Solutions in microbiome engineering: prioritizing barriers to organism establishment

Engineering multi-degrading bacterial communities to bioremediate soils contaminated with pesticides residues

Parallel to the important use of pesticides in conventional agriculture there is a growing interest for green technologies to clear contaminated soil from pesticides and their degradation products. Bioaugmentation i. e. the inoculation of degrading micro-organisms in polluted soil, is a promising method still in needs of further developments. Specifically, improvements in the understanding of how degrading microorganisms must overcome abiotic filters and interact with the autochthonous microbial communities are needed in order to efficiently design bioremediation strategies. Here we designed a protocol aiming at studying the degradation of two herbicides, glyphosate (GLY) and isoproturon (IPU), via experimental modifications of two source bacterial communities. We used statistical methods stemming from genomic prediction to link community composition to herbicides degradation potentials. Our approach proved to be efficient with correlation estimates over 0.8 - between model predictions and measured pesticide degradation values. Multi-degrading bacterial communities were obtained by coalescing bacterial communities with high GLY or IPU degradation ability based on their community-level properties. Finally, we evaluated the efficiency of constructed multi-degrading communities to remove pesticide contamination in a different soil. While results are less clear in the case of GLY, we showed an efficient transfer of degrading capacities towards the receiving soil even at relatively low inoculation levels in the case of IPU. Altogether, we developed an innovative protocol for building multi-degrading simplified bacterial communities with the help of genomic prediction tools and coalescence, and proved their efficiency in a contaminated soil.

Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two Escherichia coli mutants that are metabolically dependent (due to an inability to synthesize essential amino acids) but competitively grow on a shared substrate. The analysis of the E. coli binary consortium using our model not only showed how interactions between the two amino acid auxotrophic mutants are controlled by the dynamic shifts in limiting substrates but also enabled quantifying previously uncharacterizable complex aspects of microbial interactions, such as asymmetry in interactions. Our approach can be extended to other ecological systems to model their environment-dependent interspecies interactions from growth kinetics.IMPORTANCEModeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.

Quorum sensing bacteria improve microbial networks stability and complexity in wastewater treatment plants

Quorum-sensing bacteria (QSB) are crucial factors for microbial communication, yet their ecological role in wastewater treatment plants (WWTPs) remains unclear. Here, we developed a method to identify QSB by comparing 16S rRNA gene sequences. QSB in 388 activated sludge samples collected from 130 WWTPs across China primarily were identified as rare taxa and conditionally rare taxa. A co-occurrence network shared by all sludge communities revealed that QSB exhibited higher average clustering coefficient (0.46) than non-QSB (0.15). Individual sludge networks demonstrated that quorum sensing microbiomes were positively correlated with network robustness and network complexity, including average clustering coefficient and link density. We confirmed that QSB keystones and QSB nodes have a positive impact on network complexity by influencing network modularity through a structural equation model. Meanwhile, QSB communities directly contributed to maintaining network robustness (r = 0.29, P < 0.05). Hence, QSB play an important role in promoting network complexity and stability. Furthermore, QSB communities were positively associated with the functional composition of activated sludge communities (r = 0.33, P < 0.01), especially the denitrification capacity (r = 0.45, P < 0.001). Overall, we elucidated the ecological significance of QSB and provided support for QS-based regulation of activated sludge microbial communities.

Cooperative interactions between invader and resident microbial community members weaken the negative diversity-invasion relationship

The negative diversity-invasion relationship observed in microbial invasion studies is commonly explained by competition between the invader and resident populations. However, whether this relationship is affected by invader-resident cooperative interactions is unknown. Using ecological and mathematical approaches, we examined the survival and functionality of Aminobacter niigataensis MSH1 to mineralize 2,6-dichlorobenzamide (BAM), a groundwater micropollutant affecting drinking water production, in sand microcosms when inoculated together with synthetic assemblies of resident bacteria. The assemblies varied in richness and in strains that interacted pairwise with MSH1, including cooperative and competitive interactions. While overall, the negative diversity-invasion relationship was retained, residents engaging in cooperative interactions with the invader had a positive impact on MSH1 survival and functionality, highlighting the dependency of invasion success on community composition. No correlation existed between community richness and the delay in BAM mineralization by MSH1. The findings suggest that the presence of cooperative residents can alleviate the negative diversity-invasion relationship.

Niche availability and competitive loss by facilitation control proliferation of bacterial strains intended for soil microbiome interventions

Microbiome engineering - the targeted manipulation of microbial communities - is considered a promising strategy to restore ecosystems, but experimental support and mechanistic understanding are required. Here, we show that bacterial inoculants for soil microbiome engineering may fail to establish because they inadvertently facilitate growth of native resident microbiomes. By generating soil microcosms in presence or absence of standardized soil resident communities, we show how different nutrient availabilities limit outgrowth of focal bacterial inoculants (three Pseudomonads), and how this might be improved by adding an artificial, inoculant-selective nutrient niche. Through random paired interaction assays in agarose micro-beads, we demonstrate that, in addition to direct competition, inoculants lose competitiveness by facilitating growth of resident soil bacteria. Metatranscriptomics experiments with toluene as selective nutrient niche for the inoculant Pseudomonas veronii indicate that this facilitation is due to loss and uptake of excreted metabolites by resident taxa. Generation of selective nutrient niches for inoculants may help to favor their proliferation for the duration of their intended action while limiting their competitive loss.

