Persistence Of Infectious Diseases Research Articles

Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis. Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP). The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816. Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.

HCG18, LEF1AS1 and lncCEACAM21 as biomarkers of disease severity in the peripheral blood mononuclear cells of COVID-19 patients

BackgroundEven after 3 years from SARS-CoV-2 identification, COVID-19 is still a persistent and dangerous global infectious disease. Significant improvements in our understanding of the disease pathophysiology have now been achieved. Nonetheless, reliable and accurate biomarkers for the early stratification of COVID-19 severity are still lacking. Long noncoding RNAs (LncRNAs) are ncRNAs longer than 200 nucleotides, regulating the transcription and translation of protein‐coding genes and they can be found in the peripheral blood, thus holding a promising biomarker potential. Specifically, peripheral blood mononuclear cells (PBMCs) have emerged as a source of indirect biomarkers mirroring the conditions of tissues: they include monocytes, B and T lymphocytes, and natural killer T cells (NKT), being highly informative for immune-related events.MethodsWe profiled by RNA-Sequencing a panel of 2906 lncRNAs to investigate their modulation in PBMCs of a pilot group of COVID-19 patients, followed by qPCR validation in 111 hospitalized COVID-19 patients.ResultsThe levels of four lncRNAs were found to be decreased in association with COVID-19 mortality and disease severity: HLA Complex Group 18-242 and -244 (HCG18-242 and HCG18-244), Lymphoid Enhancer Binding Factor 1-antisense 1 (LEF1-AS1) and lncCEACAM21 (i.e. ENST00000601116.5, a lncRNA in the CEACAM21 locus). Interestingly, these deregulations were confirmed in an independent patient group of hospitalized patients and by the re-analysis of publicly available single-cell transcriptome datasets. The identified lncRNAs were expressed in all of the PBMC cell types and inversely correlated with the neutrophil/lymphocyte ratio (NLR), an inflammatory marker. In vitro, the expression of LEF1-AS1 and lncCEACAM21 was decreased upon THP-1 monocytes exposure to a relevant stimulus, hypoxia.ConclusionThe identified COVID-19-lncRNAs are proposed as potential innovative biomarkers of COVID-19 severity and mortality.

Natural Products as Mite Control Agents in Animals: A Review.

Mites have been a persistent infectious disease affecting both humans and animals since ancient times. In veterinary clinics, the primary approach for treating and managing mite infestations has long been the use of chemical acaricides. However, the widespread use of these chemicals has resulted in significant problems, including drug resistance, drug residues, and environmental pollution, limiting their effectiveness. To address these challenges, researchers have shifted their focus towards natural products that have shown promise both in the laboratory and real-world settings against mite infestations. Natural products have a wide variety of chemical structures and biological activities, including acaricidal properties. This article offers a comprehensive review of the acaricidal capabilities and mechanisms of action of natural products like plant extracts, natural compounds, algae, and microbial metabolites against common animal mites.

Perceptive movement of susceptible individuals with memory.

The perception of susceptible individuals naturally lowers the transmission probability of an infectious disease but has been often ignored. In this paper, we formulate and analyze a diffusive SIS epidemic model with memory-based perceptive movement, where the perceptive movement describes a strategy for susceptible individuals to escape from infections. We prove the global existence and boundedness of a classical solution in an n-dimensional bounded smooth domain. We show the threshold-type dynamics in terms of the basic reproduction number [Formula: see text]: when [Formula: see text], the unique disease-free equilibrium is globally asymptotically stable; when [Formula: see text], there is a unique constant endemic equilibrium, and the model is uniformly persistent. Numerical analysis exhibits that when [Formula: see text], solutions converge to the endemic equilibrium for slow memory-based movement and they converge to a stable periodic solution when memory-based movement is fast. Our results imply that the memory-based movement cannot determine the extinction or persistence of infectious disease, but it can change the persistence manner.

Descending necrotizing mediastinitis: a challenging infection. Selected results of a Moroccan bicentric study.

