Abstract
Ticks secrete hundreds to thousands of proteins into the feeding site, that presumably all play important functions in the modulation of host defense mechanisms. The current review considers the assumption that tick proteins have functional relevance during feeding. The feeding site may be described as a closed system and could be treated as an ideal equilibrium system, thereby allowing modeling of tickāhost interactions in an equilibrium state. In this equilibrium state, the concentration of host and tick proteins and their affinities will determine functional relevance at the tickāhost interface. Using this approach, many characterized tick proteins may have functional relevant concentrations and affinities at the feeding site. Conversely, the feeding site is not an ideal closed system, but is dynamic and changing, leading to possible overestimation of tick protein concentration at the feeding site and consequently an overestimation of functional relevance. Ticks have evolved different possible strategies to deal with this dynamic environment and overcome the barrier that equilibrium kinetics poses to tick feeding. Even so, cognisance of the limitations that equilibrium binding place on deductions of functional relevance should serve as an important incentive to determine both the concentration and affinity of tick proteins proposed to be functional at the feeding site.
Biological Activity at the Tick Feeding Interface
Biological function is central to the understanding of life and organismal biology. The context that function confers is exemplified in the frustration felt when a gene or protein of interest can only be annotated as a hypothetical protein with unknown function. Conversely, the ease of annotation by homology has made genome sequencing and assignment of function to orthologs an almost mundane task (). Even so, biochemical characterization remains central to the elucidation and confirmation of new function and the understanding of functional mechanism. From a biochemical reductionist perspective, biological function may be explained within a structural mechanistic context as the action of a gene, surface, motif or residue that result in a chemical reaction, activation or inhibition of an enzyme or receptor, or even a physiological process such as blood clotting or platelet aggregation. The current review considers biological function at the tickāhost interface from this reductionist perspective (). Even so, it was recently suggested that before or during evolution of new function by gene duplicates, and before negative selection maintain the adaptive advantage conferred by such new functions, new duplicates may exist in a state of undefined or non-optimized function, where protein expression is maintained while functional space is explored by random mutation: the playground hypothesis of neutral evolution (Mans et al., 2017). There is also an increasing recognition that most proteins may exhibit āpromiscuous activity,ā i.e., irrelevant secondary activities (, ). In addition, given the possibility that a biochemical assay may yield results for a broad class of proteins with diverse functions, or even results without biological meaning, it raise the question whether any particular measured function is relevant within a biological or physiological context. The current review therefore also considers functional relevance at the tickāhost interface from this perspective.
Sabbatani (1899), after reading Haycraftās work on the anti-clotting effects of the oral secretions from leeches (), made the first prescient deduction that all hematophagous organisms must secrete components that interfere or regulate host defenses, such as the hemostatic system. He tested this by showing that crude whole body tick extracts led to in vitro inhibition of blood clotting and that injecting this extract into various animals led to prolongation of blood coagulation in vivo. He also injected what may very well be the first fractionation of tick proteins to show that this purified preparation retained its inhibitory properties. Sabbataniās deduction has been confirmed by extensive research into tickāhost interactions that established a veritable pharmacopeia of bioactive components secreted by ticks during feeding (reviewed in Mans and Neitz, 2004a; ; Mans et al., 2016). However, a question that must have plagued him and remains relevant today, is whether in vitro and even in vivo observations can be causally linked with biological relevant activity at the feeding site, i.e., do what we measure in a test tube really function as a modulator of host defenses during feeding? The observation that ticks can cause paralysis in a host (Hovell, 1824 cited in Scott, 1921) and the presence of salivary glands in ticks (von Siebold and Stannius, 1854; Leydig, 1855; ), must have suggested that ticks can secrete substances into the host. Phenotypic changes in the host such as itching or ecchymosis after tick bite also suggested that ticks secrete substances into the host (Nuttall et al., 1908). Secretion and therefore presence would imply activity at the feeding site. However, the presence of toxic and anti-hemostatic molecules in tick eggs, but not salivary glands or saliva, showed that measurement of biological activity in crude extracts does not necessarily imply function at the tickāhost interface (; ; Riek, 1957, 1959; ; Neitz et al., 1981; Viljoen et al., 1985; Mans et al., 2004a). This implication was recognized soon after Sabbataniās seminal study, when researchers extended his observations by proving that anti-hemostatic and toxic activities were present in salivary glands of ticks (Nuttall and Strickland, 1908; ; Ross, 1926; ). It would take a number of years before anti-hemostatic and toxic activity could be showed to be secreted in tick saliva itself. This had to await chemical means, such as pilocarpine, or mechanical means, such as infra-red light, to stimulate salivation in order to obtain adequate quantities of salivary secretion for demonstration of biological activity (; Tatchell, 1967; Neitz et al., 1969, 1978; ; Ribeiro et al., 1985, 1987; Ribeiro and Spielman, 1986; Ribeiro et al., 1991). However, as Tatchell (1967) indicated: salivary secretions obtained with exogenous stimulants should be treated with caution, since it is unclear whether such secretions represent the total saliva complement or even represent saliva, since cement is not found in such secretions. This may be a pertinent observation since cement may readily form during feeding on artificial membranes (Krƶber and Geurin, 2007), arguing that induced salivation is not entirely the same as salivation during actual feeding.
Confirmation of secretion during feeding remains a crucial component of validation of biological relevance (Law et al., 1992). This may be achieved to various extents, by direct determination of the presence of a specific activity or molecule in saliva, or detection of host-derived antibodies generated against components secreted during feeding (Ribeiro et al., 1991; Oleaga-PƩrez et al., 1994; Mulenga et al., 2003). Detection in the salivary glands or salivary gland extract (SGE) may be used as an indication of secretion, especially if a secretory peptide signal is present in the immature protein sequence (Nielsen, 2017). The latter have been extensively used to identify potential secretory components during transcriptome analysis (reviewed in Mans et al., 2016). However, secretion of some proteins without canonical signal peptides and non-salivary gland derived proteins via apocrine or alternative secretion has complicated the distinction of true and false positive secretory components (Mulenga et al., 2003; ; Oliveira et al., 2013; Tirloni et al., 2014, 2015), thereby also obscuring deduction of biological relevance (Mans et al., 2016). Not all salivary gland proteins with signal peptides are necessarily secreted during feeding (Nielsen, 2017), nor are all secretory proteins secreted at the same time, such as the case for hard ticks, that show differential expression over the course of several days of feeding (McSwain et al., 1982; Paesen et al., 1999; Wang et al., 2001b; , ; ; Perner et al., 2018). Transcriptome and proteome data also shows a weak correlation (Schwarz et al., 2014). While this may be ascribed to technical limitations in the proteomic and transcriptomic analysis of complex samples from non-model organisms, it further complicates the assessment of the final relevant concentration of protein present during feeding.
