Common principles and best practices for engineering microbiomes

Global WWTP Microbiome-based Integrative Information Platform: From experience to intelligence

Domestic and industrial wastewater treatment plants (WWTPs) are facing formidable challenges in effectively eliminating emerging pollutants and conventional nutrients. In microbiome engineering, two approaches have been developed: a top-down method focusing on domesticating seed microbiomes into engineered ones, and a bottom-up strategy that synthesizes engineered microbiomes from microbial isolates. However, these approaches face substantial hurdles that limit their real-world applicability in wastewater treatment engineering. Addressing this gap, we propose the creation of a Global WWTP Microbiome-based Integrative Information Platform, inspired by the untapped microbiome and engineering data from WWTPs and advancements in artificial intelligence (AI). This open platform integrates microbiome and engineering information globally and utilizes AI-driven tools for identifying seed microbiomes for new plants, providing technical upgrades for existing facilities, and deploying microbiomes for accidental pollution remediation. Beyond its practical applications, this platform has significant scientific and social value, supporting multidisciplinary research, documenting microbial evolution, advancing Wastewater-Based Epidemiology, and enhancing global resource sharing. Overall, the platform is expected to enhance WWTPs' performance in pollution control, safeguarding a harmonious and healthy future for human society and the natural environment.

Synthetic microbial communities: Novel strategies to enhance the quality of traditional fermented foods

Consumers are attracted to traditional fermented foods due to their unique flavor and nutritional value. However, the traditional fermentation technique can no longer accommodate the requirements of the food industry. Traditional fermented foods produce hazardous compounds, off-odor, and anti-nutritional factors, reducing product stability. The microbial system complexity of traditional fermented foods resulting from the open fermentation process has made it challenging to regulate these problems by modifying microbial behaviors. Synthetic microbial communities (SynComs) have been shown to simplify complex microbial communities and allow for the targeted design of microbial communities, which has been applied in processing traditional fermented foods. Herein, we describe the theoretical information of SynComs, particularly microbial physiological processes and their interactions. This paper discusses current approaches to creating SynComs, including designing, building, testing, and learning, with typical applications and fundamental techniques. Based on various traditional fermented food innovation demands, the potential and application of SynComs in enhancing the quality of traditional fermented foods are highlighted. SynComs showed superior performance in regulating the quality of traditional fermented foods using the interaction of core microorganisms to reduce the hazardous compounds of traditional fermented foods and improve flavor. Additionally, we presented the current status and future perspectives of SynComs for improving the quality of traditional fermented foods.

Towards consolidated bioprocessing of biomass and plastic substrates for semi-synthetic production of bio-poly(ethylene furanoate) (PEF) polymer using omics-guided construction of artificial microbial consortia

Poly(ethylene furanoate) (PEF) plastic is a 100% renewable polyester that is currently being pursued for commercialization as the next-generation bio-based plastic. This is in line with growing demand for circular bioeconomy and new plastics economy that is aimed at minimizing plastic waste mismanagement and lowering carbon footprint of plastics. However, the current catalytic route for the synthesis of PEF is impeded with technical challenges including high cost of pretreatment and catalyst refurbishment. On the other hand, the semi-biosynthetic route of PEF plastic production is of increased biotechnological interest. In particular, the PEF monomers (Furan dicarboxylic acid and ethylene glycol) can be synthesized via microbial-based biorefinery and purified for subsequent catalyst-mediated polycondensation into PEF. Several bioengineering and bioprocessing issues such as efficient substrate utilization and pathway optimization need to be addressed prior to establishing industrial-scale production of the monomers. This review highlights current advances in semi-biosynthetic production of PEF monomers using consolidated waste biorefinery strategies, with an emphasis on the employment of omics-driven systems biology approaches in enzyme discovery and pathway construction. The roles of microbial protein transporters will be discussed, especially in terms of improving substrate uptake and utilization from lignocellulosic biomass, as well as from depolymerized plastic waste as potential bio-feedstock. The employment of artificial bioengineered microbial consortia will also be highlighted to provide streamlined systems and synthetic biology strategies for bio-based PEF monomer production using both plant biomass and plastic-derived substrates, which are important for circular and new plastics economy advances.

Understanding phycosomal dynamics to improve industrial microalgae cultivation

Algal-bacterial interactions are ubiquitous in both natural and industrial systems, and the characterization of these interactions has been reinvigorated by potential applications in biosystem productivity. Different growth conditions can be used for operational functions, such as the use of low-quality water or high pH/alkalinity, and the altered operating conditions likely constrain microbial community structure and function in unique ways. However, research is necessary to better understand whether consortia can be designed to improve the productivity, processing, and sustainability of industrial-scale cultivations through different controls that can constrain microbial interactions for maximal light-driven outputs. The review highlights current knowledge and gaps for relevant operating conditions, as well as suggestions for near-term and longer-term improvements for large-scale cultivation and polyculture engineering.

Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling

Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.

Unlocking bacterial potential to reduce farmland N2O emissions

Farmed soils contribute substantially to global warming by emitting N2O (ref. 1), and mitigation has proved difficult2. Several microbial nitrogen transformations produce N2O, but the only biological sink for N2O is the enzyme NosZ, catalysing the reduction of N2O to N2 (ref. 3). Although strengthening the NosZ activity in soils would reduce N2O emissions, such bioengineering of the soil microbiota is considered challenging4,5. However, we have developed a technology to achieve this, using organic waste as a substrate and vector for N2O-respiring bacteria selected for their capacity to thrive in soil6-8. Here we have analysed the biokinetics of N2O reduction by our most promising N2O-respiring bacterium, Cloacibacterium sp. CB-01, its survival in soil and its effect on N2O emissions in field experiments. Fertilization with waste from biogas production, in which CB-01 had grown aerobically to about 6 × 109 cells per millilitre, reduced N2O emissions by 50-95%, depending on soil type. The strong and long-lasting effect of CB-01 is ascribed to its tenacity in soil, rather than its biokinetic parameters, which were inferior to those of other strains of N2O-respiring bacteria. Scaling our data up to the European level, we find that national anthropogenic N2O emissions could be reduced by 5-20%, and more if including other organic wastes. This opens an avenue for cost-effective reduction of N2O emissions for which other mitigation options are lacking at present.

Engineered microorganisms: A new direction in kidney stone prevention and treatment

Numerous studies have shown that intestinal and urinary tract flora are closely related to the formation of kidney stones. The removal of probiotics represented by lactic acid bacteria and the colonization of pathogenic bacteria can directly or indirectly promote the occurrence of kidney stones. However, currently existing natural probiotics have limitations. Synthetic biology is an emerging discipline in which cells or living organisms are genetically designed and modified to have biological functions that meet human needs, or even create new biological systems, and has now become a research hotspot in various fields. Using synthetic biology approaches of microbial engineering and biological redesign to enable probiotic bacteria to acquire new phenotypes or heterologous protein expression capabilities is an important part of synthetic biology research. Synthetic biology modification of microorganisms in the gut and urinary tract can effectively inhibit the development of kidney stones by a range of means, including direct degradation of metabolites that promote stone production or indirect regulation of flora homeostasis. This article reviews the research status of engineered microorganisms in the prevention and treatment of kidney stones, to provide a new and effective idea for the prevention and treatment of kidney stones.

