183 research outputs found
Implications of drug-induced phenotypical resistance : is isoniazid radicalizing M. tuberculosis?
Funding: This study was funded by a grant from the British Society for Antimicrobial Chemotherapy (GA2015-172R).Background: Treatment duration is long and does not guarantee eradication of infection. Shorter treatment regimens are a critical research objective to improve uptake and reduce the risk of relapse and bacterial resistance. The explanation for the need to continue treatment after patients are culture negative remains elusive. We have previously shown that the presence of lipid inclusions in mycobacterial cells is associated with an increase in antibiotic resistance. Aim: We investigate the bactericidal effect of isoniazid and rifampicin and the expression of lipid inclusions and the associated phenotypic antibiotic resistance to a range of anti-tuberculosis agents in current use. Methods: Antibiotic killing effect for both M. tuberculosis and M. komossense were investigated by both hollow fiber bioreactor (HFS) studies and static time kill curve (STKC) experiments. Following STKC cultures were stained with resazurin, Sytox green and Nile red to establish their live/dead (resazurin positive/Sytox positive) and lipid inclusion status respectively. In addition, M. komossense was studied in the hollow fiber bioreactor model (HFS) and exposed to isoniazid (H) and rifampicin (R). The MIC of current antituberculosis agents for cells from the treated hollow fiber experiments were tested. Results: Antibiotic killing was similar for both species. For M. komossense; isoniazid was ineffective at the established MIC (1mg/L) in the hollow fiber bioreactor but rifampicin reduced the viable count rapidly at MIC (0.4mg/L). When the two drugs were combined at their respective MICs the killing effect was significant and greater than separately. Cells exposed to isoniazid (1x & 9x MIC) for 168 hours showed considerable numbers of recoverable viable cells when compared with a combination of 1x MIC R & H where there were no viable cells detectable. For both drugs the number of lipid body positive cells increased over time and this effect was most pronounced for isoniazid and was associated with phenotypic resistance to multiple anti-tuberculosis drugs. Conclusion: Our results showed that isoniazid is a potent stimulator of lipid body accumulation, culture persistence, and phenotypic resistance to multiple anti-tuberculosis drugs. These findings emphasise the importance of understanding mechanisms of drug-drug interactions and phenotypic resistance in regimen building.Publisher PDFPeer reviewe
Rapid determination of antimicrobial susceptibility of Gram-negative bacteria from clinical blood cultures using a scattered light integrated collection (SLIC) device
Funding: This work was funded by the University of St Andrews.Background A bloodstream infection (BSI) presents a complex and serious health problem, a problem that is being exacer- bated by increasing antimicrobial resistance (AMR). Gap statement The current turnaround times (TATs) for most antimicrobial susceptibility testing (AST) methods offer results retrospective of treatment decisions, and this limits the impact AST can have on antibiotic prescribing and patient care. Progress must be made towards rapid BSI diagnosis and AST to improve antimicrobial stewardship and reduce preventable deaths from BSIs. To support the successful implementation of rapid AST (rAST) in hospital settings, a rAST method that is affordable, is sustainable and offers comprehensive AMR detection is needed. Aim To evaluate a scattered light-integrated collection (SLIC) device against standard of care (SOC) to determine whether SLIC could accelerate the current TATs with actionable, accurate rAST results for Gram-negative BSIs. Methods Positive blood cultures from a tertiary referral hospital were studied prospectively. Flagged positive Gram-negative blood cultures were confirmed by Gram staining and analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Vitek 2, disc diffusion (ceftriaxone susceptibility only) and an SLIC device. Susceptibility to a panel of five antibiotics, as defined by European Committee on Antimicrobial Susceptibility Testing breakpoints, was examined using SLIC. Results A total of 505 bacterial–antimicrobial combinations were analysed. A categorical agreement of 95.5 % (482/505) was achieved between SLIC and SOC. The 23 discrepancies that occurred were further investigated by the broth microdilution method, with 10 AST results in agreement with SLIC and 13 in agreement with SOC. The mean time for AST was 10.53±0.46 h and 1.94±0.02 h for Vitek 2 and SLIC, respectively. SLIC saved 23.96±1.47 h from positive blood culture to AST result. Conclusion SLIC has the capacity to provide accurate AST 1 day earlier from flagged positive blood cultures than SOC. This significant time saving could accelerate time to optimal antimicrobial therapy, improving antimicrobial stewardship and man- agement of BSIs.Peer reviewe
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 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
Systematic assessment of clinical and bacteriological markers for tuberculosis reveals discordance and inaccuracy of symptom-based diagnosis for treatment response monitoring