The Equilibrium State and Functional Correlates
Le Chatelierās principle states that an equilibrium system will tend to counteract changes to the system to maintain its equilibrium. In biological systems this is overcome by enzymes that create intermediate states to catalyze non-reversible chemical reactions. In the case of receptor-ligand or protein-inhibitor binding, the affinity of the receptor for the ligand and the relative receptor and ligand concentrations determines the bound state at equilibrium (Figure 1). The affinity between molecules is expressed as the equilibrium dissociation constant (KD) that range for most biological systems from the fM to mM range (Smith et al., 2012). The KD is the ligand concentration at which 50% of the receptor is occupied at equilibrium (Figure 1). At a ligand concentration 10-fold the KD, a receptor would be 91% saturated and above this concentration almost all of the receptor will be occupied. However, at a ligand concentration 10-fold less than the KD, only 9% of the receptor would be occupied by the ligand and below this concentration essentially no binding occurs. At concentrations of the ligand that is equal to its KD, only 50% of the receptor will be occupied if the stoichiometry of binding is 1:1. The KD is therefore also considered to reflect a physiological relevant concentration (Sears et al., 2007). Concentrations of salivary proteins at the feeding site would therefore be physiologically relevant only at concentrations equal or exceeding their affinities for their targets by 10-fold or more if 50ā100% receptor occupancy is necessary for effective inhibition. The Ki (inhibitor constant) is determined for inhibitors of enzyme active sites and reflect the concentration necessary to reduce enzyme activity by half. It is generally used in the characterization of inhibitors using enzyme kinetics and depends on both enzyme affinity for substrate and inhibitor affinity for enzyme. Even so, it is similar to the KD and should produce similar values when enzyme activity is measured at physiological concentrations. Another measurement analogous to the KD is the IC50 value of an inhibitor. The IC50 value (half-maximal inhibitory concentration) is the concentration at which 50% inhibition of function is observed. This is generally determined for complex processes such as inhibition of platelet aggregation, blood clotting, or cell migration. This value would ultimately depend on the concentration of receptor or number of cells used in an assay, but would be close to the KD if physiologically relevant receptor or cell concentrations were used. Another measure that may indicate physiological relevance is the stoichiometric inhibition ratio (SI). This ratio indicate physiological relevance when an inhibitor interact with an enzyme or receptor close to equimolar ratios, since this imply high affinity, so that for example an SI = 2 imply saturation of receptor at 2KD. This may be seen for suicide inhibitors that bind irreversible to the enzyme active site. In enzyme kinetics the Km (Michaelis constant) is the substrate concentration that allows an enzyme to attain half Vmax. Vmax is the maximum reaction rate of the enzyme when saturated with substrate. While the Km is dependent on rate constants rather than ligand concentration it is also an indication of affinity and provide an estimate of relevant concentrations of substrates where an enzyme will function. For example, if a given agonist functions at concentrations 10-fold lower than the Km, the enzyme will not be able to effectively remove this agonist from the system and neutralize its effect. The KD, Ki, IC50, SI, and Km are therefore all useful to assess the physiological relevance of any biological activity. The reader is referred to Kuriyan et al. (2013) for a general treatment of protein-ligand affinity.
FIGURE 1
Another measure of potential functional activity is the amount of salivary gland equivalents that may have a measurable impact or functionality. For example, ā¼0.125 salivary gland equivalents from the tick Ornithodoros kalahariensis (previously Ornithodoros savignyi, ), was able to increase clotting time for the APTT test by 400%, 0.4% of a salivary gland could inhibit fXa ā¼100 and 0.07% could inhibit thrombin by ā¼100% (). As such, any function that may be measured from the equivalent of 2 salivary glands (ā¼1 tick) or less that has an appreciable effect on some function may indicate the presence of relevant functionality. Even so, if characterizing crude extracts, it should be considered that the sum of multiple functions may be measured and that individual activities may be much less.
Whether a molecule will have relevant biological activity at the feeding site depends on their affinities for their respective ligands or receptors and whether they are secreted at relevant biological concentrations. In terms of chemical equilibrium, this implies that inhibitors or kratagonists (dealt with below) needs to be present at the feeding site at higher concentrations than the KD for their respective receptors or ligands. At concentrations below the KD little or no binding will occur and inhibitors may not be effective or physiologically relevant. In addition to satisfying concentration requirements, competition between host-derived substrates, ligands or receptors and tick-derived inhibitors, enzymes or scavengers for activating biomolecules will determine whether potential host-modulatory molecules may be biologically significant. This is essentially determined by the comparative affinities of host vs. tick-derived receptor-ligand interaction. Again, the biological relevance of host-derived agonists will be determined by their active concentrations at the feeding site. Effective concentration may also be determined by protein turnover or half-life at the feeding site. This will depend on secretion into the feeding site, concentration and sequestration at the feeding site and protein stability. In the case of secretory proteins, most have disulphide bonds that increase their stability (Mans et al., 2016), contributing toward their effective concentrations. Modulation of host defenses at the tickāhost interface therefore depends on interplay between these factors, with the implication that tick-derived antagonists need to be present at higher concentrations than host-derived agonists and have higher affinities for their shared targets (Figure 2).
FIGURE 2
The Feeding Site: Effective Volume Determines Functionality
The equilibrium state is an ideal closed state and the feeding site may be considered as such. However, while the feeding site may have a defined volume approximating a closed state, the feeding site itself may be dynamic with constant changes in concentration of both host and tick proteins. Ticks ingests blood meal and salivary components, since ticks alternately salivate and ingest blood meal (; ), thereby removing both volume and active components from the feeding site. These repetitive doses of saliva, alternating by sucking events may be considered to be independent equilibrium events and in such a case may suggest that estimates of concentration at the feeding site may be lower than described below. Tick-derived molecules may also be removed into the general systemic system of the host or the general area around the feeding site, as evidenced by the systemic effects seen during paralysis and tick toxicoses (Mans et al., 2004a). Influx of blood or lymph into the feeding site may also dilute tick-derived proteins as seen in the case of edema (). As such, while the feeding site itself has been described as a hematoma or cavity that seems self-contained, the site itself may be much more dynamic than a defined cavity of blood.
A critical question remains as to what extent the feeding site may be reduced to a biochemical reaction in a test tube, i.e., can we measure the feeding site, calculate the feeding site volume and determine the amount of saliva secreted by the tick to derive estimations of biological concentrations at the feeding site? However, the feeding site is a complex and dynamic environment that changes constantly as determined by both the tick and the host (Nuttall, 2019). For example, ticks secrete enzymes that degrade the extracellular matrix over time, increasing the feeding site volume, while host wound healing responses will tend to counteract an increase in feeding site volume (Wikel, 2017). On the other hand, host inflammatory responses such as edema and cellular infiltration will tend to increase the feeding site volume, while hard ticks actively secrete excess blood-meal derived water back into the host, which will further contribute to feeding site volume, dilution and drainage of salivary proteins. As such, feeding site volumes have been conservatively estimated at 10ā50 μl (Mans et al., 2008a,b). However, feeding site volume differs between larvae, nymphs and adults, whether natural or secondary hosts are parasitized and whether hosts are naĆÆve or immune (Tatchell and Moorhouse, 1968; ,; ). Natural hosts tend to present smaller feeding lesions, while secondary hosts can produce large lesions due to inflammatory responses (,; ).