Microbial Catalysis for CO2 Sequestration: A Geobiological Approach

One of the greatest threats facing the planet is the continued increase in excess greenhouse gasses, with CO2 being the primary driver due to its rapid increase in only a century. Excess CO2 is exacerbating known climate tipping points that will have cascading local and global effects including loss of biodiversity, global warming, and climate migration. However, global reduction of CO2 emissions is not enough. Carbon dioxide removal (CDR) will also be needed to avoid the catastrophic effects of global warming. Although the drawdown and storage of CO2 occur naturally via the coupling of the silicate and carbonate cycles, they operate over geological timescales (thousands of years). Here, we suggest that microbes can be used to accelerate this process, perhaps by orders of magnitude, while simultaneously producing potentially valuable by-products. This could provide both a sustainable pathway for global drawdown of CO2 and an environmentally benign biosynthesis of materials. We discuss several different approaches, all of which involve enhancing the rate of silicate weathering. We use the silicate mineral olivine as a case study because of its favorable weathering properties, global abundance, and growing interest in CDR applications. Extensive research is needed to determine both the upper limit of the rate of silicate dissolution and its potential to economically scale to draw down significant amounts (Mt/Gt) of CO2 Other industrial processes have successfully cultivated microbial consortia to provide valuable services at scale (e.g., wastewater treatment, anaerobic digestion, fermentation), and we argue that similar economies of scale could be achieved from this research.

Perspective on Lignin Conversion Strategies That Enable Next Generation Biorefineries

The valorization of lignin, a currently underutilized component of lignocellulosic biomass, has attracted attention to promote a stable and circular bioeconomy. Successful approaches including thermochemical, biological, and catalytic lignin depolymerization have been demonstrated, enabling opportunities for lignino-refineries and lignocellulosic biorefineries. Although significant progress in lignin valorization has been made, this review describes unexplored opportunities in chemical and biological routes for lignin depolymerization and thereby contributes to economically and environmentally sustainable lignin-utilizing biorefineries. This review also highlights the integration of chemical and biological lignin depolymerization and identifies research gaps while also recommending future directions for scaling processes to establish a lignino-chemical industry.

Shaping human gut community assembly and butyrate production by controlling the arginine dihydrolase pathway

The arginine dihydrolase pathway (arc operon) present in a subset of diverse human gut species enables arginine catabolism. This specialized metabolic pathway can alter environmental pH and nitrogen availability, which in turn could shape gut microbiota inter-species interactions. By exploiting synthetic control of gene expression, we investigated the role of the arc operon in probiotic Escherichia coli Nissle 1917 on human gut community assembly and health-relevant metabolite profiles in vitro and in the murine gut. By stabilizing environmental pH, the arc operon reduced variability in community composition across different initial pH perturbations. The abundance of butyrate producing bacteria were altered in response to arc operon activity and butyrate production was enhanced in a physiologically relevant pH range. While the presence of the arc operon altered community dynamics, it did not impact production of short chain fatty acids. Dynamic computational modeling of pH-mediated interactions reveals the quantitative contribution of this mechanism to community assembly. In sum, our framework to quantify the contribution of molecular pathways and mechanism modalities on microbial community dynamics and functions could be applied more broadly.

Autoimmune diseases exhibit shared alterations in the gut microbiota

OBJECTIVE

Accumulating evidence from microbial studies have highlighted the modulatory roles of intestinal microbes in numerous human diseases, however, the shared microbial signatures across different diseases remain relatively unclear.

METHODS

To consolidate existing knowledge across multiple studies, we performed meta-analyses of 17 disease types, covering 34 case-control datasets of 16S rRNA sequencing data, to identify shared alterations among different diseases. Furthermore, the impact of a microbial species, Lactobacillus salivarius, was established in a dextran sodium sulphate-induced colitis model and a collagen type II-induced arthritis mouse model.

RESULTS

Microbial alterations among autoimmune diseases were substantially more consistent compared with that of other diseases (cancer, metabolic disease and nervous system disease), with microbial signatures exhibiting notable discriminative power for disease prediction. Autoimmune diseases were characterized by the enrichment of Enterococcus, Veillonella, Streptococcus and Lactobacillus and the depletion of Ruminococcus, Gemmiger, Oscillibacter, Faecalibacterium, Lachnospiracea incertae sedis, Anaerostipes, Coprococcus, Alistipes, Roseburia, Bilophila, Barnesiella, Dorea, Ruminococcus2, Butyricicoccus, Phascolarctobacterium, Parabacteroides and Odoribacter, among others. Functional investigation of L. salivarius, whose genus was commonly enriched in numerous autoimmune diseases, demonstrated protective roles in two separate inflammatory mouse models.

CONCLUSION

Our study highlights a strong link between autoimmune diseases and the gut microbiota, with notably consistent microbial alterations compared with that of other diseases, indicating that therapeutic strategies that target the gut microbiome may be transferable across different autoimmune diseases. Functional validation of L. salivarius highlighted that bacterial genera associated with disease may not always be antagonistic, but may represent protective or adaptive responses to disease.

Sustainable management and valorization of biomass wastes using synthetic microbial consortia

In response to the persistent expansion of global resource demands, considerable attention has been directed toward the synthetic microbial consortia (SMC) within the domain of microbial engineering, aiming to address the sustainable management and valorization of biomass wastes. This comprehensive review systematically encapsulates the most recent advancements in research and technological applications concerning the utilization of SMC for biomass waste treatment. The construction strategies of SMC are briefly outlined, and the diverse applications of SMC in biomass wastes treatment are explored, with particular emphasis on its potential advantages in waste degradation, hazardous substances control, and high value-added products conversion. Finally, recommendations for the future development of SMC technology are proposed, and prospects for its sustainable application are discussed.

Metabolic model-based ecological modeling for probiotic design

The microbial community composition in the human gut has a profound effect on human health. This observation has lead to extensive use of microbiome therapies, including over-the-counter 'probiotic' treatments intended to alter the composition of the microbiome. Despite so much promise and commercial interest, the factors that contribute to the success or failure of microbiome-targeted treatments remain unclear. We investigate the biotic interactions that lead to successful engraftment of a novel bacterial strain introduced to the microbiome as in probiotic treatments. We use pairwise genome-scale metabolic modeling with a generalized resource allocation constraint to build a network of interactions between taxa that appear in an experimental engraftment study. We create induced sub-graphs using the taxa present in individual samples and assess the likelihood of invader engraftment based on network structure. To do so, we use a generalized Lotka-Volterra model, which we show has strong ability to predict if a particular invader or probiotic will successfully engraft into an individual's microbiome. Furthermore, we show that the mechanistic nature of the model is useful for revealing which microbe-microbe interactions potentially drive engraftment.