The Complex Interplay Between Antibiotic Resistance and Pharmaceutical and Personal Care Products in the Environment

Antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) are important environmental contaminants. Nonetheless, what drives the evolution, spread, and transmission of antibiotic resistance dissemination is still poorly understood. The abundance of ARB and ARGs is often elevated in human-impacted areas, especially in environments receiving fecal wastes, or in the presence of complex mixtures of chemical contaminants, such as pharmaceuticals and personal care products. Self-replication, mutation, horizontal gene transfer, and adaptation to different environmental conditions contribute to the persistence and proliferation of ARB in habitats under strong anthropogenic influence. Our review discusses the interplay between chemical contaminants and ARB and their respective genes, specifically in reference to co-occurrence, potential biostimulation, and selective pressure effects, and gives an overview of mitigation by existing man-made and natural barriers. Evidence and strategies to improve the assessment of human health risks due to environmental antibiotic resistance are also discussed. Environ Toxicol Chem 2024;43:637-652. © 2022 SETAC.

Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers?

Advances in high throughput omics techniques provide avenues to decipher plant microbiomes. However, there is limited information on how integrated informatics can help provide deeper insights into plant-microbe interactions in a concerted way. Integrating multi-omics datasets can transform our understanding of the plant microbiome from unspecified genetic influences on interacting species to specific gene-by-gene interactions. Here, we highlight recent progress and emerging strategies in crop microbiome omics research and review key aspects of how the integration of host and microbial omics-based datasets can be used to provide a comprehensive outline of complex crop-microbe interactions. We describe how these technological advances have helped unravel crucial plant and microbial genes and pathways that control beneficial, pathogenic, and commensal plant-microbe interactions. We identify crucial knowledge gaps and synthesize current limitations in our understanding of crop microbiome omics approaches. We highlight recent studies in which multi-omics-based approaches have led to improved models of crop microbial community structure and function. Finally, we recommend holistic approaches in integrating host and microbial omics datasets to achieve precision and efficiency in data analysis, which is crucial for biotic and abiotic stress control and in understanding the contribution of the microbiota in shaping plant fitness.

Soil microbiome analysis supports claims of ineffectiveness of Pseudomonas fluorescens D7 as a biocontrol agent of Bromus tectorum

IMPORTANCE

Cheatgrass is one of North America's most problematic invasive species. Invasion by this annual grass alters ecosystem structure and function and has proven very challenging to remove with traditional approaches. Commercially available bioherbicides, like P. fluorescens D7, are applied with the goal of providing lasting control from a single application. However, experimental results suggest that this bioherbicide has limited efficacy under field conditions. Potential explanations for variable efficacy include a failure of this bioherbicide to establish in the soil microbiome. However, to our knowledge, no data exist to support or refute this hypothesis. Here, we use a deep-sequencing approach to better understand the effects of this bioherbicide on the soil microbiome and screen for P. fluorescens at 18 months post-application.

Investigating eco-evolutionary processes of microbial community assembly in the wild using a model leaf litter system

Microbial communities are not the easiest to manipulate experimentally in natural ecosystems. However, leaf litter-topmost layer of surface soil-is uniquely suitable to investigate the complexities of community assembly. Here, we reflect on over a decade of collaborative work to address this topic using leaf litter as a model system in Southern California ecosystems. By leveraging a number of methodological advantages of the system, we have worked to demonstrate how four processes-selection, dispersal, drift, and diversification-contribute to bacterial and fungal community assembly and ultimately impact community functioning. Although many dimensions remain to be investigated, our initial results demonstrate that both ecological and evolutionary processes occur simultaneously to influence microbial community assembly. We propose that the development of additional and experimentally tractable microbial systems will be enormously valuable to test the role of eco-evolutionary processes in natural settings and their implications in the face of rapid global change.

Niche differentiation in microbial communities with stable genomic traits over time in engineered systems

Microbial communities in full-scale engineered systems undergo dynamic compositional changes. However, mechanisms governing assembly of such microbes and succession of their functioning and genomic traits under various environmental conditions are unclear. In this study, we used the activated sludge and anaerobic treatment systems of four full-scale industrial wastewater treatment plants as models to investigate the niches of microbes in communities and the temporal succession patterns of community compositions. High-quality representative metagenome-assembled genomes revealed that taxonomic, functional, and trait-based compositions were strongly shaped by environmental selection, with replacement processes primarily driving variations in taxonomic and functional compositions. Plant-specific indicators were associated with system environmental conditions and exhibited strong determinism and trajectory directionality over time. The partitioning of microbes in a co-abundance network according to groups of plant-specific indicators, together with significant between-group differences in genomic traits, indicated the occurrence of niche differentiation. The indicators of the treatment plant with rich nutrient input and high substrate removal efficiency exhibited a faster predicted growth rate, lower guanine-cytosine content, smaller genome size, and higher codon usage bias than the indicators of the other plants. In individual plants, taxonomic composition displayed a more rapid temporal succession than functional and trait-based compositions. The succession of taxonomic, functional, and trait-based compositions was correlated with the kinetics of treatment processes in the activated sludge systems. This study provides insights into ecological niches of microbes in engineered systems and succession patterns of their functions and traits, which will aid microbial community management to improve treatment performance.

