Toward merging bottom-up and top-down model-based designing of synthetic microbial communities

Deciphering and designing microbial communities by genome-scale metabolic modelling

Microbial communities are shaped by the complex interactions among organisms and the environment. Genome-scale metabolic models (GEMs) can provide deeper insights into the complexity and ecological properties of various microbial communities, revealing their intricate interactions. Many researchers have modified GEMs for the microbial communities based on specific needs. Thus, GEMs need to be comprehensively summarized to better understand the trends in their development. In this review, we summarized the key developments in deciphering and designing microbial communities using different GEMs. A timeline of selected highlights in GEMs indicated that this area is evolving from the single-strain level to the microbial community level. Then, we outlined a framework for constructing GEMs of microbial communities. We also summarized the models and resources of static and dynamic community-level GEMs. We focused on the role of external environmental and intracellular resources in shaping the assembly of microbial communities. Finally, we discussed the key challenges and future directions of GEMs, focusing on the integration of GEMs with quorum sensing mechanisms, microbial ecology interactions, machine learning algorithms, and automatic modeling, all of which contribute to consortia-based applications in different fields.

Assembly of functional microbial ecosystems: from molecular circuits to communities

Microbes compete and cooperate with each other via a variety of chemicals and circuits. Recently, to decipher, simulate, or reconstruct microbial communities, many researches have been engaged in engineering microbiomes with bottom-up synthetic biology approaches for diverse applications. However, they have been separately focused on individual perspectives including genetic circuits, communications tools, microbiome engineering, or promising applications. The strategies for coordinating microbial ecosystems based on different regulation circuits have not been systematically summarized, which calls for a more comprehensive framework for the assembly of microbial communities. In this review, we summarize diverse cross-talk and orthogonal regulation modules for de novo bottom-up assembling functional microbial ecosystems, thus promoting further consortia-based applications. First, we review the cross-talk communication-based regulations among various microbial communities from intra-species and inter-species aspects. Then, orthogonal regulations are summarized at metabolites, transcription, translation, and post-translation levels, respectively. Furthermore, to give more details for better design and optimize various microbial ecosystems, we propose a more comprehensive design-build-test-learn procedure including function specification, chassis selection, interaction design, system build, performance test, modeling analysis, and global optimization. Finally, current challenges and opportunities are discussed for the further development and application of microbial ecosystems.

A metabolic modeling-based framework for predicting trophic dependencies in native rhizobiomes of crop plants

The exchange of metabolites (i.e., metabolic interactions) between bacteria in the rhizosphere determines various plant-associated functions. Systematically understanding the metabolic interactions in the rhizosphere, as well as in other types of microbial communities, would open the door to the optimization of specific predefined functions of interest, and therefore to the harnessing of the functionality of various types of microbiomes. However, mechanistic knowledge regarding the gathering and interpretation of these interactions is limited. Here, we present a framework utilizing genomics and constraint-based modeling approaches, aiming to interpret the hierarchical trophic interactions in the soil environment. 243 genome scale metabolic models of bacteria associated with a specific disease-suppressive vs disease-conducive apple rhizospheres were drafted based on genome-resolved metagenomes, comprising an in silico native microbial community. Iteratively simulating microbial community members' growth in a metabolomics-based apple root-like environment produced novel data on potential trophic successions, used to form a network of communal trophic dependencies. Network-based analyses have characterized interactions associated with beneficial vs non-beneficial microbiome functioning, pinpointing specific compounds and microbial species as potential disease supporting and suppressing agents. This framework provides a means for capturing trophic interactions and formulating a range of testable hypotheses regarding the metabolic capabilities of microbial communities within their natural environment. Essentially, it can be applied to different environments and biological landscapes, elucidating the conditions for the targeted manipulation of various microbiomes, and the execution of countless predefined functions.

Engineering Microbial Consortia as Living Materials: Advances and Prospectives

The field of Engineered Living Materials (ELMs) integrates engineered living organisms into natural biomaterials to achieve diverse objectives. Multiorganism consortia, prevalent in both naturally occurring and synthetic microbial cultures, exhibit complex functionalities and interrelationships, extending the scope of what can be achieved with individual engineered bacterial strains. However, the ELMs comprising microbial consortia are still in the developmental stage. In this Review, we introduce two strategies for designing ELMs constituted of microbial consortia: a top-down strategy, which involves characterizing microbial interactions and mimicking and reconstructing natural ecosystems, and a bottom-up strategy, which entails the rational design of synthetic consortia and their assembly with material substrates to achieve user-defined functions. Next, we summarize technologies from synthetic biology that facilitate the efficient engineering of microbial consortia for performing tasks more complex than those that can be done with single bacterial strains. Finally, we discuss essential challenges and future perspectives for microbial consortia-based ELMs.