Protein Concentration at the Feeding Site and Functionally Suspect Proteins
It may be estimated what concentrations can be expected for the average secreted protein at the feeding site, by asking what the highest protein concentration may be. In this regard, the lipocalins are known to be some of the most abundant proteins synthesized in tick salivary glands (Mans, 2011; Mans et al., 2017). The TSGP1-4 lipocalins from the soft tick O. kalahariensis has been characterized in detail. They each make up ā¼5% of the total soluble salivary gland protein, comprising ā¼20% of the total soluble protein content (Mans et al., 2001; Mans and Neitz, 2004b). In this case the total protein that may be secreted by a tick during a feeding event comprise ā¼6 μg protein with molecular masses of ā¼15 kDa each. Similarly, the savignygrins (Mr ā¼ 7 kDa) also make up ā¼3% of the total salivary gland protein with ā¼4 μg of protein secreted during a feeding event (Mans et al., 2002b). In the case of the lipocalins from the soft ticks Argas monolakensis, the histamine binding protein AM-10 (Mr ā¼ 16 kDa) comprise ā¼23% of the total soluble protein (Mans et al., 2008b,c), and in this case equates with 4.6 μg of protein secreted during feeding. These concentrations are likely to be the highest estimates, since it is known that hard ticks secrete ā¼30ā300 times less protein than soft ticks in their saliva at any given feeding stage (Ribeiro, 1987; ). The upper limit for any given protein in the adult tick salivary gland may thus be assumed to be ā¼10 μg with a dynamic protein concentration range of 10,000-fold (1 ngā10 μg). If it is also assumed that nymphs have 10-fold and larvae 100-fold lower salivary concentrations than adults some interesting observations may be made regarding feeding site concentrations. For the purpose of the current study, the feeding site volumes were estimated from the studies of ,) with feeding cavities for larvae from 0.1 to 50 nl, nymphs from 5 to 150 nl, and adults from 10 nl to 10 μl. Using these assumptions concentration fluctuation at the feeding site can be estimated at various salivary gland protein concentrations and molecular masses of proteins. Under these assumptions the concentrations at the feeding site do not differ extensively between larvae, nymphs or adults, even though feeding site volume and effective salivary gland concentrations may differ (Figure 3). Allowing for the concentration ranges estimated, maximum concentrations at the feeding site may range from nM to mM, and may even range from nM to μM for salivary gland concentrations such as 0.1, 0.01, or 0.001 μg for adults, nymphs, or larvae, respectively, that may be considered to be more representative of the average protein concentration. These concentrations may be an over estimation since the dynamic nature of the feeding site and the rate at which protein is secreted may never approximate these total estimated concentrations.
FIGURE 3
In ticks the IC50, KD, and Ki values range from pMāmM and falls within the concentration expected at the feeding site (Figure 3, 4). IC50 values generally tend to range from 10 nM to 10 μM (Figure 2). Conversely, KD values range from 1 nM to 1 μM, while Ki values range from 10 pM to 10 nM. The higher IC50 values is probably due to the use of in vitro assays that measure complex reactions such as platelet aggregation, blood clotting, complement or cell migration. These systems do not necessarily represent true in vivo conditions and may be artificial to some extent, i.e., much higher concentrations of agonists or cell numbers are needed for observation than what is found under physiological conditions. The KD values may represent true affinities, while the Ki values are dependent on the enzyme and substrate concentrations used, and the lower pM values may be due to the availability of chromogenic and fluorogenic substrates that enable sensitive measurement of enzyme activity. In this case, some of the affinities may be overestimated.
FIGURE 4

Ranges of IC50, KD, and Ki values from the tick literature. Indicated are frequency distribution curves of values obtained from Table 1 and references therein.
A number of tick proteins characterized have affinities, inhibition constants or IC50 values in the nM or pM range, which would probably be functional at the feeding site (Figure 4 and Table 1). For some, concentrations at the feeding site may be estimated based on yields of purified inhibitor and these are generally in the same range as the affinities or higher, suggesting biological relevant concentrations at the feeding site (Table 1). For a number of proteins, estimates of concentrations at the feeding site is not available and the low nM to pM range of their KD, Ki, or IC50 values is the only indication of functional relevance. A number of proteins also present extraordinary high concentration estimates at the feeding sites (>1 M), which may indicate that these proteins may not have been completely purified at the time of their characterization, or may reflect that they derived from whole body extracts and not tick salivary glands, which may suggest that these inhibitors originate from multiple organs (
Table 1
| Protein | Tick | Target | Affinity (KD, Ki, Km, IC50) | Concentration (MinimumāMaximum) | References |
|---|---|---|---|---|---|