Identifying microbiota community patterns important for plant protection using synthetic communities and machine learning

Plant-associated microbiomes contribute to important ecosystem functions such as host resistance to biotic and abiotic stresses. The factors that determine such community outcomes are inherently difficult to identify under complex environmental conditions. In this study, we present an experimental and analytical approach to explore microbiota properties relevant for a microbiota-conferred host phenotype, here plant protection, in a reductionist system. We screened 136 randomly assembled synthetic communities (SynComs) of five bacterial strains each, followed by classification and regression analyses as well as empirical validation to test potential explanatory factors of community structure and composition, including evenness, total commensal colonization, phylogenetic diversity, and strain identity. We find strain identity to be the most important predictor of pathogen reduction, with machine learning algorithms improving performances compared to random classifications (94-100% versus 32% recall) and non-modelled predictions (0.79-1.06 versus 1.5 RMSE). Further experimental validation confirms three strains as the main drivers of pathogen reduction and two additional strains that confer protection in combination. Beyond the specific application presented in our study, we provide a framework that can be adapted to help determine features relevant for microbiota function in other biological systems.

The seed microbiomes of staple food crops

The scientific community increasingly recognized that seed microbiomes are important for plant growth and nutrition. The versatile roles and modulating properties that microbiomes hold in the context of seeds seem to be an inherited approach to avert adverse conditions. These discoveries attracted extensive interest, especially in staple food crops (SFCs) where grain was consumed as food. Along with the rapid expansion of population and industrialization that posed a severe challenge to the yield of SFCs, microbiologists and botanists began to explore and engineer seed microbiomes, for safer and more fruitful grain production. To utilize seed microbiomes, we present an overall review of the most updated scientific literature on three representative SFCs (wheat, rice and maize) using the 5W1H (Which, Where, What, Why, When and How) method that provides a comprehensive understanding of the issue. These include which factors determine the composition of seed microbiomes? Where do seed microbiomes come from? What are these seed microbes? Why do these microbes choose seeds as their destination and when do microbes settle down and become seed communists? In addition, how do seed microbiomes work and can be manipulated effectively? Therefore, answering the aforementioned questions regarding SFCs seed microbiomes remain fundamental in bridging endophytic research gaps and harnessing their ecological services.

Harnessing biological nitrogen fixation in plant leaves

The importance of biological nitrogen fixation (BNF) in securing food production for the growing world population with minimal environmental cost has been increasingly acknowledged. Leaf surfaces are one of the biggest microbial habitats on Earth, harboring diverse free-living N2-fixers. These microbes inhabit the epiphytic and endophytic phyllosphere and contribute significantly to plant N supply and growth. Here, we summarize the contribution of phyllosphere-BNF to global N cycling, evaluate the diversity of leaf-associated N2-fixers across plant hosts and ecosystems, illustrate the ecological adaptation of N2-fixers to the phyllosphere, and identify the environmental factors driving BNF. Finally, we discuss potential BNF engineering strategies to improve the nitrogen uptake in plant leaves and thus sustainable food production.

Systematic mining of the human microbiome identifies antimicrobial peptides with diverse activity spectra

Human-associated bacteria secrete modified peptides to control host physiology and remodel the microbiota species composition. Here we scanned 2,229 Human Microbiome Project genomes of species colonizing skin, gastrointestinal tract, urogenital tract, mouth and trachea for gene clusters encoding RiPPs (ribosomally synthesized and post-translationally modified peptides). We found 218 lanthipeptides and 25 lasso peptides, 70 of which were synthesized and expressed in E. coli and 23 could be purified and functionally characterized. They were tested for activity against bacteria associated with healthy human flora and pathogens. New antibiotics were identified against strains implicated in skin, nasal and vaginal dysbiosis as well as from oral strains selectively targeting those in the gut. Extended- and narrow-spectrum antibiotics were found against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococci. Mining natural products produced by human-associated microbes will enable the elucidation of ecological relationships and may be a rich resource for antimicrobial discovery.

Microbiome modulation in inflammatory diseases: Progress to microbiome genetic engineering

Recent developments in sequencing technology and analytical approaches have allowed researchers to show that the healthy gut microbiome is very varied and capable of performing a wide range of tasks. The importance of gut microbiota in controlling immunological, neurological, and endocrine function is becoming well-recognized. Thereby, numerous inflammatory diseases, including those that impact the gastrointestinal system, as well as less obvious ones, including Rheumatoid arthritis (RA), cancer, gestational diabetes (GD), type 1 diabetes (T1D), and type 2 diabetes (T2D), have been linked to dysbiotic gut microbiota. Microbiome engineering is a rapidly evolving frontier for solutions to improve human health. Microbiome engineering seeks to improve the function of an ecosystem by manipulating the composition of microbes. Thereby, generating potential therapies against metabolic, inflammatory, and immunological diseases will be possible through microbiome engineering. This essay first provides an overview of the traditional technological instruments that might be used for microbiome engineering, such as Fecal Microbiota Transplantation (FMT), prebiotics, and probiotics. Moreover, we will also discuss experimental genetic methods such as Metagenomic Alteration of Gut microbiome by In situ Conjugation (MAGIC), Bacteriophage, and Conjugative plasmids in manipulating intestinal microbiota.

