Blar i forfatter Artikler, rapporter og annet (farmasi) "Abel zur Wiesch, Pia"

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    • All non-adherence is equal, but is some more equal than others? TB in the digital era 

      Stagg, Helen; Flook, Mary; Martinecz, Antal; Kielmann, Karina; Abel zur Wiesch, Pia; Karat, Aaron; Lipman, Marc; Sloan, Derek; Walker, Elizabeth; Fielding, Katherine L (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-02)
      Adherence to treatment for tuberculosis (TB) has been a concern for many decades, resulting in the World Health Organization's recommendation of the direct observation of treatment in the 1990s. Recent advances in digital adherence technologies (DATs) have renewed discussion on how to best address nonadherence, as well as offering important information on dose-by-dose adherence patterns and their ...

    • Deciphering the landscape of host barriers to Listeria monocytogenes infection 

      Zhang, Ting; Abel, Sören; Abel zur Wiesch, Pia; Sasabe, Jumpei; Davis, Brigid M.; Higgins, Darren E. (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-05-30)
      <i>Listeria monocytogenes</i> is a common food-borne pathogen that can disseminate from the intestine and infect multiple organs. Here, we used sequence tag-based analysis of microbial populations (STAMP) to investigate <i>L. monocytogenes</i> population dynamics during infection. We created a genetically barcoded library of murinized <i>L. monocytogenes</i> and then used deep sequencing to track ...

    • Drug-target binding quantitatively predicts optimal antibiotic dose levels in quinolones 

      Clarelli, Fabrizio; Palmer, Adam; Singh, Bhupender; Storflor, Merete; Lauksund, Silje; Cohen, Ted; Abel, Sören; Abel zur Wiesch, Pia (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-08-14)
      Antibiotic resistance is rising and we urgently need to gain a better quantitative understanding of how antibiotics act, which in turn would also speed up the development of new antibiotics. Here, we describe a computational model (COMBAT-COmputational Model of Bacterial Antibiotic Target-binding) that can quantitatively predict antibiotic dose-response relationships. Our goal is dual: We address a ...

    • Estimating treatment prolongation for persistent infections 

      Martinecz, Antal; Abel zur Wiesch, Pia (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-08-09)
      Treatment of infectious diseases is often long and requires patients to take drugs even after they have seemingly recovered. This is because of a phenomenon called persistence, which allows small fractions of the bacterial population to survive treatment despite being genetically susceptible. The surviving subpopulation is often below detection limit and therefore is empirically inaccessible but can ...

    • The Infectious Dose Shapes Vibrio Cholerae Within-Host Dynamics 

      Gillman, Aaron Nicholas; Mahmutovic, Anel; Abel zur Wiesch, Pia; Abel, Sören (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-07)
      During infection, the rates of pathogen replication, death, and migration affect disease progression, dissemination, transmission, and resistance evolution. Here, we follow the population dynamics of Vibrio cholerae in a mouse model by labeling individual bacteria with one of >500 unique, fitness-neutral genomic tags. Using the changes in tag frequencies and CFU numbers, we inform a mathematical ...

    • Mechanisms of antibiotic action shape the fitness landscapes of resistance mutations 

      Hemez, Colin; Clarelli, Fabrizio; Palmer, Adam C.; Bleis, Christina; Abel, Sören; Chindelevitch, Leonid; Cohen, Theodore; Abel zur Wiesch, Pia (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-24)
      Antibiotic-resistant pathogens are a major public health threat. A deeper understanding of how an antibiotic’s mechanism of action influences the emergence of resistance would aid in the design of new drugs and help to preserve the effectiveness of existing ones. To this end, we developed a model that links bacterial population dynamics with antibiotic-target binding kinetics. Our approach allows ...

    • Multi-scale modeling of drug binding kinetics to predict drug efficacy 

      Clarelli, Fabrizio; Liang, Jingyi; Martinecz, Antal; Heiland, Ines; Abel zur Wiesch, Pia (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-11-25)
      Optimizing drug therapies for any disease requires a solid understanding of pharmacokinetics (the drug concentration at a given time point in different body compartments) and pharmacodynamics (the effect a drug has at a given concentration). Mathematical models are frequently used to infer drug concentrations over time based on infrequent sampling and/or in inaccessible body compartments. Models are ...

