*3.3. MicroRNA Profiling of Infected and Uninfected Salivary Glands and Identification of Novel Tick miRNAs*

Figure 2A shows the basic hairpin-loop structure of an miRNA and other parameters (Dicer cut overhangs, total read count, mature read count, loop read count, total read count, randfold score, and total score) used to determine whether a hairpin-loop-structured RNA is an miRNA. Using miRDeep2, 254 miRNAs were predicted in the salivary gland libraries. By adopting a conservative approach, miRNAs were categorized as high- (*n* = 25) and lowconfidence (*n* = 51) miRNAs (Figure 2B), based on standard criteria [39,40]. A conservative approach was used to annotate predicted miRNAs obtained from miRDeep2 analysis. The criteria utilized for annotating predicted miRNAs included: (1) a more significant number of deep sequencing reads corresponding to the mature sequence, (2) one or more reads matching to the star sequence, at least a few loop reads, (3) short 30 duplex overhangs, characteristic of Drosha/Dicer processing, and (4) conservation of 50 end of the potential mature sequence to a known mature sequence in the miRbase. The score boosts if the 50

end of the potential mature sequence is identical to a known mature sequence. A highconfidence category will meet all the criteria mentioned above, whereas a low-confidence category will not satisfy all the criteria by missing one or two points. Of 49 *Ixodes scapularis* miRNAs present in miRBase, 41 were detected in our data. Of the 254 *Ixodes scapularis* miRNAs, several had homologs present in *D. melanogaster*. The details of the identified miRNAs and their miRDeep2 scores are presented in Supplementary Table S1. potential mature sequence is identical to a known mature sequence. A high-confidence category will meet all the criteria mentioned above, whereas a low-confidence category will not satisfy all the criteria by missing one or two points. Of 49 *Ixodes scapularis* miRNAs present in miRBase, 41 were detected in our data. Of the 254 *Ixodes scapularis* miRNAs, several had homologs present in *D. melanogaster.* The details of the identified miRNAs and their miRDeep2 scores are presented in Supplementary Table S1.

*3.3. MicroRNA Profiling of Infected and Uninfected Salivary Glands and Identification of Novel* 

Figure 2A shows the basic hairpin-loop structure of an miRNA and other parameters (Dicer cut overhangs, total read count, mature read count, loop read count, total read count, randfold score, and total score) used to determine whether a hairpin-loop-structured RNA is an miRNA. Using miRDeep2, 254 miRNAs were predicted in the salivary gland libraries. By adopting a conservative approach, miRNAs were categorized as high- (*n* = 25) and lowconfidence (n = 51) miRNAs (Figure 2B), based on standard criteria [39,40]. A conservative approach was used to annotate predicted miRNAs obtained from miRDeep2 analysis. The criteria utilized for annotating predicted miRNAs included: (1) a more significant number of deep sequencing reads corresponding to the mature sequence, (2) one or more reads matching to the star sequence, at least a few loop reads, (3) short 3′ duplex overhangs, characteristic of Drosha/Dicer processing, and (4) conservation of 5′ end of the potential mature sequence to a known mature sequence in the miRbase. The score boosts if the 5′ end of the

*Int. J. Mol. Sci.* **2022**, *23*, 5565 6 of 16

*Tick miRNAs* 

**Figure 2.** (**A**) Basic stem-loop structures of predicted microRNAs. miRDeep2 was used to identify potential miRNA precursors based on nucleotide length, star sequence, stem-loop folding, and homology to the *Ixodes scapularis* reference genome. Shown are the predicted stem-loop structures (yellow), star (pink), and mature sequences of predicted miRNAs (red) in the salivary glands of *Ixodes scapularis* ticks. (**B**) Annotation of predicted miRNAs in partially fed uninfected (clean) and *Borreliaburgdorferi*-infected *Ixodes scapularis* salivary glands. Further**,** 254 microRNAs were predicted in infected and uninfected salivary gland tissues, 25 were categorized as high confidence (*n* = 25) and 51 as low confidence (*n* = 51) based on standard criteria and a conservative approach. Out of 49 *Ixodes scapularis* miRNAs available in miRbase (v22.1), 41 were detected in this study. **Figure 2.** (**A**) Basic stem-loop structures of predicted microRNAs. miRDeep2 was used to identify potential miRNA precursors based on nucleotide length, star sequence, stem-loop folding, and homology to the *Ixodes scapularis* reference genome. Shown are the predicted stem-loop structures (yellow), star (pink), and mature sequences of predicted miRNAs (red) in the salivary glands of *Ixodes scapularis* ticks. (**B**) Annotation of predicted miRNAs in partially fed uninfected (clean) and *Borrelia-burgdorferi*-infected *Ixodes scapularis* salivary glands. Further, 254 microRNAs were predicted in infected and uninfected salivary gland tissues, 25 were categorized as high confidence (*n* = 25) and 51 as low confidence (*n* = 51) based on standard criteria and a conservative approach. Out of 49 *Ixodes scapularis* miRNAs available in miRbase (v22.1), 41 were detected in this study.