Mediastinal infection is a persistent and difficult widespread infectious disease caused by secondary complications of adjacent organs. It spreads easily and is often misdiagnosed because of the lack of typical manifestations. To highlight the clinical features, medical and surgical strategy of descending necrotizing mediastinitis we performed a retrospective study of 25 documented cases during a 10-year period at our hospital, all treated surgically, 10 from the ORL department and 15 from our thoracic surgery department. Patients were aged from 20 to 84 years, with a median age of 41 years, male predominance (19 men and 6 women), sex ratio of 3.6. A cervicotomy (in 40% of cases) was associated or not with videothoracoscopy (one case) or thoracotomy (in 20% of cases) and wide-spectrum antibiotherapy. In the postoperative period, an irrigation-suction system was used on the drains in 15 patients. In 1 case a rethoracotomy was necessary to remove a residual right pyothorax, and one patient required a tracheostomy. Twenty-two (88%) patients recovered from their mediastinitis. Death of 3 patients by sepsis multiorgan failure occurred. Postoperative follow-up during one year was uneventful without recurrence. According to our experience, we believe the more aggressive local treatment is, the better are the results.

Mathematical Model of the Immunopathological Progression of Tuberculosis

Tuberculosis is a worldwide persistent infectious disease. It is caused by bacteria from the Mycobacterium tuberculosis complex that mainly affects the lungs and can be fatal. Using an integrative systems biology approach, we study the immunopathological progression of this disease, analyzing the key interactions between the cells involved in the different phases of the infectious process. We integrated multiple in vivo and in vitro data from immunohistochemical, serological, molecular biology, and cell count assays into a mechanistic mathematical model. The ordinary differential equation (ODE) model captures the regulatory interplay between the phenotypic variation of the main cells involved in the disease progression and the inflammatory microenvironment. The model reproduces in vivo time course data of an experimental model of progressive pulmonary TB in mouse, accurately reflecting the functional adaptations of the host–pathogen interactions as the disease progresses through three phenotypically different phases. We used the model to assess the effect of genotypic variations (encoded as changes in parameters) on disease outcomes. For all genotypes, we found an all-or-nothing response, where the virtual mouse either completely clears the infection or suffers uncontrolled Tb growth. Results show that it is 84% probable that a mouse submitted to a progressive pulmonary TB assay will end up with an uncontrolled infection. The simulations also showed how the genotypic variations shape the transitions across phases, showing that 100% of the genotypes evaluated eventually progress to phase two of the disease, suggesting that adaptive immune response activation was unavoidable. All the genotypes of the network that avoided progressing to phase 3 cleared the infection. Later, by analyzing the three different phases separately, we saw that the anti-inflammatory genotype of phase 3 was the one with the highest probability of leading to uncontrolled bacterial growth, and the proinflammatory genotype associated with phase 2 had the highest probability of bacterial clearance. Forty-two percent of the genotypes evaluated showed a bistable response, with one stable steady state corresponding to infection clearance and the other one to bacteria reaching its carrying capacity. Our mechanistic model can be used to predict the outcomes of different experimental conditions through in silico assays.

Building knowledge, optimising physical and mental health and setting up healthier life trajectories in South African women (Bukhali): a preconception randomised control trial part of the Healthy Life Trajectories Initiative (HeLTI)

IntroductionSouth Africa’s evolving burden of disease is challenging due to a persistent infectious disease, burgeoning obesity, most notably among women and rising rates of non-communicable diseases (NCDs). With two thirds...

Delineating charge and capacitance transduction in system-integrated graphene-based BioFETs used as aptasensors for malaria detection

Despite significant eradication efforts, malaria remains a persistent infectious disease with high mortality due to the lack of efficient point-of-care (PoC) screening solutions required to manage low-density asymptomatic parasitemia. In response, we demonstrate a quantitative electrical biosensor based on system-integrated two-dimensional field-effect transistors (2DBioFETs) of reduced graphene oxide (rGO) as transducer for high sensitivity screening of the main malaria biomarker, Plasmodium falciparum lactate dehydrogenase (PfLDH). The 2DBioFETs were biofunctionalized with pyrene-modified 2008s aptamers as specific PfLDH receptors. While we systematically optimize biosensor interface for optimal performance, aptamer-protein transduction at 2DBioFETs is elucidated based on delineation of charge and capacitance in an updated analytical model for two-dimensional rGO/biofunctional layer/electrolyte (2DiBLE) interfaces. Our 2DBioFET-aptasensors display a limit-of-detection down to 0.78 fM (0.11 pg/mL), dynamic ranges over 9 orders of magnitude (subfemto to submicromolar), high sensitivity, and selectivity in human serum validating their diagnostic potential as rapid PoC tests for malarial management.

