Vicente Acuña – Natalia Jiménez
Title: Growth-Abundance Metabolic Mode Analysis of microbial communities (GammaCOM)
Abstract: Microbial communities undergo processes that result in synthesis of complex products which allow them to thrive and adapt to extreme environments. Understanding metabolic interactions between members of these microbial consortia is key to characterize their behavior and propose new strategies for the biotechnological industry.
Several hypotheses made in systems biology approaches for studying single cell organisms do not hold in mixed cultures or communities. Particularly, it is not clear that these organisms maximize their biomass whilst sharing resources and that they are constantly exploiting all available resources for cell growth.
In this talk we provide a new approach for characterizing metabolic interactions in microbial communities, where exploration of sub optimal states and different community compositions is performed to characterize the wide array of metabolic states reachable by microbial communities.
Title: Platforms for studying the gut microbiome’s role in the transmission dynamics of antimicrobial-resistant bacteria
Title: Development of computational methods for the prediction of metabolic interactions in human gut microbial consortia
Abstract: The bacterial community harbored by the human gut has gained great attention due to its effect on human health. The metabolic activity carried out by different bacterial consortia of individuals influences the inflammatory state of the gut lumen. Short Chain Fatty Acids (SCFA) are essential compounds produced and consumed by keystone species in the gut and their absence is correlated with various chronical diseases, like diabetes type II, Crohn’s disease, among others. Despite their importance, the interaction network between microbial members of this community is not well understood.
Constraint-Based Modeling has been frequently used to analyze the metabolic behavior of microbial consortia, as they enable the simulation of metabolite production, consumption and growth of groups of microorganisms. This, in turn, enables inferring metabolic interactions (i.e., cross-feeding) amongst members of the community and their nature (commensalism, competition, mutualism, etc.). The metabolic potential of a cell can be mathematically described by the Conversions Cone and it is represented by a set of flux vectors that describe which compounds can be produced/consumed by the network at steady-state. Application of this concept to microbial communities would enable the identification of possible interactions between its members. Here, we present advances in the development of scalable algorithms to comprehensively study the Conversions Cone of microbial members of the human gut microbiota. Monte Carlo sampling methods can be then applied to identify significant conversions underpinning cross-feeding interactions related to SCFAs production. As a result of this analysis, we expect to obtain an in silico interaction network that reveals key aspects of the cross-feeding of SCFA in the human gut.
Title: Multi-omics data integration
Abstract: The technological advances and accumulation of biomedical datasets are yielding unprecedented opportunities to better understand genetic diseases. However, translating massive and heterogeneous data into knowledge necessitates proper exploration and integration tools. The talk will focus on different computational strategies for the integration of heterogeneous omics datasets. I will first describe multilayer networks that incorporate different sources of biological interactions, as well as associated network exploration algorithms. I will then detail joint dimensionality reduction to extract biological knowledge simultaneously from multiple omics.
Alex Di Genova
Title: Characterizing the human gut microbiome through the lens of metagenomics and metabolic models
Abstract: Metagenomics has triggered a change in paradigm regarding the characterisation of microbiotas. The ever increasing number of samples makes it possible to build new models describing the diversity of species and functions inhabiting complex environment. In this talk, I will focus on the human gut microbiota and present two recent works. The first one aims at finding patterns in the diversity of bacterial composition in the gut. I will show how such large-scale metagenomic samples can be functionally-screened using metabolic networks. In the second part, I will illustrate a mathematical framework dedicated to facilitate the computation of metabolic simulations with the example of the Salmonella infection dynamics in the gut.
Title: Towards a marine agronomy of seaweed holobionts
Abstract: Seaweed aquaculture can gain in productivity and resilience if we can promote the domestication of cultivated species (most of which being still wild). This project explores the genetic basis of traits relevant for aquaculture, taking into consideration the interaction between the seaweed genome, the associated microbial metagenome and the physico-chemical environment. In addition, we aim at determining the optimal breeding strategies to maximize selection efficiency at the holobiont scale, taking into consideration the huge diversity of reproductive systems and complex life cycles of seaweeds. This presentation will briefly overview the general questions and approaches of the Nucleo Milenio Marine Agronomy of Seaweed Holobionts.
