Identification of \u3ci\u3eFrancisella tularensis\u3c/i\u3e subsp. \u3ci\u3etularensis \u3c/i\u3eA1 and A2 Infections by Real-Time Polymerase Chain Reaction

Francisella tularensis subsp. tularensis (type A) is subdivided into clades A1 and A2. Human tularemia infections caused by A1 and A2 differ with respect to clinical outcome; A1 infections are associated with a higher case fatality rate. In this study, we develop and evaluate TaqMan polymerase chain reaction (PCR) assays for identification of A1 and A2. Both assays were shown to be specific to either A1 or A2, with sensitivities of 10 genomic equivalents. Real-time PCR results for identification of A1 and A2 were in complete agreement with results obtained by pulsed field gel electrophoresis analysis or conventional PCR when specimens from sporadic tularemia cases and a tularemia outbreak involving both A1 and A2 were tested. In addition, outbreak samples not previously typed to the clade level could be classified as A1 or A2. The assays described here provide new diagnostic tools with a level of sensitivity not previously available for identification of A1 and A2 infections

Identification of \u3ci\u3eFrancisella tularensis\u3c/i\u3e subsp. \u3ci\u3etularensis \u3c/i\u3eA1 and A2 Infections by Real-Time Polymerase Chain Reaction

Francisella tularensis subsp. tularensis (type A) is subdivided into clades A1 and A2. Human tularemia infections caused by A1 and A2 differ with respect to clinical outcome; A1 infections are associated with a higher case fatality rate. In this study, we develop and evaluate TaqMan polymerase chain reaction (PCR) assays for identification of A1 and A2. Both assays were shown to be specific to either A1 or A2, with sensitivities of 10 genomic equivalents. Real-time PCR results for identification of A1 and A2 were in complete agreement with results obtained by pulsed field gel electrophoresis analysis or conventional PCR when specimens from sporadic tularemia cases and a tularemia outbreak involving both A1 and A2 were tested. In addition, outbreak samples not previously typed to the clade level could be classified as A1 or A2. The assays described here provide new diagnostic tools with a level of sensitivity not previously available for identification of A1 and A2 infections

Virulence difference between the prototypic Schu S4 strain (A1a) and Francisella tularensisA1a, A1b, A2 and type B strains in a murine model of infection

BACKGROUND: The use of prototypic strains is common among laboratories studying infectious agents as it promotes consistency for data comparability among and between laboratories. Schu S(4) is the prototypic virulent strain of Francisella tularensis and has been used extensively as such over the past six decades. Studies have demonstrated virulence differences among the two clinically relevant subspecies of F. tularensis, tularensis (type A) and holarctica (type B) and more recently between type A subpopulations (A1a, A1b and A2). Schu S(4) belongs to the most virulent subspecies of F. tularensis, subspecies tularensis. METHODS: In this study, we investigated the relative virulence of Schu S(4) in comparison to A1a, A1b, A2 and type B strains using a temperature-based murine model of infection. Mice were inoculated intradermally and a hypothermic drop point was used as a surrogate for death. Survival curves and the length of temperature phases were compared for all infections. Bacterial burdens were also compared between the most virulent type A subpopulation, A1b, and Schu S(4) at drop point. RESULTS: Survival curve comparisons demonstrate that the Schu S(4) strain used in this study resembles the virulence of type B strains, and is significantly less virulent than all other type A (A1a, A1b and A2) strains tested. Additionally, when bacterial burdens were compared between mice infected with Schu S(4) or MA00-2987 (A1b) significantly higher burdens were present in the blood and spleen of mice infected with MA00-2987. CONCLUSIONS: The knowledge gained from using Schu S(4) as a prototypic virulent strain has unquestionably advanced the field of tularemia research. The findings of this study, however, indicate that careful consideration of F. tularensis strain selection must occur when the overall virulence of the strain used could impact the outcome and interpretation of results

Simple Objective Detection of Human Lyme Disease Infection Using Immuno-PCR and a Single Recombinant Hybrid Antigen

