BACKGROUND: Post-treatment Lyme disease symptoms/syndrome (PTLDS) occurs in approximately 10% of Lyme disease patients following antibiotic treatment. Biomarkers or specific clinical symptoms to identify PTLDS patients do not currently exist and the PTLDS classification is based on the report of persistent, subjective symptoms for ≥ 6 months following antibiotic treatment for Lyme disease. METHODS: Untargeted liquid chromatography-mass spectrometry metabolomics was used to determine longitudinal metabolic responses and biosignatures in PTLDS and clinically cured non-PTLDS Lyme patients. Evaluation of biosignatures included: 1) defining altered classes of metabolites; 2) elastic net regularization to define metabolites that most strongly defined PTLDS and non-PTLDS patients at different timepoints; 3) changes in the longitudinal abundance of metabolites; 4) linear discriminant analysis to evaluate robustness in a second patient cohort. RESULTS: This study determined that observable metabolic differences exist between PTLDS and non-PTLDS patients at multiple timepoints. The metabolites with differential abundance included those from glycerophospholipid, bile acid and acylcarnitine metabolism. Distinct longitudinal patterns of metabolite abundance indicated a greater metabolic variability in PTLDS vs non-PTLDS patients. Small numbers of metabolites (6-40) could be used to define PTLDS vs. non-PTLDS patients at defined time points, and the findings were validated in a second cohort of PTLDS and non-PTLDS patients. CONCLUSIONS: These data provide evidence that an objective metabolite-based measurement can distinguish patients with PTLDS and help understand the underlying biochemistry of PTLDS.

Lyme disease is a tick-borne bacterial illness that occurs in areas of North America, Europe, and Asia. Early infection typically presents as generalized symptoms with an erythema migrans (EM) skin lesion. Dissemination of the pathogen Borrelia burgdorferi can result in multiple EM skin lesions or in extracutaneous manifestations such as Lyme neuroborreliosis. Metabolic biosignatures of patients with early Lyme disease can potentially provide diagnostic targets as well as highlight metabolic pathways that contribute to pathogenesis. Sera from well-characterized patients diagnosed with either early localized Lyme disease (ELL) or early disseminated Lyme disease (EDL), plus healthy controls (HC), from the United States were analyzed by liquid chromatography-mass spectrometry (LC-MS). Comparative analyses were performed between ELL, or EDL, or ELL combined with EDL, and the HC to develop biosignatures present in early Lyme disease. A direct comparison between ELL and EDL was also performed to develop a biosignature for stages of early Lyme disease. Metabolic pathway analysis and chemical identification of metabolites with LC-tandem mass spectrometry (LC-MS/MS) demonstrated alterations of eicosanoid, bile acid, sphingolipid, glycerophospholipid, and acylcarnitine metabolic pathways during early Lyme disease. These metabolic alterations were confirmed using a separate set of serum samples for validation. The findings demonstrated that infection of humans with B. burgdorferi alters defined metabolic pathways that are associated with inflammatory responses, liver function, lipid metabolism, and mitochondrial function. Additionally, the data provide evidence that metabolic pathways can be used to mark the progression of early Lyme disease.

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.

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.

The correlation between the Food and Drug Administration-cleared C6 enzyme immunoassay (EIA) C6 index values and a diagnosis of Lyme disease has not been examined. We used pooled patient-level data from 5 studies of adults and children with Lyme disease and control subjects who were tested with the C6 EIA. We constructed a receiver operating characteristic curve using regression clustered by study and measured the area under the curve (AUC) to examine the accuracy of the C6 index values in differentiating between patients with noncutaneous Lyme disease and control subjects. In the 4821 included patients, the C6 index value had excellent ability to distinguish between patients with noncutaneous Lyme disease and control subjects [AUC 0.99; 95% confidence interval (CI) 0.99-1.00]. An index value cut point of >/=3.0 had a sensitivity of 90.9% (95% CI, 87.8-93.3) and specificity of 99.0% (95% CI, 98.6-99.2%) for Lyme disease.