| Apyrase | Ixodes scapularis | ATP/ADP | N/A | Activity in saliva | Ribeiro et al., 1985 |
| Apyrase | Ornithodoros moubata | ATP/ADP | N/A | Activity in saliva | Ribeiro et al., 1991 |
| Apyrase | Ornithodoros kalahariensis | ATP/ADP | Km ~ 1 mM | Activity in saliva 1 μMā1 mM | Mans, 1997; Mans et al., 1998b |
| Ir-CPI | Ixodes ricinus | fXIIa, fXIa, Plasmin | KD ~ 16ā38 nM | Unknown | |
| PAI | Ixodes sinensis | Platelets | IC50 ~ 250 nM | Unknown | Liu et al., 2005 |
| Savignygrin | Ornithodoros kalahariensis | αIIbβ3 | IC50 ~ 130 nM; KD ~ 60 nM | 55 μMā57 mM | Mans et al., 2002b; Mans and Neitz, 2004c |
| Monogrin | Argas monolakensis | αIIbβ3 | IC50 ~ 150 nM | 10 μMā10 mM | Mans et al., 2008a |
| Variabilin | Dermacentor variabilis | αIIbβ3 | IC50 ~ 150 nM | 2.7 μMā2.7 mM | Wang et al., 1996 |
| Disagregin | Ornithodoros moubata | αIIbβ3 | IC50 ~ 104 nM; KD ~ 40 nM | 20 μMā20 μM | |
| YY-39 | Ixodes scapularis | αIIbβ3 | IC50 ~ 4ā20 μM | Unknown | Tang et al., 2015 |
| TAI | Ornithodoros moubata | α2β1 | IC50 ~ 5ā8 nM; KD ~ 40 nM | 50 nMā50 μM | |
| Moubatin | Ornithodoros moubata | TXA2 | IC50 ~ 50 nM KD ~ 24 nM | 1.5 μMā1.5 mM | Waxman and Connolly, 1993; Mans and Ribeiro, 2008b |
| TSGP2 | Ornithodoros kalahariensis | LTB4 | KD ~ 18 nM | 38 μMā38 mM | Mans et al., 2001; Mans and Ribeiro, 2008b |
| TSGP3 | Ornithodoros kalahariensis | TXA2; LTB4 | KD ~ 5ā21 nM | 38 μMā38 mM | Mans et al., 2001; Mans and Ribeiro, 2008b |
| Ir-LBP | Ixodes ricinus | LTB4 | KD ~ 0.5 nM | Detected in saliva | |
| TSGP4 | Ornithodoros kalahariensis | LTC4 | KD < 2 nM | 35 μMā35 mM | Mans et al., 2001; Mans and Ribeiro, 2008a |
| AM-33 | Argas monolakensis | LTC4 | KD ~ 2 nM | 3.5 μMā3.5 mM | Mans et al., 2008c; Mans and Ribeiro, 2008a |
| TSGP1 | Ornithodoros kalahariensis | Histamine Serotonin | KD < 3 nM; KD ~ 6 nM | 32 μMā32 mM | Mans et al., 2001, 2008b |
| OP-3 | Ornithodoros parkeri | Histamine Serotonin | KD ~ 106 nM; KD ~ 116 nM | Detected in SGE | |
| OtLip | Ornithodoros turicata | Histamine | Unknown | Unknown | Neelakanta et al., 2018 |
| Monomine | Argas monolakensis | Histamine | KD ~ 7 nM | 29 μMā28 mM | Mans et al., 2008b,c |
| Monotonin | Argas monolakensis | Serotonin | KD < 2 nM | 10 μMā10 mM | Mans et al., 2008b,c |
| Is-14 | Ixodes scapularis | Histamine Serotonin | KD ~ 427 nM; KD < 2 | Unknown | Mans et al., 2008c |
| Is-15 | Ixodes scapularis | Histamine Serotonin | KD ~ 746 nM; KD < 2 | Unknown | Mans et al., 2008c |
| HBP1-3 | Rhipicephalus appendiculatus | Histamine | KD ~ 1ā18 nM | Detected in SGE | Paesen et al., 1999 |
| SHBP | Dermacentor reticulatus | Histamine Serotonin | KD ~ 1ā2 nM KD ~ 0.6 nM | Unknown | Sangamnatdej et al., 2002 |
| Savignin | Ornithodoros kalahariensis | Thrombin | Ki ~ 5 pM | 850 nMā1 mM | Nienaber et al., 1999 |
| P5 | Hyalomma dromedarii | Thrombin | Ki ~ 500 nM | 30 μMā30 mM | |
| Sculptin | Amblyomma sculptum | Thrombin | IC50 ~ 2 pM Ki ~ 18 pM; | Unknown | |
| Avathrin | Amblyomma variegatum | Thrombin | IC50 ~ 7 nM Ki ~ 545 pM | Unknown | |
| Boophilin | Rhipicephalus microplus | Thrombin | IC50 ~ 1 μM Ki ~ 101, 0.5ā2 nM KD ~ 116 nM | Unknown | Macedo-Ribeiro et al., 2008; Soares et al., 2012; |
| RmS-15 | Rhipicephalus microplus | Thrombin | SI ~ 2 | Unknown | Rodriguez-Valle et al., 2015; Xu T. et al., 2016 |
| Hyalomin-1 | Hyalomma rufipes | Thrombin | Ki ~ 12 nM KD ~ 19 nM | Unknown | |
| rIxscS-1E1 | Ixodes scapularis | Thrombin | SI ~ 4 | Unknown | |
| Monobin | Argas monolakensis | Thrombin | Ki ~ 6 pM | 400 nMā400 μM | Mans et al., 2008a |
| Chimadanin | Haemaphysalis longicornis | Thrombin | IC50 ~ 300 nM | Unknown | Nakajima et al., 2006 |
| Madanins | Haemaphysalis longicornis | Thrombin | KD ~ 3ā4 μM; Ki ~ 31ā55 nM | Unknown | |
| Variegin | Amblyomma variegatum | Thrombin | IC50 ~ 1 nM; Ki ~ 10 pM | Unknown | |
| NTI-2 | Hyalomma dromedarii | Thrombin | Ki ~ 211 nM | 3.8 mMā3.8 M | |
| Americanin | Amblyomma americanum | Thrombin | Ki ~ 0.073 nM | 100 nMā100 μM | Zhu et al., 1997a |
| Saliva | Amblyomma americanum | fXa; Thrombin | 100% I ~ 0.3 SU | Unknown | Zhu et al., 1997b |
| Ornithodorin | Ornithodoros moubata | Thrombin | Ki ~ 1 pM | Unknown | van de Locht et al., 1996 |
| Anticoagulant | Ixodes holocyclus | Clotting | IC50 ~ 0.25 SGU | Unknown | |
| Ixin | Ixodes ricinus | Thrombin | IC50 ~ 0.6 SGU | Unknown | |
| Calcaratin | Rhipicephalus calcaratus | Thrombin | Unknown | Unknown | Motoyashiki et al., 2003 |
| Haemathrin | Haemaphysalis bispinosa | Thrombin | IC50 ~ 40 μM | Unknown | |
| Microphilin | Rhipicephalus microplus | Thrombin | IC50 ~ 6ā42 μM | 17 μMā17 mM | |
| BmAP | Rhipicephalus microplus | Thrombin | IC50 ~ 100 nMā1 μM | 333 nMā33 μM | |
| NTI-1 | Hyalomma dromedarii | Thrombin | Ki ~ 11.7 μM | 650 μMā6.5 M | |
| HLS2 | Haemaphysalis longicornis | Thrombin | IC50 ~ μM | Unknown | |
| IRS-2 | Ixodes ricinus | Cathepsin G; Chymase | IC50 ~ 4ā11 nM | Unknown | |
| AamS6 | Amblyomma americanum | Undefined | All tests μM range; no parameters | Immunogenic | |
| Penthalaris | Ixodes scapularis | Tissue factor pathway | IC50 ~ 100 pM | Unknown | |
| Ixolaris | Ixodes scapularis | Tissue factor pathway fXa | IC50 ~ pM range | Unknown | |
| Hd_fXaI | Hyalomma dromedarii | fXa | Ki ~ 134 nM | 0.3 mMā300 mM | |