Metagenomics coupled with thermodynamic analysis revealed a potential way to improve the nitrogen removal efficiency of the aerobic methane oxidation coupled to denitrification process under the hypoxic condition

Aerobic methane (CH4) oxidation coupled to denitrification (AME-D) is a promising wastewater treatment process for CH4 utilization and nitrogen removal. However, it is unclear which CH4-derived carbons are suitable for the AME-D process and how these organics are metabolized. In this study, metagenomics coupled with a thermodynamic model were used to explore the microorganisms and their metabolic mechanisms in an AME-D membrane biofilm reactor (MBfR) with high nitrogen removal efficiency. Results revealed that the aerobic methanotrophs of Methylomonas with the CH4-based fermentation potential were highly enriched and played an important role in CH4 conversion in the MBfR. Bacteria of Xanthomonadaceae, Methylophilaceae, Bacteroidetes, Rhodocyclaceae, Hyphomicrobium were the main denitrifiers. C1 compounds (methanol, formaldehyde and formate) and CH4-based fermentation products are promising cross-feeding intermediates of the AME-D. Specially, by means of integrating the CH4-based fermentation with denitrification, the minimum amount of CH4 required to remove per mole of nitrate can be further reduced to 1.25 mol-CH4 mol-1-NO3-, even lower than that of methanol. Compared to the choice to secrete methanol, type I aerobic methanotrophs require a 15 % reduction in the amount of oxygen required to secrete fermentation metabolites, but a 72 % increase in the amount of CH4-C released. Based on this trade-off, optimizing oxygen supply strategies will help to construct engineered microbiomes focused on aerobic methanotrophs with CH4-based fermentation potential. This study gives an insight into C and N conversions in the AME-D process and highlights the role of CH4-based fermentation in improving the nitrogen removal efficiency of the AME-D process.

From metagenomes to metabolism: Systematically assessing the metabolic flux feasibilities for "Candidatus Accumulibacter" species during anaerobic substrate uptake

With the rapid growing availability of metagenome assembled genomes (MAGs) and associated metabolic models, the identification of metabolic potential in individual community members has become possible. However, the field still lacks an unbiassed systematic evaluation of the generated metagenomic information to uncover not only metabolic potential, but also feasibilities of these models under specific environmental conditions. In this study, we present a systematic analysis of the metabolic potential in species of "Candidatus Accumulibacter", a group of polyphosphate-accumulating organisms (PAOs). We constructed a metabolic model of the central carbon metabolism and compared the metabolic potential among available MAGs for "Ca. Accumulibacter" species. By combining Elementary Flux Modes Analysis (EFMA) with max-min driving force (MDF) optimization, we obtained all possible flux distributions of the metabolic network and calculated their individual thermodynamic feasibility. Our findings reveal significant variations in the metabolic potential among "Ca. Accumulibacter" MAGs, particularly in the presence of anaplerotic reactions. EFMA revealed 700 unique flux distributions in the complete metabolic model that enable the anaerobic uptake of acetate and its conversion into polyhydroxyalkanoates (PHAs), a well-known phenotype of "Ca. Accumulibacter". However, thermodynamic constraints narrowed down this solution space to 146 models that were stoichiometrically and thermodynamically feasible (MDF > 0 kJ/mol), of which only 8 were strongly feasible (MDF > 7 kJ/mol). Notably, several novel flux distributions for the metabolic model were identified, suggesting putative, yet unreported, functions within the PAO communities. Overall, this work provides valuable insights into the metabolic variability among "Ca. Accumulibacter" species and redefines the anaerobic metabolic potential in the context of phosphate removal. More generally, the integrated workflow presented in this paper can be applied to any metabolic model obtained from a MAG generated from microbial communities to objectively narrow the expected phenotypes from community members.

Serial cultures in invert emulsion and monophase systems for microbial community shaping and propagation

BACKGROUND

Microbial communities harbor important biotechnological potential in diverse domains, however, the engineering and propagation of such communities still face both knowledge and know-how gaps. More specifically, culturing tools are needed to propagate and shape microbial communities, to obtain desired properties, and to exploit them. Previous work suggested that micro-confinement and segregation of microorganisms using invert (water-in-oil, w/o) emulsion broth can shape communities during propagation, by alleviating biotic interactions and inducing physiological changes in cultured bacteria. The present work aimed at evaluating invert emulsion and simple broth monophasic cultures for the propagation and shaping of bacterial communities derived from raw milk in a serial propagation design.

RESULTS

The monophasic setup resulted in stable community structures during serial propagation, whereas the invert emulsion system resulted in only transiently stable structures. In addition, different communities with different taxonomic compositions could be obtained from a single inoculum. Furthermore, the implementation of invert emulsion systems has allowed for the enrichment of less abundant microorganisms and consequently facilitated their isolation on culture agar plates.

CONCLUSIONS

The monophasic system enables communities to be propagated in a stable manner, whereas the invert emulsion system allowed for the isolation of less abundant microorganisms and the generation of diverse taxonomic compositions from a single inoculum.

A high-throughput platform enables in situ screening of fatty acid-producing strains using laser ablation electrospray ionization mass spectrometry and a Python package

Microbial fatty acid-producing strains are commonly engineered to improve their performance for industrial applications. However, it is challenging to efficiently and rapidly screen target strains for engineering. This study reported an in situ analytical platform using laser ablation electrospray ionization mass spectrometry (LAESI-MS) for fast profiling of triacylglycerols in cellular lipid droplets of Aurantiochytrium sp. colonies cultured on agar plates. LAESI-MS approach allowed for the direct acquisition of a colony cell's characteristic fingerprint mass spectrum and MS/MS facilitated the identification of triacylglycerol species containing three fatty acyl groups. The fatty acid contents of colony cells were calculated based on the intensities of triacylglycerols from their characteristic fingerprint mass spectrum. A Python package called TAFA-LEMS (Triacylglycerol to Fatty Acid by LAESI-MS) was also developed to process the high-throughput MS data and extract fatty acid contents in colony cells. The results demonstrated that the LAESI-MS platform is fast, stable, and reproducible, with a data acquisition rate of ≤2 s per sampling point and ≤13.69% RSDs of the relative contents of fatty acids. In addition, LAESI-MS was successfully performed on the analysis of P. tricornutum and Y lipolytica strains. This in situ MS platform has the potential to become a common biotechnology platform for microbial strain engineering.

Mixed culture biotechnology and its versatility in dark fermentative hydrogen production

Over the years, extensive research has gone into fermentative hydrogen production using pure and mixed cultures from waste biomass with promising results. However, for up-scaling of hydrogen production mixed cultures are more appropriate to overcome the operational difficulties such as a metabolic shift in response to environmental stress, and the need for a sterile environment. Mixed culture biotechnology (MCB) is a robust and stable alternative with efficient waste and wastewater treatment capacity along with co-generation of biohydrogen and platform chemicals. Mixed culture being a diverse group of bacteria with complex metabolic functions would offer a better response to the environmental variations encountered during biohydrogen production. The development of defined mixed cultures with desired functions would help to understand the microbial community dynamics and the keystone species for improved hydrogen production. This review aims to offer an overview of the application of MCB for biohydrogen production.

