Identifying the drivers of inhibitor of apoptosis protein antagonist resistance in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is the 7th leading cause of cancer related death. Deregulation of the apoptotic pathway, including upregulation of inhibitor of apoptosis proteins (IAPs), occurs at an early stage in PDAC resulting in aggressive tumours which are often resistant to therapy. Currently, use of IAP antagonists in clinical trials aims to sensitise cancer cells to apoptosis. However, these therapies show a lack of efficacy in a large proportion of the patient population. Therefore, elucidating the molecular mechanisms associated with resistance to IAP antagonists could optimise treatment strategies for PDAC. In this study, three different screening methodologies are used to identify novel resistance drivers to IAP antagonists. Firstly, a genome-wide CRISPR-Cas9 screen was conducted to identify 1025 potential genetic contributors (p<0.05) to birinapant response in the insensitive Suit-2 cell line. Secondly, two acquired resistance cell lines from Capan-1 and Panc-1 cell lines were created from prolonged treatment exposure. Differential gene expression analysis compared acquired resistance to parental cell lines to identify 494 common gene expression changes associated with resistance (P<0.05). Finally, large scale pan-cancer drug sensitivity data sets were analysed for multi-omic resistance drivers to four IAP antagonists: birinapant, LCL161, Embelin and AZD5582. This identified significant differences between IAP antagonists, with no common drivers identified for all antagonists. The three screening methods were compared to identify three birinapant resistance drivers present in all analyses: RSU1, ACVR2A and ANK2. From these findings, initial validations of several resistance drivers were conducted. These included investigations of single target knockdowns of MYC as well as the effects of ribosome biogenesis, Estrogen signalling and proteosome regulation on IAP antagonist sensitivity. Overall, cMYC silencing and BET inhibitor combinations were the most promising combinations with IAP antagonists, with significant synergies observed in several PDAC cell lines. In summary, this project successfully utilises three methodologies to uncover several novel IAP antagonist resistance drivers and suggests several rational combination targets to improve therapeutic strategies for pancreatic cancer.Open Acces

The use of a quantitative structure-activity relationship (QSAR) model to predict GABA-A receptor binding of newly emerging benzodiazepines

The illicit market for new psychoactive substances is forever expanding. Benzodiazepines and their derivatives are one of a number of groups of these substances and thus far their number has grown year upon year. For both forensic and clinical purposes it is important to be able to rapidly understand these emerging substances. However as a consequence of the illicit nature of these compounds, there is a deficiency in the pharmacological data available for these ‘new’ benzodiazepines. In order to further understand the pharmacology of ‘new’ benzodiazepines we utilised a quantitative structure-activity relationship (QSAR) approach. A set of 69 benzodiazepine-based compounds was analysed to develop a QSAR training set with respect to published binding values to GABAA receptors. The QSAR model returned an R2 value of 0.90. The most influential factors were found to be the positioning of two H-bond acceptors, two aromatic rings and a hydrophobic group. A test set of nine random compounds was then selected for internal validation to determine the predictive ability of the model and gave an R2 value of 0.86 when comparing the binding values with their experimental data. The QSAR model was then used to predict the binding for 22 benzodiazepines that are classed as new psychoactive substances. This model will allow rapid prediction of the binding activity of emerging benzodiazepines in a rapid and economic way, compared with lengthy and expensive in vitro/in vivo analysis. This will enable forensic chemists and toxicologists to better understand both recently developed compounds and prediction of substances likely to emerge in the future

Tapping into the maize root microbiome to identify bacteria that promote growth under chilling conditions