Improved serologic tests are needed for accurate diagnosis and proper treatment of early stage Lyme disease. We evaluated the 3 antigens currently used for 2-tiered IgM immunoblot testing (FlaB, OspC, and BmpA) in combination with 3 additional antigens (BBA65, BBA70, and BBA73) and measured the sensitivity and specificity against a serum repository of positive and negative controls. Using 3 statistical methods for positivity cutoff determinations and scoring criteria, we found increased sensitivities for early Lyme disease when 2 of 6 antigens were positive as compared with the 2 of 3 antigen IgM criteria currently used for second-tier immunoblot scoring. Specificities for negative controls were comparable or superior to using 2 of 3 antigens. These results indicate that IgM sensitivity and specificity of serological testing for Lyme disease in the early stages of illness can be improved by employing antigens that target the initial host antibody responses.

Metabolites detectible in human biofluids are attractive biomarkers for the diagnosis of early Lyme disease (ELD), a vector-borne infectious disease. Urine represents an easily obtained clinical sample that can be applied for diagnostic purposes. However, few studies have explored urine for biomarkers of ELD. In this study, metabolomics approaches were applied to evaluate small molecule metabolites in urine from patients with ELD (n = 14), infectious mononucleosis (n = 14) and healthy controls (n = 14). Metabolic biosignatures for ELD versus healthy controls and ELD versus infectious mononucleosis were generated using untargeted metabolomics. Pathway analyses and metabolite identification revealed the dysregulation of several metabolic processes in ELD as compared to healthy controls or mononucleosis, including metabolism of tryptophan. Linear discriminant analyses demonstrated that individual metabolic biosignatures can correctly discriminate ELD from the other patient groups with accuracies of 71 to 100%. These data provide proof-of-concept for use of urine metabolites as biomarkers for diagnostic classification of ELD.

Standard two-tiered testing (STTT) is the recommended algorithm for laboratory diagnosis of Lyme disease (LD). Several limitations are associated with STTT that include low sensitivity in the early stages of disease, as well as technical complexity and subjectivity associated with second-tier immunoblots; therefore, modified two-tiered testing (MTTT) algorithms that utilize two sequential first-tier tests and eliminate immunoblots have been evaluated. Recently, a novel MTTT that uses a VlsE chemiluminescence immunoassay followed by a C6 enzyme immunoassay has been proposed. The purpose of this study was to evaluate the performance of the VlsE/C6 MTTT using well-characterized serum samples. Serum samples from the CDC Lyme Serum Repository were tested using three MTTTs: VlsE/C6, whole cell sonicate (WCS)/C6 and WCS/VlsE, and three STTTs (immunoblots preceded by three different first-tier assays: VlsE, C6 and WCS). Significant differences were not observed between the MTTTs assessed; however, the VlsE/C6 MTTT resulted in the highest specificity (100%) when other diseases were tested and the lowest sensitivity (75%) for LD samples as compared to the other MTTTs evaluated. Significant differences were present between various MTTTs and STTTs evaluated. Specifically, all MTTTs resulted in higher sensitivities for all LD groups combined when compared to the STTTs and were significantly more accurate (i.e. higher proportion of correct classifications) for this group with the exception of the WCS/ViraStripe STTT. Additionally, when other diseases were tested, only the VlsE/C6 MTTT differed significantly from the WCS/ViraStripe STTT with the VlsE/C6 MTTT resulting in a 6.2% higher accuracy. Overall, the VlsE/C6 MTTT offers an additional laboratory testing algorithm for LD with equivalent or enhanced performance to the other MTTTs and STTTs evaluated in this study.

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.

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 unbiased metabolomics 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.

The recommended laboratory diagnostic approach for Lyme disease is a standard two-tiered testing (STTT) algorithm where the first-tier is typically an enzyme immunoassay (EIA) that if positive or equivocal is reflexed to Western immunoblotting as the second-tier. bioMerieux manufacturers one of the most commonly used first-tier EIAs in the U.S., the combined IgM/IgG VIDAS (LYT). Recently, bioMerieux launched its dissociated first-tier tests, the VIDAS Lyme IgM II (LYM) and IgG II (LYG) EIAs, which use purified recombinant test antigens and a different algorithm than STTT. The dissociated LYM/LYG EIAs were evaluated against the combined LYT EIA using samples from 471 well-characterized Lyme patients and controls. Statistical analyses were conducted to assess the performance of these EIAs as first-tier tests and when used in two-tiered algorithms, including a modified two-tiered testing (MTTT) approach, where the second-tier test was a C6 EIA. Similar sensitivities and specificities were obtained for the two testing strategies (LYT vs. LYM/LYG) when used as first-tier tests (sensitivity: 83 to 85%; specificity: 85 to 88%) with an observed agreement of 80%. Sensitivities of 68 to 69% and 76 to 77% and specificities of 97% and 98 to 99% resulted when the two EIA strategies were followed by Western immunoblotting and when used in a MTTT, respectively. The MTTT approach resulted in significantly higher sensitivities as compared to STTT. Overall, the LYM/LYG EIAs performed equivalently to the LYT EIA in test-to-test comparisons or as first-tier assays in STTT or MTTT with few exceptions.

