ulata-infected cells stimulate polyclonal naïve T lymphocyte proliferation by mechanisms involving NF-kB, MAPK and PI3-K-PKB pathways, followed by the up-regulation of pro-inflammatory cytokines and MHC class II molecules [93].
In particular, the pathway of NF-kB, one of the most important cellular factors involved in the regulation of the host innate antimicrobial response, is targeted directly by the schizont in both the transformant species T. parva and T. annulata. This factor is essential for protection against apoptosis and it contributes to maintaining a continuous proliferation, regulating the expression of anti-apoptotic proteins and downregulating tumor-suppressor genes. Its inhibition results in immediate apoptosis of Theileria-transformed cells [94]. Theileria parasites induce the constitutive NF-kB activation by the recruitment of large aggregates of IkB kinase (IKK) complexes to the surface of the transforming schizont. IKK is the regulator of NF-kB pathways and acts phosphorylating cytoplasmic inhibitors of NF-kB that are, subsequently, polyubiquitinated and degradated, allowing NF-kB to translocate to the nucleus [95].
Aberrantly activated T lymphocytes switch to a Th1 phenotype, producing large quantities of IFN-γ [96], which, together with the excessive production of pro-inflammatory cytokines, is mainly responsible for parasite-induced pathology [97]. In details, it was reported that T. parva-transformed cells produce exclusively IFN-γ, whereas T. annulata-infected cells express type I IFN, particularly IFN-β [98]. Other proinflammatory cytokines expressed by T. annulata-infected cells included IL-1α, IL-1β, IL-6, TNFα [99]. Following T. annulata-activation, macrophages elicit NO production, which can inhibit invasion and proliferation of the pathogen in host cells, even if, an excessive NO production plays a prominent role in the pathogenesis of the disease [100].
Moreover, several studies have reported a role in host immune responses against T. annulata infections for TLRs, an important group of pattern recognition receptors, whose activation leads to the induction of IFNs and cytokines acting in host defence and pathogenesis [101]. In particular, it was found that mRNA expression of TLR10 was significantly higher in T. annulata-infected PBMCs from the more resistant indigenous cattle (Bos indicus) with respect to crossbreds, suggesting a role for TLR10 in enhancing the host immune responses in T. annulata infections [102].
Recently, the transcriptional profiles of genes involved in the TLR and NLR signalling pathways in response to T. annulata infection were investigated at different sampling times during the infection course. Authors found significant differences in the transcription levels of TLR1, TLR6, TLR10, NLRP1, and MyD88 genes and their downstream signalling molecules in samples collected from 72 h to 168 h following T. annulata infection, compared to pre-infection values. The serum concentrations of IL-6, IL-1β, and TNFα significantly increased at 96 h and 168 h postinfection. These results may contribute in determining the mechanisms of TLR and NLR signalling pathways in immune response against T. annulata [103].

Gene Ontology Analysis of Interactions between Innate Immune Response and Tick-Borne Pathogens
Statistical overrepresentation analysis of enriched genes can reveal high significance in association with Gene Ontology (GO) terms for biological function, clearly reflecting a molecular signature of innate immune response to tick-borne pathogens, in particular the inflammasome activation. At least six NLRP Nucleotide-binding domain and Leucine rich Repeat-containing receptors (NLRP) with different activation stimuli functions, such as bacterial toxins able to active NLRP3 or lipopeptides activating stimuli on NLRP7, can trigger CASP1. Therefore, inflammasomes can be formed by several different NLR family sensors. As explained above, the tick-borne pathogen infections are not controlled by innate immunity, but a pro-inflammatory state occurs upon innate immune cells activation of the inflammasome via TLR2, leading to the mature forms of IL-1β and IL-18, cleaved by caspases, which consequently cause a macrophages activation. Based on protein-chemical interactions, the correlation between inflammasome and macrophages activation pathways is not direct, as they are mediated by apoptosis-related cysteine peptidase 1 (CASP1). Macrophage activation is controlled by IFN-γ signalling pathways and tick-borne pathogens infection leads to a MAS, caused by a significant increase of IFN-γ secretion induced by the transcription of cytokines like IL-12, IL-15, and IL-18 ( Figure 2). The increasing of IFN-γ has a positive transcriptional regulation or activation effect on STAT1, which contributes to the transcriptional up-regulation of a number of genes involved in the inflammasome activation.  