Dataset Information

The Factor H-Binding Site of CspZ as a Protective Target against Multistrain, Tick-Transmitted Lyme Disease.

ABSTRACT: The spirochete Borrelia burgdorferi sensu lato is the causative agent of Lyme disease (LD). The spirochetes produce the CspZ protein that binds to a complement regulator, factor H (FH). Such binding downregulates activation of host complement to facilitate spirochete evasion of complement killing. However, vaccination with CspZ does not protect against LD infection. In this study, we demonstrated that immunization with CspZ-YA, a CspZ mutant protein with no FH-binding activity, protected mice from infection by several spirochete genotypes introduced via tick feeding. We found that the sera from CspZ-YA-vaccinated mice more efficiently eliminated spirochetes and blocked CspZ FH-binding activity than sera from CspZ-immunized mice. We also found that vaccination with CspZ, but not CspZ-YA, triggered the production of anti-FH antibodies, justifying CspZ-YA as an LD vaccine candidate. The mechanistic and efficacy information derived from this study provides insights into the development of a CspZ-based LD vaccine.

SUBMITTER: Marcinkiewicz AL

PROVIDER: S-EPMC7171238 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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The Factor H-Binding Site of CspZ as a Protective Target against Multistrain, Tick-Transmitted Lyme Disease.

Marcinkiewicz Ashley L AL Lieknina Ilva I Yang Xiuli X Lederman Patricia L PL Hart Thomas M TM Yates Jennifer J Chen Wen-Hsiang WH Bottazzi Maria Elena ME Mantis Nicholas J NJ Kraiczy Peter P Pal Utpal U Tars Kaspars K Lin Yi-Pin YP

Infection and immunity 20200420 5

The spirochete <i>Borrelia burgdorferi</i><i>sensu lato</i> is the causative agent of Lyme disease (LD). The spirochetes produce the CspZ protein that binds to a complement regulator, factor H (FH). Such binding downregulates activation of host complement to facilitate spirochete evasion of complement killing. However, vaccination with CspZ does not protect against LD infection. In this study, we demonstrated that immunization with CspZ-YA, a CspZ mutant protein with no FH-binding activity, prot ...[more]

PMID: 32122944

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Project description:Mixed or multiple-strain infections are common in vector-borne diseases and have important implications for the epidemiology of these pathogens. Previous studies have mainly focused on interactions between pathogen strains in the vertebrate host, but little is known about what happens in the arthropod vector. Borrelia afzelii and Borrelia garinii are two species of spirochete bacteria that cause Lyme borreliosis in Europe and that share a tick vector, Ixodes ricinus Each of these two tick-borne pathogens consists of multiple strains that are often differentiated using the highly polymorphic ospC gene. For each Borrelia species, we studied the frequencies and abundances of the ospC strains in a wild population of I. ricinus ticks that had been sampled from the same field site over a period of 3 years. We used quantitative PCR (qPCR) and 454 sequencing to estimate the spirochete load and the strain diversity within each tick. For B. afzelii, there was a negative relationship between the two most common ospC strains, suggesting the presence of competitive interactions in the vertebrate host and possibly the tick vector. The flat relationship between total spirochete abundance and strain richness in the nymphal tick indicates that the mean abundance per strain decreases as the number of strains in the tick increases. Strains with the highest spirochete load in the nymphal tick were the most common strains in the tick population. The spirochete abundance in the nymphal tick appears to be an important life history trait that explains why some strains are more common than others in nature. Lyme borreliosis is the most common vector-borne disease in the Northern Hemisphere and is caused by spirochete bacteria that belong to the Borrelia burgdorferi sensu lato species complex. These tick-borne pathogens are transmitted among vertebrate hosts by hard ticks of the genus Ixodes Each Borrelia species can be further subdivided into genetically distinct strains. Multiple-strain infections are common in both the vertebrate host and the tick vector and can result in competitive interactions. To date, few studies on multiple-strain vector-borne pathogens have investigated patterns of cooccurrence and abundance in the arthropod vector. We demonstrate that the abundance of a given strain in the tick vector is negatively affected by the presence of coinfecting strains. In addition, our study suggests that the spirochete abundance in the tick is an important life history trait that can explain why some strains are more common in nature than others.