This work was supported by Commonwealth PhD studentship award to Dr Bariki Mtafya (Award number: TZS-2016-718) at University of St Andrews and European and Developing Countries Clinical Trials Partnership through TWENDE project (grant number; TWENDE-EDCTP-CSA-2014-283) and PanACEA II (grant number; 97118-PanACEA-TRIA.2015.1102) awarded to Professor Stephen Gillespie and Dr Wilber Sabiiti at the University of St Andrews, UK.Background : Clinical symptoms are the benchmark of tuberculosis (TB) diagnosis and monitoring of treatment response but is not clear how they relate to TB bacteriology, particularly the novel tuberculosis Molecular Bacterial Load Assay (TB-MBLA). Methods : Presumptive cases were bacteriologically confirmed for TB and assessed for symptom and bacteriological resolution using smear microscopy (SM), culture and TB-MBLA over 6-month treatment course. Kaplan Meier and Kappa statistics were used to test relationship between symptom- and bacteriological-positivity. Results : A cohort of 46 bacteriologically confirmed TB cases were analysed for treatment response over a six-month treatment course. Pre-treatment symptom and bacteriological positivity concurred in over 70% of the cases. This agreement was lost in over 50% of cases whose chest pain, night sweat, and loss of appetite had resolved by week 2 of treatment. Cough resolved at a 3.2% rate weekly and was 0.3% slower than the combined bacteriological (average of MGIT and TB-MBLA positivity) resolution rate, 3.5% per week. Drop in TB-MBLA positivity reflected fall in bacillary load, 5.7±1.3- at baseline to 0.30±1.0- log10 eCFU/mL at month 6, and closer to cough resolution than other bacteriological measures, accounting for the only one bacteriologically positive case out of seven still coughing at month 6. Low baseline bacillary load patients were more likely to be bacteriologically negative, HR 5.6, p=0.003 and, HR 3.2, p=0.014 by month-2 and 6 of treatment respectively. Conclusion : The probability of clinical symptoms reflecting bacteriological positivity weakens as patient progresses on anti-TB therapy, making symptom-based diagnosis a less reliable marker of treatment response.Publisher PDFPeer reviewe
Limited role of culture conversion for decision-making in individual patient care and for advancing novel regimens to confirmatory clinical trials
Supported by the European and Developing Country Clinical Trials Partnership (grant IP.2007.32011.011) and the Global Alliance for TB Drug Development, with support from the Bill & Melinda Gates Foundation, US Agency for International Development, UK Department for International Development, Directorate-General for International Cooperation of the Netherlands, Irish Aid and Australian Department of Foreign Affairs and Trade.Background Despite recent increased clinical trials activity, no regimen has proved able to replace the standard 6-month regimen for drug-sensitive tuberculosis. Understanding the relationship between microbiological markers measured during treatment and long-term clinical outcomes is critical to evaluate their usefulness for decision-making for both individual patient care and for advancing novel regimens into time-consuming and expensive pivotal phase III trials. Methods Using data from the randomized controlled phase III trial REMoxTB, we evaluated sputum-based markers of speed of clearance of bacilli: time to smear negative status; time to culture negative status on LJ or in MGIT; daily rate of change of log10(TTP) to day 56; and smear or culture results at weeks 6, 8 or 12; as individual- and trial-level surrogate endpoints for long-term clinical outcome. Results Time to culture negative status on LJ or in MGIT, time to smear negative status and daily rate of change in log10(TTP) were each independent predictors of clinical outcome, adjusted for treatment (p <0.001). However, discrimination between low and high risk patients, as measured by the c-statistic, was modest and not much higher than the reference model adjusted for BMI, history of smoking, HIV status, cavitation, gender and MGIT TTP. Conclusions Culture conversion during treatment for tuberculosis, however measured, has only a limited role in decision-making for advancing regimens into phase III trials or in predicting the outcome of treatment for individual patients. REMoxTB ClinicalTrials.gov number: NCT00864383.Publisher PDFPeer reviewe
Limited role of culture conversion for decision-making in individual patient care and for advancing novel regimens to confirmatory clinical trials
Supported by the European and Developing Country Clinical Trials Partnership (grant IP.2007.32011.011) and the Global Alliance for TB Drug Development, with support from the Bill & Melinda Gates Foundation, US Agency for International Development, UK Department for International Development, Directorate-General for International Cooperation of the Netherlands, Irish Aid and Australian Department of Foreign Affairs and Trade.Background Despite recent increased clinical trials activity, no regimen has proved able to replace the standard 6-month regimen for drug-sensitive tuberculosis. Understanding the relationship between microbiological markers measured during treatment and long-term clinical outcomes is critical to evaluate their usefulness for decision-making for both individual patient care and for advancing novel regimens into time-consuming and expensive