#### *3.4. In Silico DE Analysis of miRNAs in B. burgdorferi-Infected Salivary Glands 3.4. In Silico DE Analysis of miRNAs in B. burgdorferi-Infected Salivary Glands*

In the DE analysis, 11 miRNAs were upregulated and 12 were downregulated in infected salivary glands compared with uninfected salivary glands (Figure 3; Table 1). Several of the identified tick miRNAs were conserved in *D. melanogaster* (dme-miR-375-3p, dme-miR-993- 5p, dme-miR-12-5p, dme-bantam-3p, dme-miR-100-5p, dme-miR-8-3p, and dme-miR-304- In the DE analysis, 11 miRNAs were upregulated and 12 were downregulated in infected salivary glands compared with uninfected salivary glands (Figure 3 and Table 1). Several of the identified tick miRNAs were conserved in *D. melanogaster* (dme-miR-375- 3p, dme-miR-993-5p, dme-miR-12-5p, dme-bantam-3p, dme-miR-100-5p, dme-miR-8- 3p, and dme-miR-304-5p). miRNAs downregulated in *B. burgdorferi*-infected salivary glands relative to uninfected salivary glands were isc-miR-153, isc-miR-1 and isc-miR-79, nDS\_002871802.1\_376, nDS\_002633080.1\_31953, nDS\_002549652.1\_43448, nDS\_002537755.1\_ 45711, nDS\_002537755.1\_45739, nDS\_002861213.1\_1750, nDS\_002763926.1\_14582, and nDS\_002548557.1\_43749, while upregulated miRNAs were isc-miR-317, isc-miR5310, iscmiR-2001, isc-miR-5307, isc-miR-71, isc-miR-87, nDS\_002784743.1\_12165, nDS\_002664372.1\_ 28027, nDS\_002716687.1\_21278, nDS\_002620414.1\_33611, and nDS\_002680650.1\_26098.


**Table 1.** In silico differential expression of *Ixodes scapularis* miRNAs in salivary glands after *Borrelia burgdorferi* infection compared with uninfected salivary glands.

\* miRNAs with a log2 fold-change expression > |1| and FDR ≤ 0.1 were considered significantly differentially expressed. Values highlighted in red indicate significant upregulation and values highlighted in green indicate significant downregulation. nDS\_002548557.1\_43749, while upregulated miRNAs were isc-miR-317, isc-miR5310, isc-miR-2001, isc-miR-5307, isc-miR-71, isc-miR-87, nDS\_002784743.1\_12165, nDS\_002664372.1\_28027, nDS\_002716687.1\_21278, nDS\_002620414.1\_33611, and nDS\_002680650.1\_26098.

**Figure 3.** In silico differential expression of predicted miRNAs in *Borrelia-burgdorferi-*infected, partially fed salivary glands relative to partially fed clean salivary glands. EdgeR was used for differential expression analysis. As such, 12 predicted miRNAs were down-regulated, 11 were upregulated, while 39 were unaffected. miRNAs with a log2 fold-change expression > |1| and FDR ≤ 0.1 were considered significantly differentially expressed (see Table 1). Further, in Table 2, putative roles and targets of these DE-conserved miRNAs are provided based on available studies in other arthropods. **Figure 3.** In silico differential expression of predicted miRNAs in *Borrelia-burgdorferi*-infected, partially fed salivary glands relative to partially fed clean salivary glands. EdgeR was used for differential expression analysis. As such, 12 predicted miRNAs were down-regulated, 11 were upregulated, while 39 were unaffected. miRNAs with a log2 fold-change expression > |1| and FDR ≤ 0.1 were considered significantly differentially expressed (see Table 1). Further, in Table 2, putative roles and targets of these DE-conserved miRNAs are provided based on available studies in other arthropods.

