Periodic Reporting for period 4 - RuMicroPlas (The Plasmidome: a Driving Force of Rumen Microbial Evolution from Birth to Adulthood)
Periodo di rendicontazione: 2020-07-01 al 2021-12-31
In recent years, the mammalian gut, including the ruminant gut, has emerged as a fundamentally important microbial environment. The intricate relationships between mammalian hosts and their microbial communities have been shown to play a central role in the host's well-being. The rumen environment is an anaerobic compartment in the ruminant digestive system that accommodates heterogeneous microbial communities. The rumen, together with its microbial symbionts, is responsible for the ruminant's remarkable ability to convert indigestible plant mass into digestible food products. In this sense, ruminants are completely dependent on their rumen microbiome for their existence. This cooperative relationship between the ruminant and its resident microbiome has evolved over millions of years and has implications for our everyday lives with respect to food sustainability, environment, renewable energy, and economics. Ruminants hold enormous significance for mankind, as they convert the energy stored in plant biomass polymers, which are indigestible for humans, to digestible food products. Humans domesticated these animals for this purpose in the Neolithic era and have been farming them ever since for the production and consumption of animal protein in the form of meat and milk. In today's extensive production regimes, ruminants consume 30% of the crops grown on earth and occupy another 30% of the Earth's land mass. These animals also emit methane—a highly potent greenhouse gas—to the atmosphere and are considered to be responsible for a considerable portion of its emission because of anthropogenic activities. Hence, an understanding of this complex microbial ecosystem and the evolutionary rules that govern it is of major interest. The complexity of the rumen microbial environment and its key role in animal physiology raises intriguing questions regarding the genetics and mobility of its functions among its microbial members. Lateral gene transfer (LGT)—the process by which microbial species donate and receive genetic material—is a major determinant of genetic novelty and genome evolution in prokaryotes. Mobile genetic elements serve as DNA vehicles for the communal gene pool. Plasmids are self-replicating, extrachromosomal, mobile genetic elements that operate as “gene ferries”, transferring genes from one host to another. Plasmids have been recognized as key vectors of genetic exchange between microbial chromosomes. Their high abundance in microbial populations sampled from various habitats indicates that they have an important ecological role. Plasmids are composed of a conserved DNA backbone that includes replication and mobilization genes, which are important for plasmid maintenance within the host and transfer among hosts. They also carry a variable assortment of accessory genes, which often contribute to the phenotypic diversity of their host. Plasmids isolated from different ecological niches encode a versatile array of accessory functions, ranging from antibiotic resistance to nitrogen fixation. These plasmid-borne functions may confer an advantage to their host in its niche, making the burden of carrying the plasmid worthwhile. An understanding of plasmid biology and biodiversity is expected to greatly contribute to our understanding of microbial ecology and evolution in diverse environments.
An ecological and mechanistic understanding of the rumen microbiome, which we aimed with this project, could lead to an increase in available food resources and environmentally friendly livestock agriculture. Therefore, this funding was instrumental for our ability to make several important breakthroughs in the field. In RuMicroPlas, we proposed to study the evolutionary and ecological dynamics of the rumen plasmidome and its interaction with the rumen microbiome using our established approaches, together with a dense host-sampling resolution.
An ecological and mechanistic understanding of the rumen microbiome, which we aimed with this project, could lead to an increase in available food resources and environmentally friendly livestock agriculture. Therefore, this funding was instrumental for our ability to make several important breakthroughs in the field. In RuMicroPlas, we proposed to study the evolutionary and ecological dynamics of the rumen plasmidome and its interaction with the rumen microbiome using our established approaches, together with a dense host-sampling resolution.
Our work brought light to the origins and assembly of the rumen microbiome. We revealed that together with strong deterministic constraints imposed by diet and age, stochastic colonization in early life has long-lasting impacts on the development of animal microbiomes. We further identified niches modification and redox potential as pivotal factors that sculpt the anaerobic rumen microbial community assembly. We found that genetics and physiology are correlated with microbiome structure and that host genetics may shape the microbiome landscape by enriching for phylogenetically related taxa.
By developing a set of molecular and bioinformatic tools that enable the study of mobile genetic elements, we have explored the effect of early assemblages on the adult plasmidome and microbiome phenotypes and were able to describe such elements in the rumen and rat ecosystem as well as more systematic experimental systems. Our results allowed us to understand the role played by plasmids within this complex microbial community, the co-evolutionary relationships between plasmidome and microbiome and plasmids importance to the overall rumen ecosystem.
