Project sanitarium:playing tuberculosis to its end game

Interdisciplinary and collaborative projects between industry and academia provide exceptional opportunities for learning. Project Sanitarium is a serious game for Windows PC and Tablet which aims to embed learning about tuberculosis (TB) through the player taking on the role of a doctor and solving cases across the globe. The project developed as a collaboration between staff and undergraduate students at the School of Arts, Media and Computer Games at Abertay University working with academics and researchers from the Infection Group at the University of St Andrews. The project also engaged industry partners Microsoft and DeltaDNA. The project aimed to educate students through a workplace simulation pedagogical model, encourage public engagement at events and through news coverage and lastly to prototype whether games could be used to simulate a virtual clinical trial. The project was embedded in the Abertay undergraduate programme where students are presented with real world problems to solve through design and technology. The result was a serious game prototype that utilized game design techniques and technology to demystify and educate players about the diagnosis and treatment of one of the world’s oldest and deadliest diseases, TB. Project Sanitarium aims to not only educate the player, but allows the player to become a part of a simulated drug trial that could potentially help create new treatments in the fight against TB. The game incorporates a mathematical model that is based on data from real-world drug trials. The interdisciplinary pedagogical model provides undergraduates with workplace simulation, wider industry collaboration and access to academic expertise to solve challenging and complex problems

A simple label-free method reveals bacterial growth dynamics and antibiotic action in real-time

Funding: The authors gratefully acknowledge the financial support of Scottish Enterprise, NESTA Longitude Prize and the University of St Andrews.Understanding the response of bacteria to environmental stress is hampered by the relative insensitivity of methods to detect growth. This means studies of antibiotic resistance and other physiological methods often take 24 h or longer. We developed and tested a scattered light and detection system (SLIC) to address this challenge, establishing the limit of detection, and time to positive detection of the growth of small inocula. We compared the light-scattering of bacteria grown in varying high and low nutrient liquid medium and the growth dynamics of two closely related organisms. Scattering data was modelled using Gompertz and Broken Stick equations. Bacteria were also exposed meropenem, gentamicin and cefoxitin at a range of concentrations and light scattering of the liquid culture was captured in real-time. We established the limit of detection for SLIC to be between 10 and 100 cfu mL−1 in a volume of 1–2 mL. Quantitative measurement of the different nutrient effects on bacteria were obtained in less than four hours and it was possible to distinguish differences in the growth dynamics of Klebsiella pneumoniae 1705 possessing the BlaKPC betalactamase vs. strain 1706 very rapidly. There was a dose dependent difference in the speed of action of each antibiotic tested at supra-MIC concentrations. The lethal effect of gentamicin and lytic effect of meropenem, and slow bactericidal effect of cefoxitin were demonstrated in real time. Significantly, strains that were sensitive to antibiotics could be identified in seconds. This research demonstrates the critical importance of improving the sensitivity of bacterial detection. This results in more rapid assessment of susceptibility and the ability to capture a wealth of data on the growth dynamics of bacteria. The rapid rate at which killing occurs at supra-MIC concentrations, an important finding that needs to be incorporated into pharmacokinetic and pharmacodynamic models. Importantly, enhanced sensitivity of bacterial detection opens the possibility of susceptibility results being reportable clinically in a few minutes, as we have demonstrated.Publisher PDFPeer reviewe

A Hybrid Individual-based Mathematical Model to study Bladder Infections

Funding: RB was supported by a fellowship funded by the Medical Research Council, MR/P014704/1, and also acknowledges funding from the Academy of Medical Sciences (London), the Wellcome Trust (London), the UK Government Department of Business, Energy and Industrial Strategy (London), the British Heart Foundation (London), and the Global Challenges Research Fund (Swindon, UK; grant number SBF003\1052). TL gratefully acknowledges support from the Italian Ministry of University and Research (MUR) through the grant Dipartimenti di Eccellenza 2018-2022 (Project no. E11G18000350001) and the PRIN 2020 project (No. 2020JLWP23) Integrated Mathematical Approaches to Socio-Epidemiological Dynamics (CUP: E15F21005420006).Introduction : Bladder infections are common, affecting millions each year, and are often recurrent problems. Methods : We have developed a spatial mathematical framework consisting of a hybrid individual-based model to simulate these infections in order to understand more about the bacterial mechanisms and immune dynamics. We integrate a varying bacterial replication rate and model bacterial shedding as an immune mechanism. Results : We investigate the effect that varying the initial bacterial load has on infection outcome, where we find that higher bacterial burden leads to poorer outcomes, but also find that only a single bacterium is needed to establish infection in some cases. We also simulate an immunocompromised environment, confirming the intuitive result that bacterial spread typically progresses at a higher rate. Conclusions : With future model developments, this framework is capable of providing new clinical insight into bladder infections.Publisher PDFPeer reviewe