| Anticoagulant | Rhipicephalus appendiculatus | fXa | 450% clotting time increase for 2 SGU | 100 nMā125 μM | Limo et al., 1991 |
| TAP | Ornithodoros moubata | fXa | Ki ~ 0.6 nM | 8 μMā8 mM | Waxman et al., 1990 |
| fXaI | Ornithodoros kalahariensis | fXa | Ki ~ 0.8 nM | 250 nMā250 μM | |
| Salp14 | Ixodes scapularis | fXa | IC50 ~ 150 nM | Immunogenic | Narasimhan et al., 2002 |
| Amblyomin-X | Amblyomma sculptum | fXa | IC50 ~ 10 μM; Ki ~ 4 μM | Unknown | |
| TIX-5 | Ixodes scapularis | fV | IC50 ~ 3.2 μM; all tests μM range | Immunogenic | Schuijt et al., 2011, 2013 |
| Rhipilin-1 | Rhipicephalus haemaphysaloides | Elastase | SI ~ 6 | Unknown | |
| BmTI-A | Rhipicephalus microplus | Elastase; Kallikrein | Ki ~ 1.4 nM; Ki ~ 120 nM | Unknown | Tanaka et al., 1999 |
| Iris | Ixodes ricinus | Elastase TNF-α | IC50 ~ μM IC50 ~ 50 nM | Unknown | Leboulle et al., 2002; Prevot et al., 2006, 2009 |
| RsTIQ 2, 5, 7 | Rhipicephalus sanguineus | Elastase; plasmin | Ki ~ 1ā38 nM | Unknown | SantāAnna Azzolini et al., 2003 |
| Haemaphysalin | Haemaphysalis longicornis | fXIIa | IC50 ~ 50ā100 nM; KD ~ 3 nM | Unknown | |
| AAS19 | Amblyomma americanum | Plasmin; Thrombin | SI ~ 3ā9 | Unknown | |
| TdPI | Rhipicephalus appendiculatus | Tryptase | Ki < 1.5 nM | Unknown | Paesen et al., 2007 |
| Tryptogalinin | Ixodes scapularis | Plasmin Tryptase | Ki ~ 5.83 nM Ki ~ 10 pM | Unknown | ValdƩs et al., 2013 |
| Sialostatin L | Ixodes scapularis | Cathepsin L | IC50 ~ 5 nM; Ki ~ 95 pM | Detected in saliva | Kotsyfakis et al., 2006 |
| Sialostatin L2 | Ixodes scapularis | Cathepsin L | IC50 ~ 70 pM; Ki ~ 65 pM | Unknown | Kotsyfakis et al., 2007 |
| Iristatin | Ixodes ricinus | Cathepsin L and C | IC50 ~ 500 nMā3 μM | Unknown | KotĆ”l et al., 2019 |
| OmC2 | Ornithodoros moubata | Cathepsin L and S | IC50 ~ 150 pM; Ki ~ 65 pM | Detected in saliva | |
| BrBmcys2b | Rhipicephalus microplus | Cathepsin B and L | Ki ~ 1ā3 nM | Detected in saliva | Parizi et al., 2013 |
| RHcyst-2 | Rhipicephalus haemaphysaloides | Cathepsin S | IC50 ~ 100 pM | Detected in saliva | Wang et al., 2015 |
| TCI | Rhipicephalus bursa | Carboxy-peptidase | Ki ~ 1ā4 nM | 150 nMā150 μM | |
| HlTCI | Haemaphysalis longicornis | Carboxy-peptidase | IC50 ~ 10 μM | Unknown | |
| Evasin-1 | Rhipicephalus sanguineus | CCL3; CCL8; CCL18 | KD ~ 160 pM; KD ~ 810 pM; KD ~ 3 nM | Detected in saliva | |
| Evasin-3 | Rhipicephalus sanguineus | CXCL1; CXCL8 | KD ~ 340 pM; KD ~ 700 pM; | Detected in saliva | |
| Evasin-4 | Rhipicephalus sanguineus | CCL1-CCL27 | KD ~ 10ā700 pM; | Detected in saliva | |
| P1243 (AAM-02) | Amblyomma americanum | CCL1-CCL27 | KD ~ 1ā100 nM | Unknown | |
| P1156 | Ixodes ricinus | CXCL1-8 | KD ~ 3ā70 nM | Unknown | |
| RPU-01, RPU-02, AAM-01, AAM-02, ACA-01, ACA-02, AMA-01, ATR-02, IRI-01 | Rhipicephalus pulchellus Amblyomma americanum Amblyomma cajennense Ixodes ricinus Ixodes holocyclus | Eotaxin-1; Eotaxin-2; Eotaxin-3; MCP-1; MCP-2; MCP-3 | KD ~ 5ā1,000 nM | Unknown | |
| P991, P985, P546, P974, P983, P1181, P1182, P1183, P1180, P467 | Amblyomma maculatum Amblyomma triste Amblyomma parvum Rhipicephalus pulchellus | CCL2, CCL3, CCL4, CCL7, CCL8, CCL11, CCL13,CCL14, CCL16, CL17, CCL18,CCL19 CCL20,CCL21, CCL22, CL23 CCL24,CCL27, CCL28, CCL25 | KD ~ 1 pMā3 μM | Unknown | Singh et al., 2017 |
| P672 | R. pulchellus | CCL3, CCL8, CCL11, CCL13, CCL14, CCL16, CCL18, CCl23 | KD ~ 1ā10 nM; IC50 ~ 2ā6 nM | Unknown | |
| OMCI | Ornithodoros moubata | C5 complement | IC50 ~ 12ā27 nM KD ~ 18 nM KD < 100 pM | 29 μMā29 mM | Nunn et al., 2005; |
| TSGP2 | Ornithodoros kalahariensis | C5 complement | KD ~ 26 nM | 38 μMā38 mM | Mans et al., 2001; Mans and Ribeiro, 2008b |
| TSGP3 | Ornithodoros kalahariensis | C5 complement | KD ~ 14 nM | 38 μMā38 μM | Mans et al., 2001; Mans and Ribeiro, 2008b |
| RaCI | Rhipicephalus appendiculatus | C5 complement | IC50-6ā21 nM | Unknown | |
| Isac; Salp9; Salp20 | Ixodes scapularis | C3 complement | IC50 ~ 200 nM | Detected in saliva | Valenzuela et al., 2000; Soares et al., 2005; Tyson et al., 2007, 2008 |
| IRAC; IxAC | Ixodes ricinus | C3 complement | IC50 ~ 10ā50 nM | Unknown | |
| HT1-12 | Ixodes holocyclus | Presynapse | IC50 ~ 1ā10 mM | Detected in saliva | |
| Salp15 | Ixodes scapularis | T cell proliferation IL2 production CD4 | KD ~ 47 nM | Detected in saliva | |
| Longistatin | Haemaphysalis longicornis | RAGE | KD ~ 72 nM | Detected in saliva | |
| Adrenomedullin | Ornithodoros moubata | Vasodilation | IC50 ~ 7 nM | Unknown | |
| Ra-KLP | Rhipicephalus appendiculatus | maxiK channels | AC50 ~ 1 μM | Unknown | Paesen et al., 2009 |
| Ixonnexin | Ixodes scapularis | Plasminogen-tPA | Km ~ 70ā200 nM KD ~ 4ā19 nM | Detected in saliva | |
Tick inhibitors of host defenses considered to have relevant physiological function.
Indicated are relative affinity reported as the dissociation equilibrium constant (KD), inhibitory constant (Ki), Michaelis constant (Km), stoichiometric inhibition ration (SI), or inhibitory concentration (IC50). Salivary gland unit (SGU) refers to a fraction of a salivary gland. Minimum and maximum concentrations were calculated based on yields per tick reported and a feeding site volume of 10 nlā10 μl. Were indicated that proteins were detected in saliva or salivary gland extract (SGE), this was done with either western blot, affinity pull-down or proteomics.