Synthetic microbial communities: A gateway to understanding resistance, resilience, and functionality in spontaneously fermented food microbiomes

This review delves into the intricate traits of microbial communities encountered in spontaneously fermented foods (SFF), contributing to resistance, resilience, and functionality drivers. Traits of SFF microbiomes comprise of fluctuations in community composition, genetic stability, and condition-specific phenotypes. Synthetic microbial communities (SMCs) serve as a portal for mechanistic insights and strategic re-programming of microbial communities. Current literature underscores the pivotal role of microbiomes in SFF in shaping quality attributes and preserving the cultural heritage of their origin. In contrast to starter driven fermentations that tend to be more controlled but lacking the capacity to maintain or reproduce the complex flavors and intricacies found in SFF. SMCs, therefore, become indispensable tools, providing a nuanced understanding and control over fermented food microbiomes. They empower the prediction and engineering of microbial interactions and metabolic pathways with the aim of optimizing outcomes in food processing. Summarizing the current application of SMCs in fermented foods, there is still space for improvement. Challenges in achieving stability and reproducibility in SMCs are identified, stemming from non-standardized approaches. The future direction should involve embracing standardized protocols, advanced monitoring tools, and synthetic biology applications. A holistic, multi-disciplinary approach is paramount to unleashing the full potential of SMCs and fostering sustainable and innovative applications in fermented food systems.

The optimization of microbial functions through rational environmental manipulations

Microorganisms play a central role in biotechnology and it is key that we develop strategies to engineer and optimize their functionality. To this end, most efforts have focused on introducing genetic manipulations in microorganisms which are then grown either in monoculture or in mixed-species consortia. An alternative strategy to optimize microbial processes is to rationally engineer the environment in which microbes grow. The microbial environment is multidimensional, including factors such as temperature, pH, salinity, nutrient composition, etc. These environmental factors all influence the growth and phenotypes of microorganisms and they generally "interact" with one another, combining their effects in complex, non-additive ways. In this piece, we overview the origins and consequences of these "interactions" between environmental factors and discuss how they have been built into statistical, bottom-up predictive models of microbial function to identify optimal environmental conditions for monocultures and microbial consortia. We also overview alternative "top-down" approaches, such as genetic algorithms, to finding optimal combinations of environmental factors. By providing a brief summary of the state of this field, we hope to stimulate further work on the rational manipulation and optimization of the microbial environment.

Recent advances in genome-scale engineering in Escherichia coli and their applications

Owing to the rapid advancement of genome engineering technologies, the scale of genome engineering has expanded dramatically. Genome editing has progressed from one genomic alteration at a time that could only be employed in few species, to the simultaneous generation of multiple modifications across many genomic loci in numerous species. The development and recent advances in multiplex automated genome engineering (MAGE)-associated technologies and clustered regularly interspaced short palindromic repeats and their associated protein (CRISPR-Cas)-based approaches, together with genome-scale synthesis technologies offer unprecedented opportunities for advancing genome-scale engineering in a broader range. These approaches provide new tools to generate strains with desired phenotypes, understand the complexity of biological systems, and directly evolve a genome with novel features. Here, we review the recent major advances in genome-scale engineering tools developed for Escherichia coli, focusing on their applications in identifying essential genes, genome reduction, recoding, and beyond.

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

Plants and endophytes interaction: a "secret wedlock" for sustainable biosynthesis of pharmaceutically important secondary metabolites

