Biology subjects

Mukundan, H.

Publications and source records attributed to Mukundan, H..

4 recordsLinked to original sources

bioRxiv2022

Serum lipoproteins and lipoarabinomannan suppress the inflammatory response induced by the mycolactone toxin

Mycobacterium ulcerans is the causative agent of the chronic and debilitating neglected tropical disease Buruli ulcer (BU) which mostly affects children. The early detection and treatment of M. ulcerans infections can significantly minimize life-long disability resulting from surgical intervention. However, the disease is characterized by relatively few systemic systems as a result of complex host-pathogen interactions that have yet to be fully characterized, which has limited the development of both diagnostic and therapeutic approaches to treat BU. In this work, we study the interactions of the host immune system with two principle M. ulcerans virulence factors: mycolactone, an amphiphilic macrolide toxin, and lipoarabinomannan (LAM), a cell wall component of most mycobacterial pathogens. We observe that human lipoproteins have a profound effect on the interaction of both mycolactone and LAM with the immune system. Individually, both molecules are pro-inflammatory in the absence of serum and immunosuppressive in the presence of serum. When combined, mycolactone and LAM are immunosuppressive regardless of serum conditions. We also show that Toll-like receptor 2 (TLR2), a macrophage pathogen pattern recognition receptor, is critical for LAM immune stimulation but aids in mycolactone immunosuppression. These findings are a first step towards unraveling mycolactone-mediated immunosuppression during BU disease and may facilitate the development of effective diagnostics and therapeutics in the future. Author SummaryBuruli ulcer (BU) is a neglected tropical disease caused by the pathogen Mycobacterium ulcerans. The principal virulence factors associated with it are the macrolide toxin mycolactone and the major cell wall component lipoarabinomannan (LAM). Here, we examine the impact of the amphiphilic biochemistry of mycolactone and LAM on their interaction with the human immune system. We show that both mycolactone and LAM associate with serum lipoproteins, and that this association is critical for the immune evasion seen in early-stage M. ulcerans infections. In the absence of serum, mycolactone is pro-inflammatory. Immunosuppression occurs only in the presence of human serum lipoproteins. In the presence of LAM, mycolactone is immunosuppressive, regardless of serum conditions. Immunosuppression is a hallmark of BU disease, and understanding the mechanisms of this immunosuppression can support the development of effective diagnostic and therapeutic strategies.

microbiology↗

bioRxiv2020

Interaction of Amphiphilic Lipoarabinomannan with Host Carrier Lipoproteins in Tuberculosis Patients: Implications for Blood-based Diagnostics.

Lipoarabinomannan (LAM), an amphiphilic lipoglycan of the Mycobacterium tuberculosis cell wall, is a diagnostic target for tuberculosis. Previous work from our laboratory and others suggests that LAM is associated with host serum lipoproteins, which may in turn have implications for diagnostic assays. Our team has developed two serum assays for amphiphile detection: lipoprotein capture and membrane insertion. The lipoprotein capture assay relies on capture of the host lipoproteins, exploiting the biological association of host lipoprotein with microbial amphiphilic biomarkers to "concentrate" LAM. In contrast, the membrane insertion assay is independent of the association between pathogen amphiphiles and host lipoprotein association, and directly captures LAM based on its thermodynamic propensity for association with a supported lipid membrane, which forms the functional surface of an optical biosensor. In this manuscript, we explored the use of these assays for the detection of LAM in sera from adults whose tuberculosis status had been well-characterized using conventional microbiological tests, and endemic controls. Using the lipoprotein capture assay, LAM signal/noise ratios were >1.0 in 29/35 (83%) individuals with culture-confirmed active tuberculosis, 8/13 (62%) individuals with tuberculosis symptoms but no positive culture for M. tuberculosis, and 0/6 (0%) symptom-free endemic controls. To evaluate serum LAM levels without bias associated with potential differences in circulating host lipoprotein concentrations between individuals, we subsequently processed available samples to liberate LAM from associated host lipoprotein assemblies followed by direct detection of the pathogen biomarker using the membrane insertion approach. Using the membrane insertion assay, signal/noise for detection of serum LAM was greater than that observed using the lipoprotein capture method for culture-confirmed TB patients (6/6), yet remained negative for controls (2/2). Taken together, these results suggest that detection of serum LAM is a promising TB diagnostic approach. Further work is required to optimize assay performance and to decipher the implications of LAM/host lipoprotein associations for diagnostic assay performance and TB pathogenesis.

microbiology↗

bioRxiv2019

A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern

INTRODUCTIONEpidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible and actionable the information produced by these studies was.\n\nMETHODSTo improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE and grey literature review, we identified studies that forecasted, predicted or simulated ecological or epidemiological phenomenon related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility and clarity by independent reviewers.\n\nRESULTS2034 studies were identified, of which n = 73 met eligibility criteria. Spatial spread, R0 (basic reproductive number) and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barre Syndrome burden (4%), sexual transmission risk (4%) and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%) and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions and 54% provided sufficient methodological detail allowing complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median 119 days sooner than journal publication dates, they were used in only 30% of studies.\n\nCONCLUSIONSMany ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates that there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response, it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics and pandemics.\n\nAuthor summaryResearchers published many studies which sought to predict and forecast important features of Zika virus (ZIKV) infections and their spread during the 2016-2017 ZIKV pandemic. We conducted a comprehensive review of such ZIKV prediction studies and evaluated their aims, the data sources they used, which methods were used, how timely they were published, and whether they provided sufficient information to be used or reproduced by others. Of the 73 studies evaluated, we found that the accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates that there is substantial room for improvement. We identified that the release of study findings before formal journal publication ( pre-prints) increased the timeliness of Zika prediction studies, but note they were infrequently used during this public health emergency. Addressing these areas can improve our understanding of Zika and other outbreaks and ensure that forecasts can inform preparedness and response to future outbreaks, epidemics and pandemics.

epidemiology↗

bioRxiv2018

Point of Care Diagnostic Deployment and Targeted Treatment of Antimicrobial Resistant Non-Typhoidal Salmonella: a New Mathematical Model and Cost-Benefit Analysis

Invasive non-typhoidal Salmonella (NTS) is among the leading causes of blood stream infections in sub-Saharan Africa and other developing regions, especially among pediatric populations. Invasive NTS can be difficult to treat and have high case-fatality rates, in part due to emergence of strains resistant to broad-spectrum antibiotics. Furthermore, improper treatment contributes to increased antibiotic resistance and death. Point of care (POC) diagnostic tests that rapidly identify invasive NTS infection, and differentiate between resistant and non-resistant strains, may greatly improve patient outcomes and decrease resistance at the community level. Here we present for the first time a model for NTS dynamics in high risk populations that can analyze the potential advantages and disadvantages of four strategies involving POC diagnostic deployment, and the resulting impact on antimicrobial treatment for patients. Our analysis strongly supports the use of POC diagnostics coupled with targeted antibiotic use for patients upon arrival in the clinic for optimal patient and public health outcomes. We show that even the use of imperfect POC diagnostics can significantly reduce total costs and number of deaths, provided that the diagnostic gives results quickly enough that patients are likely to return or stay to receive targeted treatment.

epidemiology↗