**Table 1.** In silico differential expression of *Ixodes scapularis* miRNAs in salivary glands after *Borrelia* 

isc-miR-71 5.226443 11.95849 48.94389 2.63 × 10−12 3.69 × 10−<sup>11</sup> isc-miR-5307 2.570363 12.34313 24.71399 6.65 × 10−7 1.55 × 10−<sup>6</sup> nDS\_002664372.1\_28027 5.362184 11.43227 26.80077 2.26 × 10−7 5.84 × 10−<sup>7</sup> nDS\_002716687.1\_21278 5.511153 11.48887 29.72059 4.99 × 10−8 1.55 × 10−<sup>7</sup> isc-miR-2001 3.146271 11.78845 19.75379 8.81 × 10−6 1.64 × 10−<sup>5</sup> nDS\_002620414.1\_33611 5.361301 11.43227 26.76848 2.29 × 10−7 5.84 × 10−<sup>7</sup> isc-miR-5310 5.009416 11.31195 20.86089 4.94 × 10−6 1.06 × 10−<sup>5</sup> nDS\_002680650.1\_26098 1.567661 15.43032 103.3589 2.80 × 10−24 7.83 × 10−<sup>23</sup>

*burgdorferi* infection compared with uninfected salivary glands.

**Differentially Expressed miRNA Log2FC logCPM LR** *p***-Value FDR** 


**Table 2.** List of differentially expressed microRNAs detected in *Borrelia-burgdorferi*-infected tick salivary glands and their putative roles.

miR-2001 was upregulated in *B. burgdorferi*-infected salivary glands compared with controls. miR-2001 is not present in the *Drosophila* genome but is an evolutionarily conserved miRNA in ticks [81] It has previously been shown to play a role in host immunomodulation, required for pathogen survival. miR-2001 has been detected in *I. ricinus* saliva [63] and *H. longicornis* saliva extracellular vesicles (EVs) [82], along with several other miRNAs, suggesting that EVs containing these miRNAs could be transferred to the host to modulate host cellular functions to facilitate tick and pathogen survival [63,82]. EVs are involved in the intercellular transfer of miRNAs, lipids, and proteins and the disposal of unnecessary cell contents [82,83]. The discovery of EVs in the excretory-secretory products of ectoparasites suggests that EVs are probably taken up by host cells, deliver their cargoes to the host, and favor immunomodulation, pathogen survival, and disease progression [84,85].

miR-1 was downregulated in *B. burgdorferi*-infected tick salivary glands compared with uninfected salivary glands. miR-1 belongs to a family of miRNAs, including miR-7 and miR-34 conserved across fruit flies, shrimps, and humans, where it modulates similar pathways (development, apoptosis) and is upregulated during stress insults [53]. In mosquitoes, miR-1 is upregulated during *Plasmodium* infection [54] and also facilitates West Nile virus infection [55]. miR-1 has been shown to be generally upregulated in response to infection, while we detected its downregulation in *B. burgdorferi*-infected SGs. In *Listeria*infected macrophages, miR-1 promotes IFN-γ-dependent activation of the innate immune response [56].

