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712 results for “tick”
Data from: Accounting for missing ticks: Use (or lack thereof) of hierarchical models in tick ecology studies
<p>Ixodid (hard) ticks play important ecosystem roles and have significant impacts on animal and human health via tick-borne diseases and physiological stress from parasitism. Tick occurrence, abundance, behavior, and key life-history traits are highly influenced by host availability, weather, microclimate, and landscape features. As such, changes in the environment can have profound impacts on ticks, their hosts, and the spread of diseases. Researchers interested in enumerating questing ticks attempt to integrate this heterogeneity by conducting replicate sampling bouts spread over the tick questing period as common field methods notoriously underestimate ticks. However, it is unclear how (or if) tick studies account for this heterogeneity in the modeling process. This step is critical as unaccounted variance in detection can lead to biased estimates of occurrence and abundance. We performed a descriptive review to evaluate the extent to which studies account for the detection process while modeling tick data. We also categorized the types of analyses that are commonly used to model tick data. We used hierarchical models (HMs) that account for imperfect detection to analyze simulated and empirical tick data, demonstrating that inference is muddled when detection probability is not accounted for in the modeling process. Our review indicates that only 5 of 412 (1%) papers explicitly accounted for imperfect detection while modeling ticks. By comparing HMs with the most common approaches used for modeling tick data (e.g., ANOVA), we show that population estimates are biased low for simulated and empirical data when using non-HMs, and that confounding occurs due to not explicitly modeling factors that influenced both detection and abundance. Our review and analysis of simulated and empirical data shows that it is important to account for our ability to detect ticks using field methods with imperfect detection. Not doing so leads to biased estimates of occurrence and abundance which could complicate our understanding of parasite-host relationships and the spread of tick-borne diseases. We highlight the resources available for learning HM approaches and applying them to analyzing tick data.</p>
Fig. 1 in Infestation With Ixodes Ricinus Ticks On Migrating Passerine Birds In Lithuania And Norway
Fig. 1 Molecular taxonomical identification of the I. ricinus by PCR assay. Lines 1 and 15 – 50 bp marker; Line 2 –negative control; Lines 2-13 –positive results: amplified 150 bp specific fragment for I. ricinus; Line 14 – positive control of I. ricinus (150 bp)
Raw data of compounds extracted by GC-MS from each population replicate's of I. uriae ticks from Iceland.
<p>Raw data representing all the compounds extracted by GC-MS from each population replicate’s of <em>I. uriae</em> ticks from three sites in Iceland. Each replicate contain a pool of 10 living flat female ticks.</p> <p>Site: name of the site where ticks were collected.</p> <p>Host: name of the host bird.</p> <p>Replicate: number of the replicate (1 to 4).</p> <p>Peak: number of the detected peaks correponding to extracted compounds.</p> <p>Retention Time: time elapsed between sample introduction and the maximum signal of the given compound.</p> <p>Area: area under the curves of each detected coumpounds on the chromatogram.</p>
Data from: A novel laboratory method to simulate climatic stress with successful application to experiments with medically relevant ticks
<p>Ticks are the most important vectors of zoonotic disease-causing pathogens in North America and Europe. Many tick species are expanding their geographic range. Although correlational evidence suggests that climate change is driving the range expansion of ticks, experimental evidence is necessary to develop a mechanistic understanding of ticks' response to a range of climatic conditions. Previous experiments used simulated microclimates, but these protocols require hazardous salts or expensive laboratory equipment to manipulate humidity. We developed a novel, safe, stable, convenient, and economical method to isolate individual ticks and manipulate their microclimates. The protocol involves placing individual ticks in plastic tubes, and placing six tubes along with a commercial two-way humidity control pack in an airtight container. We successfully used this method to investigate how humidity affects survival and host-seeking (questing) behavior of three tick species: the lone star tick (Amblyomma americanum), American dog tick (Dermacentor variabilis), and black-legged tick (Ixodes scapularis). We placed 72 adult females of each species individually into plastic tubes and separated them into three experimental relative humidity (RH) treatments representing distinct climates: 32% RH, 58% RH, and 84% RH. We assessed the survival and questing behavior of each tick for 30 days. In all three species, survivorship significantly declined in drier conditions. Questing height was negatively associated with RH in Amblyomma, positively associated with RH in Dermacentor, and not associated with RH in Ixodes. The frequency of questing behavior increased significantly with drier conditions for Dermacentor but not for Amblyomma or Ixodes. This report demonstrates an effective method for assessing the viability and host-seeking behavior of tick vectors of zoonotic diseases under different climatic conditions.</p>
Figure 1 in Molecular detection of Borrelia anserina in Argas persicus (Acari: Argasidae) ticks collected from Lorestan province, west of Iran
Figure 1. The aggregated Argas persicus ticks at different stages around a thatched birdhouse in Lorestan province.