Deconstructing taxa x taxa xenvironment interactions in the microbiota: A theoretical examination

A major objective of microbial ecology is to identify how the composition of microbial taxa shapes host phenotypes. However, most studies focus on pairwise interactions and ignore the potentially significant effects of higher-order microbial interactions.Here, we quantify the effects of higher-order interactions among taxa on host infection risk. We apply our approach to an in silico dataset that is built to resemble a population of insect hosts with gut-associated microbial communities at risk of infection from an intestinal parasite across a breadth of nutrient environmental contexts.We find that the effect of higher-order interactions is considerable and can change appreciably across environmental contexts. Furthermore, we show that higher-order interactions can stabilize community structure thereby reducing host susceptibility to parasite invasion.Our approach illustrates how incorporating the effects of higher-order interactions among gut microbiota across environments can be essential for understanding their effects on host phenotypes.

Deep insight into oriented propionate production from food waste: Microbiological interpretation and design practice

Using mixed microbial cultures (MMCs) for oriented volatile fatty acids (VFAs) refining in an open environment is a typical challenge due to the microbial diversiform and the process complexity. Especially for carbohydrate-rich waste (such as food waste), butyrate-type fermentation is usually dominant in a single-stage MMCs anaerobic process, while the production of odd-carbon VFAs (such as propionate) is difficult although it plays a significant role in chemicals industries. In this study, firstly, we gave a new perspective on the rationality of the oriented propionate production using MMCs with lactate as feedstock by conducting in-depth microbial informatics and reaction analysis. Secondly, we verified the feasibility of the "food waste-lactate-propionate" route to reverse the original butyrate-type fermentation situation and explore mechanisms for maintaining stability. In the first stage, a defined lactate fermentation microbiome was used to produce lactate-containing broth (80% of total chemical oxygen demand) at pH=4. In the second stage, an undomesticated undefined anaerobic microbiome was used to drive propionate production (45.26% ± 2.23% of total VFAs) under optimized conditions (C/N = 100:1-200:1 and pH=5.0). The low pH environment in the first stage enhanced the lactic acid bacteria to resist the invasion of non-functional flanking bacteria, making the community stable. In the second stage, the system maintained the propionate-type fermentation due to the absence of the ecological niche of the invasive lactic acid bacteria; The selection of propionate-producing specialists was a necessary but not sufficient condition for propionate-type fermentation. At last, this study proposed an enhanced engineering strategy framework for understanding elaborate MMCs fermentation.

Ecological principles of fecal microbiota transplantation

Fecal microbiota transplantation (FMT) is a procedure used to treat diseases related to microbiome imbalances. We discuss how ecological principles can inform the design of FMT clinical trials and contribute to data interpretation. This effort will promote a better understanding of microbiome engraftment and assist the development of clinical protocols.

Microbiome rescue: directing resilience of environmental microbial communities

Earth's climate crisis threatens to disrupt ecosystem services and destabilize food security. Microbiome management will be a crucial component of a comprehensive strategy to maintain stable microbinal functions for ecosystems and plants in the face of climate change. Microbiome rescue is the directed, community-level recovery of microbial populations and functions lost after an environmental disturbance. Microbiome rescue aims to propel a resilience trajectory for community functions. Rescue can be achieved via demographic, functional, adaptive, or evolutionary recovery of disturbance-sensitive populations. Various ecological mechanisms support rescue, including dispersal, reactivation from dormancy, functional redundancy, plasticity, and diversification, and these mechanisms can interact. Notably, controlling microbial reactivation from dormancy is a potentially fruitful but underexplored target for rescue.

The potential of tailoring the gut microbiome to prevent and treat cardiometabolic disease

Despite milestones in preventive measures and treatment, cardiovascular disease (CVD) remains associated with a high burden of morbidity and mortality. The protracted nature of the development and progression of CVD motivates the identification of early and complementary targets that might explain and alleviate any residual risk in treated patients. The gut microbiota has emerged as a sentinel between our inner milieu and outer environment and relays a modified risk associated with these factors to the host. Accordingly, numerous mechanistic studies in animal models support a causal role of the gut microbiome in CVD via specific microbial or shared microbiota-host metabolites and have identified converging mammalian targets for these signals. Similarly, large-scale cohort studies have repeatedly reported perturbations of the gut microbial community in CVD, supporting the translational potential of targeting this ecological niche, but the move from bench to bedside has not been smooth. In this Review, we provide an overview of the current evidence on the interconnectedness of the gut microbiome and CVD against the noisy backdrop of highly prevalent confounders in advanced CVD, such as increased metabolic burden and polypharmacy. We further aim to conceptualize the molecular mechanisms at the centre of these associations and identify actionable gut microbiome-based targets, while contextualizing the current knowledge within the clinical scenario and emphasizing the limitations of the field that need to be overcome.

The microbiome of cereal plants: The current state of knowledge and the potential for future applications

The plant microbiota fulfils various crucial functions related to host health, fitness, and productivity. Over the past years, the number of plant microbiome studies continued to steadily increase. Technological advancements not only allow us to produce constantly increasing datasets, but also to extract more information from them in order to advance our understanding of plant-microbe interactions. The growing knowledge base has an enormous potential to improve microbiome-based, sustainable agricultural practices, which are currently poorly understood and have yet to be further developed. Cereal plants are staple foods for a large proportion of the world's population and are therefore often implemented in microbiome studies. In the present review, we conducted extensive literature research to reflect the current state of knowledge in terms of the microbiome of the four most commonly cultivated cereal plants. We found that currently the majority of available studies are targeting the wheat microbiome, which is closely followed by studies on maize and rice. There is a substantial gap, in terms of published studies, addressing the barley microbiome. Overall, the focus of most microbiome studies on cereal plants is on the below-ground microbial communities, and there is more research on bacteria than on fungi and archaea. A meta-analysis conducted in the frame of this review highlights microbiome similarities across different cereal plants. Our review also provides an outlook on how the plant microbiota could be harnessed to improve sustainability of cereal crop production.