Current recommendation for the laboratory confirmation of Lyme disease is serology-based diagnostics. Specifically, a standardized two-tiered testing (STTT) algorithm is applied that utilizes a first-tier immunofluorescence assay (IFA) or enzyme immunoassay (EIA) that if positive or equivocal is followed by second-tier immunoblotting. Despite the standardization and performance achievements, STTT is considered technically complex and subjective, as well as insensitive for early acute infection. These issues have prompted development of novel algorithms and testing platforms. In this study, we evaluated the performance of several commonly used assays for STTT. Several modified two-tiered testing (MTTT) algorithms, including a 2-EIA algorithm and modified criteria for second-tier IgG immunoblots, were also evaluated. All tests were performed on sera from a recently available, well-defined archive of positive and negative control patients. Our study demonstrated differences in the results between individual first- and second-tier tests although the overall agreement of the different STTT algorithms used was strong. Additionally, the MTTT algorithm utilizing 2-EIAs was found to be equivalent to all STTT algorithms tested, with agreement ranging from 94 to 97%. The 2-EIA MTTT algorithm slightly enhanced sensitivity in early disease as compared to the STTT algorithms evaluated. Furthermore, these data add to the mounting evidence that a 2-EIA-based MTTT algorithm, where immunoblotting is replaced by the C6 EIA, performs equally well or better than STTT.

Laboratory testing for the diagnosis of Lyme disease is performed primarily by serologic assays and is accurate for detection beyond the acute stage of the infection. Serodiagnostic assays to detect the early stages of infection, however, are limited in their sensitivity and improvement is warranted. We analyzed a series of Borrelia burgdorferi proteins known to be induced either within feeding ticks and/or during mammalian infection for their utility as serodiagnostic markers against a comprehensive panel of Lyme disease patient serum samples. The antigens were assayed for IgM and IgG reactivity in line immunoblots and separately by ELISA, with a focus on reactivity against early Lyme erythema migrans (EM), early disseminated Lyme neuroborreliosis, and early Lyme carditis patient serum samples. By IgM immunoblotting, we found that recombinant proteins BBA65, BBA70, and BBA73 reacted with early Lyme EM samples at levels comparable to the OspC antigen used in the current IgM blotting criteria. Additionally, these proteins reacted with serum samples from patients with early neuroborreliosis and early carditis suggesting value in detecting early stages of this disease progression. We also found serological reactivity against recombinant proteins BBA69 and BBA73 with early Lyme samples using IgG immunoblotting and ELISA. Significantly, some samples that had been scored negative by the Centers for Disease Control and Prevention recommended 2-tiered testing algorithm demonstrated positive reactivity to one or more of the antigens by IgM/IgG immunoblot and ELISA. These results suggest that incorporating additional in vivo expressed antigens in the current IgM/IgG immunoblotting tier in a recombinant protein platform assay may improve the performance of early Lyme disease serologic testing.

