Journal Club

AHMRN Journal Club

Working in the field of human microbiome research? 

Join us for our AHMRN Journal Club where we get to the nitty gritty of microbiome study methods and practical issues.

To keep the Journal Club on track we've put together some brief guidelines below. Please have a look at these before presenting.

Guidelines


Join our mailing list to keep up to date with upcoming presenters and to volunteer to present.


Next Journal Club

Please join us for: Enhanced microbiota data exploration through Taxon Set Enrichment Analysis


Presented by: Dr Feargal J. Ryan. NHMRC Investigator. South Australian Health and Medical Research


Date: Wed 24 July 2024

Time: 12:30-1:15pm ACST

Venue: Online

Zoom: TBA

 

Paper: Enhanced microbiota data exploration through Taxon Set Enrichment Analysis 


Abstract: The microbiota is critical regulator of host health and its composition is frequently assessed via sequencing of microbial DNA. Current tools largely focus on identifying changes at the level of individual taxa (e.g. species, genera). In other omics technologies such as transcriptomics, individual gene level changes are used as input for enrichment analyses using pre-defined gene sets allowing for researchers to rapidly identify changes matching previously reported signatures, and molecular pathways. Here, we present TaxSEA, an R package for taxon set enrichment analysis which utilizes five different microbiota databases (BugSigDB, MiMeDB, GutMGene, mBodyMap and GMRepoV2) to assess whether previously identified disease signatures, metabolite producers or published associations are enriched in a dataset of interest. When applied to Inflammatory Bowel Disease or Type 2 Diabetes metagenomic datasets, TaxSEA can detect a significant enrichment of appropriate disease signatures and enrichments/depletions metabolite producers associated with disease (e.g. short chain fatty acids, various tryptophan metabolites). TaxSEA can be applied to datasets generated using any taxonomic profiling technology requiring only a taxonomic label and rank as input. Although TaxSEA can be applied to samples from any environment, existing databases largely focus on the human gut microbiome. TaxSEA enables researchers to rapidly contextualize their findings within the broader literature to accelerate interpretation of results.


Bio: Feargal is a NHMRC-funded investigator (EL1) in the Computational & Systems Biology Program at SAHMRI and holds a level B appointment in the College of Medicine and Public Health at Flinders University. Feargal’s research combines microbiology, bioinformatics, and systems immunology to understand how host-microbe interactions shape health in the fields of gut microbiome, infection (COVID-19, ZIKV) and cancer. He has co-authored >35 peer reviewed articles including in top ranked journals such as Science, Gut and Cell Host & Microbe. Feargal has worked with global leaders in the gut microbiome field including at the APC Microbiome Institute (Ireland), Kings College London (UK) and the Janssen Human Microbiome Institute (USA). He has also led development of highly cited computational analysis tools (Allard, Ryan et al. BMC Bioinformatics 2018) and reproducible protocols for generating metagenomic data (Shkoporov, Ryan et al. Microbiome 2018).



Next Journal Club

Please join us for: Detailed mapping of Bifidobacterium strain transmission from mother to infant via a dual culture-based and metagenomic approach.


Presented by: Dr Callum Walsh


Date: Thu 30 May 2024

Time: 12:30-1:15pm ACST

Venue: Online

Zoom: Zoom link

 

Paper: Detailed mapping of Bifidobacterium strain transmission from mother to infant via a dual culture-based and metagenomic approach


Abstract: A significant proportion of the infant gut microbiome is considered to be acquired from the mother during and after birth. Thus begins a lifelong and dynamic relationship with microbes that has an enduring impact on host health. Based on a cohort of 135 mother-infant dyads, we investigated the phenomenon of microbial strain transfer, with a particular emphasis on the use of a combined metagenomic-culture-based approach to determine the frequency of strain transfer involving members of the genus Bifidobacterium, including species/strains present at low relative abundance. From the isolation and genome sequencing of over 449 bifidobacterial strains, we validate and augment metagenomics-based evidence to reveal strain transfer in almost 50% of dyads. Factors important in strain transfer include vaginal birth, spontaneous rupture of amniotic membranes, and avoidance of intrapartum antibiotics. Importantly, we reveal that several transfer events are uniquely detected employing either cultivation or metagenomic sequencing, highlighting the requirement for a dual approach to obtain an in-depth insight into this transfer process.