By developing a set of molecular and bioinformatic tools that enable the study of mobile genetic elements, we have explored the effect of early assemblages on the adult plasmidome and microbiome phenotypes and were able to describe such elements in the rumen and rat ecosystem as well as more systematic experimental systems. Our results allowed us to understand the role played by plasmids within this complex microbial community, the co-evolutionary relationships between plasmidome and microbiome and plasmids importance to the overall rumen ecosystem.
During the course of the project, we have developed several methodologies:
-For the study of the mobile elements in natural microbial ecosystems, we have developed a set of bioinformatic tools (Pellow et al. 2021; Rozov et al. 2017). In 2017, we introduced Recycler (Rozov et al. 2017), the first tool that can extract complete circular contigs from sequence data of isolated microbial genomes, plasmidomes and metagenome sequence data We then improved it by developing SCAPP in 2021 (Sequence Contents-Aware Plasmid Peeler)—an algorithm and tool to assemble plasmid sequences from metagenomic sequencing. SCAPP builds on some key ideas from the Recycler algorithm while improving plasmid assemblies by integrating biological knowledge about plasmids (Pellow et al. 2021). In addition, PlasClass was developed to improve plasmid sequence classification (Pellow, Mizrahi, and Shamir 2020).
-Given the highly dynamic and complex nature of the gut microbial community, the ability to identify and predict time-dependent compositional patterns of microbes is crucial to our understanding of the structure and function of this ecosystem. Microbial interactions and community composition at a given time point are factors that may affect the microbial composition at a later time point, though it is still not settled. Specifically, it has been recently suggested that only a minority of the microbes depend on the microbial composition in earlier times. To address the issue of identifying and predicting temporal microbial patterns we developed a new model, MTV-LMM (Microbial Temporal Variability Linear Mixed Model), a linear mixed model for the prediction of the microbial community temporal dynamics based on the community composition at previous time stamps. MTV-LMM can identify time-dependent microbes in time series datasets, which can then be used to analyze the trajectory of the microbiome over time (Shenhav, Furman, et al. 2019). Additionally we developed together with our colleagues a tool for identifying the sources and origins of the microbiome (Shenhav, Thompson, et al. 2019), Fast Expectation-mAximization microbial Source Tracking (FEAST), is a ready-to-use scalable framework that can simultaneously estimate the contribution of thousands of potential source environments in a timely manner, thereby helping unravel the origins of complex microbial communities.
-For the study of the mobile elements in natural microbial ecosystems, we have developed a set of bioinformatic tools (Pellow et al. 2021; Rozov et al. 2017). In 2017, we introduced Recycler (Rozov et al. 2017), the first tool that can extract complete circular contigs from sequence data of isolated microbial genomes, plasmidomes and metagenome sequence data We then improved it by developing SCAPP in 2021 (Sequence Contents-Aware Plasmid Peeler)—an algorithm and tool to assemble plasmid sequences from metagenomic sequencing. SCAPP builds on some key ideas from the Recycler algorithm while improving plasmid assemblies by integrating biological knowledge about plasmids (Pellow et al. 2021). In addition, PlasClass was developed to improve plasmid sequence classification (Pellow, Mizrahi, and Shamir 2020).
-Given the highly dynamic and complex nature of the gut microbial community, the ability to identify and predict time-dependent compositional patterns of microbes is crucial to our understanding of the structure and function of this ecosystem. Microbial interactions and community composition at a given time point are factors that may affect the microbial composition at a later time point, though it is still not settled. Specifically, it has been recently suggested that only a minority of the microbes depend on the microbial composition in earlier times. To address the issue of identifying and predicting temporal microbial patterns we developed a new model, MTV-LMM (Microbial Temporal Variability Linear Mixed Model), a linear mixed model for the prediction of the microbial community temporal dynamics based on the community composition at previous time stamps. MTV-LMM can identify time-dependent microbes in time series datasets, which can then be used to analyze the trajectory of the microbiome over time (Shenhav, Furman, et al. 2019). Additionally we developed together with our colleagues a tool for identifying the sources and origins of the microbiome (Shenhav, Thompson, et al. 2019), Fast Expectation-mAximization microbial Source Tracking (FEAST), is a ready-to-use scalable framework that can simultaneously estimate the contribution of thousands of potential source environments in a timely manner, thereby helping unravel the origins of complex microbial communities.