Light Intensity Modulates the Functional Composition of Leaf Metabolite Groups and Phyllosphere Prokaryotic Community in Garden Lettuce (Lactuca sativa L.) Plants at the Vegetative Stage

Light intensity primarily drives plant growth and morphogenesis, whereas the ecological impact of light intensity on the phyllosphere (leaf surface and endosphere) microbiome is poorly understood. In this study, garden lettuce (Lactuca sativa L.) plants were grown under low, medium, and high light intensities. High light intensity remarkably induced the leaf contents of soluble proteins and chlorophylls, whereas it reduced the contents of leaf nitrate. In comparison, medium light intensity exhibited the highest contents of soluble sugar, cellulose, and free amino acids. Meanwhile, light intensity resulted in significant changes in the composition of functional genes but not in the taxonomic compositions of the prokaryotic community (bacteria and archaea) in the phyllosphere. Notably, garden lettuce plants under high light intensity treatment harbored more sulfur-cycling mdh and carbon-cycling glyA genes than under low light intensity, both of which were among the 20 most abundant prokaryotic genes in the leaf phyllosphere. Furthermore, the correlations between prokaryotic functional genes and lettuce leaf metabolite groups were examined to disclose their interactions under varying light intensities. The relative abundance of the mdh gene was positively correlated with leaf total chlorophyll content but negatively correlated with leaf nitrate content. In comparison, the relative abundance of the glyA gene was positively correlated with leaf total chlorophyll and carotenoids. Overall, this study revealed that the functional composition of the phyllosphere prokaryotic community and leaf metabolite groups were tightly linked in response to changing light intensities. These findings provided novel insights into the interactions between plants and prokaryotic microbes in indoor farming systems, which will help optimize environmental management in indoor farms and harness beneficial plant-microbe relationships for crop production.

The Exometabolome of Xylella fastidiosa in Contact with Paraburkholderia phytofirmans Supernatant Reveals Changes in Nicotinamide, Amino Acids, Biotin, and Plant Hormones

Microbial competition within plant tissues affects invading pathogens' fitness. Metabolomics is a great tool for studying their biochemical interactions by identifying accumulated metabolites. Xylella fastidiosa, a Gram-negative bacterium causing Pierce's disease (PD) in grapevines, secretes various virulence factors including cell wall-degrading enzymes, adhesion proteins, and quorum-sensing molecules. These factors, along with outer membrane vesicles, contribute to its pathogenicity. Previous studies demonstrated that co-inoculating X. fastidiosa with the Paraburkholderia phytofirmans strain PsJN suppressed PD symptoms. Here, we further investigated the interaction between the phytopathogen and the endophyte by analyzing the exometabolome of wild-type X. fastidiosa and a diffusible signaling factor (DSF) mutant lacking quorum sensing, cultivated with 20% P. phytofirmans spent media. Liquid chromatography-mass spectrometry (LC-MS) and the Method for Metabolite Annotation and Gene Integration (MAGI) were used to detect and map metabolites to genomes, revealing a total of 121 metabolites, of which 25 were further investigated. These metabolites potentially relate to host adaptation, virulence, and pathogenicity. Notably, this study presents the first comprehensive profile of X. fastidiosa in the presence of a P. phytofirmans spent media. The results highlight that P. phytofirmans and the absence of functional quorum sensing affect the ratios of glutamine to glutamate (Gln:Glu) in X. fastidiosa. Additionally, two compounds with plant metabolism and growth properties, 2-aminoisobutyric acid and gibberellic acid, were downregulated when X. fastidiosa interacted with P. phytofirmans. These findings suggest that P. phytofirmans-mediated disease suppression involves modulation of the exometabolome of X. fastidiosa, impacting plant immunity.

Why do lactic acid bacteria thrive in chain elongation microbiomes?

Efficient waste management is necessary to transition towards a more sustainable society. An emerging trend is to use mixed culture biotechnology to produce chemicals from organic waste. Insights into the metabolic interactions between community members and their growth characterization are needed to mediate knowledge-driven bioprocess development and optimization. Here, a granular sludge bioprocess for the production of caproic acid through sugar-based chain elongation metabolism was established. Lactic acid and chain-elongating bacteria were identified as the two main functional guilds in the granular community. The growth features of the main community representatives (isolate Limosilactobacillus musocae G03 for lactic acid bacteria and type strain Caproiciproducens lactatifermentans for chain-elongating bacteria) were characterized. The measured growth rates of lactic acid bacteria (0.051 ± 0.005 h-1) were two times higher than those of chain-elongating bacteria (0.026 ± 0.004 h-1), while the biomass yields of lactic acid bacteria (0.120 ± 0.005 g biomass/g glucose) were two times lower than that of chain-elongating bacteria (0.239 ± 0.007 g biomass/g glucose). This points towards differential growth strategies, with lactic acid bacteria resembling that of a r-strategist and chain-elongating bacteria resembling that of a K-strategist. Furthermore, the half-saturation constant of glucose for L. mucosae was determined to be 0.35 ± 0.05 g/L of glucose. A linear trend of caproic acid inhibition on the growth of L. mucosae was observed, and the growth inhibitory caproic acid concentration was predicted to be 13.6 ± 0.5 g/L, which is the highest reported so far. The pre-adjustment of L. mucosae to 4 g/L of caproic acid did not improve the overall resistance to it, but did restore the growth rates at low caproic acid concentrations (1-4 g/L) to the baseline values (i.e., growth rate at 0 g/L of caproic acid). High resistance to caproic acid enables lactic acid bacteria to persist and thrive in the systems intended for caproic acid production. Here, insights into the growth of two main functional guilds of sugar-based chain elongation systems are provided which allows for a better understanding of their interactions and promotes future bioprocess design and optimization.

Metabolite cross-feeding enables concomitant catabolism of chlorinated methanes and chlorinated ethenes in synthetic microbial assemblies

Isolate studies have been a cornerstone for unraveling metabolic pathways and phenotypical (functional) features. Biogeochemical processes in natural and engineered ecosystems are generally performed by more than a single microbe and often rely on mutualistic interactions. We demonstrate the rational bottom-up design of synthetic, interdependent co-cultures to achieve concomitant utilization of chlorinated methanes as electron donors and organohalogens as electron acceptors. Specialized anaerobes conserve energy from the catabolic conversion of chloromethane or dichloromethane to formate, H2, and acetate, compounds that the organohalide-respiring bacterium Dehalogenimonas etheniformans strain GP requires to utilize cis-1,2-dichloroethenene and vinyl chloride as electron acceptors. Organism-specific qPCR enumeration matched the growth of individual dechlorinators to the respective functional (i.e. dechlorination) traits. The metabolite cross-feeding in the synthetic (co-)cultures enables concomitant utilization of chlorinated methanes (i.e. chloromethane and dichloromethane) and chlorinated ethenes (i.e. cis-1,2-dichloroethenene and vinyl chloride) without the addition of an external electron donor (i.e. formate and H2). The findings illustrate that naturally occurring chlorinated C1 compounds can sustain anaerobic food webs, an observation with implications for the development of interdependent, mutualistic communities, the sustenance of microbial life in oligotrophic and energy-deprived environments, and the fate of chloromethane/dichloromethane and chlorinated electron acceptors (e.g. chlorinated ethenes) in pristine environments and commingled contaminant plumes.

Re-considering and designing microbiomes for future waste biorefinery

It is an increasingly promising research direction using microbiomes to produce various chemicals in order to support people's growing need for sustainability. Currently, bottom-up constructed defined microbiomes and top-down constructed undefined microbiomes play an essential role in the fields of synthetic biology and environmental engineering, respectively. However, if we are goal-oriented and want to align scientific principles with technology and engineering in future waste biorefinery, we need to reconsider and design microbiomes interdisciplinarily. In this editorial, we briefly review the latest applications of two approaches to microbiome design (bottom-up and top-down) and the dilemmas faced in using complex waste. Consequently, we introduce the concept of 'sustainable synthetic microbiomics' to apply combined bottom-up and top-down constructed microbiomes to provide products for human needs from low-value waste. Furthermore, we outline the relatively comprehensive research contents and expected prospects based on the pressing problems. Finally, burning questions on key research contents are proposed for specific cases, hoping to provide valuable views for future microbiome biorefinery.

