Synthetic microbial communities of heterotrophs and phototrophs facilitate sustainable growth

Mixed and membrane-separated culturing of synthetic cyanobacteria-yeast consortia reveals metabolic cross-talk mimicking natural cyanolichens

Metabolite exchange mediates crucial interactions in microbial communities, significantly impacting global carbon and nitrogen cycling. Understanding these chemically-mediated interactions is essential for elucidating natural community functions and developing engineered synthetic communities. This study investigated membrane-separated bioreactors (mBRs) as a novel tool to identify transient metabolites and their producers/consumers in mixed microbial communities. We compared three co-culture methods (direct mixed, 2-chamber mBR, and 3-chamber mBR) to grow a synthetic binary community of the cyanobacterium Synechococcus elongatus PCC 7942 and the fungus Rhodotorula toruloides NBRC 0880, as well as axenic S. elongatus. Despite not being natural lichen constituents, these organisms exhibited interactions resembling those in cyanolichens. S. elongatus fixed CO2 into sugars as the primary shared metabolite, while R. toruloides secreted various biochemicals, predominantly sugar alcohols, mirroring the metabolite exchange observed in natural lichens. The mBR systems successfully captured metabolite gradients and revealed rapidly consumed compounds, including TCA cycle intermediates and amino acids. Our approach demonstrated that the 2-chamber mBR optimally balanced metabolite exchange and growth dynamics. This study provides insights into cross-species metabolic interactions and presents a valuable tool for investigating and engineering synthetic microbial communities with potential applications in biotechnology and environmental science.

Mixotrophic growth of a ubiquitous marine diatom

Diatoms are major players in the global carbon cycle, and their metabolism is affected by ocean conditions. Understanding the impact of changing inorganic nutrients in the oceans on diatoms is crucial, given the changes in global carbon dioxide levels. Here, we present a genome-scale metabolic model (iMK1961) for Cylindrotheca closterium, an in silico resource to understand uncharacterized metabolic functions in this ubiquitous diatom. iMK1961 represents the largest diatom metabolic model to date, comprising 1961 open reading frames and 6718 reactions. With iMK1961, we identified the metabolic response signature to cope with drastic changes in growth conditions. Comparing model predictions with Tara Oceans transcriptomics data unraveled C. closterium's metabolism in situ. Unexpectedly, the diatom only grows photoautotrophically in 21% of the sunlit ocean samples, while the majority of the samples indicate a mixotrophic (71%) or, in some cases, even a heterotrophic (8%) lifestyle in the light. Our findings highlight C. closterium's metabolic flexibility and its potential role in global carbon cycling.

A new era of synthetic biology-microbial community design

Synthetic biology conceptualizes biological complexity as a network of biological parts, devices, and systems with predetermined functionalities and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesize and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms, can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multispecies communities. We argue for a shift in perspective from single organism-centred approaches to emphasizing the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities. Graphical Abstract.

High-throughput profiling of metabolic responses to exogenous nutrients in Synechocystis sp. PCC 6803

Cyanobacteria fix carbon dioxide and release carbon-containing compounds into the wider ecosystem, yet they are sensitive to small metabolites that may impact their growth and physiology. Several cyanobacteria can grow mixotrophically, but we currently lack a molecular understanding of how specific nutrients may alter the compounds they release, limiting our knowledge of how environmental factors might impact primary producers and the ecosystems they support. In this study, we develop a high-throughput phytoplankton culturing platform and identify how the model cyanobacterium Synechocystis sp. PCC 6803 responds to nutrient supplementation. We assess growth responses to 32 nutrients at two concentrations, identifying 15 that are utilized mixotrophically. Seven nutrient sources significantly enhance growth, while 19 elicit negative growth responses at one or both concentrations. High-throughput exometabolomics indicates that oxidative stress limits Synechocystis' growth but may be alleviated by antioxidant metabolites. Furthermore, glucose and valine induce strong changes in metabolite exudation in a possible effort to correct pathway imbalances or maintain intracellular elemental ratios. This study sheds light on the flexibility and limits of cyanobacterial physiology and metabolism, as well as how primary production and trophic food webs may be modulated by exogenous nutrients.IMPORTANCECyanobacteria capture and release carbon compounds to fuel microbial food webs, yet we lack a comprehensive understanding of how external nutrients modify their behavior and what they produce. We developed a high throughput culturing platform to evaluate how the model cyanobacterium Synechocystis sp. PCC 6803 responds to a broad panel of externally supplied nutrients. We found that growth may be enhanced by metabolites that protect against oxidative stress, and growth and exudate profiles are altered by metabolites that interfere with central carbon metabolism and elemental ratios. This work contributes a holistic perspective of the versatile response of Synechocystis to externally supplied nutrients, which may alter carbon flux into the wider ecosystem.