Tick Feeding and Modulation of Host Defenses
Ticks need to modulate their vertebrate hostās defense mechanisms to obtain a successful blood-meal (
FIGURE 5

Various mechanisms used by ticks to modulate vertebrate host defenses.
Inhibitors That Target Enzyme Active Sites and/or Substrate-Binding Exosites
Various enzymes are involved in host hemostasis and many are part of enzyme cascades such as the blood clotting or complement cascade that enable efficient control as well as rapid response to injury or infection (
With regard to host protein concentrations and affinities, prothrombin occurs at ~1.4 μM in plasma, although only sub μM quantities are generally converted to thrombin (
Inhibitors That Target Sites Distant From Enzyme Active Sites
Inhibitors may target enzymes at sites distant from the active site, thereby disrupting complex assembly and downstream activation and include inhibitors of C5 complement such as Ornithodoros moubata complement inhibitor (OMCI) and Rhipicephalus appendiculatus complement inhibitor (RaCI) (Nunn et al., 2005;
Inhibitors That Target Receptor Ligand-Binding Sites
Inhibitors that target cell receptors thereby blocking binding of natural ligands and receptor activation includes fibrinogen receptor (GPIIbIIIa; αIIbβ3) antagonists that inhibit platelet aggregation induced by any agonist (
Tick adhesion inhibitor (TAI) inhibits adhesion of platelets to collagen with an IC50 ~ 8 nM (
Longistatin binds to the V domain of the receptor for advanced glycation end products (RAGE) with a KD ~ 72 nM, thereby inhibiting ligand-induced inflammation in tissues (
Inhibitors that target receptors and upon binding induce antagonistic responses do exist. Salp15 binds to the CD4 coreceptor on T cells with a KD ~ 47 nM and inhibits T-cell receptor ligation induced activation resulting in immunosuppression (
Inhibitors That Target Soluble Protein Agonists
A number of soluble host protein agonists exist that play a role in inflammation and immunity. These generally bind to receptors on leukocytes to activate cellular responses and cellular migration and are collectively known as cytokines or chemokines (Sokol and Luster, 2015). Leukocytes include eosinophils, mast cells, monocytes, neutrophils and natural killer cells that migrate along chemokine concentration gradients caused by release of chemokines from sites of infection or inflammation (Moore et al., 2018). A large number of chemokines exist that have specificities for different cell types. Chemokines are classified based on their conserved disulphide bond patterns. C chemokines possess a single disulphide bond and consist of two chemokines (XCL1 and XCL2). CC chemokines (β-chemokines) possess two disulphide bonds, with adjacent cysteines near the N-terminal and consist of 28 chemokines (CCL1āCCL28), described thus far. CXC chemokines (α-chemokines) possess two disulphide bonds with the adjacent cysteines near the N-terminal separated by a single amino acid and consist of 17 chemokines (CXCL1āCXCL17), described to date. A number of inhibitors from ticks that interact directly with these soluble agonists and prevent binding to their receptors have been described and are known as the evasins (
In the case of chemokines where leukocytes respond to concentration gradients for directional chemotaxis, the measured gradients suggest that these may range across low pM to several hundred nM (Moore et al., 2018). Naturally formed gradients depend on various factors that will influence the concentration gradient, notably, the type of cell secreting the chemokine, the amount secreted that depend on environmental cues, the presence of flow-induced shear stress and interaction of the chemokines with the extracellular matrix (Moore et al., 2018). Depending on the KD of the evasins (low nM), chemotaxis may only be efficiently inhibited somewhere along the concentration gradient and not across the whole range, especially since competition of evasins for different chemokines might occur.
Enzymes That Target Matrices or Matrix Components
Ticks feed from a feeding cavity where blood pools (Tatchell and Moorhouse, 1968). The feeding site needs to be remodeled to form this cavity (Wikel, 2017). Ticks may secrete a variety of enzymes that will enable such remodeling. This includes hyaluronidase that targets hyaluronic acid, a major component of the extracellular matrix (Neitz et al., 1978). Salivary transcriptomes also indicate that an abundant class of enzymes are the metalloproteases (Mans et al., 2016). While their role in feeding site remodeling has not been established beyond doubt, the general assumption is that these enzymes would play a role in remodeling (Mans, 2016; Wikel, 2017). Other metalloproteases that has been identified with a defined function include fibrin(ogen)ase activity that remove fibrinogen, both substrate for thrombin or platelet aggregation, or fibrin that forms the blood clot (
Enzymes That Perform Scavenging Functions
Some enzymes may perform scavenging functions by targeting bioactive molecules and catalyzing chemical reactions that inactivate or remove these molecules. This may prevent activation of receptors, or induce antagonistic responses in receptors by removal of activating ligand. In ticks, the enzyme apyrase (ATP-diphosphohydrolase; EC 3.6.2.5) hydrolyse ATP that function in inflammation (
Kratagonists That Perform Scavenging Functions
Kratagonists are related to āscavengingā enzymatic functions, by scavenging or mopping up of bioactive molecules, but without chemically changing their structures. Kratagonists may have similar functional activity as āscavengingā enzymes, such as preventing activation of receptors by ligands, or competitive removal of ligand from receptors causing an antagonistic response (Ribeiro and ArcĆ , 2009;
In the case of small chemical agonists that are scavenged by either enzymes or kratagonists, the concentrations at which they activate their respective receptors are important. Platelets secrete ADP and ATP at 3ā7 μM concentrations, which are also the concentration necessary for primary and secondary aggregation (Packham and Rand, 2011). Apyrase from ticks has been shown to effectively inhibit platelet aggregation at these activator concentrations, at enzyme concentrations well below the expected secretory levels (Mans et al., 1998b). Basophils and mast cells may secrete histamine to attain local concentrations of 20 μM in the skin that can lead to inflammatory responses when histamine binds to its receptors with KD ~ 10 nMā30 μM (Petersen, 1997; MacGlashan, 2003). Serotonin is secreted by platelets at local concentrations of ~5 μM where it can cause vasoconstriction and platelet aggregation by binding to various serotonin receptors with Ki ~ 10 nMā1 μM (Watts et al., 2012). The very high concentrations of biogenic amine binding kratagonists at the feeding site (μMāmM) and their low affinities (low nM) indicate that they will be biologically relevant at the feeding site (Table 1).
Leukotriene B4 secreted by neutrophils may reach high concentrations at the site of neutrophil release (~950 nM) (Lewis et al., 1982). The affinity of LTB4 for its neutrophil receptor BLT1 ranges from 0.1 to 2 nM (Yokomizo, 2015). Again, the low affinities observed for the LTB4 scavengers and their high concentrations (μM) at the feeding sites would make them relevant competitors at the feeding site.