Background When maize (Zea mays L.) is grown in the Northern hemisphere, its development is heavily arrested by chilling temperatures, especially at the juvenile phase. As some endophytes are beneficial for plants under stress conditions, we analyzed the impact of chilling temperatures on the root microbiome and examined whether microbiome-based analysis might help to identify bacterial strains that could promote growth under these temperatures. Results We investigated how the maize root microbiome composition changed by means of 16S rRNA gene amplicon sequencing when maize was grown at chilling temperatures in comparison to ambient temperatures by repeatedly cultivating maize in field soil. We identified 12 abundant and enriched bacterial families that colonize maize roots, consisting of bacteria recruited from the soil, whereas seed-derived endophytes were lowly represented. Chilling temperatures modified the root microbiome composition only slightly, but significantly. An enrichment of several chilling-responsive families was detected, of which the Comamonadaceae and the Pseudomonadaceae were the most abundant in the root endosphere of maize grown under chilling conditions, whereas only three were strongly depleted, among which the Streptomycetaceae. Additionally, a collection of bacterial strains isolated from maize roots was established and a selection was screened for growth-promoting effects on juvenile maize grown under chilling temperatures. Two promising strains that promoted maize growth under chilling conditions were identified that belonged to the root endophytic bacterial families, from which the relative abundance remained unchanged by variations in the growth temperature. Conclusions Our analyses indicate that chilling temperatures affect the bacterial community composition within the maize root endosphere. We further identified two bacterial strains that boost maize growth under chilling conditions. Their identity revealed that analyzing the chilling-responsive families did not help for their identification. As both strains belong to root endosphere enriched families, visualizing and comparing the bacterial diversity in these communities might still help to identify new PGPR strains. Additionally, a strain does not necessarely need to belong to a high abundant family in the root endosphere to provoke a growth-promoting effect in chilling conditions

Daring to be differential : metabarcoding analysis of soil and plant-related microbial communities using amplicon sequence variants and operational taxonomical units

Background: Microorganisms are not only indispensable to ecosystem functioning, they are also keystones for emerging technologies. In the last 15 years, the number of studies on environmental microbial communities has increased exponentially due to advances in sequencing technologies, but the large amount of data generated remains difficult to analyze and interpret. Recently, metabarcoding analysis has shifted from clustering reads using Operational Taxonomical Units (OTUs) to Amplicon Sequence Variants (ASVs). Differences between these methods can seriously affect the biological interpretation of metabarcoding data, especially in ecosystems with high microbial diversity, as the methods are benchmarked based on low diversity datasets. Results: In this work we have thoroughly examined the differences in community diversity, structure, and complexity between the OTU and ASV methods. We have examined culture-based mock and simulated datasets as well as soil- and plant-associated bacterial and fungal environmental communities. Four key findings were revealed. First, analysis of microbial datasets at family level guaranteed both consistency and adequate coverage when using either method. Second, the performance of both methods used are related to community diversity and sample sequencing depth. Third, differences in the method used affected sample diversity and number of detected differentially abundant families upon treatment; this may lead researchers to draw different biological conclusions. Fourth, the observed differences can mostly be attributed to low abundant (relative abundance < 0.1%) families, thus extra care is recommended when studying rare species using metabarcoding. The ASV method used outperformed the adopted OTU method concerning community diversity, especially for fungus-related sequences, but only when the sequencing depth was sufficient to capture the community complexity. Conclusions: Investigation of metabarcoding data should be done with care. Correct biological interpretation depends on several factors, including in-depth sequencing of the samples, choice of the most appropriate filtering strategy for the specific research goal, and use of family level for data clustering

Bacterial community profiling of plastic litter in the Belgian part of the North Sea

Bacterial colonization of marine plastic litter (MPL) is known for over four decades. Still, only a few studies on the plastic colonization process and its influencing factors are reported. In this study, seafloor MPL was sampled at different locations across the Belgian part of the North Sea to study bacterial community structure using 16S metabarcoding. These marine plastic bacterial communities were compared with those of sediment and seawater, and resin pellets sampled on the beach, to investigate the origin and uniqueness of plastic bacterial communities. Plastics display great variation of bacterial community composition, while each showed significant differences from those of sediment and seawater, indicating that plastics represent a distinct environmental niche. Various environmental factors correlate with the diversity of MPL bacterial composition across plastics. In addition, intrinsic plastic-related factors such as pigment content may contribute to the differences in bacterial colonization. Furthermore, the differential abundance of known primary and secondary colonizers across the various plastics may indicate different stages of bacterial colonization, and may confound comparisons of free-floating plastics. Our studies provide insights in the factors that shape plastic bacterial colonization and shed light on the possible role of plastic as transport vehicle for bacteria through the aquatic environment

Exploring the methanogen and bacterial communities of rumen environments : solid adherent, fluid and epimural

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