Pseudomonas putida as saviour for troubled Synechococcus elongatus in a synthetic co-culture - interaction studies based on a multi-OMICs approach

In their natural habitats, microbes rarely exist in isolation; instead, they thrive in consortia, where various interactions occur. In this study, a defined synthetic co-culture of the cyanobacterium S. elongatus cscB, which supplies sucrose to the heterotrophic P. putida cscRABY, is investigated to identify potential interactions. Initial experiments reveal a remarkable growth-promoting effect of the heterotrophic partner on the cyanobacterium, resulting in an up to 80% increase in the growth rate and enhanced photosynthetic capacity. Vice versa, the presence of the cyanobacterium has a neutral effect on P. putida cscRABY, highlighting the resilience of pseudomonads against stress and their potential as co-culture partners. Next, a suitable reference process reinforcing the growth-promoting effect is established in a parallel photobioreactor system, which sets the basis for the analysis of the co-culture at the transcriptome, proteome, and metabolome levels. In addition to several moderate changes, including alterations in the metabolism and stress response in both microbes, this comprehensive multi-OMICs approach strongly hints towards the exchange of further molecules beyond the unidirectional feeding with sucrose. Taken together, these findings provide valuable insights into the complex dynamics between both co-culture partners, indicating multi-level interactions, which can be employed for further streamlining of the co-cultivation system.

Harnessing the potential: advances in cyanobacterial natural product research and biotechnology

Covering: 2000 to 2023Cyanobacteria produce a variety of bioactive natural products that can pose a threat to humans and animals as environmental toxins, but also have potential for or inspire pharmaceutical use. As oxygenic phototrophs, cyanobacteria furthermore hold great promise for sustainable biotechnology. Yet, the necessary tools for exploiting their biotechnological potential have so far been established only for a few model strains of cyanobacteria, while large untapped biosynthetic resources are hidden in slow-growing cyanobacterial genera that are difficult to access by genetic techniques. In recent years, several approaches have been developed to circumvent the bottlenecks in cyanobacterial natural product research. Here, we summarize current progress that has been made in unlocking or characterizing cryptic metabolic pathways using integrated omics techniques, orphan gene cluster activation, use of genetic approaches in original producers, heterologous expression and chemo-enzymatic techniques. We are mainly highlighting genomic mining concepts and strategies towards high-titer production of cyanobacterial natural products from the last 10 years and discuss the need for further research developments in this field.

Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass

Growing environmental concerns and the need to adopt a circular economy have highlighted the importance of waste valorization for resource recovery. Microbial consortia-enabled biotechnologies have made significant developments in the biomanufacturing of valuable resources from waste biomass that serve as suitable alternatives to petrochemical-derived products. These microbial consortia-based processes are designed following a top-down or bottom-up engineering approach. The top-down approach is a classical method that uses environmental variables to selectively steer an existing microbial consortium to achieve a target function. While high-throughput sequencing has enabled microbial community characterization, the major challenge is to disentangle complex microbial interactions and manipulate the structure and function accordingly. The bottom-up approach uses prior knowledge of the metabolic pathway and possible interactions among consortium partners to design and engineer synthetic microbial consortia. This strategy offers some control over the composition and function of the consortium for targeted bioprocesses, but challenges remain in optimal assembly methods and long-term stability. In this review, we present the recent advancements, challenges, and opportunities for further improvement using top-down and bottom-up approaches for microbiome engineering. As the bottom-up approach is relatively a new concept for waste valorization, this review explores the assembly and design of synthetic microbial consortia, ecological engineering principles to optimize microbial consortia, and metabolic engineering approaches for efficient conversion. Integration of top-down and bottom-up approaches along with developments in metabolic modeling to predict and optimize consortia function are also highlighted.

ONE-SENTENCE SUMMARY

This review highlights the microbial consortia-driven waste valorization for biomanufacturing through top-down and bottom-up design approaches and describes strategies, tools, and unexplored opportunities to optimize the design and stability of such consortia.