Many plants possess immense pharmacological properties because of the presence of various therapeutic bioactive secondary metabolites that are of great importance in many pharmaceutical industries. Therefore, to strike a balance between meeting industry demands and conserving natural habitats, medicinal plants are being cultivated on a large scale. However, to enhance the yield and simultaneously manage the various pest infestations, agrochemicals are being routinely used that have a detrimental impact on the whole ecosystem, ranging from biodiversity loss to water pollution, soil degradation, nutrient imbalance and enormous health hazards to both consumers and agricultural workers. To address the challenges, biological eco-friendly alternatives are being looked upon with high hopes where endophytes pitch in as key players due to their tight association with the host plants. The intricate interplay between plants and endophytic microorganisms has emerged as a captivating subject of scientific investigation, with profound implications for the sustainable biosynthesis of pharmaceutically important secondary metabolites. This review delves into the hidden world of the "secret wedlock" between plants and endophytes, elucidating their multifaceted interactions that underpin the synthesis of bioactive compounds with medicinal significance in their plant hosts. Here, we briefly review endophytic diversity association with medicinal plants and highlight the potential role of core endomicrobiome. We also propose that successful implementation of in situ microbiome manipulation through high-end techniques can pave the way towards a more sustainable and pharmaceutically enriched future.

Inferring microbial interactions with their environment from genomic and metagenomic data

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized, and so name our tool MetConSIN: Metabolically Contextualized Species Interaction Networks.

An ecological explanation for carbon source-associated denitrification performance in wastewater treatment plants

The underlying mechanism associated with the roles of dosed carbon source in denitrification performance remains largely unknown. In this study, three denitrifying consortia (DNC) were constructed via evolutionary top-down enrichment method with well-defined conditions and specific carbon sources (acetate, glucose and their mixture). The reactor operation shows that nearly complete nitrate removal was achieved; however, the glucose feeding resulted in much higher concentrations of biomass and non-settable flocs. The 16S rRNA sequencing suggests that the bacterial diversity of the acetate-fed DNC was significantly higher than those of acetate/glucose-fed and glucose-fed DNCs. The dentrifying population in the acetate-fed DNC was dominated by Propionivibrio (16.1 %) and Thauera (3.4 %); whereas those of acetate/glucose- and glucose-fed DNCs were dominated by Pleomorphomonas (21.5 % and 26.3 %, respectively). Interestingly, the supernatant of acetate-fed DNC contained a high abundance of genera Thauera (averaged at 85.1 %), indicating the free-living nature of Thauera. Both PICURSt2 analysis of 16S rRNA sequencing and metagenomic analysis indicate that the acetate-fed DNC contained higher abundances of denitrifying genes; the acetate/glucose-fed and glucose-fed DNCs, in comparison, enriched genes related to glucose transportation and metabolism. Additionally, the acetate-fed DNC had better network stability than other two groups. This study adds important knowledge regarding the ecological traits of DNC, providing important clues for rational addition of carbon sources in wastewater treatment plants.

The phytomicrobiome: solving plant stress tolerance under climate change

With extraordinary global climate changes, increased episodes of extreme conditions result in continuous but complex interaction of environmental variables with plant life. Exploring natural phytomicrobiome species can provide a crucial resource of beneficial microbes that can improve plant growth and productivity through nutrient uptake, secondary metabolite production, and resistance against pathogenicity and abiotic stresses. The phytomicrobiome composition, diversity, and function strongly depend on the plant's genotype and climatic conditions. Currently, most studies have focused on elucidating microbial community abundance and diversity in the phytomicrobiome, covering bacterial communities. However, least is known about understanding the holistic phytomicrobiome composition and how they interact and function in stress conditions. This review identifies several gaps and essential questions that could enhance understanding of the complex interaction of microbiome, plant, and climate change. Utilizing eco-friendly approaches of naturally occurring synthetic microbial communities that enhance plant stress tolerance and leave fewer carbon-foot prints has been emphasized. However, understanding the mechanisms involved in stress signaling and responses by phytomicrobiome species under spatial and temporal climate changes is extremely important. Furthermore, the bacterial and fungal biome have been studied extensively, but the holistic interactome with archaea, viruses, oomycetes, protozoa, algae, and nematodes has seldom been studied. The inter-kingdom diversity, function, and potential role in improving environmental stress responses of plants are considerably important. In addition, much remains to be understood across organismal and ecosystem-level responses under dynamic and complex climate change conditions.

More Than the Sum of Its Parts: Unlocking the Power of Network Structure for Understanding Organization and Function in Microbiomes

Plant and soil microbiomes are integral to the health and productivity of plants and ecosystems, yet researchers struggle to identify microbiome characteristics important for providing beneficial outcomes. Network analysis offers a shift in analytical framework beyond "who is present" to the organization or patterns of coexistence between microbes within the microbiome. Because microbial phenotypes are often significantly impacted by coexisting populations, patterns of coexistence within microbiomes are likely to be especially important in predicting functional outcomes. Here, we provide an overview of the how and why of network analysis in microbiome research, highlighting the ways in which network analyses have provided novel insights into microbiome organization and functional capacities, the diverse network roles of different microbial populations, and the eco-evolutionary dynamics of plant and soil microbiomes.