Figure 2 in Infestation of Zebu cattle (Bos indicus Linnaeus) by hard ticks (Acari: Ixodidae) in Maiduguri, Northeastern Nigeria
Figure 2. Numbers of individual ticks of different species collected from different body parts of cattle.
Figure 3 in Molecular detection of Borrelia anserina in Argas persicus (Acari: Argasidae) ticks collected from Lorestan province, west of Iran
Figure 3. The phylogenetic tree inferred from flaB amino acids sequence data of B. anserina (clade I) and other Borrelia taxa (clade II, KX171816 and JF693808) constructed using Neighbor-Joining (NJ) method with bootstrap test (1,000 replicates). The main clade in right side of tree separated with colored rectangular shape. Taxa are as species name following GenBank accession number, taxon of the present study indicated as bold. Nodes indicated with bootstrap value. Branch lengths are proportional to evolutionary changes, the units of the number of amino acid substitutions per site. The analysis involved 12 amino acid sequences. All positions containing gaps and missing data were eliminated. There were a total of 166 positions in the final dataset. The more diverged Pakistani strain of B. anserina (JF693808) located outside the main B. anserina (clade I). The members of clade II and B. hermsii are as outgroup.
Figure 2 in Molecular detection of Borrelia anserina in Argas persicus (Acari: Argasidae) ticks collected from Lorestan province, west of Iran
Figure 2. The stereomicroscopic view of dissected salivary glands (A); ovary and uterus (B) of female Argas tick in normal saline.
Figure 4 in Molecular detection of Borrelia anserina in Argas persicus (Acari: Argasidae) ticks collected from Lorestan province, west of Iran
Figure 4. The phylogenetic tree inferred from flaB nucleotide sequence data of B. anserina (clade I) and other Borrelia taxa (clade II and KX171816) constructed using Neighbor-Joining (NJ) method with bootstrap test (1000 replicates). The main clade in right side of tree separated with colored rectangular shape. Taxa are as species name following GenBank accession number, taxon of the present study indicated as bold. Nodes indicated with bootstrap value. Branch lengths are proportional to evolutionary changes, the units of the number of base substitutions per site the units of the number of amino acid substitutions per site. The analysis involved 12 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 500 positions in the final dataset. The more diverged Pakistani strain of B. anserina (JF693808) located inside the main B. anserina (clade I). The members of clade II and B. hermsii are as outgroup.
Figure 1 in Aegyptianella pullorum (Rickettsiales: Anaplasmataceae) in tick Argas persicus (Acari: Argasidae) from Iran: a preliminary assessment
Figure 1. Phylogenetic tree generated based on 16SrRNA sequence data of the Aegyptianella pullorum species generated in this study and similar sequences from GenBank database constructed using Bayesian Inference method. Main clade of tree is separated by a rectangular shape. The taxa of the present study are bold and defined with a name and GenBank accession number. Posterior probability values are inserted at nodes. Branch lengths are proportional to the evolutionary changes. Tree is re-rooted by Rickettsia slovaca as out-group.