Metabolic engineering of Synechococcus elongatus 7942 for enhanced sucrose biosynthesis

The capability of cyanobacteria to produce sucrose from CO2 and light has a remarkable societal and biotechnological impact since sucrose can serve as a carbon and energy source for a variety of heterotrophic organisms and can be converted into value-added products. However, most metabolic engineering efforts have focused on understanding local pathway alterations that drive sucrose biosynthesis and secretion in cyanobacteria rather than analyzing the global flux re-routing that occurs following induction of sucrose production by salt stress. Here, we investigated global metabolic flux alterations in a sucrose-secreting (cscB-overexpressing) strain relative to its wild-type Synechococcus elongatus 7942 parental strain. We used targeted metabolomics, 13C metabolic flux analysis (MFA), and genome-scale modeling (GSM) as complementary approaches to elucidate differences in cellular resource allocation by quantifying metabolic profiles of three cyanobacterial cultures - wild-type S. elongatus 7942 without salt stress (WT), wild-type with salt stress (WT/NaCl), and the cscB-overexpressing strain with salt stress (cscB/NaCl) - all under photoautotrophic conditions. We quantified the substantial rewiring of metabolic fluxes in WT/NaCl and cscB/NaCl cultures relative to WT and identified a metabolic bottleneck limiting carbon fixation and sucrose biosynthesis. This bottleneck was subsequently mitigated through heterologous overexpression of glyceraldehyde-3-phosphate dehydrogenase in an engineered sucrose-secreting strain. Our study also demonstrates that combining 13C-MFA and GSM is a useful strategy to both extend the coverage of MFA beyond central metabolism and to improve the accuracy of flux predictions provided by GSM.

A Coculture of Photoautotrophs and Hydrolytic Heterotrophs Enables Efficient Upcycling of Starch from Wastewater toward Biomass-Derived Products: Synergistic Interactions Impacting Metabolism of the Consortium

Even with particular interest in sustainable development, due to the limited types of bioavailable carbon sources that could support heterotrophic/mixotrophic growth, microalgae-derived products still suffer from inconsistent yield and high costs. This study demonstrates a successful cocultivation of the photoautotroph Chlorella vulgaris with a hydrolytic-enzyme-abundant heterotroph, Saccharomycopsis fibuligera, enabling efficient starch upcycling from water/wastewater toward enhancing microalgae-dominant biomass and lipid production. The enzymatic activities of S. fibuligera contributed to the hydrolysis of starch into glucose, generating a 7-fold higher biomass through mixotrophic/heterotrophic growth of C. vulgaris. Further, scanning transmission electron microscopy (STEM) and quantitative analysis suggested a significantly induced accumulation of lipids in C. vulgaris. Results of meta-transcriptomics revealed the critical regulatory role of illumination in interaction shifting. Gene expression for glycolysis and lipid biosynthesis of C. vulgaris were highly activated during dark periods. Meanwhile, during illumination periods, genes coding for glucoamylase and the sulfur-related activities in S. fibuligera were significantly upregulated, leading to induced starch hydrolysis and potential increased competition for sulfur utilization, respectively. This study indicates that hydrolytic organisms could collaborate to make starch bioavailable for nonhydrolytic microalgae, thus broadening the substrate spectrum and making starch a novel biotechnological feedstock for microalgae-derived products, e.g., biofuels or single-cell protein.

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.

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.

Synthetic Denitrifying Communities Reveal a Positive and Dynamic Biodiversity-Ecosystem Functioning Relationship during Experimental Evolution