A review of the therapeutic properties of dithiocarbamates

The persistence of infectious diseases that continue to plague the world, as well as the formation of harmful substances within the human body, such as free radicals and reactive oxygen species (ROS) have sparked new research. Thus, the need for innovative approaches for developing new or modification of existing therapeutic agents. The design of biologically important metal complexes of dithiocarbamates (DTCs) has been made possible by recent advancements in innovative research. Dithiocarbamates are reduced thiuram disulfides with excellent complexing capabilities and have various applications. They are potent and work in tandem with the core metal ions of coordinating compounds to produce synergistic effects. Dithiocarbamates have many uses, including as antidotes for metal poisoning, cisplatin or carboplatin toxicity, and clinical trials for cancer, Lyme disease, human immunodeficiency virus and antibiotics. They exert anti-oxidant effect in cells. The understanding of the mechanisms of action of this therapeutic agent is important in drug repurposing. This review highlights the protective and therapeutic properties of dithiocarbamate compounds in biological systems.

Modelling management strategies for chronic disease in wildlife: Predictions for the control of respiratory disease in bighorn sheep

Abstract Controlling persistent infectious disease in wildlife populations is an ongoing challenge for wildlife managers and conservationists worldwide, and chronic diseases in particular remain a pernicious problem. Here, we develop a dynamic pathogen transmission model capturing key features of Mycoplasma ovipneumoniae infection, a major cause of population declines in North American bighorn sheep Ovis canadensis. We explore the effects of model assumptions and parameter values on disease dynamics, including density‐ versus frequency‐dependent transmission, the inclusion of a carrier class versus a longer infectious period, host survival rates, disease‐induced mortality and recovery rates and the epidemic growth rate. Along the way, we estimate the basic reproductive ratio, R0, for M. ovipneumoniae in bighorn sheep to fall between approximately 1.36 and 1.74. We apply the model to compare efficacies across a suite of management actions following an epidemic, including test‐and‐remove, depopulation‐and‐reintroduction, range expansion, herd augmentation and density reduction. Our results suggest that test‐and‐remove, depopulation‐and‐reintroduction and range expansion could help persistently infected bighorn sheep herds recovery following an epidemic. By contrast, augmentation could lead to worse outcomes than those expected in the absence of management. Other management actions that improve host survival or reduce disease‐induced mortality are also likely to improve population size and persistence of chronically infected herds. Synthesis and applications. Dynamic transmission models like the one employed here offer a structured, logical approach for exploring hypotheses, planning field experiments and designing adaptive management. We find that management strategies that removed infected animals or isolated them within a structured metapopulation were most successful at facilitating herd recovery from a low‐prevalence, chronic pathogen. Ideally, models like ours should operate iteratively with field experiments to triangulate on better approaches for managing wildlife diseases.

Multiplexed colorimetric detection of SARS-CoV-2 and other pathogens in wastewater on a 3D printed integrated microfluidic chip

Severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic has become a global public health emergency. The detection of SARS-CoV-2 and human enteric pathogens in wastewater can provide an early warning of disease outbreak. Herein, a sensitive, multiplexed, colorimetric detection (termed “SMCD”) method was established for pathogen detection in wastewater samples. The SMCD method integrated on-chip nucleic acid extraction, two-stage isothermal amplification, and colorimetric detection on a 3D printed microfluidic chip. The colorimetric signal during nucleic acid amplification was recorded in real-time and analyzed by a programmed smartphone without the need for complicated equipment. By combining two-stage isothermal amplification assay into the integrated microfluidic platform, we detected SARS-CoV-2 and human enteric pathogens with sensitivities of 100 genome equivalent (GE)/mL and 500 colony-forming units (CFU)/mL, respectively, in wastewater within one hour. Additionally, we realized smart, connected, on-site detection with a reporting framework embedded in a portable detection platform, which exhibited potential for rapid spatiotemporal epidemiologic data collection regarding the environmental dynamics, transmission, and persistence of infectious diseases.