Annotation table - Whole body transcriptomes of the tick Ixodes ricinus at different stage and feeding conditions
<p>Annotation table for a <em>de novo</em> assembled transcriptome of<em> Ixodes ricinus</em> in different stages and conditions.</p> <p>Description of the fields of each column (Trinotate results, and additionnal statistics):</p> <p>1. Contig_name: name of the contig (Trinity assembly)</p> <p>2. sprot_Top_BLASTX_hit: first hit of the blastx search against SwissProt (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>3. TrEMBL_Top_BLASTX_hit: first hit of the blastx search against Uniref90 (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>4. RNAMMER: identification of non-coding RNAs</p> <p>5. prot_id: identifier of the predicted protein (TransDecoder)</p> <p>6. prot_coords: coordinates (start, end and strand) of the predicted protein on the contig</p> <p>7. sprot_Top_BLASTP_hit: first hit of the blastp search between the predicted protein and SwissProt (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>8. TrEMBL_Top_BLASTP_hit: first hit of the blastp search between the predicted protein and Uniref90 (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>9. Pfam: result of the search against PfamA database</p> <p>10. SignalP: prediction of a signal peptide with SignalP</p> <p>11. TmHMM: prediction of a transmembrane domain with THMM</p> <p>12. eggnog: eggNOG database of orthologous genes (v3.0) assignation</p> <p>13. gene_ontology_blast: GO assignation based on blast results</p> <p>14. gene_ontology_pfam: GO assignation based on pfam results</p> <p>15. Contig_length: length of the contig in bp</p> <p>16. Busco_Id: name of the BUSCO (v1)</p> <p>17. Busco_status: status of the BUSCO (complete/fragmented/duplicated)</p> <p>18-32: Kallisto read counts for the 15 libraries</p> <p>A, B, C: unfed nymphs (replicates 1, 2, 3)</p> <p>D, E, F: partially fed nymphs (replicates 1, 2, 3)</p> <p>G, H, I: males (unfed) (replicates 1, 2, 3)</p> <p>J, K, L: unfed adult females (replicates 1, 2, 3)</p> <p>M, N, O: partially fed adult females (replicates 1, 2, 3)</p> <p>33. log2FoldChange_UnfedVsPartiallyFed: log fold change in base 2 of expression (comparison between "unfed" -including males- and "fed" ticks)</p> <p>34. pvalue_UnfedVsPartiallyFed: p-value of the comparison between "unfed" -including males- and "fed" ticks</p> <p>35. log2FoldChange_MaleVsFemale: log fold change in base 2 of expression (comparison between "males" and "females")</p> <p>36. pvalue_MaleVsFemale: p-value of the comparison between "males" and "females"</p> <p>37. log2FoldChange_NymphsVsAdults: log fold change in base 2 of expression (comparison between "nymphs" and "adults" -males and females-)</p> <p>38. pvalue_NymphsVsAdults: p-value of the comparison between "nymphs" and "adults" -males and females-)</p> <p> </p> <p> </p>
Fig. 2 in The great gerbil (RhombomYS opimUS) as a host for tick species in Gurbantunggut Desert
Fig. 2 Maximum likelihood phylogenic tree inferred from the COI sequences of the ticks (A Ixodes acuminatus, B Hyalomma asiaticum, Rhipicephalus turanicus and Haemaphysalis erinacei, C Ornithodoros tartakovskyi) sampled from wildlife and pastured sheep in Gurbantunggut Desert, northwestern China. The new sequences provided by the present study are indicated by black circle/diamond/inverted triangle/square/triangle
Fig. 6 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 6 Phenotype associated with dynein, kinesin, isocitrate dehydrogenase and citrate synthase mRNA subjected to RNAi in female ticks via injection with the corresponding dsRNA. a Dynein dsRNA injection. b Kinesin dsRNA injection. c Isocitrate dehydrogenase dsRNA injection. d Citrate synthase dsRNA injection. e GFP dsRNA injection, control. f No injection, control. Scale-bars: 5 mm
Fig. 7 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 7 Digital micrographs of salivary gland acinar morphological changes in unfed female H. longicornis after RNAi.The time at which the tick bit the host and began sucking blood was recorded as day 0. a–e Dynein dsRNA injection. f–j Kinesin dsRNA injection. k–o Isocitrate dehydrogenase dsRNA injection. p–t Citrate synthase dsRNA injection. u–y GFP dsRNA injection, control. Scale-bars: 25 µm