The Hydroponic Rockwool Root Microbiome: Under Control or Underutilised?

Land plants have an ancient and intimate relationship with microorganisms, which influences the composition of natural ecosystems and the performance of crops. Plants shape the microbiome around their roots by releasing organic nutrients into the soil. Hydroponic horticulture aims to protect crops from damaging soil-borne pathogens by replacing soil with an artificial growing medium, such as rockwool, an inert material made from molten rock spun into fibres. Microorganisms are generally considered a problem to be managed, to keep the glasshouse clean, but the hydroponic root microbiome assembles soon after planting and flourishes with the crop. Hence, microbe–plant interactions play out in an artificial environment that is quite unlike the soil in which they evolved. Plants in a near-ideal environment have little dependency on microbial partners, but our growing appreciation of the role of microbial communities is revealing opportunities to advance practices, especially in agriculture and human health. Hydroponic systems are especially well-suited to active management of the root microbiome because they allow complete control over the root zone environment; however, they receive much less attention than other host–microbiome interactions. Novel techniques for hydroponic horticulture can be identified by extending our understanding of the microbial ecology of this unique environment.

Microbes to support plant health: understanding bioinoculant success in complex conditions

A promising, sustainable way to enhance plant health and productivity is by leveraging beneficial microbes. Beneficial microbes are natural soil residents with proven benefits for plant performance and health. When applied in agriculture to improve crop yield and performance, these microbes are commonly referred to as bioinoculants. Yet, despite their promising properties, bioinoculant efficacy can vary dramatically in the field, hampering their applicability. Invasion of the rhizosphere microbiome is a critical determinant for bioinoculant success. Invasion is a complex phenomenon that is shaped by interactions with the local, resident microbiome and the host plant. Here, we explore all of these dimensions by cross-cutting ecological theory and molecular biology of microbial invasion in the rhizosphere. We refer to the famous Chinese philosopher and strategist Sun Tzu, who believed that solutions for problems require deep understanding of the problems themselves, to review the major biotic factors determining bioinoculant effectiveness.

Microbiome engineering for bioremediation of emerging pollutants

Axenic microbial applications in the open environment are unrealistic and may not be always practically viable. Therefore, it is important to use mixed microbial cultures and their interactions with the microbiome in the targeted ecosystem to perform robust functions towards their sustainability in harsh environmental conditions. Emerging pollutants like phthalates and hydrocarbons that are toxic to several aquatic and terrestrial life forms in the water bodies and lands are an alarming situation. The present review explores the possibility of devising an inclusive eco-friendly strategy like microbiome engineering which proves to be a unique and crucial technology involving the power of microbial communication through quorum sensing. This review discusses the interspecies and intra-species communications between different microbial groups with their respective environments. Moreover, this review also envisages the efforts for designing the next level of microbiome-host engineering concept (MHEC). The focus of the review also extended toward using omics and metabolic network analysis-based tools for effective microbiome engineering. These approaches might be quite helpful in the future to understand such microbial interactions but it will be challenging to implement in the real environment to get the desired functions. Finally, the review also discusses multiple approaches for the bioremediation of toxic chemicals from the soil environment.

The Use of Probiotics during Rearing of Hermetia illucens: Potential, Caveats, and Knowledge Gaps

Given the novelty of the industrial production of the edible insects sector, research has primarily focused on the zootechnical performances of black soldier fly larvae (BSFL) in response to different substrates and rearing conditions as a basis to optimize yield and quality. However recently, research has started to focus more on the associated microbes in the larval digestive system and their substrates and the effect of manipulating the composition of these communities on insect performance as a form of microbiome engineering. Here we present an overview of the existing literature on the use of microorganisms during rearing of the BSFL to optimize the productivity of this insect. These studies have had variable outcomes and potential explanations for this variation are offered to inspire future research that might lead to a better success rate for microbiome engineering in BSFL.

Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia

Microbes naturally coexist in complex, multistrain communities. However, extracting individual microbes from and specifically manipulating the composition of these consortia remain challenging. The sequence-specific nature of CRISPR guide RNAs can be leveraged to accurately differentiate microorganisms and facilitate the creation of tools that can achieve these tasks. We developed a computational program, ssCRISPR, which designs strain-specific CRISPR guide RNA sequences with user-specified target strains, protected strains, and guide RNA properties. We experimentally verify the accuracy of the strain specificity predictions in both Escherichia coli and Pseudomonas spp. and show that up to three nucleotide mismatches are often required to ensure perfect specificity. To demonstrate the functionality of ssCRISPR, we apply computationally designed CRISPR-Cas9 guide RNAs to two applications: the purification of specific microbes through one- and two-plasmid transformation workflows and the targeted removal of specific microbes using DNA-loaded liposomes. For strain purification, we utilize gRNAs designed to target and kill all microbes in a consortium except the specific microbe to be isolated. For strain elimination, we utilize gRNAs designed to target only the unwanted microbe while protecting all other strains in the community. ssCRISPR will be of use in diverse microbiota engineering applications.