Tick saliva and salivary gland extracts reduce IFN-γ and IL-2 production in T cells and inhibit T cell proliferation [86,87], suggesting immune suppression, a possible survival mechanism for tick pathogens. mir-79 was also downregulated in *Borrelia-burgdorferi*infected salivary glands, and has been shown to participate in immunity and other processes, such as cellular differentiation, neurogenesis, and apoptosis. In *Rhipicephalus haemaphysaloides*, mir-79 was downregulated upon lipopolysaccharide (LPS) induction in female and male ticks, suggesting a role in LPS-mediated stimulation in the innate immune response [57]. The JNK pathway is an immune response pathway against Gram-negative bacteria [58], and mir-79 is known to disrupt JNK signaling by targeting its component genes, *pvr* (CG8222) and *puc* (CG7850) [59]. Our detection of the downregulation of mir-79 in *B. burgdorferi*-infected salivary glands is probably due to stimulation of the JNK pathway

as a tick immune response against *B. burgdorferi*. Although *B. burgdorferi* is described as an atypical Gram-negative bacterium due to its double membrane, it lacks classical lipopolysaccharide (LPS). It also has a different cellular organization and membrane composition to other diderms [88]. However, surprisingly, in *A. phagocytophilum* (an intracellular Gram-negative bacterial pathogen)-infected ticks, mir-79 was upregulated to facilitate infection by targeting the Roundabout protein 2 pathway (Robo2) [60], suggesting different roles for mir-79 in ticks when infected with different bacterial pathogens. *Borrelia burgdorferi* (Bb) is extracellular and a Gram-negative bacterial pathogen, but *A. phagocytophilum* is a well-known intracellular, Gram-negative bacterial pathogen. The status of *B. burgdorferi* as extracellular pathogen is true only in ticks, its intracellular localization has been reported in mammalian cells, including fibroblast, endothelial cells, neuron and even epithelial cells [89–93]. Do the extracellular and pseudo-Gram-negative status of *B. burgdorferi* in ticks make it a different bacterial pathogen than Gram negative or positive? More clarity of tick immune response is required in case of *B. burgdorferi* infection.

In Drosophila [35], miR-317 negatively regulates Toll pathway signaling, and its upregulation in *B. burgdorferi*-infected salivary glands may suggest a similar role to facilitate *B. burgdorferi* survival inside tick salivary glands. In silico, miR-317 targets Dif-Rc, an important transcription factor in the Toll pathway in Drosophila [64] and STAT in JAK-STAT signaling in Manduca sexta [62]. An in silico study in *I. ricinus* suggested a combinatorial effect of tick salivary miRNAs on host genes important for maintaining host homeostasis and tick–host interactions, including miR-317 targeting gap junctions and TRP channels, which play significant roles in host homeostatic responses [63]. miR-71 was upregulated in B. burgdorferi-infected salivary glands, and its predicted targets include MyD88, which is activated when ligands bind to the Toll-like receptor (TLR), interleukin 1 receptor (IL-1R), or IFN-γR1 and trigger MyD88-mediated signaling and pro-inflammatory cytokine responses. Another miR-71 target is IML3, an arthropod immunolectin that recognizes LPS on Gramnegative bacteria as a part of arthropod immune defenses. Immunolectins are also predicted targets of miR-87, -276, -9a, and -71 [62]. We hypothesize that miR-71 disrupts tick immune pathways and protects B. burgdorferi in the salivary gland. It has also been shown to prolong the life and regulate stress responses in nematodes, being upregulated in the Dauer larval stage, when food or other life-sustaining resources are scarce [69].

miR-87 was upregulated in *B. burgdorferi*-infected salivary glands. Previous studies in other arthropods, such as *Manduca sexta* and *Aedes albopictus*, suggested a role in disrupting innate immunity, particularly via IMD and Toll signaling pathways [62,73,74]. In *Aedes albopictus*, miR-87's predicted targets are Toll pathway signaling Ser/Thr kinase, Tolllike receptor Toll1A, class A scavenger receptor with Ser-protease domain, galectin [74], and TLR5b [73], while in *Manduca sexta*, its predicted target is FADD, an adaptor protein involved in DISC formation [62]. Our in silico data also showed upregulation of miR-5310 in *B. burgdorferi*-infected salivary glands. miR-5310 is a tick-specific miRNA [81], and a recent study demonstrated its downregulation in *Anaplasma*-*phagocytophilum*-infected nymphs compared with unfed uninfected nymphs [75]. Previous studies have also indicated modulation of signaling events via miR-5310 upon *A*. *phagocytophilum* infection [75–80]. In *B. burgdorferi* infection, we speculate that it might modulate signaling events and protect *B. burgdorferi* in the tick salivary glands. miR-5310 might also be involved in tick feeding, as it was found to be downregulated in *Rhipicephalus microplus* tick larvae upon exposure to host odor but not being allowed to feed [81].

