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Siu, L. L.

Publications and source records attributed to Siu, L. L..

4 recordsLinked to original sources

Assessment of ecological fidelity of human microbiome-associated mice in observational studies and an interventional trial

Composition and function of the gut microbiome is associated with diverse health conditions and treatment responses. Human microbiota-associated (HMA) mouse models are used to establish causal links for these associations but have important limitations. We assessed the fidelity of HMA mouse models to recapitulate ecological responses to a microbial consortium using stools collected from a human clinical trial. HMA mice were generated using different routes of consortium exposure and their ecological features were compared to human donors by metagenomic sequencing. HMA mice were more similar in gut composition to other mice than their respective human donors, with taxa including Akkermansia muciniphila and Bacteroides species enriched in mouse recipients. A limited repertoire of microbes was able to engraft into HMA mice regardless of route of consortium exposure. In publicly available HMA mouse datasets from four distinct health conditions, we confirmed our observation that a taxonomically restricted set of microbes reproducibly engrafts in HMA mice and observed that stool microbiome composition of HMA mice were more like other mice than their human donor. Our data suggest that HMA mice are limited models to assess the ecological impact of microbial consortia, with ecological effects in HMA mice being more strongly associated with host species than donor stool ecology or ecological responses to treatment in humans. Comparisons to published studies suggest this may be due to comparatively large host-species effects that overwhelm ecological effects of treatment in humans that HMA models aim to recapitulate. ImportanceHuman microbiota-associated (HMA) mice are models that better represent human gut ecology compared to conventional laboratory mice and are commonly used to test the effect of the gut microbiome on disease or treatment response. We evaluated the fidelity of using HMA mice as avatars of ecological response to a human microbial consortium, MET4. Our results show that HMA mice in our cohort and across other published studies are more similar to each other than the human donors or inoculum they are derived from and harbour a taxonomically restricted gut microbiome. These findings highlight the limitations of HMA mice in evaluating the ecological effects of complex human microbiome-targeting interventions, such as microbial consortia.

microbiology↗

CanDIG: Secure Federated Genomic Queries and Analyses Across Jurisdictions

Rapid expansions of bioinformatics and computational biology have broadened the collection and use of -omics data including genomic, transcriptomic, methylomic and a myriad of other health data types, in the clinic and the laboratory. Both clinical and research uses of such data require co-analysis with large datasets, for which participant privacy and the need for data custodian controls must remain paramount. This is particularly challenging in multi-jurisdictional settings, such as Canada, where health privacy and security requirements are often heterogeneous. Data federation presents a solution to this, allowing for integration and analysis of large datasets from various sites while abiding by local policies. The Canadian Distributed Infrastructure for Genomics platform (CanDIG) enables federated querying and analysis of -omics and health data while keeping that data local and under local control. It builds upon existing infrastructures to connect five health and research institutions across Canada, relies heavily on standards and tooling brought together by the Global Alliance for Genomics and Health (GA4GH), implements a clear division of responsibilities among its participants and adheres to international data sharing standards. Participating researchers and clinicians can therefore contribute to and quickly access a critical mass of -omics data across a national network in a manner that takes into account the multi-jurisdictional nature of our privacy and security policies. Through this, CanDIG gives medical and research communities the tools needed to use and analyze the ever-growing amount of -omics data available to them in order to improve our understanding and treatment of various conditions and diseases. CanDIG is being used to make genomic and phenotypic data available for querying across Canada as part of data sharing for five leading pan-Canadian projects including the Terry Fox Comprehensive Cancer Care Centre Consortium Network (TF4CN) and Terry Fox PRecision Oncology For Young peopLE (PROFYLE), and making data from provincial projects such as POG (Personalized Onco- Genomics) more widely available.

genomics↗

Two-target quantitative PCR to predict library composition for shallow shotgun sequencing

Shotgun sequencing enables retrieving high resolution information 40 from complex microbial communities. However, the technique is limited by missing information about host-to-microbe ratios observed in different sample types. This makes it challenging to plan sequencing experiments, especially in the context of high sample multiplexing and/or limited sequencing output. We evaluated a qPCR-based assay to predict host-to microbe ratio prior to sequencing. Using a two-target assay aimed at conserved human and bacterial genes, we predicted human-to-microbe ratios in two sample types and validated it on independently collected samples. The assay enabled accurate prediction for a broad range of sample compositions.

microbiology↗

Genome analysis and data sharing informs timing of molecular events in pancreatic neuroendocrine tumour

Neuroendocrine tumours (NETs) are rare, slow growing cancers that present in a diversity of tissues. To understand molecular underpinnings of gastrointestinal (GINET) and pancreatic NETs (PNETs), we profiled 45 tumours combining exome, RNA, and shallow whole genome sequencing, as well as fluorescent in situ hybridization. In addition to expected somatic mutations and copy number alterations, we found that PNETs contained a highly consistent copy neutral loss-of-heterozygosity (CN-LOH) profile affecting over half of the genome; a greater percentage than any cancer analyzed to date. Our data indicates that onset of extreme autozygosity may be progressive, associated with metastasis, and initially triggered by the loss of DAXX/ATRX, and subsequent biallelic loss of MEN1. We confirmed this molecular timing model using targeted clinical sequencing data from an additional 43 NETs made available by the AACR GENIE project. Against this background of CN-LOH, several chromosomal regions consistently retained heterozygosity, suggesting selection for crucial allele-specific components specific to PNET progression and potential new therapeutic targets.\n\nStatement of significanceWe have discovered that pancreatic neuroendocrine tumours contain a characteristic pattern of copy neutral loss-of-heterozygosity affecting the majority of the genome following mutations of MEN1 and ATRX/DAXX. Against this background of loss-of-heterozygosity, specific genomic regions are consistently retained and may therefore contain vulnerable therapeutic targets for pancreatic neuroendocrine tumours.

cancer biology↗