Biology subjects

Geelen, A. R.

Publications and source records attributed to Geelen, A. R..

3 recordsLinked to original sources

bioRxiv2025

Manufacture of Clostridioides difficile spores for experimental infection of human volunteers

BackgroundInfections with C. difficile remain a significant global healthcare problem for which novel (preventive) treatment strategies are urgently needed. Controlled human infection models (CHIMs) can contribute to a better understanding of the disease and accelerate (novel) medicinal product development. MethodsA robust production process for C. difficile spores for experimental human administration, was implemented. Direct-release capsules containing viable C. difficile spores were formulated. The manufacturing process aligns with good manufacturing practices (GMP) guidelines, including quality controls and release by a qualified person (QP). ResultsSelected non-toxigenic and toxigenic C. difficile strains were used to create a master cell bank and working cell bank from which multiple batches of purified active substance were produced. Substance was then used to manufacture the final active product. The active product and its intermediate products passed all quality controls for identity, potency, purity and safety, and were individually released by the QP. Stability of active substance and product is confirmed up to 12 months. ConclusionAlthough there are no clear standardized international guidelines for challenge material production, we demonstrate that it is feasible to produce C. difficile human challenge material for small scale application in CHIM trials. This application of GMP principles to an unconventional production process of a bacterial spore-forming anaerobic challenge agent is an example for the production of challenge material as described in the auxiliary medicinal product guidelines of EMA and FDA.

microbiology↗

bioRxiv2021

Impacts of dietary exposure to pesticides on faecal microbiome metabolism in adult twins

Concerns have been raised as to whether the consumption of foodstuffs contaminated with pesticides can contribute to the development of chronic human diseases by affecting microbial community function in the gut. We provide the first associations between urinary pesticide excretion and the composition and function of the faecal microbiome in 65 twin pairs in the UK. Biomonitoring of exposure to 186 common insecticide, herbicide, or fungicide residues showed the presence of pyrethroid and/or organophosphorus insecticide residues in all urine samples, while the herbicide glyphosate was found in 45% of individuals. Other pesticides such as DEET, imidacloprid or dithiocarbamate fungicides were less frequently detected. While the geographic location or the rural/urban environment had no influence on pesticide urinary excretion, food frequency questionnaires showed that DMTP levels, a metabolite of organophosphates, was higher with increased consumption of fruit and vegetables. Multivariable association between urinary pesticide excretion and faecal microbial composition and function were determined with shotgun metagenomics and metabolomics. A total of 34 associations between pesticide residues concentrations and faecal metabolite concentrations were detected. Glyphosate excretion was positively associated to an increased bacterial species richness, as well as to fatty acid metabolites and phosphate levels. The insecticide metabolite Br2CA, reflecting deltamethrin exposure, was positively associated with the mammalian phytoestrogens enterodiol and enterolactone, and negatively associated with some N-methyl amino acids. Urine metabolomics performed on a subset of samples did not reveal associations with the excretion of pesticide residues. Our results highlight the need for future interventional studies to understand effects of pesticide exposure on the gut microbiome and possible health consequences.

pharmacology and toxicology↗

bioRxiv2019

Toward standards in clinical microbiome studies: comparison of three DNA extraction methods and two bioinformatic pipelines

When studying the microbiome using next generation sequencing, DNA extraction method, sequencing procedures and bioinformatic processing are crucial to obtain reliable data. Method choice has been demonstrated to strongly affect the final biological interpretation. We assessed the performance of three DNA extraction methods and two bioinformatic pipelines for bacterial microbiota profiling through 16S rRNA gene amplicon sequencing, using positive and negative controls for DNA extraction and sequencing, and eight different types of high- or low-biomass samples. Performance was evaluated based on quality control passing, DNA yield, richness, diversity and compositional profiles. All DNA extraction methods retrieved the theoretical relative bacterial abundance with maximum three-fold change, although differences were seen between methods, and library preparation and sequencing induced little variation. Bioinformatic pipelines showed different results for estimating richness, but diversity and compositional profiles were comparable. DNA extraction methods were successful for feces and oral swabs and variation induced by DNA extraction methods was lower than inter-subject (biological) variation. For low-biomass samples, a mixture of genera present in negative controls and sample-specific genera, possibly representing biological signal, were observed. We conclude that the tested bioinformatic pipelines perform equally with pipeline-specific advantages and disadvantages. Two out of three extraction methods performed equally well, while one method was less accurate regarding retrieval of compositional profiles. Lastly, we demonstrate the importance of including negative controls when analyzing low bacterial biomass samples.\n\nIMPORTANCEMethod choice throughout the workflow of a microbiome study, from sample collection to DNA extraction and sequencing procedures, can greatly affect results. This study evaluated three different DNA extraction methods and two bioinformatic pipelines by including positive and negative controls, and various biological specimens. By identifying an optimal combination of DNA extraction method and bioinformatic pipeline use, we hope to contribute to increased methodological consistency in microbiome studies. Our methods were not only applied to commonly studied samples for microbiota analysis, e.g. feces, but also for more rarely studied, low-biomass samples. Microbiota composition profiles of low-biomass samples (e.g. urine and tumor biopsies) were not always distinguishable from negative controls, or showed partial overlap, confirming the importance of including negative controls in microbiome studies, especially when low bacterial biomass is expected.

microbiology↗