## *3.5. Prediction of Target Genes and Gene Ontology (GO) and Functional Enrichment Analyses of the Target Network*

Target proteins were used to build a high-confidence interaction network (interaction scores >0.9). STRING web analysis (Figure 4) showed that the target proteins of 23 DE miRNAs (11 upregulated and 12 downregulated) had similar interactions to those expected for a random set of proteins of similar size sampled from the *I. scapularis* genome (nodes = 687, edges = 79, average node degree = 0.23, average local clustering coefficient

= 0.0966, expected number of edges = 77, PPI enrichment *p*-value = 0.411). This does not necessarily mean that these selected proteins are not biologically meaningful, rather that these tick proteins may not be very well studied and their interactions might not yet be known to STRING. 0.0966, expected number of edges = 77, PPI enrichment *p*-value = 0.411). This does not necessarily mean that these selected proteins are not biologically meaningful, rather that these tick proteins may not be very well studied and their interactions might not yet be known to STRING.

*3.5. Prediction of Target Genes and Gene Ontology (GO) and Functional Enrichment Analyses* 

Target proteins were used to build a high-confidence interaction network (interaction scores >0.9). STRING web analysis (Figure 4) showed that the target proteins of 23 DE miRNAs (11 upregulated and 12 downregulated) had similar interactions to those expected for a random set of proteins of similar size sampled from the *I. scapularis* genome (nodes = 687, edges = 79, average node degree = 0.23, average local clustering coefficient =

miR-87 was upregulated in *B. burgdorferi-*infected salivary glands. Previous studies in other arthropods, such as *Manduca sexta* and *Aedes albopictus,* suggested a role in disrupting innate immunity, particularly via IMD and Toll signaling pathways [62,73,74]. In *Aedes albopictus*, miR-87′s predicted targets are Toll pathway signaling Ser/Thr kinase, Toll-like receptor Toll1A, class A scavenger receptor with Ser-protease domain, galectin [74], and TLR5b [73], while in *Manduca sexta,* its predicted target is FADD, an adaptor protein involved in DISC formation [62]. Our in silico data also showed upregulation of miR-5310 in *B. burgdorferi*-infected salivary glands. miR-5310 is a tick-specific miRNA [81], and a recent study demonstrated its downregulation in *Anaplasma*-*phagocytophilum*-infected nymphs compared with unfed uninfected nymphs [75]. Previous studies have also indicated modulation of signaling events via miR-5310 upon *A*. *phagocytophilum* infection [75–80]. In *B. burgdorferi* infection, we speculate that it might modulate signaling events and protect *B. burgdorferi* in the tick salivary glands. miR-5310 might also be involved in tick feeding, as it was found to be downregulated in *Rhipicephalus microplus* tick larvae

*Int. J. Mol. Sci.* **2022**, *23*, 5565 10 of 16

upon exposure to host odor but not being allowed to feed [81].

*of the Target Network* 

**Figure 4.** A network built exclusively from *Ixodes scapularis* proteins targeted by in silico differentially expressed miRNAs in *Borrelia-burgdorferi-*infected, partially fed salivary glands relative to partially fed clean salivary glands. Red boxes indicates the proteins involved in significant KEGG pathways such as sphingolipid metabolism (EEC07251.1, KEGG:R02541); valine, leucine, and isoleucine degradation (EEC10220.1, KEGG:R04188); lipid transport and metabolism (EEC02614.1, **Figure 4.** A network built exclusively from *Ixodes scapularis* proteins targeted by in silico differentially expressed miRNAs in *Borrelia-burgdorferi*-infected, partially fed salivary glands relative to partially fed clean salivary glands. Red boxes indicates the proteins involved in significant KEGG pathways such as sphingolipid metabolism (EEC07251.1, KEGG:R02541); valine, leucine, and isoleucine degradation (EEC10220.1, KEGG:R04188); lipid transport and metabolism (EEC02614.1, KEGG:R01178); exosome biogenesis and secretion (EEC07251.1, EEC17749.1, KEGG:R02541); and phosphate-containing compound metabolic process (EEC02290.1, KEGG:R00004).