Temperate bacteriophages infecting the mucin-degrading bacterium Ruminococcus gnavus from the human gut

Ruminococcus gnavus is a prevalent gut microbe reported to occur in higher abundance among individuals with inflammatory bowel disease (IBD). This study reports the isolation and characterization of six bacteriophages (phages) isolated from human fecal material and environmental samples that infect this species. Isolated phages have a siphovirus morphology, with genomes ranging between 36.5 and 37.8 kbp. Genome analysis indicates that the phages have a temperate lifestyle, which was confirmed by their ability to form lysogens on their host bacterial species. In contrast to the finding that phages lyse their host in liquid medium, results from a mouse trial indicate these phages can co-exist with the host bacterium in the gut without causing a significant reduction of R. gnavus. The bacterial counts in the feces of phage-treated mice did not significantly differ in the presence of phage. Furthermore, analysis of publicly available gut virome sequence data indicates a high abundance of these phages among individuals suffering from IBD. This work provides the first insight into how phages interact with R. gnavus in the human gut microbiome.

Translating neonatal microbiome science into commercial innovation: metabolism of human milk oligosaccharides as a basis for probiotic efficacy in breast-fed infants

For over a century, physicians have witnessed a common enrichment of bifidobacteria in the feces of breast-fed infants that was readily associated with infant health status. Recent advances in bacterial genomics, metagenomics, and glycomics have helped explain the nature of this unique enrichment and enabled the tailored use of probiotic supplementation to restore missing bifidobacterial functions in at-risk infants. This review documents a 20-year span of discoveries that set the stage for the current use of human milk oligosaccharide-consuming bifidobacteria to beneficially colonize, modulate, and protect the intestines of at-risk, human milk-fed, neonates. This review also presents a model for probiotic applications wherein bifidobacterial functions, in the form of colonization and HMO-related catabolic activity in situ, represent measurable metabolic outcomes by which probiotic efficacy can be scored toward improving infant health.

Impact of Plant-Beneficial Bacterial Inocula on the Resident Bacteriome: Current Knowledge and Future Perspectives

The inoculation of plant growth-promoting bacteria (PGPB) as biofertilizers is one of the most efficient and sustainable strategies of rhizosphere manipulation leading to increased plant biomass and yield and improved plant health, as well as the ameliorated nutritional value of fruits and edible seeds. During the last decades, exciting, but heterogeneous, results have been obtained growing PGPB inoculated plants under controlled, stressful, and open field conditions. On the other hand, the possible impact of the PGPB deliberate release on the resident microbiota has been less explored and the little available information is contradictory. This review aims at filling this gap: after a brief description of the main mechanisms used by PGPB, we focus our attention on the process of PGPB selection and formulation and we provide some information on the EU regulation for microbial inocula. Then, the concept of PGPB inocula as a tool for rhizosphere engineering is introduced and the possible impact of bacterial inoculant on native bacterial communities is discussed, focusing on those bacterial species that are included in the EU regulation and on other promising bacterial species that are not yet included in the EU regulation.

Plant Microbiome Engineering: Hopes or Hypes

Rhizosphere microbiome is a dynamic and complex zone of microbial communities. This complex plant-associated microbial community, usually regarded as the plant's second genome, plays a crucial role in plant health. It is unquestioned that plant microbiome collectively contributes to plant growth and fitness. It also provides a safeguard from plant pathogens, and induces tolerance in the host against abiotic stressors. The revolution in omics, gene-editing and sequencing tools have somehow led to unravel the compositions and latent interactions between plants and microbes. Similarly, besides standard practices, many biotechnological, (bio)chemical and ecological methods have also been proposed. Such platforms have been solely dedicated to engineer the complex microbiome by untangling the potential barriers, and to achieve better agriculture output. Yet, several limitations, for example, the biological obstacles, abiotic constraints and molecular tools that capably impact plant microbiome engineering and functionality, remained unaddressed problems. In this review, we provide a holistic overview of plant microbiome composition, complexities, and major challenges in plant microbiome engineering. Then, we unearthed all inevitable abiotic factors that serve as bottlenecks by discouraging plant microbiome engineering and functionality. Lastly, by exploring the inherent role of micro/macrofauna, we propose economic and eco-friendly strategies that could be harnessed sustainably and biotechnologically for resilient plant microbiome engineering.

Machine learning and deep learning applications in microbiome research

The many microbial communities around us form interactive and dynamic ecosystems called microbiomes. Though concealed from the naked eye, microbiomes govern and influence macroscopic systems including human health, plant resilience, and biogeochemical cycling. Such feats have attracted interest from the scientific community, which has recently turned to machine learning and deep learning methods to interrogate the microbiome and elucidate the relationships between its composition and function. Here, we provide an overview of how the latest microbiome studies harness the inductive prowess of artificial intelligence methods. We start by highlighting that microbiome data - being compositional, sparse, and high-dimensional - necessitates special treatment. We then introduce traditional and novel methods and discuss their strengths and applications. Finally, we discuss the outlook of machine and deep learning pipelines, focusing on bottlenecks and considerations to address them.