Main Results of the Research on the Far Eastern Scarlet-Like Fever as a Specific Clinical and Epidemic Manifestation of Pseudotuberculosis: A Review of Comprehensive Studies

Introduction: Until 1950s, pseudotuberculosis in humans was known in the world as a sporadic disease with appendicular syndrome. In 1959, the first outbreak of a previously unknown disease called Far Eastern scarlet-like fever (FESLF) was registered in Vladivostok. The purpose of this article is to review priority achievements of the Research Institute of Epidemiology and Microbiology named after G.P. Somov in the field of studying FESLF as a specific clinical and epidemic manifestation of pseudotuberculosis in Russia. Materials and methods: The priority data were obtained based on microbiological, epidemiological, molecular genetic, as well as pathomorphological and electron microscopic studies of biological samples from human FESLF cases and experimental animals infected with Yersinia pseudotuberculosis strains with different plasmid characteristics. Results: It has been proven that the FESLF pathogen is a specific clone of Yersinia pseudotuberculosis having a certain plasmid profile pVM82, pYV 48 MDa, sequence type (2ST) and the first allele of the yadA gene. The causative agent of FESLF is characterized by the phenomenon of psychrophilicity, which consists in its ability to multiply in the environment with its biologically low and changing temperature (4–12 °C), at which the pathogen multiplies and accumulates while preserving or increasing its virulence, thus inducing the epidemic process. The article describes the main genetic and biochemical mechanisms of Y. pseudotuberculosis adaptation to changing environmental conditions, reveals morphological manifestations of the adaptive variability of these bacteria under different conditions of their habitat, and presents the main features of the pathogenesis and morphogenesis of FESLF, including those associated with plasmid characteristics and toxigenicity of Y. pseudotuberculosis. Conclusion: Currently, the epidemic process of pseudotuberculosis/FESLF is characterized by a decrease in the proportion of outbreaks and predominance of sporadic cases. The relevance of further research is associated with the study of the dormant forms of Y. pseudotuberculosis and the formation of ideas about pseudotuberculosis as a persistent infectious disease.

Characterizing EBV-associated lymphoproliferative diseases and the role of myeloid-derived suppressor cells

AbstractChronic active Epstein-Barr virus (CAEBV) typically presents as persistent infectious mononucleosis-like disease and/or hemophagocytic lymphohistocytosis (HLH), reflecting ectopic Epstein-Barr virus (EBV) infection and lymphoproliferation of T and/or NK cells. Clinical behavior ranges from indolent, stable disease through to rapidly progressive, life-threatening disease. Although it is thought the chronicity and/or progression reflect an escape from immune control, very little is known about the phenotype and function of the infected cells vs coresident noninfected population, nor about the mechanisms that could underpin their evasion of host immune surveillance. To investigate these questions, we developed a multicolor flow cytometry technique combining phenotypic and functional marker staining with in situ hybridization for the EBV-encoded RNAs (EBERs) expressed in every infected cell. This allows the identification, phenotyping, and functional comparison of infected (EBERPOS) and noninfected (EBERNEG) lymphocyte subset(s) in patients' blood samples ex vivo. We have characterized CAEBV and HLH cases with monoclonal populations of discrete EBV-activated T-cell subsets, in some cases accompanied by EBV-activated NK-cell subsets, with longitudinal data on the infected cells' progression despite standard steroid-based therapy. Given that cytotoxic CD8+ T cells with relevant EBV antigen specificity were detectable in the blood of the best studied patient, we searched for means whereby host surveillance might be impaired. This revealed a unique feature in almost every patient with CAEBV studied: the presence of large numbers of myeloid-derived suppressor cells that exhibited robust inhibition of T-cell growth. We suggest that their influence is likely to explain the host's failure to contain EBV-positive T/NK-cell proliferation.

Diagnosis and Treatment of Retroperitoneal Infection.