BACKGROUND: Early Lyme disease patients often present to the clinic prior to developing a detectable antibody response to Borrelia burgdorferi, the etiologic agent. Thus, existing two-tier serology-based assays yield low sensitivities (29-40%) for early infection. The lack of an accurate laboratory test for early Lyme disease contributes to misconceptions about diagnosis and treatment, and underscores the need for new diagnostic approaches. METHODS: Retrospective serum samples from patients with early Lyme disease, other diseases, and healthy controls were analyzed for small molecule metabolites by liquid chromatography-mass spectrometry (LC-MS). A metabolomics data workflow was applied to select a biosignature for classifying early Lyme disease and non-Lyme disease patients. A statistical model of the biosignature was trained using the patients' LC-MS data, and subsequently applied as an experimental diagnostic tool with LC-MS data from additional patient sera. The accuracy of this method was compared with standard two-tier serology. RESULTS: Metabolic biosignature development selected 95 molecular features that distinguished early Lyme disease patients from healthy controls. Statistical modeling reduced the biosignature to 44 molecular features, and correctly classified early Lyme disease patients and healthy controls with a sensitivity of 88% (84-95%), and a specificity of 95% (90-100%). Importantly, the metabolic biosignature correctly classified 77-95% of the of serology negative Lyme disease patients. CONCLUSION: The data provide proof-of-concept that metabolic profiling for early Lyme disease can achieve significantly greater (p<0.0001) diagnostic sensitivity than current two-tier serology, while retaining high specificity.

Francisella tularensis causes disease (tularemia) in a large number of mammals, including man. We previously demonstrated enhanced efficacy of conventional antibiotic therapy for tularemia by postexposure passive transfer of immune sera developed against a F. tularensis LVS membrane protein fraction (MPF). However, the protein composition of this immunogenic fraction was not defined. Proteomic approaches were applied to define the protein composition and identify the immunogens of MPF. MPF consisted of at least 299 proteins and 2-D Western blot analyses using sera from MPF-immunized and F. tularensis LVS-vaccinated mice coupled to liquid chromatography-tandem mass spectrometry identified 24 immunoreactive protein spots containing 45 proteins. A reverse vaccinology approach that applied labeling of F. tularensis LVS surface proteins and bioinformatics was used to reduce the complexity of potential target immunogens. Bioinformatics analyses of the immunoreactive proteins reduced the number of immunogen targets to 32. Direct surface labeling of F. tularensis LVS resulted in the identification of 31 surface proteins. However, only 13 of these were reactive with MPF and/or F. tularensis LVS immune sera. Collectively, this use of orthogonal proteomic approaches reduced the complexity of potential immunogens in MPF by 96% and allowed for prioritization of target immunogens for antibody-based immunotherapies against tularemia.

Serological assays and a two-tiered test algorithm are recommended for laboratory confirmation of Lyme disease. In the U.S. the sensitivity of two-tiered testing using commercially available serology-based assays is dependent on the stage of infection and ranges from 30% in the early localized disease to near 100% in late stage disease. Other variables, including subjectivity in reading Western blots, compliance with two-tiered recommendations, use of different first and second tier test combinations, and use of different test samples, all contribute to variation in two-tiered test performance. The availability and use of sample sets from well-characterized Lyme disease patients and controls are needed to better assess the performance of existing tests and for development of improved assays. To address this need, the Centers for Disease Control and Prevention and the National Institutes of Health prospectively collected sera from patients at all stages of Lyme disease, as well as healthy donors and patients with look-alike diseases. Patients and healthy controls were recruited using strict inclusion and exclusion criteria. Samples from all included patients were retrospectively characterized by two-tiered testing. The results from two-tiered testing corroborated the need for novel and improved diagnostics, particularly for laboratory diagnosis of earlier stages of infection. Furthermore, the two-tier results provide a baseline with samples from well-defined patients that can be used in comparing the sensitivity and specificity of novel diagnostics. Panels of sera and accompanying clinical and laboratory testing results are now available to Lyme disease serological test users and researchers developing novel tests.

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

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 S4 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 S4 belongs to the most virulent subspecies of F. tularensis, subspecies tularensis. METHODS: In this study, we investigated the relative virulence of Schu S4 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 S4 at drop point. RESULTS: Survival curve comparisons demonstrate that the Schu S4 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 S4 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 S4 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.