Bio: Dr. Calum Walsh is a postdoctoral bioinformatician in the lab group of Prof. Tim Stinear at The Peter Doherty Institute for Infection and Immunity. His current research is centred on the interaction dynamics within the human microbiome to understand the roles of different commensal microorganisms in health and disease. Particularly in the context of multidrug resistant human pathogens such as vancomycin-resistant Enterococcus faecium and carbapenem-resistant Enterobacterales.

He has a decade of experience in the analysis of microbiome-centric datasets including 16S amplicons, shotgun metagenomics and metatranscriptomics, as well as bacterial genomes and transcriptomes.

He is also bioinformatics coordinator at Doherty Applied Microbial Genomics, a collaborative research initiative established to assist researchers, particularly those from other disciplines, use microbial genomics methods in their work.



Next Journal Club

Please join us for: Autologous Faecal Microbiota Transplantation to Improve Outcomes of Haematopoietic Stem Cell Transplantation: Results of a Single-Centre Feasibility Study 


Presented by: Ms Anna Li


Date: Mon 25 March 2024

Time: 1:00pm AEDST

Venue: Online

Zoom: https://adelaide.zoom.us/j/81218265426?pwd=OUlJeUNlVkhsR2ZLcW8zQWRmQm55UT09&from=addon

 

Paper: Biomedicines | Free Full-Text | Autologous Faecal Microbiota Transplantation to Improve Outcomes of Haematopoietic Stem Cell Transplantation: Results of a Single-Centre Feasibility Study (mdpi.com)

  
Further details to be added soon!


Previous Journal Clubs

Informal Bioinformatics Seminar

Hosted by the Monash Genomics and Bioinformatics Platform in conjunction with the Australasian Human Microbiome Research Network


Please join us for: Metagenomics and the microbiome: disentangling complex biology from complex data


Date: Wed 09 August 2023

Time: 2:30pm AEST

Venue: Bld 76, 19 Innovation Walk, level 2, room 204 (central meeting room opposite lifts),
Monash University Clayton Campus

Zoom: https://monash.zoom.us/j/86788669392?pwd=QWZDemhRbTlqYmpEYVBUSkgzbWNtZz09

 

Abstract:

Our understanding of the role and significance of the human microbiome in health and disease has been spearheaded by major developments in DNA sequencing technologies, as well as conceptual and methodological advances in the field of metagenomics. In my talk, I'll discuss the challenges of doing data-driven research on the gut microbiome, using my recent work on faecal microbiota transplantation as a case study (Science 2016, PMID:27126044; Nature Medicine 2022, PMID: 36109636).

 
Bio:
Simone is a computational biologist and NHMRC CJ Martin Research Fellow, and leads the new Microbiome Systems research group at the Biomedicine Discovery Institute at Monash University.
Trained as an engineer in Sydney at the University of New South Wales, she's happy to be back in Australia after doing her PhD in Germany (EMBL, Heidelberg) and a postdoc in Denmark (Novo Nordisk Foundation Center for Biosustainability, Copenhagen) that was supported by a competitive EMBO Fellowship. Her research has often bridged discovery and translational sciences - spanning systems biology, metagenomics and antimicrobial resistance in both clinical and biotechnology contexts.
Simone and her team will use bioinformatics, microbiomics and machine learning approaches to study microbial communities in their native ecosystems and create data-oriented methods to analyse and disentangle the biological complexity contained within them. One focus will be to look at how the microbes collectively respond to human-mediated interventions and identify ways we can leverage this information to enable improved and rational design of sustainable microbiome-based therapeutic and remediation strategies.