Cysteinyl leukotrienes can only be detected in plasma during inflammatory reactions such as asthma attacks and then occur at concentrations of ~100ā765 pM (Sasagawa et al., 1994). It has been shown to cause vasoconstriction and vasopermeability at a concentration of ~100 nM, and bind with affinities from 5 to 35 nM to its receptors (
Thromboxane A2 is released from platelets at concentrations of 11ā35 nM, which is capable of inducing platelet aggregation and bind to platelet receptors with KD ~ 4 nM (
Activators of Host Regulatory Systems
The majority of tick host modulatory mechanisms described so far comprise inhibitors. However, activators may also play important roles since these may target the natural regulatory feedback systems of host hemostasis. Plasminogen activators that result in degradation of the fibrin clot have already been discussed. Recently, a small peptide named ixonnexin that belongs to the basic tail family was described that act by promoting interaction of plasminogen and tissue plasminogen activator (tPA) by forming a enzymatically productive ternary complex that forms plasmin to promote fibrinolysis (
The adrenomedullins are a special case of tick-derived inhibitors that bind to host calcitonin-receptor-like receptor and receptor activity-modifying protein receptor complexes to cause vasodilation (
An activator of MaxiK channels have been described in R. appendiculatus, where it presumably play a role in regulation of blood vessel tonus and blood flow (Paesen et al., 2009). It invoked a half maximal response in MaxiK channels at 1 μM. Its functionality at the feeding site remains to be resolved.
Non-protein Agonists and Inhibitors
Ticks may also secrete non-protein agonists that could affect the hostās defense mechanisms. As such, ixodid ticks secrete prostaglandin E2 (PGE2), a potent vasodilator, at ~40ā500 ng/ml saliva (Ribeiro et al., 1985, 1992;
Strategies to Circumvent the Affinity/Equilibrium Barrier
It is evident that the majority of tick proteins thus far characterized would have physiological functionality at the feeding site (Figure 3 and Table 1). However, expression and secretion of high concentrations of secretory proteins via the salivary secretory granules may be restricted to very few proteins given physical constraints of granule packaging (Mans and Neitz, 2004b). The dynamic nature of the feeding site may also make the actual concentrations of tick proteins present at any given moment much more haphazard than expected. The concentrations at the feeding site may very well be 100ā10,000-fold lower than estimated, in which case concentrations may drop to pMānM for most proteins, which may be below the KD values for many proteins. To address this, ticks may employ various alternative strategies that allow adequate expression and optimal use of secreted proteins at the feeding site that allow ticks to circumvent or eliminate the problems posed by an equilibrium system (Figure 6). The next section discusses such strategies in more detail.
FIGURE 6

Strategies to circumvent the equilibrium barrier. Ticks can use various strategies to increase local concentrations at the feeding site to satisfy equilibrium binding conditions.
Redundancy as Means to Control Complexity and Chaos
The hostās defense systems such as the clotting, platelet aggregation, complement and inflammatory cascades are part of one big redundant integrated feedback system that allows rapid response as well as control of the system (
Fast Feeding, Storage and Secretion of a Large Bolus of Salivary Proteins
Soft ticks feed within minutes to hours to repletion, drop off, digest the blood meal slowly over the course of weeks to months, lay a small egg batch and can then feed several times more using the same pattern (Mans and Neitz, 2004a). During fast feeding most salivary proteins may be secreted in the course of 10ā30 min and will be replenished within several days after feeding. Secretory proteins are stored in large granules up to 10 μM in diameter that effectively fill the salivary gland cells to their maximum extent (Mans and Neitz, 2004b; Mans et al., 2004b). The protein profiles of soft tick SGE attest to this, since protein spectra rarely show the presence of genomic DNA, in contrast to SGE from hard ticks that predominantly show genomic DNA/RNA, while the protein peak and concentration is obscured (Figure 7). This strategy from soft ticks allows concentrations of proteins that can overcome relatively high equilibrium dissociation constants by sheer concentration effects alone. Hard ticks utilize this strategy to some extent, since different salivary gland cells are filled with secretory granules over the course of the feeding period that can last several days to weeks (
FIGURE 7

The absorbance spectra of salivary gland extracts (SGE) from hard and soft ticks. The top graph shows the spectrum of SGE of 4 glands from Amblyomma hebraeum suspended in 100 μl water. Based on the 280 nm absorbance a single gland would have a soluble protein concentration of ~128 μg. Bradford determination indicated a concentration closer to ~60 μg/gland. The bottom graph shows the spectrum of SGE of 42 glands from Ornithodoros phacochoerus suspended in 500 μl water. Based on the 280 nm absorbance a single gland would have a soluble protein concentration of ~127 μg. Bradford determination indicated a concentration of ~125 μg/gland. These absorbance spectra are representative of hard and soft tick SGE in general.
Communal Feeding to Increase Local Concentrations at the Feeding Site
Hard ticks feed for several days to weeks and mating on the host (or off the host for some Ixodes species) during the slow pre-feeding phase is required before the rapid engorgement phase can occur (
Gene Dosage and Cumulative Contributions From Multigene Families
Proteins may be maintained as gene duplicates to allow high level expression from each family member (Mans et al., 2017). While each member may by itself completely inhibit host functions, even partial inhibition by each gene duplicate can result in complete inhibition. This is a relatively simple example of the gene dosage effect that has been observed for fibrinogen receptor antagonists (Mans et al., 2003a, 2008a) and LTB4 scavengers (Mans et al., 2003b; Mans and Ribeiro, 2008b). It has been proposed that multigene families express different antigenic variable family members at low concentration levels to escape the immune system, the varying epitope hypothesis (
Increasing Concentration at the Feeding Site
The vertebrate host uses localized cues and responses to maintain and regulate haemostasis. As such, wounds or breakdown in system integrity are detected by exposure of localized collagen or other extracellular matrix components, activation of platelets and exposure of procoagulant platelet surfaces, initiation of blood-clotting and the complement cascade on activated platelet surfaces (
Increasing Effective Concentration Using Multiple Binding Sites or Multiple Functions
In the case of some tick lipocalins their effective concentration is increased by possessing two independent binding sites for histamine or one for histamine and one for serotonin (Paesen et al., 2000; Sangamnatdej et al., 2002; Mans et al., 2008b). This increase their capacity for scavenging twofold. Another variation on this may be proteins that can potentially target many independent ligands or targets and may therefore have multiple functions. While this certainly expands the potential of proteins to work within a complex redundant environment, the most effective of these would be proteins that have independent function and mechanisms. For example, targeting of complement C5 and LTB4 allows OMCI and its homologs to inhibit both complement and LTB4 mediated inflammation at the same time (Nunn et al., 2005; Mans and Ribeiro, 2008b; Roversi et al., 2013). In this case, both functions target the two key non-redundant mediators of neutrophil recruitment during inflammation that seems to be intricately linked (Sadik et al., 2018). This is a remarkable convergence of function in a single protein (Mans et al., 2017). On the other hand, if the functional mechanisms are not independent, i.e., use the same site for ligand binding or the same protein surface to target different proteins, competition between targets will effectively lower the concentration of available inhibitor, thereby impacting its functionality. This may be seen for moubatin and its homologs that bind both LTB4 and TXA2 within the same lipocalin cavity at similar affinities (Mans and Ribeiro, 2008b). If both LTB4 and TXA2 are present at similar concentrations, the effective scavenging capability may be halved. One way to compensate for this may be multiple proteins or very high concentrations at the feeding site as observed for moubatin, TSGP2 and TSGP3. The same problem would face many of the enzyme inhibitors that can inhibit two or more enzymes from a specific class such as the cystatins, where the presence of many different host enzymes at the feeding site would lead to competition with the tick inhibitors. Similarly, the evasins can bind to many chemokines with similar affinities that may lead to competition of evasins for different chemokines, thereby reducing their effectivity.