In-situ substitution and community dynamics modeling for enhanced safety in Chinese rice wine brewing

This research paper focuses on the application of the "Design-Build-Test-Learn" framework to design and evaluate a synthetic microbial community aimed at studying the impact of Lactic Acid Bacteria (LAB) interactions and fitness on the formation of biogenic amines (BAs) in Chinese rice wine (CRW). The study reveals a close correlation between the assembly model of LAB and the accumulation of BAs in CRW, and multiple interactions were observed between amine-producing and non-amine-producing LAB, including commensalism, amensalism, and competition. The commensalism among amine-producing LAB was found to promote BAs accumulation through metabolic cross-feeding of amino acids. Moreover, the higher-order interaction community was designed to regulate the BAs formation effectively. For instance, the interference of Lactiplantibacillus plantarum (ACBC271) resulted in the elimination of amine-producing LAB viability, resulting in a 22% decrease (not exceeding 43.54 mg/L) in the total amount of BAs. Simulation of community dynamics models further suggests that LAB with quantitative social interactions can effectively control LAB accumulation in CRW by forecasting fluctuation in BAs generation through fitness competition and metabolic interference. Overall, this study provides valuable insights into the complex interaction networks within microbial communities in traditional fermentation ecosystems. It also proposes a novel approach for quality control of nitrogen food safety factors in fermented foods.

Expanding the toolbox of probiotic Escherichia coli Nissle 1917 for synthetic biology

Escherichia coli Nissle 1917 (EcN) is a probiotic microbe that has the potential to be developed as a promising chassis for synthetic biology applications. However, the molecular tools and techniques for utilizing EcN remain to be further explored. To address this opportunity, the EcN-based toolbox was systematically expanded, enabling EcN as a powerful platform for more applications. First, two EcN cryptic plasmids and other compatible plasmids were genetically engineered to enrich the manipulable plasmid toolbox for multiple gene coexpression. Next, two EcN-based technologies were developed, including the conjugation strategy for DNA transfer, and quantification of protein expression capability. Finally, the EcN-based applications were further expanded by developing EcN native integrase-mediated genetic engineering and establishing an in vitro cell-free protein synthesis (CFPS) system. Overall, this study expanded the toolbox for manipulating and making full use of EcN as a commonly used probiotic chassis, providing several simplified, dependable, and predictable strategies for researchers working in synthetic biology fields.

Co-Occurrence Analysis of Citrus Root Bacterial Microbiota under Citrus Greening Disease

Candidatus Liberibacter asiaticus (CLas) is associated with Citrus Huanglongbing (HLB), a devastating disease in the US. Previously, we conducted a two-year-long monthly HLB survey by quantitative real-time PCR using root DNA fractions prepared from 112 field grapefruit trees grafted on sour orange rootstock. Approximately 10% of the trees remained CLas-free during the entire survey period. This study conducted 16S metagenomics using the time-series root DNA fractions, monthly prepared during twenty-four consecutive months, followed by microbial co-occurrence network analysis to investigate the microbial factors contributing to the CLas-free phenotype of the aforementioned trees. Based on the HLB status and the time when the trees were first diagnosed as CLas-positive during the survey, the samples were divided into four groups, Stage H (healthy), Stage I (early), II (mid), and III (late) samples. The 16S metagenomics data using Silva 16S database v132 revealed that HLB compromised the diversity of rhizosphere microbiota. At the phylum level, Actinobacteria and Proteobacteria were the predominant bacterial phyla, comprising >93% of total bacterial phyla, irrespective of HLB status. In addition, a temporal change in the rhizosphere microbe population was observed during a two-year-long survey, from which we confirmed that some bacterial families differently responded to HLB disease status. The clustering of the bacterial co-occurrence network data revealed the presence of a subnetwork composed of Streptomycetaceae and bacterial families with plant growth-promoting activity in Stage H and III samples. These data implicated that the Streptomycetaceae subnetwork may act as a functional unit against HLB.

Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures

IMPORTANCE

Microbes present one of the most diverse sources of biochemistry in nature, and mRNA sequencing provides a comprehensive view of this biological activity by quantitatively measuring microbial transcriptomes. However, efficient mRNA capture for sequencing presents significant challenges in prokaryotes as mRNAs are not poly-adenylated and typically make up less than 5% of total RNA compared with rRNAs that exceed 80%. Recently developed methods for sequencing bacterial mRNA typically rely on depleting rRNA by tiling large probe sets against rRNAs; however, such approaches are expensive, time-consuming, and challenging to scale to varied bacterial species and complex microbial communities. Therefore, we developed EMBR-seq+, a method that requires fewer than 10 short oligonucleotides per rRNA to achieve up to 99% rRNA depletion in diverse bacterial species. Finally, EMBR-seq+ resulted in a deeper view of the transcriptome, enabling systematic quantification of how microbial interactions result in altering the transcriptional state of bacteria within co-cultures.

Control points for design of taxonomic composition in synthetic human gut communities

Microbial communities offer vast potential across numerous sectors but remain challenging to systematically control. We develop a two-stage approach to guide the taxonomic composition of synthetic microbiomes by precisely manipulating media components and initial species abundances. By combining high-throughput experiments and computational modeling, we demonstrate the ability to predict and design the diversity of a 10-member synthetic human gut community. We reveal that critical environmental factors governing monoculture growth can be leveraged to steer microbial communities to desired states. Furthermore, systematically varied initial abundances drive variation in community assembly and enable inference of pairwise inter-species interactions via a dynamic ecological model. These interactions are overall consistent with conditioned media experiments, demonstrating that specific perturbations to a high-richness community can provide rich information for building dynamic ecological models. This model is subsequently used to design low-richness communities that display low or high temporal taxonomic variability over an extended period. A record of this paper's transparent peer review process is included in the supplemental information.

An evolution-based framework for describing human gut bacteria

The human gut microbiome contains many bacterial strains of the same species ('strain-level variants'). Describing strains in a biologically meaningful way rather than purely taxonomically is an important goal but challenging due to the genetic complexity of strain-level variation. Here, we measured patterns of co-evolution across >7,000 strains spanning the bacterial tree-of-life. Using these patterns as a prior for studying hundreds of gut commensal strains that we isolated, sequenced, and metabolically profiled revealed widespread structure beneath the phylogenetic level of species. Defining strains by their co-evolutionary signatures enabled predicting their metabolic phenotypes and engineering consortia from strain genome content alone. Our findings demonstrate a biologically relevant organization to strain-level variation and motivate a new schema for describing bacterial strains based on their evolutionary history.

Subcellular compartmentalization in the biosynthesis and engineering of plant natural products

Plant natural products (PNPs) are specialized metabolites with diverse bioactivities. They are extensively used in the pharmaceutical, cosmeceutical and food industries. PNPs are synthesized in plant cells by enzymes that are distributed in different subcellular compartments with unique microenvironments, such as ions, co-factors and substrates. Plant metabolic engineering is an emerging and promising approach for the sustainable production of PNPs, for which the knowledge of the subcellular compartmentalization of their biosynthesis is instrumental. In this review we describe the state of the art on the role of subcellular compartments in the biosynthesis of major types of PNPs, including terpenoids, phenylpropanoids, alkaloids and glucosinolates, and highlight the efforts to target biosynthetic pathways to subcellular compartments in plants. In addition, we will discuss the challenges and strategies in the field of plant synthetic biology and subcellular engineering. We expect that newly developed methods and tools, together with the knowledge gained from the microbial chassis, will greatly advance plant metabolic engineering.

Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics

The ability to effectively represent microbiome dynamics is a crucial challenge in their quantitative analysis and engineering. By using autoencoder neural networks, we show that microbial growth dynamics can be compressed into low-dimensional representations and reconstructed with high fidelity. These low-dimensional embeddings are just as effective, if not better, than raw data for tasks such as identifying bacterial strains, predicting traits like antibiotic resistance, and predicting community dynamics. Additionally, we demonstrate that essential dynamical information of these systems can be captured using far fewer variables than traditional mechanistic models. Our work suggests that machine learning can enable the creation of concise representations of high-dimensional microbiome dynamics to facilitate data analysis and gain new biological insights.

Biocontrol mechanisms of Bacillus: Improving the efficiency of green agriculture

Species of the genus Bacillus have been widely used for the biocontrol of plant diseases in the demand for sustainable agricultural development. New mechanisms underlying Bacillus biocontrol activity have been revealed with the development of microbiome and microbe-plant interaction research. In this review, we first briefly introduce the typical Bacillus biocontrol mechanisms, such as the production of antimicrobial compounds, competition for niches/nutrients, and induction of systemic resistance. Then, we discussed in detail the new mechanisms of pathogen quorum sensing interference and reshaping of the soil microbiota. The "cry for help" mechanism was also introduced, in which plants can release specific signals under pathogen attack to recruit biocontrol Bacillus for root colonization against invasion. Finally, two emerging strategies for enhancing the biocontrol efficacy of Bacillus agents, including the construction of synthetic microbial consortia and the application of rhizosphere-derived prebiotics, were proposed.

Emerging technologies in adipose tissue research

Technologies are transforming the understanding of adipose tissue as a complex and dynamic tissue that plays a critical role in energy homoeostasis and metabolic health. This mini-review provides a brief overview of the potential impact of novel technologies in biomedical research and aims to identify areas where these technologies can make the most significant contribution to adipose tissue research. It discusses the impact of cutting-edge technologies such as single-cell sequencing, multi-omics analyses, spatial transcriptomics, live imaging, 3D tissue engineering, microbiome analysis, in vivo imaging, and artificial intelligence/machine learning. As these technologies continue to evolve, we can expect them to play an increasingly important role in advancing our understanding of adipose tissue and improving the treatment of related diseases.

Functional Redundancy Secures Resilience of Chain Elongation Communities upon pH Shifts in Closed Bioreactor Ecosystems

For anaerobic mixed cultures performing microbial chain elongation, it is unclear how pH alterations affect the abundance of key players, microbial interactions, and community functioning in terms of medium-chain carboxylate yields. We explored pH effects on mixed cultures enriched in continuous anaerobic bioreactors representing closed model ecosystems. Gradual pH increase from 5.5 to 6.5 induced dramatic shifts in community composition, whereas product range and yields returned to previous states after transient fluctuations. To understand community responses to pH perturbations over long-term reactor operation, we applied Aitchison PCA clustering, linear mixed-effects models, and random forest classification on 16S rRNA gene amplicon sequencing and process data. Different pH preferences of two key chain elongation species─one Clostridium IV species related to Ruminococcaceae bacterium CPB6 and one Clostridium sensu stricto species related to Clostridium luticellarii─were determined. Network analysis revealed positive correlations of Clostridium IV with lactic acid bacteria, which switched from Olsenella to Lactobacillus along the pH increase, illustrating the plasticity of the food web in chain elongation communities. Despite long-term cultivation in closed systems over the pH shift experiment, the communities retained functional redundancy in fermentation pathways, reflected by the emergence of rare species and concomitant recovery of chain elongation functions.

Infant microbiome cultivation and metagenomic analysis reveal Bifidobacterium 2'-fucosyllactose utilization can be facilitated by coexisting species

The early-life gut microbiome development has long-term health impacts and can be influenced by factors such as infant diet. Human milk oligosaccharides (HMOs), an essential component of breast milk that can only be metabolized by some beneficial gut microorganisms, ensure proper gut microbiome establishment and infant development. However, how HMOs are metabolized by gut microbiomes is not fully elucidated. Isolate studies have revealed the genetic basis for HMO metabolism, but they exclude the possibility of HMO assimilation via synergistic interactions involving multiple organisms. Here, we investigate microbiome responses to 2'-fucosyllactose (2'FL), a prevalent HMO and a common infant formula additive, by establishing individualized microbiomes using fecal samples from three infants as the inocula. Bifidobacterium breve, a prominent member of infant microbiomes, typically cannot metabolize 2'FL. Using metagenomic data, we predict that extracellular fucosidases encoded by co-existing members such as Ruminococcus gnavus initiate 2'FL breakdown, thus critical for B. breve's growth. Using both targeted co-cultures and by supplementation of R. gnavus into one microbiome, we show that R. gnavus can promote extensive growth of B. breve through the release of lactose from 2'FL. Overall, microbiome cultivation combined with genome-resolved metagenomics demonstrates that HMO utilization can vary with an individual's microbiome.

Construction of synthetic anti-fouling consortia: fouling control effects and polysaccharide degradation mechanisms

The physical states and chemical components of bulk sludge determine the occurrence and development of membrane fouling in membrane bioreactors. Thus, regulation of sludge suspensions can provide new strategies for fouling control. In this study, we used "top-down" enrichment to construct a synthetic anti-fouling consortium (SAC) from bio-cake and evaluate its roles in preventing membrane fouling. The SAC was identified as Massilia-dominated and could almost wholly degrade the alginate solution (1,000 mg/L) within 72 h. Two-dimensional Fourier transformation infrared correlation spectroscopy (2D-FTIR-CoS) analysis demonstrated that the SAC induced the breakage of glycosidic bond in alginates. The co-cultivation of sludge with a low dosage of SAC (ranging from 0 to 1%) led to significant fouling mitigation, increased sludge floc size, and decreased unified membrane fouling index value (0.55 ± 0.06 and 0.11 ± 0.05). FTIR spectra and X-ray spectroscopy analyses demonstrated that the addition of SAC decreased the abundance of the O-acetylation of polysaccharides in extracellular polymeric substances. Secondary derivatives analysis of amide I spectra suggested a strong reduction in the α-helix/(β-sheet + random coil) ratio in the presence of SAC, which was expected to enhance cell aggregation. Additionally, the extracellular secretions of SAC could both inhibit biofilm formation and strongly disperse the existing biofilm strongly during the biofilm incubation tests. In summary, this study illustrates the feasibility and benefits of using SAC for fouling control and provides a new strategy for fouling control.

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.