A serology-based tiered approach has, to date, provided the most effective means of laboratory confirmation of clinically suspected cases of Lyme disease, but it lacks sensitivity in the early stages of disease and is often dependent on subjectively scored immunoblots. We recently demonstrated the use of immuno-PCR (iPCR) for detecting Borrelia burgdorferi antibodies in patient serum samples that were positive for Lyme disease. To better understand the performance of the Lyme disease iPCR assay, the repeatability and variability of the background of the assay across samples from a healthy population (n = 36) were analyzed. Both of these parameters were found to have coefficients of variation of \u3c 3%. Using eight antigen-specific iPCR assays and positive call thresholds established for each assay, iPCR IgM and/or IgG diagnosis from Lyme disease patient serum samples (n = 12) demonstrated a strong correlation with that of 2-tier testing. Furthermore, a simplified iPCR approach using a single hybrid antigen and detecting only IgG antibodies confirmed the 2-tier diagnosis in the Lyme disease patient serum samples (n = 12). Validation of the hybrid antigen IgG iPCR assay using a blinded panel of Lyme disease and non-Lyme disease patient serum samples (n = 92) resulted in a sensitivity of 69% (95% confidence interval [CI], 50% to 84%), compared to that of the 2-tier analysis at 59% (95% CI, 41% to 76%), and a specificity of 98% (95% CI, 91% to 100%) compared to that of the 2-tier analysis at 97% (95% CI, 88% to 100%). A single-tier hybrid antigen iPCR assay has the potential to be an improved method for detecting host-generated antibodies against B. burgdorferi

Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses

The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host–virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans

Metabolic Differentiation Of Early Lyme Disease From Southern Tickassociated Rash Illness (Stari)

Lyme disease, the most commonly reported vector-borne disease in the United States, results from infection with Borrelia burgdorferi. Early clinical diagnosis of this disease is largely based on the presence of an erythematous skin lesion for individuals in high-risk regions. This, however, can be confused with other illnesses including southern tick-associated rash illness (STARI), an illness that lacks a defined etiological agent or laboratory diagnostic test, and is coprevalent with Lyme disease in portions of the eastern United States. By applying an unbiasedmetabolomics approach with sera retrospectively obtained from well-characterized patients, we defined biochemical and diagnostic differences between early Lyme disease and STARI. Specifically, a metabolic biosignature consisting of 261 molecular features (MFs) revealed that altered N-acyl ethanolamine and primary fatty acid amide metabolism discriminated early Lyme disease from STARI. Development of classification models with the 261-MF biosignature and testing against validation samples differentiated early Lyme disease from STARI with an accuracy of 85 to 98%. These findings revealed metabolic dissimilarity between early Lyme disease and STARI, and provide a powerful and new approach to inform patient management by objectively distinguishing early Lyme disease from an illness with nearly identical symptoms

Evaluation of a Sequential Enzyme Immunoassay Testing Algorithm for Lyme Disease Demonstrates Lack of Test Independence but High Diagnostic Specificity

To diagnose Lyme disease, a two-tier testing algorithm is used in which supplemental IgM and IgG immunoblots to detect antibody to Borrelia burgdorferi are reflexively performed if a first-tier assay, such as a whole-cell sonicate-based enzyme immunoassay (WCS EIA), is reactive. Recent data suggest that equal specificity is found by substituting the C6 peptide EIA for immunoblots. In this study using 3956 control sera, we demonstrated that although this two-tier testing algorithm does significantly improve diagnostic specificity compared with each of the EIAs individually, the WCS EIA and the C6 peptide EIA are not independent tests. Therefore, when the C6 peptide EIA is used as the second-tier test, it should be regarded as a supplemental rather than a confirmatory test

Immunoproteomic Analysis of Borrelia miyamotoi for the Identification of Serodiagnostic Antigens

The tick-borne spirochete, Borrelia miyamotoi, is an emerging pathogen of public health significance. Current B. miyamotoi serodiagnostic testing depends on reactivity against GlpQ which is not highly sensitive on acute phase serum samples. Additionally, anti-B. miyamotoi antibodies can cross-react with C6 antigen testing for B. burgdorferi, the causative agent of Lyme disease, underscoring the need for improved serological assays that produce accurate diagnostic results. We performed an immunoproteomics analysis of B. miyamotoi proteins to identify novel serodiagnostic antigens. Sera from mice infected with B. miyamotoi by subcutaneous inoculation or tick bite were collected for immunoblotting against B. miyamotoi membrane-associated proteins separated by 2-dimensional electrophoresis (2DE). In total, 88 proteins in 40 2DE immunoreactive spots were identified via mass spectrometry. Multiple variable large proteins (Vlps) and a putative lipoprotein were among those identified and analyzed. Reactivity of anti-B. miyamotoi sera against recombinant Vlps and the putative lipoprotein confirmed their immunogenicity. Mouse anti-B. burgdorferi serum was cross-reactive to all recombinant Vlps, but not against the putative lipoprotein by IgG. Furthermore, antibodies against the recombinant putative lipoprotein were present in serum from a B. miyamotoi-infected human patient, but not a Lyme disease patient. Results presented here provide a comprehensive profile of B. miyamotoi antigens that induce the host immune response and identify a putative lipoprotein as a potentially specific antigen for B. miyamotoi serodetection