pivotal phase III trials. Methods Using data from the randomized controlled phase III trial REMoxTB, we evaluated sputum-based markers of speed of clearance of bacilli: time to smear negative status; time to culture negative status on LJ or in MGIT; daily rate of change of log10(TTP) to day 56; and smear or culture results at weeks 6, 8 or 12; as individual- and trial-level surrogate endpoints for long-term clinical outcome. Results Time to culture negative status on LJ or in MGIT, time to smear negative status and daily rate of change in log10(TTP) were each independent predictors of clinical outcome, adjusted for treatment (p <0.001). However, discrimination between low and high risk patients, as measured by the c-statistic, was modest and not much higher than the reference model adjusted for BMI, history of smoking, HIV status, cavitation, gender and MGIT TTP. Conclusions Culture conversion during treatment for tuberculosis, however measured, has only a limited role in decision-making for advancing regimens into phase III trials or in predicting the outcome of treatment for individual patients. REMoxTB ClinicalTrials.gov number: NCT00864383.Publisher PDFPeer reviewe
Reduction of blood C-reactive protein concentration complements the resolution of sputum bacillary load in patients on anti-tuberculosis therapy
Funding: This study was conducted under the PanACEA Biomarkers Expansion (PanBIOME) programme and the establishment of Maputo Tuberculosis Trial Unit (MaTuTU Project) which was funded in parts through the European and Developing Countries Clinical Trials Partnership (EDCTP), PZA-study and Federal Ministry of Education and Research (BMBF), Germany.Background: Tuberculosis (TB) is a difficult-to-treat disease requiring the combination of four antibiotics for a minimum of 6 months. Rapid and quantitative biomarkers to monitor treatment response are urgently needed for individual patient management and clinical trials. C-reactive protein (CRP) is often used clinically as a rapid marker of inflammation caused by infection. We assessed the relationship of TB bacillary load and CRP as biomarkers of treatment response. Methods: Xpert MTB/RIF-confirmed pulmonary TB cases were enrolled for treatment response assessment in Mozambique. Treatment response was measured using the Tuberculosis Molecular Bacterial Load Assay (TB-MBLA) in comparison with standard-of-care Mycobacterium Growth Indicator Tube (MGIT) culture at baseline and at weeks 1, 2, 4, 8, 12, 17, and 26 of treatment. Blood CRP concentration was measured at baseline, week 8, and week 26. Treatment response was defined as increase in MGIT culture time to positivity (TTP), and reduction in TB-MBLA-measured bacillary load and blood CRP concentration. Results: Out of the 81 screened presumptive TB cases, 69 were enrolled for 6-month treatment follow-up resulting in 94% treatment completion rate. Four participants did not complete TB treatment and 22 participants had missing CRP or TB-MBLA results and were excluded from TB-MBLA-CRP analysis. The remaining 43 participants—median age, 31 years old [interquartile range (IQR): 18–56]; 70% (30/43) male; and 70% (30/43) infected with HIV—were considered for analysis. Culture TTP and bacillary load were inversely correlated, Spearman’s r = −0.67, p < 0.0001. Resolution of sputum bacillary load concurred with reduction of blood CRP, r = 0.70, p < 0.0001. At baseline, bacillary load had a median (IQR) of 6.4 (5.5–7.2), which reduced to 2.4 (0.0–2.9) and 0.0 (0.0–0.0) log10 CFU/ml at months 2 and 6 of treatment, respectively. Correspondingly, blood CRP reduced from 1.9 (1.6–2.1) at baseline to 1.3 (0.9–1.7) and 0.4 (0.1–0.8) log10 mg/dl at months 2 and 6 of treatment, respectively. CRP reduction trialed bacteriological resolution at a rate of −0.06 log10 mg/dl compared to a bacillary load of 0.23 log10 CFU/ml per week. Consequently, 14 (33%) and 37 (88%) patients had reduced CRP to normal concentration and bacillary load to zero by the end of treatment, respectively. Pre-treatment CRP concentration and bacillary load, and resolution during treatment were slightly lower in HIV co-infected patients but not significantly different from HIV-uninfected TB patients. Conclusion: TB-MBLA-measured bacillary load and blood CRP complement each other in response to anti-TB therapy. Slow CRP reduction probably reflects residual TB bacilli in the lung not expectorated in sputum. Combining both measures can improve the accuracy of these biomarkers for monitoring TB treatment response and shorten turnaround time since the results of both assays could be available in 24 h.Publisher PDFPeer reviewe
Use of a molecular bacterial load assay to distinguish between active TB and post-TB lung disease
Authors acknowledge financial support from the EDCTP2 programme supported by the European Union project (grant #: TMA2016SF-1463-REMODELTZ) and DELTAS Africa Initiative (Afrique One-ASPIRE /DEL-15-008). The Afrique One-ASPIRE is funded by a consortium of donors including the African Academy of Sciences, Alliance for Accelerating Excellence in Science in Africa, the New Partnership for Africa's Development Planning and Coordinating Agency, the Wellcome Trust (107753/A/15/Z), and the UK Government. PMM, SKH and SGM were also supported by NIH U01AI115594.Publisher PDFPeer reviewe
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