Background: Retroperitoneal infection is a persistent and widespread infectious disease that is difficult to treat. It is usually caused by secondary complications such as inflammation, damage, or perforation of adjacent organs in the retroperitoneal space. Pathogenic bacteria invade the retroperitoneal space through retroperitoneal and interstitial organs, peripheral tissue, and the blood. As a result, infections mostly arise from severe acute pancreatitis, acute colonic diverticulitis, inflammatory bowel disease, kidney abscess, and biliary tract injury. Initially manifested by the presence of lumbago, this disease spreads easily, is persistent, and is often misdiagnosed. Methods: Review and synthesis of pertinent literature and guidelines pertaining to abdominal infection and retroperitoneal infection. Results: Recent data indicate that mortality rates associated with retroperitoneal infection have been increasing annually. Early diagnosis and treatment have been shown to improve the prognosis. In the early stage, infection is insidious and lacks typical symptoms, and is primarily diagnosed with computed tomography (CT). Strategies that control the source of infection, rational use of antibiotic agents, and nutritional interventions are the primary approaches to treat the infections. Emergence of minimally invasive drainage technologies, including the ultrasound/CT-guided puncture and drainage, percutaneous nephroscope puncture and drainage, and drainage using a catheter through an abdominal puncture device (trocar) have shortened the treatment cycle and disease burden. However, current diagnosis and treatment for retroperitoneal infection are not sufficiently effective because some patients do not show typical clinical manifestations. Moreover, sensitivity and specificity of available auxiliary examination methods are not supported by sufficient evidence-based medical research. Additionally, there are no uniform standards on the timing of surgical intervention and treatment options. Therefore, we summarized the progresses on current diagnosis and treatment approaches for retroperitoneal infection.

Efficient Bayesian Model Choice for Partially Observed Processes: With Application to an Experimental Transmission Study of an Infectious Disease

Infectious diseases such as avian influenza pose a global threat to human health. Mathematical and statistical models can provide key insights into the mechanisms that underlie the spread and persistence of infectious diseases, though their utility is linked to the ability to adequately calibrate these models to observed data. Performing robust inference for these systems is challenging. The fact that the underlying models exhibit complex non-linear dynamics, coupled with practical constraints to observing key epidemiological events such as transmission, requires the use of inference techniques that are able to numerically integrate over multiple hidden states and/or infer missing information. Simulation-based inference techniques such as Approximate Bayesian Computation (ABC) have shown great promise in this area, since they rely on the development of suitable simulation models, which are often easier to code and generalise than routines that require evaluations of an intractable likelihood function. In this manuscript we make some contributions towards improving the efficiency of ABC-based particle Markov chain Monte Carlo methods, and show the utility of these approaches for performing both model inference and model comparison in a Bayesian framework. We illustrate these approaches on both simulated data, as well as real data from an experimental transmission study of highly pathogenic avian influenza in genetically modified chickens.

Dynamic of Non-Autonomous Vector Infectious Disease Model with Cross Infection

In the article, we established a non-autonomous vector infectious disease model, studied the long-term dynamic behavior of the system, and obtained sufficient conditions for the extinction and persistence of infectious diseases by constructing integral functions.

Cattle movements in Northern Ireland form a robust network: implications for disease management