    • Perspectives for systems biology in the management of tuberculosis 

      Kontsevaya, Irina; Lange, Christoph; Comella-Del-barrio, Patricia; Coarfa, Cristian; Dinardo, Andrew R.; Gillespie, Stephen H.; Hauptmann, Matthias; Leschczyk, Christoph; Mandalakas, Anna M.; Martinecz, Antal; Merker, Matthias; Niemann, Stefan; Reimann, Maja; Rzhepishevska, Olena; Schaible, Ulrich E.; Scheu, Katrin M.; Schurr, Erwin; Abel zur Wiesch, Pia; Heyckendorf, Jan (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-05-25)
      Standardised management of tuberculosis may soon be replaced by individualised, precision medicineguided therapies informed with knowledge provided by the field of systems biology. Systems biology is a rapidly expanding field of computational and mathematical analysis and modelling of complex biological systems that can provide insights into mechanisms underlying tuberculosis, identify novel ...

    • Quantifying the impact of treatment history on plasmid-mediated resistance evolution in human gut microbiota 

      Tepekule, Burcu; Abel zur Wiesch, Pia; Kouyos, Roger D.; Bonhoeffer, Sebastian (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-10-30)
      To understand how antibiotic use affects the risk of a resistant infection, we present a computational model of the population dynamics of gut microbiota including antibiotic resistance-conferring plasmids. We then describe how this model is parameterized based on published microbiota data. Finally, we investigate how treatment history affects the prevalence of resistance among opportunistic ...

    • Reaction Kinetic Models of Antibiotic Heteroresistance 

      Martinecz, Antal; Clarelli, Fabrizio; Abel, Sören; Abel zur Wiesch, Pia (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-08-15)
      Bacterial heteroresistance (i.e., the co-existence of several subpopulations with different antibiotic susceptibilities) can delay the clearance of bacteria even with long antibiotic exposure. Some proposed mechanisms have been successfully described with mathematical models of drug-target binding where the mechanism’s downstream of drug-target binding are not explicitly modeled and subsumed in ...

    • The Role of Adherence and Retreatment in De Novo Emergence of MDR-TB 

      Cadosch, Dominique; Abel zur Wiesch, Pia; Kouyos, Roger; Bonhoeffer, Sebastian (Journal article; Tidsskriftartikkel; Peer reviewed, 2016)
      Treatment failure after therapy of pulmonary tuberculosis (TB) infections is an important challenge, especially when it coincides with de novo emergence of multi-drug-resistant TB (MDR-TB). We seek to explore possible causes why MDR-TB has been found to occur much more often in patients with a history of previous treatment. We develop a mathematical model of the replication of Mycobacterium tuberculosis ...

    • Selection or drift: The population biology underlying transposon insertion sequencing experiments 

      Mahmutovic, Anel; Abel zur Wiesch, Pia; Abel, Sören (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-25)
      <p>Transposon insertion sequencing methods such as Tn-seq revolutionized microbiology by allowing the identification of genomic loci that are critical for viability in a specific environment on a genome-wide scale. While powerful, transposon insertion sequencing suffers from limited reproducibility when different analysis methods are compared. From the perspective of population biology, this may be ...

    • Transposon-insertion sequencing screens unveil requirements for EHEC growth and intestinal colonization 

      Warr, Alyson R; Hubbard, Troy P; Munera, Diana; Blondel, Carlos J; Abel zur Wiesch, Pia; Abel, Sören; Wang, Xiaoxue; Davis, Brigid M.; Waldor, Matthew K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-08-12)
      Enterohemorrhagic <i>Escherichia coli</i> O157:H7 (EHEC) is an important food-borne pathogen that colonizes the colon. Transposon-insertion sequencing (TIS) was used to identify genes required for EHEC and <i>E. coli</i> K-12 growth <i>in vitro</i> and for EHEC growth <i>in vivo</i> in the infant rabbit colon. Surprisingly, many conserved loci contribute to EHEC’s but not to K-12’s growth <i>in ...

    • Using chemical reaction kinetics to predict optimal antibiotic treatment strategies 

      Abel zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-01-06)
      Identifying optimal dosing of antibiotics has proven challenging—some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. ...

    • vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding 

      Tran, Vi Ngoc-Nha; Shams, Alireza; Ascioglu, Sinan; Martinecz, Antal; Liang, Jingyi; Clarelli, Fabrizio; Mostowy, Rafal; Cohen, Ted; Abel zur Wiesch, Pia (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-06)
      Background: As antibiotic resistance creates a signifcant global health threat, we need not only to accelerate the development of novel antibiotics but also to develop better treatment strategies using existing drugs to improve their efcacy and prevent the selection of further resistance. We require new tools to rationally design dosing regimens from data collected in early phases of antibiotic ...