Microbial community composition in the rhizosphere of Pteris vittata and its effects on arsenic phytoremediation under a natural arsenic contamination gradient

Arsenic contamination causes numerous health problems for humans and wildlife via bioaccumulation in the food chain. Phytoremediation of arsenic-contaminated soils with the model arsenic hyperaccumulator Pteris vittata provides a promising way to reduce the risk, in which the growth and arsenic absorption ability of plants and the biotransformation of soil arsenic may be greatly affected by rhizosphere microorganisms. However, the microbial community composition in the rhizosphere of P. vittata and its functional role in arsenic phytoremediation are still poorly understood. To bridge this knowledge gap, we carried out a field investigation and pot experiment to explore the composition and functional implications of microbial communities in the rhizosphere of four P. vittata populations with a natural arsenic contamination gradient. Arsenic pollution significantly reduced bacterial and fungal diversity in the rhizosphere of P. vittata (p < 0.05) and played an important role in shaping the microbial community structure. The suitability of soil microbes for the growth of P. vittata gradually decreased following increased soil arsenic levels, as indicated by the increased abundance of pathogenic fungi and parasitic bacteria and the decrease in symbiotic fungi. The analysis of arsenic-related functional gene abundance with AsChip revealed the gradual enrichment of the microbial genes involved in As(III) oxidation, As(V) reduction, and arsenic methylation and demethylation in the rhizosphere of P. vittata following increased arsenic levels (p < 0.05). The regulation of indigenous soil microbes through the field application of fungicide, but not bactericide, significantly reduced the remediation efficiency of P. vittata grown under an arsenic contamination gradient, indicating the important role of indigenous fungal groups in the remediation of arsenic-contaminated soil. This study has important implications for the functional role and application prospects of soil microorganisms in the phytoremediation of arsenic-polluted soil.

Founder cell configuration drives competitive outcome within colony biofilms

Bacteria can form dense communities called biofilms, where cells are embedded in a self-produced extracellular matrix. Exploiting competitive interactions between strains within the biofilm context can have potential applications in biological, medical, and industrial systems. By combining mathematical modelling with experimental assays, we reveal that spatial structure and competitive dynamics within biofilms are significantly affected by the location and density of the founder cells used to inoculate the biofilm. Using a species-independent theoretical framework describing colony biofilm formation, we show that the observed spatial structure and relative strain biomass in a mature biofilm comprising two isogenic strains can be mapped directly to the geographical distributions of founder cells. Moreover, we define a predictor of competitive outcome that accurately forecasts relative abundance of strains based solely on the founder cells’ potential for radial expansion. Consequently, we reveal that variability of competitive outcome in biofilms inoculated at low founder density is a natural consequence of the random positioning of founding cells in the inoculum. Extension of our study to non-isogenic strains that interact through local antagonisms, shows that even for strains with different competition strengths, a race for space remains the dominant mode of competition in low founder density biofilms. Our results, verified by experimental assays using Bacillus subtilis, highlight the importance of spatial dynamics on competitive interactions within biofilms and hence to related applications.

Brassicaceae host plants mask the feedback from the previous year's soil history on bacterial communities, except when they experience drought

Soil history operates through time to influence the structure and biodiversity of soil bacterial communities. Examining how different soil histories endure will help clarify the rules of bacterial community assembly. In this study, we established three different soil histories in field trials; the following year these plots were planted with five different Brassicaceae species. We hypothesized that the previously established soil histories would continue to structure the subsequent Brassicaceae bacterial root and rhizosphere communities. We used a MiSeq 16S rRNA metabarcoding strategy to determine the impact of different soil histories on the structure and biodiversity of the bacterial root and rhizosphere communities from the five different Brassicaceae host plants. We found that the Brassicaceae hosts were consistently significant factors in structuring the bacterial communities. Four host plants (Sinapis alba, Brassica napus, B. juncea, B. carinata) formed similar bacterial communities, regardless of different soil histories. Camelina sativa host plants structured phylogenetically distinct bacterial communities compared to the other hosts, particularly in their roots. Soil history established the previous year was only a significant factor for bacterial community structure when the feedback of the Brassicaceae host plants was weakened, potentially due to limited soil moisture during a dry year. Understanding how soil history is involved in the structure and biodiversity of bacterial communities through time is a limitation in microbial ecology and is required for employing microbiome technologies in improving agricultural systems. This article is protected by copyright. All rights reserved.

Microbiome breeding: conceptual and practical issues

Microbiome breeding is a new artificial selection technique that seeks to change the genetic composition of microbiomes in order to benefit plant or animal hosts. Recent experimental and theoretical analyses have shown that microbiome breeding is possible whenever microbiome-encoded genetic factors affect host traits (e.g., health) and microbiomes are transmissible between hosts with sufficient fidelity, such as during natural microbiome transmission between individuals of social animals, or during experimental microbiome transplanting between plants. To address misunderstandings that stymie microbiome-breeding programs, we (i) clarify and visualize the corresponding elements of microbiome selection and standard selection; (ii) elucidate the eco-evolutionary processes underlying microbiome selection within a quantitative genetic framework to summarize practical guidelines that optimize microbiome breeding; and (iii) characterize the kinds of host species most amenable to microbiome breeding.