Suicide Inhibitors
Inhibitors that bind in a 1:1 manner to their target enzymes, and then serve as substrate, resulting in the formation of a covalent enzyme-inhibitor complex, circumvent the equilibrium dissociation problem completely. Their initial affinities need only to be high enough for the enzyme to catalyze its reaction and form the covalent complex to result in permanent inhibition. In ticks, such inhibitors are found in the serpins that target various enzymes of the clotting cascade (
Differential Expression
Ixodid ticks express different proteins at different periods during feeding (McSwain et al., 1982; Paesen et al., 1999; Wang et al., 2001b;
Minimizing Feeding Site Volume
Comparison of adult, nymphal, and larval concentrations at the feeding site indicates that the relative concentrations remain constant between the various life stages even though salivary gland concentrations may differ several fold (Figure 3). This is mostly due to the differences observed in feeding cavity size that scale relative to the life stage and tick size. If this observation holds for all tick species it would imply that smaller ticks compensate by creating smaller feeding cavities. Feeding cavity size may then be related to protein concentration secreted during feeding.
Smaller Proteins Allow Higher Molar Concentrations
The majority of secretory salivary proteins in ticks have low molecular masses below 25 kDa. This include the majority of highly abundant protein families such as the basic tail secretory, Kunitz-BPTI and lipocalin families (Mans et al., 2008c, 2016; Mans, 2011). Lower molecular masses allow higher relative molar concentrations at the feeding site, which could result in an up to a 10-fold difference between a 5 and 50 kDa protein (Figure 3).
Functional Relevance and Mechanism
Understanding the mechanism of action (how a given protein works) is important in accessing functional relevance. As example, the case of moubatin may be considered. Originally moubatin was identified as a specific inhibitor of collagen-induced platelet aggregation with an IC50 ~ 50 nM, that did not affect ADP, arachidonic acid, thrombin, ristocetin, or calcium ionophore A23187 induced platelet aggregation (Waxman and Connolly, 1993). Subsequently, recombinant moubatin was shown to inhibit collagen-induced platelet aggregation with IC50 ~ 100 nM but did not inhibit adhesion to collagen (
Systems Biology, Bioinformatics and Functional Relevance
While the majority of functions found in ticks may be assigned functional significance (Table 1), enough reports in the literature indicate that caution should be exercised when evaluating functional relevance. This is compounded by advances in technology that allow systems approaches to the analysis of salivary gland protein dynamics and bioinformatics that allows functional analysis in silico. As such, recent advances in technology, both in next-generation transcriptome sequencing and proteomics, has allowed an unprecedented view of salivary gland dynamics from a systems perspective (Schwarz et al., 2014;
Is Functional Relevance Relevant?
It may be considered whether it really matters whether a measured function is relevant during feeding, given the emerging recognition that all proteins may be moonlighting to some extent. From this perspective, any function present in tick saliva should be relevant at some level and our goal for the next few decades would be to assign functions to salivary proteins, whether relevant or not. A more comprehensive understanding would later emerge once we have gathered enough data to truly assess relevance. This position is appealing since it buys some time for dubious functions. It is, however, also a philosophical āeverything goesā viewpoint (
Functional Relevance From a Practical Perspective
The use of tick salivary proteins as therapeutic agents within a clinical or pharmaceutical setting remains an important and promising goal (Mans, 2005). From this perspective any function determined for a protein need not be functionally relevant at the tick feeding site, as long as the specific parameters for use has been determined that would allow it to function under clinical or therapeutic controlled conditions. For example, the half-life of OMCI could be improved >50-fold by PASylation, making it more relevant for clinical use (Kuhn et al., 2016). In a similar vein, anti-tick vaccines may be developed against proteins with unknown functions or even irrelevant function, as long as the vaccine shows efficacy, as for example for hidden antigens (Nuttall et al., 2006). On the other hand, development of vaccines against exposed antigens may work better if antigens with real functional significance at the feeding site can be defined, their mechanism of action elucidated and this information used to rationally design target strategies that would neutralize function at the feeding site effectively.
Conclusion
Functional relevance is determined by the concentration of tick proteins at the feeding site as well as their affinity for their respective host targets. The current review showed that the majority of proteins found in tick saliva or salivary glands thus far characterized will be functional at the tick feeding site. It was also shown how ticks may circumvent the problems presented by an equilibrium system. Even so, inferring functional relevance without estimating concentration or affinity at the feeding site remains a risky endeavor. Future aims in salivary gland biology should focus on quantification of protein concentration secreted during feeding as well as in the actual feeding site. This should provide more accurate estimates of functional relevance.
Statements
Author contributions
BM conceptualized the study and wrote the manuscript.
Funding
This work was supported by the Economic Competitive Support Programme (30/01/V010), the National Research Foundation (NRF) Incentive Funding (IFR2011032400016) for Rated Researchers (NRF-Mans), and the National Research Foundation (NRF) Competitive Funding for Rated Researchers (CPRR180101296400). The funding bodies had no role in study design, data collection, analysis and interpretation, decision to publish, or preparation of the manuscript.
Acknowledgments
Ronel Pienaar is thanked for assistance with the graphic figures in the study. The reviewers are thanked for constructive criticism and additional ideas that improved the study.
Conflict of interest
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
tick, host, feeding, affinity, equilibrium, function, relevance
Citation
Mans BJ (2019) Chemical Equilibrium at the TickāHost Feeding Interface:A Critical Examination of Biological Relevance in Hematophagous Behavior. Front. Physiol. 10:530. doi: 10.3389/fphys.2019.00530
Received
12 March 2019
Accepted
15 April 2019
Published
01 May 2019
Volume
10 - 2019
Edited by
Abid Ali, Abdul Wali Khan University Mardan, Pakistan
Reviewed by
Jose Ribeiro, National Institute of Allergy and Infectious Diseases (NIAID), United States; Tae Kim, Texas A&M University, United States; Jan Perner, Institute of Parasitology (ASCR), Czechia
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Copyright
Ā© 2019 Mans.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ben J. Mans, mansb@arc.agric.za
This article was submitted to Invertebrate Physiology, a section of the journal Frontiers in Physiology
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