A hybrid individual-based mathematical model to study bladder infections

RB was supported by a fellowship funded by the Medical Research Council, MR/P014704/1, and also acknowledges funding from the Academy of Medical Sciences (London), the Wellcome Trust (London), the UK Government Department of Business, Energy and Industrial Strategy (London), the British Heart Foundation (London), and the Global Challenges Research Fund (Swindon, UK; grant number SBF003\1052). TL gratefully acknowledges support from the Italian Ministry of University and Research (MUR) through the grant Dipartimenti di Eccellenza 2018-2022 (Project no. E11G18000350001) and the PRIN 2020 project (No. 2020JLWP23) Integrated Mathematical Approaches to Socio-Epidemiological Dynamics (CUP: E15F21005420006).Introduction: Bladder infections are common, affecting millions each year, and are often recurrent problems. Methods: We have developed a spatial mathematical framework consisting of a hybrid individual-based model to simulate these infections in order to understand more about the bacterial mechanisms and immune dynamics. We integrate a varying bacterial replication rate and model bacterial shedding as an immune mechanism. Results: We investigate the effect that varying the initial bacterial load has on infection outcome, where we find that higher bacterial burden leads to poorer outcomes, but also find that only a single bacterium is needed to establish infection in some cases. We also simulate an immunocompromised environment, confirming the intuitive result that bacterial spread typically progresses at a higher rate. Conclusions: With future model developments, this framework is capable of providing new clinical insight into bladder infections.Publisher PDFPeer reviewe

Evolution of CD8(+) T Cell Responses after Acute PARV4 Infection

PARV4 is a small DNA human virus that is strongly associated with hepatitis C virus (HCV) and HIV infections. The immunologic control of acute PARV4 infection has not been previously described. We define the acute onset of PARV4 infection and the characteristics of the acute-phase and memory immune responses to PARV4 in a group of HCV- and HIV-negative, active intravenous drug users. Ninety-eight individuals at risk of blood-borne infections were tested for PARV4 IgG. Gamma interferon enzyme-linked immunosorbent spot assays, intracellular cytokine staining, and a tetrameric HLA-A2-peptide complex were used to define the T cell populations responding to PARV4 peptides in those individuals who acquired infection during the study. Thirty-five individuals were found to be PARV4 seropositive at the end of the study, eight of whose baseline samples were found to be seronegative. Persistent and functional T cell responses were detected in the acute infection phase. These responses had an active, mature, and cytotoxic phenotype and were maintained several years after infection. Thus, PARV4 infection is common in individuals exposed to blood-borne infections, independent of their HCV or HIV status. Since PARV4 elicits strong, broad, and persistent T cell responses, understanding of the processes responsible may prove useful for future vaccine design

A spatially heterogeneous network-based metapopulation software model applied to the simulation of a pulmonary tuberculosis infection