Ecological and Evolutionary Implications of Microbial Dispersal

Dispersal is simply defined as the movement of species across space and time. Despite this terse definition, dispersal is an essential process with direct ecological and evolutionary implications that modulate community assembly and turnover. Seminal ecological studies have shown that environmental context (e.g., local edaphic properties, resident community), dispersal timing and frequency, and species traits, collectively account for patterns of species distribution resulting in either their persistence or unsuccessful establishment within local communities. Despite the key importance of this process, relatively little is known about how dispersal operates in microbiomes across divergent systems and community types. Here, we discuss parallels of macro- and micro-organismal ecology with a focus on idiosyncrasies that may lead to novel mechanisms by which dispersal affects the structure and function of microbiomes. Within the context of ecological implications, we revise the importance of short- and long-distance microbial dispersal through active and passive mechanisms, species traits, and community coalescence, and how these align with recent advances in metacommunity theory. Conversely, we enumerate how microbial dispersal can affect diversification rates of species by promoting gene influxes within local communities and/or shifting genes and allele frequencies via migration or de novo changes (e.g., horizontal gene transfer). Finally, we synthesize how observed microbial assemblages are the dynamic outcome of both successful and unsuccessful dispersal events of taxa and discuss these concepts in line with the literature, thus enabling a richer appreciation of this process in microbiome research.

GMEmbeddings: An R Package to Apply Embedding Techniques to Microbiome Data

Large-scale microbiome studies investigating disease-inducing microbial roles base their findings on differences between microbial count data in contrasting environments (e.g., stool samples between cases and controls). These microbiome survey studies are often impeded by small sample sizes and database bias. Combining data from multiple survey studies often results in obvious batch effects, even when DNA preparation and sequencing methods are identical. Relatedly, predictive models trained on one microbial DNA dataset often do not generalize to outside datasets. In this study, we address these limitations by applying word embedding algorithms (GloVe) and PCA transformation to ASV data from the American Gut Project and generating translation matrices that can be applied to any 16S rRNA V4 region gut microbiome sequencing study. Because these approaches contextualize microbial occurrences in a larger dataset while reducing dimensionality of the feature space, they can improve generalization of predictive models that predict host phenotype from stool associated gut microbiota. The GMEmbeddings R package contains GloVe and PCA embedding transformation matrices at 50, 100 and 250 dimensions, each learned using ∼15,000 samples from the American Gut Project. It currently supports the alignment, matching, and matrix multiplication to allow users to transform their V4 16S rRNA data into these embedding spaces. We show how to correlate the properties in the new embedding space to KEGG functional pathways for biological interpretation of results. Lastly, we provide benchmarking on six gut microbiome datasets describing three phenotypes to demonstrate the ability of embedding-based microbiome classifiers to generalize to independent datasets. Future iterations of GMEmbeddings will include embedding transformation matrices for other biological systems. Available at: https://github.com/MaudeDavidLab/GMEmbeddings.

Renaissance for Phage-Based Bacterial Control

Bacteriophages (phages) are an underutilized biological resource with vast potential for pathogen control and microbiome editing. Phage research and commercialization have increased rapidly in biomedical and agricultural industries, but adoption has been limited elsewhere. Nevertheless, converging advances in DNA sequencing, bioinformatics, microbial ecology, and synthetic biology are now poised to broaden phage applications beyond pathogen control toward the manipulation of microbial communities for defined functional improvements. Enhancements in sequencing combined with network analysis make it now feasible to identify and disrupt microbial associations to elicit desirable shifts in community structure or function, indirectly modulate species abundance, and target hub or keystone species to achieve broad functional shifts. Sequencing and bioinformatic advancements are also facilitating the use of temperate phages for safe gene delivery applications. Finally, integration of synthetic biology stands to create novel phage chassis and modular genetic components. While some fundamental, regulatory, and commercialization barriers to widespread phage use remain, many major challenges that have impeded the field now have workable solutions. Thus, a new dawn for phage-based (chemical-free) precise biocontrol and microbiome editing is on the horizon to enhance, suppress, or modulate microbial activities important for public health, food security, and more sustainable energy production and water reuse.

The Evolution of Microbial Facilitation: Sociogenesis, Symbiogenesis, and Transition in Individuality

Metabolic cooperation is widespread, and it seems to be a ubiquitous and easily evolvable interaction in the microbial domain. Mutual metabolic cooperation, like syntrophy, is thought to have a crucial role in stabilizing interactions and communities, for example biofilms. Furthermore, cooperation is expected to feed back positively to the community under higher-level selection. In certain cases, cooperation can lead to a transition in individuality, when freely reproducing, unrelated entities (genes, microbes, etc.) irreversibly integrate to form a new evolutionary unit. The textbook example is endosymbiosis, prevalent among eukaryotes but virtually lacking among prokaryotes. Concerning the ubiquity of syntrophic microbial communities, it is intriguing why evolution has not lead to more transitions in individuality in the microbial domain. We set out to distinguish syntrophy-specific aspects of major transitions, to investigate why a transition in individuality within a syntrophic pair or community is so rare. We review the field of metabolic communities to identify potential evolutionary trajectories that may lead to a transition. Community properties, like joint metabolic capacity, functional profile, guild composition, assembly and interaction patterns are important concepts that may not only persist stably but according to thought-provoking theories, may provide the heritable information at a higher level of selection. We explore these ideas, relating to concepts of multilevel selection and of informational replication, to assess their relevance in the debate whether microbial communities may inherit community-level information or not.

Next steps after 15 stimulating years of human gut microbiome research

Gut microbiome research has bloomed over the past 15 years. We have learnt a lot about the complex microbial communities that colonize our intestine. Promising avenues of research and microbiome-based applications are being implemented, with the goal of sustaining host health and applying personalized disease management strategies. Despite this exciting outlook, many fundamental questions about enteric microbial ecosystems remain to be answered. Organizational measures will also need to be taken to optimize the outcome of discoveries happening at an extremely rapid pace. This article highlights our own view of the field and perspectives for the next 15 years.