The movements of undetected infected animals can facilitate long-distance pathogen spread, making control and eradication difficult by (re)infecting disease-free populations. Characterising movement patterns is essential in understanding pathogen spread and how potential interventions, particularly animal movement restrictions, could help as a control mechanism. In Northern Ireland (NI), cattle movements are important contributors to a significant portion of agricultural trade. They can be disrupted due to statutory interventions, for example, during bovine tuberculosis (bTB) control. Identifying populations at risk of becoming infected would allow for improved resource allocation. This could be through targeting herds with an above-average risk of becoming infected or spreading (amplifying) infection, and restricting their movement to manage future outbreaks.In this study, cattle movements were investigated using social network analysis (SNA) at the monthly temporal scale across NI during 2010-2015. Targeted and random herd restrictions were compared and their impact on the structure and connectivity of the networks’ was assessed (e.g. connected component subgraphs). This work was contextualised in relation to bTB, the most persistent infectious disease currently impacting agriculture in NI, where reduced connectivity would represent potential reduced vulnerability from infection introduction.There was seasonal variation in network size and level of connectivity with spring and autumn being the largest and most connected due to common farming practices in NI. Across the study period, there was limited inter-annual variation in global network metrics. On average there were 6.28 movements between each pair of nodes each month, low reciprocity (mean of 0.155) and the networks were moderately accessible with an average path length of 4.28. Movements were not confined to within each disease management area but frequently occurred between these areas (mean assortativity of -0.0731) and herds with high degree interacted with herds of low degree (mean assortativity of -0.351). The Giant Weakly Connected Component (GWCC) spanned most of the networks (between 75% and 100% of nodes); however the Giant Strongly Connected Component (GSCC) included, at most, 23% of the network. There was heterogeneous contributions across NI with little participation in the GSCC from some disease management areas, and the GSCC was comprised predominantly of ‘beef breeders’, ‘beef rearers’, and ‘other/mixed’ type herds. Targeted restrictions were more effective at fragmenting the network than randomly restricting movements when 25% of nodes or more were removed. Cattle networks in NI are extremely interconnected and robust to movement restrictions, suggesting potential vulnerability to movement-facilitated pathogen spread, such as bTB.

Diabetes, alcohol abuse, and inequality in southern Mexico

Despite the serious persistence of infectious diseases, low-income, indigenous people in southern Mexico are increasingly burdened by noncommunicable diseases, type 2 diabetes in particular. Most studies on diabetes and indigenous peoples focus on the dietary transition they are experiencing, with an emphasis on the biological role of processed foods and soft drinks on the onset of this disease. Little, however, is known about the synergistic interaction of alcohol abuse, diabetes, and inequality. This article adopts a syndemic approach to investigate how alcohol abuse among women and men in a rural, indigenous community in southern Mexico contributes to exacerbating health outcomes. Based on a one-year qualitative ethnographic study, this article advocates the use of a syndemic approach into the study of noncommunicable diseases because it offers critical insights into political economy, individual and social suffering, and the biosocial nature of health and illness.

DYNAMICS OF A STOCHASTIC SIR MODEL WITH BOTH HORIZONTAL AND VERTICAL TRANSMISSION

A stochastic mathematical model with both horizontal and vertical transmission is proposed to investigate the dynamical behavior of SIR disease. By employing theories of stochastic differential equation and inequality techniques, the threshold associating on extinction and persistence of infectious diseases is deduced for the case of the small noise. Our results show that the threshold completely depends on the stochastic perturbation and the basic reproductive number of the corresponding deterministic model. Moreover, we find that large noise is conducive to control the spread of diseases and the persistent disease in deterministic model may eliminate ultimately due to the effect of large noise. Finally, numerical simulations are performed to illustrate the theoretical results.

A safe and molecular-tagged Brucella canis ghosts confers protection against virulent challenge in mice

Canine brucellosis, caused by Brucella canis, is a persistent infectious reproductive disease in dogs. The absence of effective treatment to the intracellular pathogen and the irreversible consequence of infection makes the need of a specific vaccine urgent. Bacterial ghosts (BGs) are the empty envelopes of bacteria with no genome content inside, which emerge as a proper vaccine candidate due to its intact outer antigen. It is generally derived from a genetically engineered strain, through the expression of Bacteriophage phiX174 lysis E gene upon induction. In this study, we combined the homologous recombination (HR) and bacterial ghost technologies, generating a genetically stable B. canis ghost strain which bears no drug resistance gene. When the ghost strain grows to OD600 of 0.6, 100% inactivation can be achieved under 42°C in 60h. The resultant BGs showed guaranteed safety and comparable immunogenicity to a live vaccine. The bacterial B0419 protein was depleted during HR process, which is subsequently proved to work as a molecular tag in distinguishing natural infection and BGs immunization through ELISA. Additionally, the BGs also conferred protection against B. canis RM6/66 and B. melitensis 16M. Therefore, the application of current BGs as a vaccine candidate and the corresponding serological diagnostic approach may provide better B. canis prevention strategy.