quantity and quality of the total RNA sample was evaluated by Nanodrop and Agilent 5400. Messenger RNA (mRNA) was purified from total RNA using poly-T oligo-attached magnetic beads. Following fragmentation, the first-strand cDNA was synthesized using random hexamer primers followed by the second-strand cDNA synthesis. Library preparation involved end repair, A-tailing, adapter ligation, size selection, amplification, and purification. The library quality was assessed using Qubit for quantification, real-time PCR for amplification verification, and a bioanalyzer for size distribution analysis. Quantified libraries were pooled and paired-end sequenced on the NovaSeq X Plus platform (Illumina, San Diego, CA, USA) based on effective library concentration and desired data volume.\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eBioinformatic analysis of RNA-seq data\u003c/h2\u003e\u003cp\u003eRNA-seq data analysis was carried out on the servers of the Linux Cluster of the Interfaculty Bioinformatics Unit at the University of Bern. Sequence quality was first assessed with FastQC (Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioinformatics.babraham.ac.uk/projects/fastqc\u003c/span\u003e\u003cspan address=\"http://www.bioinformatics.babraham.ac.uk/projects/fastqc\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (version 0.12.1)). Adapter sequences were removed and reads with a Phred base quality threshold below 15 (Q\u0026thinsp;\u0026lt;\u0026thinsp;15) or shorter than 15 bp were filtered out using fastp (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e) (version 0.22.0). High-quality reads were mapped to the \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e reference genomes (ARS-UCD2.0 GCF_002263795.3 and UOA_Brahman_1 GCF_003369695.1, respectively) using STAR (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e) (version 2.7.11b). FeatureCounts (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e) (version 2.0.6) was employed to quantify the number of reads assigned to each gene. Read quality and alignment was generated with MultiQC (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e) (version 1.22.2). Two samples were removed from downstream analysis due to low mapping rates.\u003c/p\u003e\u003cp\u003eDifferential gene expression analysis between experimental groups was conducted using the Bioconductor DESeq2 package (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). All analyses were carried out in R (version 4.4). Raw read counts were normalized and rlog-transformed across all samples for exploratory data analysis using PCA and hierarchical clustering. For unbiased analysis, stimulated samples of each subset were compared to corresponding control samples. Differentially expressed genes (DEGs) were identified based on an adjusted p value threshold of 0.05 and an absolute log\u003csub\u003e2\u003c/sub\u003e fold change greater than 1.\u003c/p\u003e\u003cp\u003eFunctional enrichment analysis of all DEGs were accomplished on the basis of the gene ontology (GO) database using DAVID (Database for Annotation, Visualization and Integrated Discovery) (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eStatistical analysis was done using the GraphPad Prism 8 software (GraphPad software, La Jolla, CA, USA). To determine differences between groups, paired t tests, non-parametric paired Wilcoxon tests or one-way repeated measure ANOVA followed by Geisser-Greenhouse correction were used, as appropriate. Associations were tested using the Spearman rank correlation test. A p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant (* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **** p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Stephanie Talker, James Prendergast and Olivier Hanotte for useful discussion and the Swiss Zebu farmers for their collaboration; \u0026nbsp;Bernd Hoffmannfor supplying the viruses. We are grateful to the previous and current Jores lab members not listed as authors for lively discussions and assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;Mapping assemblies\u0026rdquo;, i.e., called variants after mapping reads to the bovine reference genome version ARS-UCD1.3 (GCF_002263795.2) (Holstein = PRJEB66341; Zebu; PRJEB67281).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRNA sequencing data have been deposited in the European Nucleotide Archive (ENA) and can be retrieved from Bioproject\u0026nbsp;\u003c/em\u003ePRJEB96282.\u003c/p\u003e\n\u003cp\u003eAccession numbers for the raw data are available in \u003cstrong\u003eAdditional File 12\u003c/strong\u003e.