Construction and Modeling of a Coculture Microplate for Real-Time Measurement of Microbial Interactions

Metabolic picture of microbial interaction: chemical crosstalk during co-cultivation between three dominant genera of bacteria and fungi in medicinal plants rhizosphere

INTRODUCTION

Microbial communities affect several aspects of the earth's ecosystem through their metabolic interaction. The dynamics of this interaction emerge from complex multilevel networks of crosstalk. Elucidation of this interaction could help us to maintain the balance for a sustainable future.

OBJECTIVES

To investigate the chemical language among highly abundant microbial genera in the rhizospheres of medicinal plants based on the metabolomic analysis at the interaction level.

METHODS

Coculturing experiments involving three microbial species: Aspergillus (A), Trichoderma (T), and Bacillus (B), representing fungi (A, T) and bacteria (B), respectively. These experiments encompassed various interaction levels, including dual cultures (AB, AT, TB) and triple cultures (ATB). Metabolic profiling by LC-QTOFMS revealed the effect of interaction level on the productivity and diversity of microbial specialized metabolites.

RESULTS

The ATB interaction had the richest profile, while the bacterial profile in the monoculture condition had the lowest. Two native compounds of the Aspergillus genus, aspergillic acid and the dipeptide asperopiperazine B, exhibited decreased levels in the presence of the AT interaction and were undetectable in the presence of bacteria during the interaction. Trichodermarin N and Trichodermatide D isolated from Trichoderma species exclusively detected during coexistence with bacteria (TB and ATB). These findings indicate that the presence of Bacillus activates cryptic biosynthetic gene clusters in Trichoderma. The antibacterial activity of mixed culture extracts was stronger than that of the monoculture extracts. The TB extract exhibited strong antifungal activity compared to the monoculture extract and other mixed culture treatments.

CONCLUSION

The elucidation of medicinal plant microbiome interaction chemistry and its effect on the environment will also be of great interest in the context of medicinal plant health Additionally, it sheds light on the content of bioactive constituents, and facilitating the discovery of novel antimicrobials.

Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D in vitro tissue models of disease

Rapid advances in tissue engineering have resulted in more complex and physiologically relevant 3D in vitro tissue models with applications in fundamental biology and therapeutic development. However, the complexity provided by these models is often not leveraged fully due to the reductionist methods used to analyze them. Computational and mathematical models developed in the field of systems biology can address this issue. Yet, traditional systems biology has been mostly applied to simpler in vitro models with little physiological relevance and limited cellular complexity. Therefore, integrating these two inherently interdisciplinary fields can result in new insights and move both disciplines forward. In this review, we provide a systematic overview of how systems biology has been integrated with 3D in vitro tissue models and discuss key application areas where the synergies between both fields have led to important advances with potential translational impact. We then outline key directions for future research and discuss a framework for further integration between fields.

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Genome-scale community modelling reveals conserved metabolic cross-feedings in epipelagic bacterioplankton communities

Marine microorganisms form complex communities of interacting organisms that influence central ecosystem functions in the ocean such as primary production and nutrient cycling. Identifying the mechanisms controlling their assembly and activities is a major challenge in microbial ecology. Here, we integrated Tara Oceans meta-omics data to predict genome-scale community interactions within prokaryotic assemblages in the euphotic ocean. A global genome-resolved co-activity network revealed a significant number of inter-lineage associations across diverse phylogenetic distances. Identified co-active communities include species displaying smaller genomes but encoding a higher potential for quorum sensing, biofilm formation, and secondary metabolism. Community metabolic modelling reveals a higher potential for interaction within co-active communities and points towards conserved metabolic cross-feedings, in particular of specific amino acids and group B vitamins. Our integrated ecological and metabolic modelling approach suggests that genome streamlining and metabolic auxotrophies may act as joint mechanisms shaping bacterioplankton community assembly in the global ocean surface.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Culturing the unculturables: strategies, challenges, and opportunities for gut microbiome study

Metagenome sequencing techniques revolutionized the field of gut microbiome study. However, it is equipped with experimental and computational biases, which affect the downstream analysis results. Also, live microbial strains are needed for a better understanding of host-microbial crosstalks and for designing next-generation treatment therapies based on probiotic strains and postbiotic molecules. Conventional culturing methodologies are insufficient to get the dark gut matter on the plate; therefore, there is an urgent need to propose novel culturing methods that can fill the limitations of metagenomics. The current work aims to provide a consolidated evaluation of the available methods for host-microbe interaction with an emphasis on in vitro culturing of gut microbes using organoids, gut on a chip, and gut bioreactor. Further, the knowledge of microbial crosstalk in the gut helps us to identify core microbiota, and key metabolites that will aid in designing culturing media and co-culturing systems for gut microbiome study. After the deeper mining of the current culturing methods, we recommend that 3D-printed intestinal cells in a multistage continuous flow reactor equipped with an extended organoid system might be a good practical choice for gut microbiota-based studies.

Microbial interactions in theory and practice: when are measurements compatible with models?

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.

Guild and Niche Determination Enable Targeted Alteration of the Microbiome

Microbiome science has greatly contributed to our understanding of microbial life and its essential roles for the environment and human health1-5. However, the nature of microbial interactions and how microbial communities respond to perturbations remains poorly understood, resulting in an often descriptive and correlation-based approach to microbiome research6-8. Achieving causal and predictive microbiome science would require direct functional measurements in complex communities to better understand the metabolic role of each member and its interactions with others. In this study we present a new approach that integrates transcription and translation measurements to predict competition and substrate preferences within microbial communities, consequently enabling the selective manipulation of the microbiome. By performing metatranscriptomic (metaRNA-Seq) and metatranslatomic (metaRibo-Seq) analysis in complex samples, we classified microbes into functional groups (i.e. guilds) and demonstrated that members of the same guild are competitors. Furthermore, we predicted preferred substrates based on importer proteins, which specifically benefited selected microbes in the community (i.e. their niche) and simultaneously impaired their competitors. We demonstrated the scalability of microbial guild and niche determination to natural samples and its ability to successfully manipulate microorganisms in complex microbiomes. Thus, the approach enhances the design of pre- and probiotic interventions to selectively alter members within microbial communities, advances our understanding of microbial interactions, and paves the way for establishing causality in microbiome science.