Rbec: a tool for analysis of amplicon sequencing data from synthetic microbial communities

Synthetic microbial communities (SynComs) constitute an emerging and powerful tool in biological, biomedical, and biotechnological research. Despite recent advances in algorithms for the analysis of culture-independent amplicon sequencing data from microbial communities, there is a lack of tools specifically designed for analyzing SynCom data, where reference sequences for each strain are available. Here we present Rbec, a tool designed for the analysis of SynCom data that accurately corrects PCR and sequencing errors in amplicon sequences and identifies intra-strain polymorphic variation. Extensive evaluation using mock bacterial and fungal communities show that our tool outperforms current methods for samples of varying complexity, diversity, and sequencing depth. Furthermore, Rbec also allows accurate detection of contaminants in SynCom experiments.

Chaos in small microbial communities

Predictability is a fundamental requirement in biological engineering. As we move to building coordinated multicellular systems, the potential for such systems to display chaotic behaviour becomes a concern. Therefore understanding which systems show chaos is an important design consideration. We developed a methodology to explore the potential for chaotic dynamics in small microbial communities governed by resource competition, intercellular communication and competitive bacteriocin interactions. We show that we can expect to find chaotic states in relatively small synthetic microbial systems, understand the governing dynamics and provide insights into how to control such systems. This work is the first to query the existence of chaotic behaviour in synthetic microbial communities and has important ramifications for the fields of biotechnology, bioprocessing and synthetic biology.

From Microbial Dynamics to Functionality in the Rhizosphere: A Systematic Review of the Opportunities With Synthetic Microbial Communities

Synthetic microbial communities (SynComs) are a useful tool for a more realistic understanding of the outcomes of multiple biotic interactions where microbes, plants, and the environment are players in time and space of a multidimensional and complex system. Toward a more in-depth overview of the knowledge that has been achieved using SynComs in the rhizosphere, a systematic review of the literature on SynComs was performed to identify the overall rationale, design criteria, experimental procedures, and outcomes of in vitro or in planta tests using this strategy. After an extensive bibliography search and a specific selection process, a total of 30 articles were chosen for further analysis, grouping them by their reported SynCom size. The reported SynComs were constituted with a highly variable number of members, ranging from 3 to 190 strains, with a total of 1,393 bacterial isolates, where the three most represented phyla were Proteobacteria, Actinobacteria, and Firmicutes. Only four articles did not reference experiments with SynCom on plants, as they considered only microbial in vitro studies, whereas the others chose different plant models and plant-growth systems; some of them are described and reviewed in this article. Besides, a discussion on different approaches (bottom-up and top-down) to study the microbiome role in the rhizosphere is provided, highlighting how SynComs are an effective system to connect and fill some knowledge gaps and to have a better understanding of the mechanisms governing these multiple interactions. Although the SynCom approach is already helpful and has a promising future, more systematic and standardized studies are needed to harness its full potential.

Legume tasters: symbiotic rhizobia host preference and smart inoculant formulations

Mutualistic interactions have great importance in ecology, with genetic information that takes shape through interactions within the symbiotic partners and between the partners and the environment. It is known that variation of the host-associated microbiome contributes to buffer adaptation challenges of the host’s physiology when facing varying environmental conditions. In agriculture, pivotal examples are symbiotic nitrogen-fixing rhizobia, known to contribute greatly to host (legume plants) adaptation and host productivity. A holistic view of increasing crop yield and resistance to biotic and abiotic stresses is that of microbiome engineering, the exploitation of a host-associated microbiome through its rationally designed manipulation with synthetic microbial communities. However, several studies highlighted that the expression of the desired phenotype in the host resides in species-specific, even genotype-specific interactions between the symbiotic partners. Consequently, there is a need to dissect such an intimate level of interaction, aiming to identify the main genetic components in both partners playing a role in symbiotic differences/host preferences. In the present paper, while briefly reviewing the knowledge and the challenges in plant–microbe interaction and rhizobial studies, we aim to promote research on genotype x genotype interaction between rhizobia and host plants for a rational design of synthetic symbiotic nitrogen-fixing microbial communities to be used for sustainably improving leguminous plants yield.

Microbial Interactions within the Cheese Ecosystem and Their Application to Improve Quality and Safety

The cheese microbiota comprises a consortium of prokaryotic, eukaryotic and viral populations, among which lactic acid bacteria (LAB) are majority components with a prominent role during manufacturing and ripening. The assortment, numbers and proportions of LAB and other microbial biotypes making up the microbiota of cheese are affected by a range of biotic and abiotic factors. Cooperative and competitive interactions between distinct members of the microbiota may occur, with rheological, organoleptic and safety implications for ripened cheese. However, the mechanistic details of these interactions, and their functional consequences, are largely unknown. Acquiring such knowledge is important if we are to predict when fermentations will be successful and understand the causes of technological failures. The experimental use of “synthetic” microbial communities might help throw light on the dynamics of different cheese microbiota components and the interplay between them. Although synthetic communities cannot reproduce entirely the natural microbial diversity in cheese, they could help reveal basic principles governing the interactions between microbial types and perhaps allow multi-species microbial communities to be developed as functional starters. By occupying the whole ecosystem taxonomically and functionally, microbiota-based cultures might be expected to be more resilient and efficient than conventional starters in the development of unique sensorial properties.

Automated design of synthetic microbial communities

Microbial species rarely exist in isolation. In naturally occurring microbial systems there is strong evidence for a positive relationship between species diversity and productivity of communities. The pervasiveness of these communities in nature highlights possible advantages for genetically engineered strains to exist in cocultures as well. Building synthetic microbial communities allows us to create distributed systems that mitigate issues often found in engineering a monoculture, especially as functional complexity increases. Here, we demonstrate a methodology for designing robust synthetic communities that include competition for nutrients, and use quorum sensing to control amensal bacteriocin interactions in a chemostat environment. We computationally explore all two- and three- strain systems, using Bayesian methods to perform model selection, and identify the most robust candidates for producing stable steady state communities. Our findings highlight important interaction motifs that provide stability, and identify requirements for selecting genetic parts and further tuning the community composition.

Reference-based error correction of amplicon sequencing data from synthetic communities

MotivationSynthetic microbial communities (SynComs) constitute an emergent and powerful tool in biological, biomedical, and biotechnological research. Despite recent advances in algorithms for analysis of culture-independent amplicon sequencing data from microbial communities, there is a lack of tools specifically designed for analysing SynCom data, where reference sequences for each strain are available.ResultsHere we present Rbec, a tool designed for analysing SynCom data that outperforms current methods by accurately correcting errors in amplicon sequences and identifying intra-strain polymorphic variation. Extensive evaluation using mock bacterial and fungal communities show that our tool performs robustly for samples of varying complexity, diversity, and sequencing depth. Further, Rbec also allows accurate detection of contaminations in SynCom experiments.AvailabilityRbec is freely available as an open-source R package and can be downloaded at: https://github.com/PengfanZhang/Microbiome.