Many target genes were identified for the DE miRNAs using the sRNAtoolbox miR-NAconsTarget program [47]. To minimize false-positive targets, we chose only those targets predicted by all three miRNA target-prediction algorithms (TargetSpy, MIRANDA, and PITA). Forty-one KEGG pathways were enriched for target genes (proteins) of DE miRNAs (Supplementary Table S2) and included sphingolipid metabolism; valine, leucine, and isoleucine degradation; lipid transport and metabolism; exosome biogenesis and secretion; and phosphate-containing compound metabolic processes (Figure 4). Gene ontology (GO) analysis indicated that most target genes of DE miRNAs play significant roles in cellular processes, metabolic processes, biological regulation, developmental processes, and responses to stimuli (Figure 5). Surprisingly, immune response genes were one of the least affected functions.

Lipid metabolism was one of the main KEGG pathways detected by Pannzer and STRING analyses and was predicted to be regulated by tick salivary gland miRNAs miR-1, miR-5310, miR-71, and miR-79. It has previously been shown that the binding of *B. burgdorferi* to host glycosphingolipid can contribute to tissue-specific adhesion of *B. burgdorferi*, and the inflammatory process in Lyme borreliosis might be affected by interactions between *B. burgdorferi* and glycosphingolipid [94]. Therefore, we hypothesize that tick miRNAs (via saliva) promote sphingolipid synthesis inside hosts to promote *Borrelia* adhesion, and indeed, there is evidence that its infection affects lipid metabolism in hosts [95].

KEGG:R01178); exosome biogenesis and secretion (EEC07251.1, EEC17749.1, KEGG:R02541); and

Many target genes were identified for the DE miRNAs using the sRNAtoolbox miR-NAconsTarget program [47]. To minimize false-positive targets, we chose only those targets predicted by all three miRNA target-prediction algorithms (TargetSpy, MIRANDA, and PITA). Forty-one KEGG pathways were enriched for target genes (proteins) of DE miRNAs (Supplementary Table S2) and included sphingolipid metabolism; valine, leucine, and isoleucine degradation; lipid transport and metabolism; exosome biogenesis and secretion; and phosphate-containing compound metabolic processes (Figure 4). Gene ontology (GO) analysis indicated that most target genes of DE miRNAs play significant roles in cellular processes, metabolic processes, biological regulation, developmental processes, and responses to stimuli (Figure 5). Surprisingly, immune response genes were one of the

phosphate-containing compound metabolic process (EEC02290.1, KEGG:R00004).

#### Lipid metabolism was one of the main KEGG pathways detected by Pannzer and STRING analyses and was predicted to be regulated by tick salivary gland miRNAs miR-*3.6. Validation of DE miRNAs by qRT-PCR*

least affected functions.

1, miR-5310, miR-71, and miR-79. It has previously been shown that the binding of *B. burgdorferi* to host glycosphingolipid can contribute to tissue-specific adhesion of *B. burgdorferi*, and the inflammatory process in Lyme borreliosis might be affected by interactions between *B. burgdorferi* and glycosphingolipid [94]. Therefore, we hypothesize that tick miRNAs (via saliva) promote sphingolipid synthesis inside hosts to promote *Borrelia* adhesion, and indeed, there is evidence that its infection affects lipid metabolism in hosts [95]. The expressions of DE miRNAs were validated in *B. burgdorferi*-infected and uninfected ISE6 cells by qRT-PCR (Figure 6 and Supplementary Table S3), which closely mirrored the RNA-seq data for many targets, although some differences were not statistically significant by qRT-PCR and isc-miR-317 was downregulated rather than upregulated. These differences could be due to the use of different methodologies to quantify miRNA expression [10]. *Int. J. Mol. Sci.* **2022**, *23*, 5565 12 of 16 differences could be due to the use of different methodologies to quantify miRNA expression [10].