\u003c/p\u003e\n\u003ch3\u003eEthics statement\u003c/h3\u003e\n\u003cp\u003eThe collection of ruminant blood was performed in compliance with the Swiss animal protection law (TSchG SR 455; TSchV SR 455.1; TVV SR 455.163) under the cantonal license BE55/2022. The application was reviewed and authorized by the cantonal veterinary authorities of the cantons of Bern, Fribourg and Solothurn, Switzerland.\u003cbr /\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTomley, F.M., Shirley, M.W.: Livestock infectious diseases and zoonoses. Philos. Trans. R Soc. Lond. B Biol. Sci. \u003cb\u003e364\u003c/b\u003e(1530), 2637\u0026ndash;2642 (2009)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilson, A.L., Courtenay, O., Kelly-Hope, L.A., Scott, T.W., Takken, W., Torr, S.J., et al.: The importance of vector control for the control and elimination of vector-borne diseases. PLoS Negl. Trop. Dis. \u003cb\u003e14\u003c/b\u003e(1), e0007831 (2020)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGolding, N., Wilson, A.L., Moyes, C.L., Cano, J., Pigott, D.M., Velayudhan, R., et al.: Integrating vector control across diseases. 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Nucleic Acids Res. \u003cb\u003e50\u003c/b\u003e(W1), W216\u0026ndash;W21 (2022)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Vector-borne diseases, Bos indicus, Bos taurus, RNA vector-borne viruses, Disease susceptibility, Ex vivo immune response, Bluetongue virus, Schmallenberg virus, genetic background","lastPublishedDoi":"10.21203/rs.3.rs-7748972/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7748972/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCattle are the mammalian species with most global biomass, encompass the two subspecies \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e, which are phenotypically distinguishable and have distinct genetic backgrounds as a result of their different evolutionary trajectories. We used fresh primary bovine blood cells to characterize and dissect host-pathogen interactions, hypothesizing that \u003cem\u003eBos taurus\u003c/em\u003e and \u003cem\u003eBos indicus\u003c/em\u003e cattle exhibit different immune responses towards vector-borne diseases (VBDs) impacting the clinical disease outcome. We tested Schmallenberg virus (SBV) and Bluetongue virus (BTV), examples of vector-borne pathogens responsible for recent European disease outbreaks, driven by increased vector activity linked to rising temperatures. \u003cem\u003eBos taurus\u003c/em\u003e cattle showed a moderate \u003cem\u003eex vivo\u003c/em\u003e response towards SBV compared to BTV, which indicates a fine-tuning of the immune response depending on vector-borne virus. The most striking finding was the differential immune response towards BTV: broad and over-exuberant in \u003cem\u003eBos taurus\u003c/em\u003e, mainly antiviral in \u003cem\u003eBos indicus\u003c/em\u003e. Moreover, fever-like temperature, a classical clinical sign of disease, reduced the capacity of most immune cell subsets to respond to the pathogens tested. Overall, our findings of different immune responses are in line with other studies that suggest different susceptibilities of the \u003cem\u003eBos indicus\u003c/em\u003e versus \u003cem\u003eBos taurus\u003c/em\u003e towards major pathogens like bovine tuberculosis.\u003c/p\u003e","manuscriptTitle":"Orchestrated immune responses of Bos indicus versus Bos taurus cattle towards vector-borne pathogens such as bluetongue virus differ significantly affecting disease outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-24 23:32:50","doi":"10.21203/rs.3.rs-7748972/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-biology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsbio","sideBox":"Learn more about [Communications Biology](http://www.nature.com/commsbio/)","snPcode":"","submissionUrl":"","title":"Communications Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6cb97948-23f5-455f-9165-601e59ce8237","owner":[],"postedDate":"October 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":56100356,"name":"Biological sciences/Immunology/Infectious diseases/Viral infection"},{"id":56100357,"name":"Biological sciences/Immunology/Antimicrobial responses"}],"tags":[],"updatedAt":"2026-04-28T07:07:33+00:00","versionOfRecord":{"articleIdentity":"rs-7748972","link":"https://doi.org/10.1038/s42003-026-09804-7","journal":{"identity":"communications-biology","isVorOnly":false,"title":"Communications Biology"},"publishedOn":"2026-03-10 04:00:00","publishedOnDateReadable":"March 10th, 2026"},"versionCreatedAt":"2025-10-24 23:32:50","video":"","vorDoi":"10.1038/s42003-026-09804-7","vorDoiUrl":"https://doi.org/10.1038/s42003-026-09804-7","workflowStages":[]},"version":"v1","identity":"rs-7748972","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7748972","identity":"rs-7748972","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}