Title: SYSTEMIX: Systems Biology Center for the study of extremophile communities from mining tailings.
Abstract: With the opening of the “El Teniente” mine in 1905, Chile launched the large-scale exploitation of copper called the “Gran Minería del Cobre”. Since then, 757 mining tailings have been registered, of which 85% have been abandoned or remained inactive. In particular, the Cauquenes tailing located in the O’Higgins Region is, to date, the oldest and largest copper tailing reservoir of the material deposited by El Teniente. In this context, identifying and characterizing communities of extremophile microorganisms that inhabit the Cauquenes tailing will provide valuable information about the structure of these communities and how they have been maintained or changed over time. In addition, studying their metabolic capacities and how they interact inside the community is essential for understanding the adaptation of organisms to an extreme environment. The latter has not been practically addressed to date in any mining tailings, and exploring this part of the Chilean Heritage might be the source of attractive biotechnological products.
For these reasons, and through the integration of the various capacities of national and international researchers, this project seeks to establish the foundations for creating a Systems Biology Center to study the communities that inhabit mining tailings. At the research level, we seek for: i) Characterization of the structure of the extremophile communities; ii) Identification and validation of the metabolic potentials of the communities and their members; iii) To catalog and classify obtained information through the development of a genomic database for collected strains and; iv) Biotechnology applications. Overall, we aim to uncover the functional potential of species that inhabit extreme mining environments.
With a strong regional commitment and using a multidisciplinary and comprehensive perspective, our project will generate valuable molecular, genomic, and phenotypic information about microorganisms from extreme environments, data will be fully available for the Chilean bioinformatic community to promote new bridges of collaboration.
Title: Characterizing microbial interactions in controlled and natural microbial communities
Abstract: The massive development and use of multi omics data permits a better understanding of complex microbial ecosystems at the metabolic level. However, this data and their integration varies depending on the size and characteristics of the considered ecosystems. In this talk, I will discuss of two different approaches applied respectively to a controlled microbial community and natural communities in order to reveal putative bacterium-bacterium interactions. I will first describe how numerical optimisation of metabolic models constrained by genomics and metatranscriptomics data can accurately describe a cheese starter community. I will then detail a discrete method based on only genomic data aiming to characterize the competition and cooperation potentials in natural communities.
Title: Probing metabolic modules and cross-feeding interactions in genome-scale
networks of single organisms and microbial communities
Abstract: Genome-scale metabolic reconstructions seek to represent all biochemical
reactions that an organism can accomplish. While these reconstructions are a
rich source of information, their complex nature often difficult their
analysis. In this talk, I will review effective strategies and methods for
probing specific structural properties of these networks. In particular, I
will present recent applications tackling two common problems for their
analysis: i) identification of biologically relevant modules in large
metabolic networks (illustrated in E. coli and human metabolism), and ii)
prediction of experimentally valid cross-feeding interactions between
microbial members of the human gut microbiota (illustrated in P. dorei and
L. symbiosum co-cultures). Finally, I will offer my perspective on some of
the challenges lying ahead.
Title: In silico screening of metabolic functions of families of species: what can we deduce from genomes and OTUs ?
Abstract: Comparative analysis of Genome-Scale Metabolic Networks (GSMNs) may yield important information on the biology, evolution, and adaptation of species. However, it is impeded by the high heterogeneity of the quality and completeness of structural and functional genome annotations, which may bias the results of such comparisons.
However, the comparison of metabolic capabilities from genome-scale metabolic networks suffers from the available and/or the heterogeneity of the genome annotations at hand. in this talk, we will present different approaches allowing to capture different metabolic features of species according to the level of information at hand on the species and the number of considered species. The methods combine genome annotations, knowledge engineering and sequence comparisons and are integrated in pipelines which allow for the identification of specific functions in OTUs characterizing different conditions (with the tool esmecata), the homogeneisation of genomes for capturing the metabolic specificities of eukaryotes with a given family (with the tool aucome), or the extraction of information about thousands of genomes of MAGs (with the tools mpwt and askomics). This paves the way to large-scale microbial and systems ecology.