**Figure 6.** qRT-PCR validation of differentially expressed miRNAs detected in *Borrelia-burgdorferi*infected, partially fed salivary glands relative to partially fed uninfected salivary glands from *Ixodes scapularis* ticks. qPCR validation was performed in *Borrelia-burgdorferi*-infected and clean ISE6 cells. Expression of miRNAs was normalized to clean ISE6 cells (indicated as 1 on the *y*-axis). Statistical significance for qRT-PCR-based differential expression was determined by the 2-tailed Student's *t*test, where \* is *p* < 0.05. **Figure 6.** qRT-PCR validation of differentially expressed miRNAs detected in *Borrelia-burgdorferi*-infected, partially fed salivary glands relative to partially fed uninfected salivary glands from *Ixodes scapularis* ticks. qPCR validation was performed in *Borrelia-burgdorferi*-infected and clean ISE6 cells. Expression of miRNAs was normalized to clean ISE6 cells (indicated as 1 on the *y*-axis). Statistical significance for qRT-PCR-based differential expression was determined by the 2-tailed Student's *t*-test, where \* is *p* < 0.05.

glands, with and without *Borrelia burgdorferi* infection. Here, we identified several potential miRNAs targets in tick salivary glands which might play a significant role in *Borrelia* colonization, survival, transmission, and host immunomodulation. Functional validation of these miRNAs is now required. Further characterization of tick salivary gland miRNAs would contribute to a better understanding of the mechanisms underpinning *Borrelia* transmission and propagation inside hosts, not least due to its special status as an extracellular spirochaete and atypical Gram-negative organism that might exploit different survival mechanisms. The impact of *B. burgdorferi* on miRNA expression must also be studied in other tick tissues and hosts to understand cues of its vector competence in ticks and

**Supplementary Materials:** The following supporting information can be downloaded at:

**Author Contributions:** Conceptualization, D.K. and S.K.; methodology, D.K., L.P.D., M.E., A.S.F. and S.K.; software, D.K. and A.S.F.; validation, D.K. and L.P.D.; formal analysis, D.K. and S.K.; investigation, D.K. and S.K.; resources, S.K.; data curation, D.K. and S.K.; writing—original draft preparation, D.K. and S.K.; writing—review and editing, D.K., L.P.D., M.E., A.S.F. and S.K.; visualization, D.K.; supervision, S.K.; project administration, S.K.; funding acquisition, S.K. All authors have

**4. Conclusions** 

immunomodulation in vertebrates.

www.mdpi.com/article/10.3390/ijms23105565/s1.

read and agreed to the published version of the manuscript.

#### **4. Conclusions**

This is the first comprehensive miRNA profiling study of *Ixodes scapularis* salivary glands, with and without *Borrelia burgdorferi* infection. Here, we identified several potential miRNAs targets in tick salivary glands which might play a significant role in *Borrelia* colonization, survival, transmission, and host immunomodulation. Functional validation of these miRNAs is now required. Further characterization of tick salivary gland miRNAs would contribute to a better understanding of the mechanisms underpinning *Borrelia* transmission and propagation inside hosts, not least due to its special status as an extracellular spirochaete and atypical Gram-negative organism that might exploit different survival mechanisms. The impact of *B. burgdorferi* on miRNA expression must also be studied in other tick tissues and hosts to understand cues of its vector competence in ticks and immunomodulation in vertebrates.

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ijms23105565/s1.

**Author Contributions:** Conceptualization, D.K. and S.K.; methodology, D.K., L.P.D., M.E., A.S.F. and S.K.; software, D.K. and A.S.F.; validation, D.K. and L.P.D.; formal analysis, D.K. and S.K.; investigation, D.K. and S.K.; resources, S.K.; data curation, D.K. and S.K.; writing—original draft preparation, D.K. and S.K.; writing—review and editing, D.K., L.P.D., M.E., A.S.F. and S.K.; visualization, D.K.; supervision, S.K.; project administration, S.K.; funding acquisition, S.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by USDA NIFA award #2017-67017-26171; Pakistan-US Science and Technology Cooperation award (US Department of State); the Mississippi INBRE, an institutional Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under award P20GM103476 and The APC was funded by NIH NIAID award AI135049.

**Institutional Review Board Statement:** Not applicable.

**Data Availability Statement:** Publicly available datasets were analyzed in this study. This data can be found here: NCBI (accession: PRJNA837369).

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**