Engineering membrane architecture for biotechnological applications

Cellular membranes, predominantly described as a dynamic bilayer, are composed of different lipids, transmembrane proteins, and carbohydrates. Most research on biological membranes focuses on the identification, characterization, and mechanistic aspects of their different components. These studies provide a fundamental understanding of membrane structure, function, and dynamics, establishing a basis for the development of membrane engineering strategies. To date, approaches in this field concentrate on membrane adaptation to harsh conditions during industrial fermentation, which can be caused by temperature, osmotic, or organic solvent stress. With advances in the field of metabolic engineering and synthetic biology, recent breakthroughs include proof of concept microbial production of essential medicines, such as cannabinoids and vinblastine. However, long pathways, low yields, and host adaptation continue to pose challenges to the efficient scale up production of many important compounds. The lipid bilayer is profoundly linked to the activity of heterologous membrane-bound enzymes and transport of metabolites. Therefore, strategies for improving enzyme performance, facilitating pathway reconstruction, and enabling storage of products to increase the yields directly involve cellular membranes. At the forefront of membrane engineering research are re-emerging approaches in lipid research and synthetic biology that manipulate membrane size and composition and target lipid profiles across species. This review summarizes engineering strategies applied to cellular membranes and discusses the challenges and future perspectives, particularly with regards to their applications in host engineering and bioproduction.

Dissecting skin microbiota and microenvironment for the development of therapeutic strategies

The skin is a pivotal barrier between the human body and the environment, and is a habitat for numerous microorganisms. While host-microbiota interactions in the skin are essential for homeostasis, disturbances in microbial composition and the abnormal growth of certain bacteria are associated with various diseases. Here, we identify strains and communities of skin commensals that contribute to or impair skin barrier function. Furthermore, we discuss the skin microenvironments suitable for specific microbiota that exert therapeutic effects and suggest focus areas for the prospective development of therapeutic strategies using bacterial agents. Finally, we highlight recent efforts to treat skin diseases associated with live bacteria.

Enhancing plant growth promoting rhizobacterial activities through consortium exposure: A review

Plant Growth Promoting Rhizobacteria (PGPR) has gained immense importance in the last decade due to its in-depth study and the role of the rhizosphere as an ecological unit in the biosphere. A putative PGPR is considered PGPR only when it may have a positive impact on the plant after inoculation. From the various pieces of literature, it has been found that these bacteria improve the growth of plants and their products through their plant growth-promoting activities. A microbial consortium has a positive effect on plant growth-promoting (PGP) activities evident by the literature. In the natural ecosystem, rhizobacteria interact synergistically and antagonistically with each other in the form of a consortium, but in a natural consortium, there are various oscillating environmental conditions that affect the potential mechanism of the consortium. For the sustainable development of our ecological environment, it is our utmost necessity to maintain the stability of the rhizobacterial consortium in fluctuating environmental conditions. In the last decade, various studies have been conducted to design synthetic rhizobacterial consortium that helps to integrate cross-feeding over microbial strains and reveal their social interactions. In this review, the authors have emphasized covering all the studies on designing synthetic rhizobacterial consortiums, their strategies, mechanism, and their application in the field of environmental ecology and biotechnology.

Assembly strategies for polyethylene-degrading microbial consortia based on the combination of omics tools and the "Plastisphere"

Numerous microorganisms and other invertebrates that are able to degrade polyethylene (PE) have been reported. However, studies on PE biodegradation are still limited due to its extreme stability and the lack of explicit insights into the mechanisms and efficient enzymes involved in its metabolism by microorganisms. In this review, current studies of PE biodegradation, including the fundamental stages, important microorganisms and enzymes, and functional microbial consortia, were examined. Considering the bottlenecks in the construction of PE-degrading consortia, a combination of top-down and bottom-up approaches is proposed to identify the mechanisms and metabolites of PE degradation, related enzymes, and efficient synthetic microbial consortia. In addition, the exploration of the plastisphere based on omics tools is proposed as a future principal research direction for the construction of synthetic microbial consortia for PE degradation. Combining chemical and biological upcycling processes for PE waste could be widely applied in various fields to promote a sustainable environment.