This work was supported by the PreDiCT-TB consortium (IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.Tuberculosis (TB) is an ancient disease that, although curable, still accounts for over 1 million deaths worldwide. Shortening treatment time is an important area of research but is hampered by the lack of models that mimic the full range of human pathology. TB shows distinct localisations during different stages of infection, the reasons for which are poorly understood. Greater understanding of how heterogeneity within the human lung influences disease progression may hold the key to improving treatment efficiency and reducing treatment times. In this work, we present a novel in silico software model which uses a networked metapopulation incorporating both spatial heterogeneity and dissemination possibilities to simulate a TB infection over the whole lung and associated lymphatics. The entire population of bacteria and immune cells is split into a network of patches: members interact within patches and are able to move between them. Patches and edges of the lung network include their own environmental attributes which influence the dynamics of interactions between the members of the subpopulations of the patches and the translocation of members along edges. In this work, we detail the initial findings of a whole-organ model that incorporates distinct spatial heterogeneity features which are not present in standard differential equation approaches to tuberculosis modelling. We show that the inclusion of heterogeneity within the lung landscape when modelling TB disease progression has significant outcomes on the bacterial load present: a greater differential of oxygen, perfusion and ventilation between the apices and the basal regions of the lungs creates micro-environments at the apex that are more preferential for bacteria, due to increased oxygen availability and reduced immune activity, leading to a greater overall bacterial load present once latency is established. These findings suggest that further whole-organ modelling incorporating more sophisticated heterogeneities within the environment and complex lung topologies will provide more insight into the environments in which TB bacteria persist and thus help develop new treatments which are factored towards these environmental conditions.Publisher PDFPeer reviewe

Parvovirus 4 Infection and Clinical Outcome in High-Risk Populations

Parvovirus 4 (PARV4) is a DNA virus frequently associated with human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections, but its clinical significance is unknown. We studied the prevalence of PARV4 antibodies in 2 cohorts of HIV- and HCV-infected individuals (n=469) and the correlations with disease status. We found that PARV4 infection frequently occurred in individuals exposed to bloodborne viruses (95% in HCV-HIV coinfected intravenous drug users [IDUs]). There were no correlations between PARV4 serostatus and HCV outcomes. There was, however, a significant association with early HIV-related symptoms, although because this was tightly linked to both HCV status and clinical group (IDU), the specific role of PARV4 is not yet clea

Parvovirus 4 Infection and Clinical Outcome in High-Risk Populations

Parvovirus 4 (PARV4) is a DNA virus frequently associated with human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections, but its clinical significance is unknown. We studied the prevalence of PARV4 antibodies in 2 cohorts of HIV- and HCV-infected individuals (n = 469) and the correlations with disease status. We found that PARV4 infection frequently occurred in individuals exposed to bloodborne viruses (95% in HCV-HIV coinfected intravenous drug users [IDUs]). There were no correlations between PARV4 serostatus and HCV outcomes. There was, however, a significant association with early HIV-related symptoms, although because this was tightly linked to both HCV status and clinical group (IDU), the specific role of PARV4 is not yet clear

Modelling the effects of environmental heterogeneity within the lung on the tuberculosis life-cycle

Funding: This work was supported by the Medical Research Council [grant number MR/P014704/1] and the PreDiCT-TB consortium (IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EF-PIA companies’ in kind contribution.Progress in shortening the duration of tuberculosis (TB) treatment is hampered by the lack of a predictive model that accurately reflects the diverse environment within the lung. This is important as TB has been shown to produce distinct localisations to different areas of the lung during different disease stages, with the environmental heterogeneity within the lung of factors such as air ventilation, blood perfusion and oxygen tension believed to contribute to the apical localisation witnessed during the post-primary form of the disease. Building upon our previous model of environmental lung heterogeneity, we present a networked metapopulation model that simulates TB across the whole lung, incorporating these notions of environmental heterogeneity across the whole TB life-cycle to show how different stages of the disease are influenced by different environmental and immunological factors. The alveolar tissue in the lung is divided into distinct patches, with each patch representing a portion of the total tissue and containing environmental attributes that reflect the internal conditions at that location. We include populations of bacteria and immune cells in various states, and events are included which determine how the members of the model interact with each other and the environment. By allowing some of these events to be dependent on environmental attributes, we create a set of heterogeneous dynamics, whereby the location of the tissue within the lung determines the disease pathological events that occur there. Our results show that the environmental heterogeneity within the lung is a plausible driving force behind the apical localisation during post-primary disease. After initial infection, bacterial levels will grow in the initial infection location at the base of the lung until an adaptive immune response is initiated. During this period, bacteria are able to disseminate and create new lesions throughout the lung. During the latent stage, the lesions that are situated towards the apex are the largest in size, and once a post-primary immune-suppressing event occurs, it is the uppermost lesions that reach the highest levels of bacterial proliferation. Our sensitivity analysis also shows that it is the differential in blood perfusion, causing reduced immune activity towards the apex, which has the biggest influence of disease outputs.Publisher PDFPeer reviewe