Furthermore, the TNFα and IL-4 play a critical role in this downregulation and in MAS. As can be seen in figure 1, IL-4 has a negative transcriptional regulation action on toll-like receptor 2, while the expression of TNFα has inhibition action on IFN-γ; consequently, this balance may have effect on the inflammasome assembly. To better understand the role of this inhibition in human and animal infection models, we chose some biological terms to create an annotation data set to analyse the weak part of innate immunity, which cannot control the infection in its early onset. These Gene Ontology (GO) terms are: interferon-gamma secretion (GO:0072643), inflammasome complex (GO:0061702), transferrin receptor activity (GO:0004998), macrophage activation (GO:0042116), and toll-like receptor signaling pathway (GO:0002224). A total number of 2388 of annotations were recorded (Table 1).  Furthermore, the TNFα and IL-4 play a critical role in this downregulation and in MAS. As can be seen in Figure 1, IL-4 has a negative transcriptional regulation action on toll-like receptor 2, while the expression of TNFα has inhibition action on IFN-γ; consequently, this balance may have effect on the inflammasome assembly. To better understand the role of this inhibition in human and animal infection models, we chose some biological terms to create an annotation data set to analyse the weak part of innate immunity, which cannot control the infection in its early onset. These Gene Ontology (GO) terms are: interferon-gamma secretion (GO:0072643), inflammasome complex (GO:0061702), transferrin receptor activity (GO:0004998), macrophage activation (GO:0042116), and toll-like receptor signaling pathway (GO:0002224). A total number of 2388 of annotations were recorded (Table 1).
Based on this gene set, the GO analysis was run on PANTHER GO-slim Biological Process on False Discovery Rate (FDR), with p < 0.05. Then, the GO biological process, which is related to innate immunity, was chosen with a total number of 166 genes observed ( Table 2).
Another role in inducing the expression of Transferrin receptor and iron control is played by iron ion transport genes, with seven genes involved in our dataset (TCIRG1, TFR2, TFRC, ATP6V1G2, LTF, TF, SLC11A1). Moreover, in our gene interaction analysis, we showed that transferrin has a positive activation on IL-18. As explained before, the increasing of IFN-γ can cause MAS, as NK cells display a pivotal role in early innate immunity against rickettsial infection by IFN-γ secretion via different pathways. We also chose some biological terms for creating an annotation dataset to study how NK cells and IFN-γ secretion lead to an early innate immune response against Rickettsia or other pathogens. These terms were: natural killer cell activation (GO:0030101), regulation of interferon-gamma secretion (GO:1902713), interferon-gamma secretion (GO:0072643), response to redox state (GO:0051775), tryptophan metabolic process (GO:0006568), nitric-oxide synthase activity (GO:0004517), regulation of interleukin-17 secretion (GO:1905076). A total of 202 annotations were recorded for these gene ontology terms (Table 3).  Table 3. Cont.
In our dataset, there is a significant score for JAK2 receptor involved in various processes either in innate or adaptive immunity, consequently leading to IFN-γ production where there is a lack of IL-12A and IL-18 due to MAS, for example in response to A. phagocytophilum infection (Figure 3). Total genes 166 immune system process 28 regulation of immune system process 18 Based on this gene set, GO analysis was run on PANTHER GO-slim Biological Process on FDR with p < 0.05. Then GO biological process was chosen with a total number of 202 genes observed. Our GO study and gene product interaction showed that at the level of high confidence interaction score (0.700), there is an significant interaction score between Myeloid Differentiation Primary Response Protein (MyD88) and the TLR and IL-1 receptor signalling pathway in the innate immune response ( Figure 1). Furthermore, the interaction between these two biological functions (IFN-γ production/regulation of NK-mediated immunity) probably represent the hotlink between macrophages and NK cells innate immune response. Based on experimental and biochemical data, posttranslational modifications between MyD88 and JAK2 were identified.
In our dataset, there is a significant score for JAK2 receptor involved in various processes either in innate or adaptive immunity, consequently leading to IFN-γ production where there is a lack of IL-12A and IL-18 due to MAS, for example in response to A. phagocytophilum infection (Figure