A review of microbial nitrogen transformations and microbiome engineering for biological nitrogen removal under salinity stress

The osmotic stress caused by salinity exerts severe inhibition on the process of biological nitrogen removal (BNR), leading to the deterioration of biosystems and the discharge of nitrogen with saline wastewater. Feasible strategies to solve the bottleneck in saline wastewater treatment have attracted great attention, but relevant studies to improve nitrogen transformations and enhance the salt-tolerance of biosystems in terms of microbiome engineering have not been systematically reviewed and discussed. This work attempted to provide a more comprehensive explanation of both BNR and microbiome engineering approaches for saline wastewater treatment. The effect of salinity on conventional BNR pathways, nitrification-denitrification and anammox, was summarized at cellular and metabolic levels, including the nitrogen metabolic pathways, the functional microorganisms, and the inhibition threshold of salinity. Promising nitrogen transformations, such as heterotrophic nitrification-aerobic denitrification, ammonium assimilation and the coupling of conventional pathways, were introduced and compared based on advantages and challenges in detail. Strategies to improve the salt tolerance of biosystems were proposed and evaluated from the perspective of microbiome engineering. Finally, prospects of future investigation and applications on halophilic microbiomes in saline wastewater treatment were discussed.

Progress and Prospects of Natural Glycoside Sweetener Biosynthesis: A Review

To achieve an adequate sense of sweetness with a healthy low-sugar diet, it is necessary to explore and produce sugar alternatives. Recently, glycoside sweeteners and their biosynthetic approaches have attracted the attention of researchers. In this review, we first outlined the synthetic pathways of glycoside sweeteners, including the key enzymes and rate-limiting steps. Next, we reviewed the progress in engineered microorganisms producing glycoside sweeteners, including de novo synthesis, whole-cell catalysis synthesis, and in vitro synthesis. The applications of metabolic engineering strategies, such as cofactor engineering and enzyme modification, in the optimization of glycoside sweetener biosynthesis were summarized. Finally, the prospects of combining enzyme engineering and machine learning strategies to enhance the production of glycoside sweeteners were discussed. This review provides a perspective on synthesizing glycoside sweeteners in microbial cells, theoretically guiding the bioproduction of glycoside sweeteners.

Exploring the controllability of the Baijiu fermentation process with microbiota orientation

Product quality and stability improvement is important for development of the Baijiu industry. Generally, Baijiu brewing is carried out in a spontaneous fermentation system mediated by microbiota. Thus, complexity and instability are major features. Due to the insufficient understanding of the mechanism for producing Baijiu, the precise control of the fermentation progress has still not been realized, ultimately affecting product quality and stability. The flavor of Baijiu is the most important factor in determining its quality and is formed by microbiota under the driving force of various physicochemical parameters, such as moisture, acidity, and temperature. Therefore, exploring the association among microbiota (core), physicochemical factors (reference) and flavor compounds (target) has become a key point to clarify the formation mechanism for the flavor quality of Baijiu. Daqu fermentation and liquor fermentation are the two major stages of Baijiu brewing. Daqu, distillers' grains, and pit mud, as the most important fermentation substrates of the microbiota respectively, provide a large number of functional microorganisms related to the flavor components. To this end, we reviewed the relevant research progress of microbiota diversity in different fermentation substrates and the interaction mechanisms among microbiota, physicochemical parameters, and flavor components in this paper. Moreover, a research hypothesis of precise control of the Baijiu fermentation process by building fermentation models based on this is proposed. The key point for this idea is the identification of core microbiota closely associated with the formation of key flavor components by multi-omics technology and the acquisition of culturable strains. With this foundation, fermentation models suitable for different brewing environments will be established by constructing synthetic microbiota, designing mathematical models, and determining key fermentation model parameters. The ultimate goal will be to effectively improve the quality and stability of Baijiu products through model regulation.

Species' functional traits and interactions drive nitrate-mediated sulfur-oxidizing community structure and functioning

IMPORTANCE

Understanding the processes and mechanisms governing microbial community assembly and their linkages to ecosystem functioning has long been a core issue in microbial ecology. An in-depth insight still requires combining with analyses of species' functional traits and microbial interactions. Our study showed how species' functional traits and interactions determined microbial community structure and functions by a well-controlled laboratory experiment with nitrate-mediated sulfur oxidation systems using high-throughput sequencing and culture-dependent technologies. The results provided solid evidences that species' functional traits and interactions were the intrinsic factors determining community structure and function. More importantly, our study established quantitative links between community structure and function based on species' functional traits and interactions, which would have important implications for the design and synthesis of microbiomes with expected functions.

Systems and synthetic biology-driven engineering of live bacterial therapeutics

The past decade has seen growing interest in bacterial engineering for therapeutically relevant applications. While early efforts focused on repurposing genetically tractable model strains, such as Escherichia coli, engineering gut commensals is gaining traction owing to their innate capacity to survive and stably propagate in the intestine for an extended duration. Although limited genetic tractability has been a major roadblock, recent advances in systems and synthetic biology have unlocked our ability to effectively harness native gut commensals for therapeutic and diagnostic purposes, ranging from the rational design of synthetic microbial consortia to the construction of synthetic cells that execute "sense-and-respond" logic operations that allow real-time detection and therapeutic payload delivery in response to specific signals in the intestine. In this review, we outline the current progress and latest updates on microbial therapeutics, with particular emphasis on gut commensal engineering driven by synthetic biology and systems understanding of their molecular phenotypes. Finally, the challenges and prospects of engineering gut commensals for therapeutic applications are discussed.

Promotion of plasmid maintenance by heterogeneous partitioning of microbial communities

Transferable plasmids play a critical role in shaping the functions of microbial communities. Previous studies suggested multiple mechanisms underlying plasmid persistence and abundance. Here, we focus on the interplay between heterogeneous community partitioning and plasmid fates. Natural microbiomes often experience partitioning that creates heterogeneous local communities with reduced population sizes and biodiversity. Little is known about how population partitioning affects the plasmid fate through the modulation of community structure. By modeling and experiments, we show that heterogeneous community partitioning can paradoxically promote the persistence of a plasmid that would otherwise not persist in a global community. Among the local communities created by partitioning, a minority will primarily consist of members able to transfer the plasmid fast enough to support its maintenance by serving as a local plasmid haven. Our results provide insights into plasmid maintenance and suggest a generalizable approach to modulate plasmid persistence for engineering and medical applications.

Unraveling the functional instability of bacterial consortia in crude oil degradation via integrated co-occurrence networks

Introduction

Soil ecosystems are threatened by crude oil contamination, requiring effective microbial remediation. However, our understanding of the key microbial taxa within the community, their interactions impacting crude oil degradation, and the stability of microbial functionality in oil degradation remain limited.

Methods

To better understand these key points, we enriched a crude oil-degrading bacterial consortium generation 1 (G1) from contaminated soil and conducted three successive transfer passages (G2, G3, and G4). Integrated Co-occurrence Networks method was used to analyze microbial species correlation with crude oil components across G1-G4.

Results and discussion

In this study, G1 achieved a total petroleum hydrocarbon (TPH) degradation rate of 32.29% within 10 days. Through three successive transfer passages, G2-G4 consortia were established, resulting in a gradual decrease in TPH degradation to 23.14% at the same time. Specifically, saturated hydrocarbon degradation rates ranged from 18.32% to 14.17% among G1-G4, and only G1 exhibited significant aromatic hydrocarbon degradation (15.59%). Functional annotation based on PICRUSt2 and FAPROTAX showed that functional potential of hydrocarbons degradation diminished across generations. These results demonstrated the functional instability of the bacterial consortium in crude oil degradation. The relative abundance of the Dietzia genus showed the highest positive correlation with the degradation efficiency of TPH and saturated hydrocarbons (19.48, 18.38, p < 0.05, respectively), Bacillus genus demonstrated the highest positive correlation (21.94, p < 0.05) with the efficiency of aromatic hydrocarbon degradation. The key scores of Dietzia genus decreased in successive generations. A significant positive correlation (16.56, p < 0.05) was observed between the Bacillus and Mycetocola genera exclusively in the G1 generation. The decline in crude oil degradation function during transfers was closely related to changes in the relative abundance of key genera such as Dietzia and Bacillus as well as their interactions with other genera including Mycetocola genus. Our study identified key bacterial genera involved in crude oil remediation microbiome construction, providing a theoretical basis for the next step in the construction of the oil pollution remediation microbiome.