Biodiversity is vital for ecosystem functions and services, and many studies have reported positive, negative, or neutral biodiversity-ecosystem functioning (BEF) relationships in plant and animal systems. However, if the BEF relationship exists and how it evolves remains elusive in microbial systems. Here, we selected 12 Shewanella denitrifiers to construct synthetic denitrifying communities (SDCs) with a richness gradient spanning 1 to 12 species, which were subjected to approximately 180 days (with 60 transfers) of experimental evolution with generational changes in community functions continuously tracked. A significant positive correlation was observed between community richness and functions, represented by productivity (biomass) and denitrification rate, however, such a positive correlation was transient, only significant in earlier days (0 to 60) during the evolution experiment (180 days). Also, we found that community functions generally increased throughout the evolution experiment. Furthermore, microbial community functions with lower richness exhibited greater increases than those with higher richness. Biodiversity effect analysis revealed positive BEF relationships largely attributable to complementary effects, which were more pronounced in communities with lower richness than those with higher richness. This study is one of the first studies that advances our understanding of BEF relationships and their evolutionary mechanisms in microbial systems, highlighting the crucial role of evolution in predicting the BEF relationship in microbial systems. IMPORTANCE Despite the consensus that biodiversity supports ecosystem functioning, not all experimental models of macro-organisms support this notion with positive, negative, or neutral biodiversity-ecosystem functioning (BEF) relationships reported. The fast-growing, metabolically versatile, and easy manipulation nature of microbial communities allows us to explore well the BEF relationship and further interrogate if the BEF relationship remains constant during long-term community evolution. Here, we constructed multiple synthetic denitrifying communities (SDCs) by randomly selecting species from a candidate pool of 12 Shewanella denitrifiers. These SDCs differ in species richness, spanning 1 to 12 species, and were monitored continuously for community functional shifts during approximately 180-day parallel cultivation. We demonstrated that the BEF relationship was dynamic with initially (day 0 to 60) greater productivity and denitrification among SDCs of higher richness. However, such pattern was reversed thereafter with greater productivity and denitrification increments in lower-richness SDCs, likely due to a greater accumulation of beneficial mutations during the experimental evolution.

Stress-induced metabolic exchanges between complementary bacterial types underly a dynamic mechanism of inter-species stress resistance

Metabolic cross-feeding plays vital roles in promoting ecological diversity. While some microbes depend on exchanges of essential nutrients for growth, the forces driving the extensive cross-feeding needed to support the coexistence of free-living microbes are poorly understood. Here we characterize bacterial physiology under self-acidification and establish that extensive excretion of key metabolites following growth arrest provides a collaborative, inter-species mechanism of stress resistance. This collaboration occurs not only between species isolated from the same community, but also between unrelated species with complementary (glycolytic vs. gluconeogenic) modes of metabolism. Cultures of such communities progress through distinct phases of growth-dilution cycles, comprising of exponential growth, acidification-triggered growth arrest, collaborative deacidification, and growth recovery, with each phase involving different combinations of physiological states of individual species. Our findings challenge the steady-state view of ecosystems commonly portrayed in ecological models, offering an alternative dynamical view based on growth advantages of complementary species in different phases.

Remediation of metals and plastic from e-waste by iron mine indigenous acidophilic bacteria

The growing consumption of electrical and electronic equipment leads to high amounts of electronic waste (e-waste), which is now considered the fastest-growing waste stream at the national and international levels. As well as being a potential secondary resource due to its precious metals content, e-waste also contains strategic metals and plastics. For instance, mobile phones have about 25-55% plastic substances. A few studies have been performed to investigate the potential of indigenous bacteria in metals' bioleaching from the polluted environment. Heterotrophic bioleaching potential in acidic conditions had been preliminarily investigated. Two soil types of iron ore were considered the source of indigenous bacteria. Despite the acidophilic nature of the bacterial consortium, they continued their leaching activity regardless of alkaline conditions. Maximum biorecovery rate related to copper (4%) responding to the main soil, owing to the higher copper content of mobile phone waste. Chromium had the least recovery rate (⩽0.002%). Overall, the maximum metal recovery rate was 4.7%, achieved by tailing heterotrophs at an e-waste loading of 10 g l^-1. Statistical analysis had shown that there was no significant difference between the metal recovery rates and soil type or even the solid-liquid ratio (p > 0.05). Although acidophilic indigenous heterotrophs could not be an appropriate alternative for a large amount of metal recovery process, they might have considerable potential in the bioremediation of e-waste plastic fractions and metals in low concentrations simultaneously.

A model industrial workhorse: Bacillus subtilis strain 168 and its genome after a quarter of a century

The vast majority of genomic sequences are automatically annotated using various software programs. The accuracy of these annotations depends heavily on the very few manual annotation efforts that combine verified experimental data with genomic sequences from model organisms. Here, we summarize the updated functional annotation of Bacillus subtilis strain 168, a quarter century after its genome sequence was first made public. Since the last such effort 5 years ago, 1168 genetic functions have been updated, allowing the construction of a new metabolic model of this organism of environmental and industrial interest. The emphasis in this review is on new metabolic insights, the role of metals in metabolism and macromolecule biosynthesis, functions involved in biofilm formation, features controlling cell growth, and finally, protein agents that allow class discrimination, thus allowing maintenance management, and accuracy of all cell processes. New 'genomic objects' and an extensive updated literature review have been included for the sequence, now available at the International Nucleotide Sequence Database Collaboration (INSDC: AccNum AL009126.4).