The study of infectious agents, their pathogenesis, the host response and the evaluation of newly developed countermeasures often requires the use of a living system. Murine models are frequently used to undertake such investigations with the caveat that non-biased measurements to assess the progression of infection are underutilized. Instead, murine models predominantly rely on symptomology exhibited by the animal to evaluate the state of the animal's health and to determine when euthanasia should be performed. In this study, we used subcutaneous temperature as a non-subjective measurement to follow and compare infection in mice inoculated with Francisella tularensis, a Gram-negative pathogen that produces an acute and fatal illness in mice. A reproducible temperature pattern defined by three temperature phases (normal, febrile and hypothermic) was identified in all mice infected with F. tularensis, regardless of the infecting strain. More importantly and for the first time a non-subjective, ethical, and easily determined surrogate endpoint for death based on a temperature, termed drop point, was identified and validated with statistical models. In comparative survival curve analyses for F. tularensis strains with differing virulence, the drop point temperature yielded the same results as those obtained using observed time to death. Incorporation of temperature measurements to evaluate F. tularensis was standardized based on statistical models to provide a new level of robustness for comparative analyses in mice. These findings should be generally applicable to other pathogens that produce acute febrile disease in animal models and offers an important tool for understanding and following the infection process.

Genotyping of Francisella tularensis (A1a, A1b, A2, and type B) and Francisella novicida has identified multiple differences between species and among F. tularensis subspecies and subpopulations. Variations in virulence, geographic distribution, and ecology are also known to exist among this group of bacteria, despite the >95% nucleotide identity in their genomes. This study expands the description of phenotypic differences by evaluating the ability of F. tularensis and F. novicida to degrade chitin analogs and produce active chitinases. Endochitinase activities were observed to vary among F. tularensis and F. novicida strains. The activity observed for F. tularensis strains was predominantly associated with whole-cell lysates, while the chitinase activity of F. novicida localized to the culture supernatant. In addition, the overall level of chitinase activity differed among the subpopulations of F. tularensis and between the species. Bioinformatic analyses identified two new putative chitinase genes (chiC and chiD), as well as the previously described chiA and chiB. However, the presence of these four open reading frames as intact genes or pseudogenes was found to differ between Francisella species and F. tularensis subspecies and subpopulations. Recombinant production of the putative chitinases and enzymatic evaluations revealed ChiA, ChiB, ChiC, and ChiD possessed dissimilar chitinase activities. These biochemical studies coupled with bioinformatic analyses and the evaluation of chiA and chiC knockouts in F. tularensis A1 and A2 strains, respectively, provided a molecular basis to explain the differential chitinase activities observed among the species and subpopulations of Francisella.

Francisella tularensis subspecies tularensis (type A) and holarctica (type B) are of clinical importance in causing tularemia. Molecular typing methods have further separated type A strains into three genetically distinct clades, A1a, A1b and A2. Epidemiological analyses of human infections in the United States suggest that A1b infections are associated with a significantly higher mortality rate as compared to infections caused by A1a, A2 and type B. To determine if genetic differences as defined by molecular typing directly correlate with differences in virulence, A1a, A1b, A2 and type B strains were compared in C57BL/6 mice. Here we demonstrate significant differences between survival curves for infections caused by A1b versus A1a, A2 and type B, with A1b infected mice dying earlier than mice infected with A1a, A2 or type B; these results were conserved among multiple strains. Differences were also detected among type A clades as well as between type A clades and type B with respect to bacterial burdens, and gross anatomy in infected mice. Our results indicate that clades defined within F. tularensis subsp. tularensis by molecular typing methods correlate with virulence differences, with A1b strains more virulent than A1a, A2 and type B strains. These findings indicate type A strains are not equivalent with respect to virulence and have important implications for public health as well as basic research programs.

Tularemia is primarily caused by two subspecies of Francisella tularensis worldwide, ssp. tularensis (type A) and ssp. holarctica (type B), which were originally delineated by phenotypic differences. Application of molecular typing methods to investigate population structure of F. tularensis has confirmed that catagorizing the two subspecies via phenotypic characteristics corresponds with genotypic differentiation. In addition, genotyping methods have demonstrated that both subspecies, type A and type B, can be further distinguished into subpopulations and, in some cases, biological relevance has been ascribed to these identified subpopulations. Genetic variation among both type A and type B subpopulations has been shown to correlate with differences in geographic distribution and has also been coupled to distinct ecological niches, animal hosts and replication foci. Among type A subpopulations, strain variation is linked to differing clinical manifestations in humans and virulence in mice. This article will highlight our current understanding of F. tularensis subpopulations, including methods for their detection, their observed epidemiologic differences, implications for public health and basic research programs, as well as future challenges yet to be solved.