Fig. 4 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 4 KEGG pathway enrichment analysis of the differentially expressed proteins in 5 different Clusters. Terms with a P-value <0.05 were used to draw the column diagrams. a–e KEGG pathway enrichment for the proteins in Cluster 1 to Cluster 5
Fig. 3 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 3 GO functional annotations for all the differentially expressed proteins. a–c GO annotations of differentially expressed proteins in the salivary glands of partially fed ticks compared with unfed ticks (115:114). d–f GO annotations of differentially expressed proteins in the salivary glands of mated semi-engorged ticks compared with partially fed ticks (116:115). g–i GO annotations of differentially expressed proteins in the salivary glands of engorged ticks compared with mated semi-engorged ticks (117:116). Abbreviations: BP, biological process; CC, cellular component; MF, molecular function; CO, cellular component organization or biogenesis
Fig. 5 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 5 RT-qPCR analyzed the mRNA expression levels of dynein, kinesin, isocitrate dehydrogenase, and citrate synthase during the four feeding stages of salivary gland development
Fig. 2 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 2 Statistics and cluster analysis for the identified proteins and their expression levels in the salivary glands of female H. longicornis. a Venn diagram showing the number of proteins (with CV <20%) identified in the three experiments. b Venn diagram showing the number of proteins with quantitative information. c Cluster analysis according to trends in protein expression in the salivary glands of female ticks
Fig. 1 in Salivary gland proteome analysis of developing adult female HaemaphYSaliS longiCorniS ticks: molecular motor and TCA cycle-related proteins play an important role throughout development
Fig. 1 Workflow for quantitative proteomics analysis of changes in protein expression in the salivary glands of female H. longicornis during the blood-feeding process
Comparative ecological analysis and predictive modeling of tick-borne pathogens
<p>Tick-borne diseases constitute the predominant vector-borne health threat in North America. Recent observations have noted a significant expansion in the range of the black-legged tick (<em>Ixodes scapularis</em> Say, Acari: Ixodidae), alongside a rise in the incidence of diseases caused by its vectored pathogens: <em>Borrelia burgdorferi</em> (Spirochaetales: Spirochaetaceae), <em>Babesia microti</em> (Piroplasmida: Babesiidae), and <em>Anaplasma phagocytophilium</em> (Rickettsiales: Anaplasmataceae), the causative agents of Lyme disease, babesiosis, and anaplasmosis, respectively. Prior research identified environmental features that influence the ecological dynamics of <em>I. scapularis</em> and <em>B. burgdorferi</em> that can be used to predict the distribution and abundance of these organisms, and thus Lyme disease risk. In contrast, there is a paucity of research into the environmental determinants of <em>B. microti</em> and <em>A. phagocytophilium</em>. Here we use over a decade of surveillance data to model the impact of environmental features on the infection prevalence of these increasingly common human pathogens in ticks across New York State (NYS). Our findings reveal a consistent northward and westward expansion of <em>B. microti</em> in NYS from 2009 to 2019, while the range of <em>A. phagocytophilum</em> varied at fine spatial scales. We constructed biogeographic models using data from over 1000 site-year visits and encompassing more than 250 environmental variables to accurately forecast infection prevalence for each pathogen to future years that were not included in model training. Several environmental features were identified to have divergent effects on the pathogens, revealing potential ecological differences governing their distribution and abundance. These validated biogeographic models are immediately useful for disease prevention efforts.</p>
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