Project description:PurposeNumerous clinical studies have suggested that chemopreventive drugs for breast cancer such as tamoxifen and exemestane can effectively reduce the incidence of estrogen receptor (ER)-positive breast cancer. However, it remains unclear how to identify those who are susceptible to ER-positive breast cancer. Accordingly, there is a great demand for a probe into the predisposing factors so as to provide precise chemoprevention. Recent evidence has indicated that ERα expression can be regulated by microRNAs (miRNAs), such as miR-206, in breast cancer. We assumed that single-nucleotide polymorphisms (SNPs) in the miR-206-binding sites of the target genes may be associated with breast cancer susceptibility with different ER statuses.MethodsWe genotyped the SNPs that reside in and around the miR-206-binding sites of two target genes - heparan sulfatase 1 (SULF1) and RPTOR-independent companion of mammalian target of rapamycin Complex 2 (RICTOR) - which were related to the progression or metastasis of breast cancer cells in 710 breast cancer patients and 294 controls by the matrix-assisted laser desorption ionization-time of flight mass spectrometry method. Modified odds ratios (ORs) with their 95% confidence intervals (CIs) were calculated by a multivariate logistic regression analysis to evaluate the potential association between the SNPs and breast cancer susceptibility.ResultsFor rs3802278, which is located in the 3'-untranslated region (3'-UTR) of SULF1, the frequency of the AA genotype was less in breast cancer patients than that in the controls as compared to that of the GG + GA genotype not only for ER-positive breast cancer patients (adjusted OR =0.663, P=0.032) but also for hormone receptor-positive breast cancer patients (adjusted OR =0.610, P=0.018). Besides, the frequency of the AA genotype was less than that of the GG genotype between the ER-positive breast cancer patients and the controls (adjusted OR =0.791, P=0.038). For rs66916453, which is located in the 3'-UTR of RICTOR, no significant difference was observed between the case and the control group for the genotypes or alleles (P>0.05).ConclusionThe SNPs in the miRNA-binding sites within the 3'-UTR of SULF1 may serve as protective factors against the susceptibility to breast cancer, especially to ER-positive breast cancer in the Chinese population. These SNPs are promising candidate biomarkers to predict the susceptibility of breast cancer and guide the administration of targeted preventive endocrine therapy.

Project description:Background: The distribution and composition of cis-regulatory modules composed of transcription factor (TF) binding site (TFBS) clusters in promoters substantially determine gene expression patterns and TF targets. TF knockdown experiments have revealed that TF binding profiles and gene expression levels are correlated. We use TFBS features within accessible promoter intervals to predict genes with similar tissue-wide expression patterns and TF targets using Machine Learning (ML). Methods: Bray-Curtis Similarity was used to identify genes with correlated expression patterns across 53 tissues. TF targets from knockdown experiments were also analyzed by this approach to set up the ML framework. TFBSs were selected within DNase I-accessible intervals of corresponding promoter sequences using information theory-based position weight matrices (iPWMs) for each TF. Features from information-dense clusters of TFBSs were input to ML classifiers which predict these gene targets along with their accuracy, specificity and sensitivity. Mutations in TFBSs were analyzed in silico to examine their impact on TFBS clustering and predict changes in gene regulation. Results: The glucocorticoid receptor gene ( NR3C1), whose regulation has been extensively studied, was selected to test this approach. SLC25A32 and TANK exhibited the most similar expression patterns to NR3C1. A Decision Tree classifier exhibited the best performance in detecting such genes, based on Area Under the Receiver Operating Characteristic curve (ROC). TF target gene prediction was confirmed using siRNA knockdown, which was more accurate than CRISPR/CAS9 inactivation. TFBS mutation analyses revealed that accurate target gene prediction required at least 1 information-dense TFBS cluster. Conclusions: ML based on TFBS information density, organization, and chromatin accessibility accurately identifies gene targets with comparable tissue-wide expression patterns. Multiple information-dense TFBS clusters in promoters appear to protect promoters from effects of deleterious binding site mutations in a single TFBS that would otherwise alter regulation of these genes.

Dataset Information

The Factor H-Binding Site of CspZ as a Protective Target against Multistrain, Tick-Transmitted Lyme Disease.

Publications

The Factor H-Binding Site of CspZ as a Protective Target against Multistrain, Tick-Transmitted Lyme Disease.

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