Bioinoculants as a means of increasing crop tolerance to drought and phosphorus deficiency in legume-cereal intercropping systems

Ensuring plant resilience to drought and phosphorus (P) stresses is crucial to support global food security. The phytobiome, shaped by selective pressures, harbors stress-adapted microorganisms that confer host benefits like enhanced growth and stress tolerance. Intercropping systems also offer benefits through facilitative interactions, improving plant growth in water- and P-deficient soils. Application of microbial consortia can boost the benefits of intercropping, although questions remain about the establishment, persistence, and legacy effects within resident soil microbiomes. Understanding microbe- and plant-microbe dynamics in drought-prone soils is key. This review highlights the beneficial effects of rhizobacterial consortia-based inoculants in legume-cereal intercropping systems, discusses challenges, proposes a roadmap for development of P-solubilizing drought-adapted consortia, and identifies research gaps in crop-microbe interactions.

Regulation on Pathway Metabolic Fluxes to Enhance Colanic Acid Production in Escherichia coli

Colanic acid (CA) is a natural polysaccharide macromolecule with rich and unique biological properties and is a promising candidate for use in food and cosmetics. To date, the efficient biosynthesis of CA and the influence of product accumulation on the strains used have yet to be precisely investigated. Herein, bottlenecks in the CA metabolic pathway were untangled by finely regulating the expression of manA, cpsG, fcl, and rcsA. Engineered strains produced CA at >1 g/L in shake flasks without dependence on cold temperatures, and it was verified in a 1 L bioreactor with a titer up to 18.64 g/L within 24 h. The accumulation of CA caused a decrease in the saturated fatty acid content (represented by C16:0 and C18:0) in the cell membrane. This study demonstrated pathway engineering for efficient CA production in cell factories and provided insights into the barriers and solutions faced in the biosynthesis of natural products.

Synthetic Light-Driven Consortia for Carbon-Negative Biosynthesis

Synthetic light-driven consortia composed of phototrophs and heterotrophs have attracted increasing attention owing to their potential to be used in sustainable biotechnology. In recent years, synthetic phototrophic consortia have been used to produce bulk chemicals, biofuels, and other valuable bioproducts. In addition, autotrophic-heterotrophic symbiosis systems have potential applications in wastewater treatment, bioremediation, and as a method for phytoplankton bloom control. Here, we discuss progress made on the biosynthesis of phototrophic microbial consortia. In addition, strategies for optimizing the synthetic light-driven consortia are summarized. Moreover, we highlight current challenges and future research directions for the development of robust and controllable synthetic light-driven consortia.

Multi-omic profiling of a novel activated sludge strain Sphingobacterium sp. WM1 reveals the mechanism of tetracycline biodegradation and its merits of potential application

As an emerging pollutant, the antibiotic tetracycline (TC) has been consistently detected in wastewater and activated sludge. Biodegradation represents a potentially crucial pathway to dissipate TC contamination. However, few efficient TC-degrading bacteria have been isolated and a comprehensive understanding of the molecular mechanisms underlying TC degradation is still lacking. In this study, a novel TC-degrading bacterium, designated as Sphingobacterium sp. WM1, was successfully isolated from activated sludge. Strain WM1 exhibited a remarkable performance in degrading 50 mg/L TC within 1 day under co-metabolic conditions. Genomic analysis of the strain WM1 unveiled the presence of three functional tetX genes. Unraveling the complex molecular mechanisms, transcriptome analysis highlighted the role of upregulated transmembrane transport and accelerated electron transport in facilitating TC degradation. Proteomics confirmed the up-regulation of proteins involved in cellular biosynthesis/metabolism and ribosomal processes. Crucially, the tetX gene-encoding protein showed a significant upregulation, indicating its role in TC degradation. Heterologous expression of the tetX gene resulted in TC dissipation from an initial 51.9 mg/L to 4.2 mg/L within 24 h. The degradation pathway encompassed TC hydroxylation, transforming into TP461 and subsequent metabolites, which effectively depleted TC's inhibitory activity. Notably, the tetX genes in strain WM1 showed limited potential for horizontal gene transfer. Collectively, strain WM1's potent TC degradation capacity signals a promise for enhancing TC clean-up strategies.

Integrating a tailored recurrent neural network with Bayesian experimental design to optimize microbial community functions

Microbiomes interact dynamically with their environment to perform exploitable functions such as production of valuable metabolites and degradation of toxic metabolites for a wide range of applications in human health, agriculture, and environmental cleanup. Developing computational models to predict the key bacterial species and environmental factors to build and optimize such functions are crucial to accelerate microbial community engineering. However, there is an unknown web of interactions that determine the highly complex and dynamic behavior of these systems, which precludes the development of models based on known mechanisms. By contrast, entirely data-driven machine learning models can produce physically unrealistic predictions and often require significant amounts of experimental data to learn system behavior. We develop a physically-constrained recurrent neural network that preserves model flexibility but is constrained to produce physically consistent predictions and show that it can outperform existing machine learning methods in the prediction of certain experimentally measured species abundance and metabolite concentrations. Further, we present a closed-loop, Bayesian experimental design algorithm to guide data collection by selecting experimental conditions that simultaneously maximize information gain and target microbial community functions. Using a bioreactor case study, we demonstrate how the proposed framework can be used to efficiently navigate a large design space to identify optimal operating conditions. The proposed methodology offers a flexible machine learning approach specifically tailored to optimize microbiome target functions through the sequential design of informative experiments that seek to explore and exploit community functions.

Synthetic phylogenetically diverse communities promote denitrification and stability

Denitrification is an important process of the global nitrogen cycle as some of its intermediates are environmentally important or related to global warming. However, how the phylogenetic diversity of denitrifying communities affects their denitrification rates and temporal stability remains unclear. Here we selected denitrifiers based on their phylogenetic distance to construct two groups of synthetic denitrifying communities: one closely related (CR) group with all strains from the genus Shewanella and the other distantly related (DR) group with all constituents from different genera. All synthetic denitrifying communities (SDCs) were experimentally evolved for 200 generations. The results showed that high phylogenetic diversity followed by experimental evolution promoted the function and stability of synthetic denitrifying communities. Specifically, the productivity and denitrification rates were significantly (P < 0.05) higher with Paracocus denitrificans as the dominant species (since the 50th generation) in the DR community than those in the CR community. The DR community also showed significantly (t = 7.119, df = 10, P < 0.001) higher stability through overyielding and asynchrony of species fluctuations, and showed more complementarity than the CR group during the experimental evolution. This study has important implications for applying synthetic communities to remediate environmental problems and mitigate greenhouse gas emissions.