Integrated multi-omic analyses of mobile genetic elements within a mixed microbial community

Doctoral thesis (2021)

Microbial communities are ubiquitous, complex and dynamic systems that constantly adapt to changing environmental conditions, while playing important roles in natural environments, human health and ... [more ▼]

Microbial communities are ubiquitous, complex and dynamic systems that constantly adapt to changing environmental conditions, while playing important roles in natural environments, human health and biotechnological processes. Invasive mobile genetic elements (iMGE) are considered as important biotic components of microbial communities, in particular (bacterio)-phages and plasmids are some of the most abundant and diverse biological entities, which may influence community structure and dynamics. Microbial populations within naturally occurring communities are constantly interacting with each other. Ecological interactions between those populations can be generally classified as competitive and cooperative relationships. To date, extensive studies on biotic interactions, i.e. relationships between microbial hosts with iMGEs and between microbial populations, have been somewhat limited, thus restricting our understanding of microbial community dynamics. Fortunately, high-throughput multi-omics derived from microbiomes, i.e. metagenomics and metatranscriptomics, enables access to both functional -potential and -expression information of those biotic components. Combining longitudinal multi-omics data with mathematical frameworks allows us to model microbial community interactions and dynamics, unlike ever before. Here, I present a longitudinal integrated multi-omics analysis of biotic components within foaming activated sludge, spanning ~1.5 years to unravel i) iMGE-host dynamics and ii) ecological interactome. In the first part of this work, empirical host-iMGE CRISPR-based links in combination with mathematical modelling highlighted the importance of plasmids, relative to phages, in shaping community structure, while also showing that plasmids vastly outnumbered, and were more targeted via CRISPR-Cas systems, compared to their phage counterparts. In the second part of this work, mathematical modelling is used to provide ecological contexts for the relationships between microbial community members. In general, we observed a dynamic interactome, with higher cooperative interactions, despite these populations encoding highly similar functional potential. In summary, this work demonstrates the potential of longitudinal multi-omics in expanding our understanding of microbial community dynamics, which could be expanded to other microbial ecosystems and potentially lead to applications in human health and biotechnological processes. [less ▲]

Roles of bacteriophages, plasmids and CRISPR immunity in microbial community dynamics revealed using time-series integrated meta-omics

in Nature Microbiology (2020)

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We ... [more ▼]

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes. [less ▲]

Critical transitions in microbial communities: mobile genetic elements as drivers of the microbial community dynamics within activated sludge of wastewater treatment

Poster (2018, October 19)

A multi-omic view of invasive genetic elements and their linked prokaryotic population dynamics within a mixed microbial community

Presentation (2018, August 16)

A multi-omic view of invasive genetic elements and their linked prokaryotic population dynamics within a mixed microbial community

Presentation (2018, May 17)

A multi-omic view of phage-host dynamics within a mixed microbial community

Presentation (2017, December 07)

A systems biology approach to identify niche determinants of cellular phenotypes

in Stem Cell Research (2016)

Recent reports indicate a dominant role for cellular microenvironment or niche for stably maintaining cellular phenotypic states. Identification of key niche mediated signaling that maintains stem cells ... [more ▼]

Recent reports indicate a dominant role for cellular microenvironment or niche for stably maintaining cellular phenotypic states. Identification of key niche mediated signaling that maintains stem cells in specific phenotypic states remains a challenge, mainly due to the complex and dynamic nature of stem cell-niche interactions. In order to overcome this, we consider that stem cells maintain their phenotypic state by experiencing a constant effect created by the niche by integrating its signals via signaling pathways. Such a constant niche effect should induce sustained activation/inhibition of specific stem cell signaling pathways that controls the gene regulatory program defining the cellular phenotypic state. Based on this view, we propose a computational approach to identify the most likely receptor mediated signaling responsible for transmitting niche signals to the transcriptional regulatory network that maintain cell-specific gene expression patterns, termed as niche determinants. We demonstrate the utility of our method in different stem cell systems by identifying several known and novel niche determinants. Given the key role of niche in several degenerative diseases, identification of niche determinants can aid in developing strategies for potential applications in regenerative medicine. [less ▲]