River sediment microbial community composition and function impacted by thallium spill

Thallium (Tl) is widely used in various industries, which increases the risk of leakage into the environment. Since Tl is highly toxic, it can do a great harm to human health and ecosystem. In order to explore the response of freshwater sediment microorganisms to sudden Tl spill, metagenomic technique was used to elucidate the changes of microbial community composition and functional genes in river sediments. Tl pollution could have profound impacts on microbial community composition and function. Proteobacteria remained the dominance in contaminated szediments, indicating that it had a strong resistance to Tl contamination, and Cyanobacteria also showed a certain resistance. Tl pollution also had a certain screening effect on resistance genes and affected the abundance of resistance genes. Metal resistance genes (MRGs) and antibiotic resistance genes (ARGs) were enriched at the site near the spill site, where Tl concentration was relatively low among polluted sites. When Tl concentration was higher, the screening effect was not obvious and the resistance genes even became lower. Moreover, there was a significant correlation between MRGs and ARGs. In addition, co-occurrence network analysis showed that Sphingopyxis had the most links with resistance genes, indicating that it was the biggest potential host of resistance genes. This study provided new insight towards the shifts in the composition and function of microbial communities after sudden serious Tl contamination.

Cyanobacteria as cell factories for the photosynthetic production of sucrose

Biofuels and other biologically manufactured sustainable goods are growing in popularity and demand. Carbohydrate feedstocks required for industrial fermentation processes have traditionally been supplied by plant biomass, but the large quantities required to produce replacement commodity products may prevent the long-term feasibility of this approach without alternative strategies to produce sugar feedstocks. Cyanobacteria are under consideration as potential candidates for sustainable production of carbohydrate feedstocks, with potentially lower land and water requirements relative to plants. Several cyanobacterial strains have been genetically engineered to export significant quantities of sugars, especially sucrose. Sucrose is not only naturally synthesized and accumulated by cyanobacteria as a compatible solute to tolerate high salt environments, but also an easily fermentable disaccharide used by many heterotrophic bacteria as a carbon source. In this review, we provide a comprehensive summary of the current knowledge of the endogenous cyanobacterial sucrose synthesis and degradation pathways. We also summarize genetic modifications that have been found to increase sucrose production and secretion. Finally, we consider the current state of synthetic microbial consortia that rely on sugar-secreting cyanobacterial strains, which are co-cultivated alongside heterotrophic microbes able to directly convert the sugars into higher-value compounds (e.g., polyhydroxybutyrates, 3-hydroxypropionic acid, or dyes) in a single-pot reaction. We summarize recent advances reported in such cyanobacteria/heterotroph co-cultivation strategies and provide a perspective on future developments that are likely required to realize their bioindustrial potential.

A Highly Compatible Phototrophic Community for Carbon-Negative Biosynthesis

CO₂ sequestration engineering is promising for carbon-negative biosynthesis, and artificial communities can solve more complex problems than monocultures. However, obtaining an ideal photosynthetic community is still a great challenge. Herein, we describe the development of a highly compatible photosynthetic community (HCPC) by integrating a sucrose-producing CO₂ sequestration module and a super-coupled module. The cyanobacteria CO₂ sequestration module was obtained using stepwise metabolic engineering and then coupled with the efficient sucrose utilization module Vibrio natriegens. Integrated omics analysis indicated that enhanced photosynthetic electron transport and extracellular vesicles promote intercellular communication. Additionally, the HCPC was used to channel CO₂ into valuable chemicals, enabling the overall release of -22.27 to -606.59 kgCO₂ e kg^-1 in the end products. This novel light-driven community could facilitate circular economic implementation in the future.

Streamlining of a synthetic co-culture towards an individually controllable one-pot process for polyhydroxyalkanoate production from light and CO2

Rationally designed synthetic microbial consortia carry a vast potential for biotechnological applications. The application of such a consortium in a bioprocess, however, requires tight and individual controllability of the involved microbes. Here, we present the streamlining of a co-cultivation process consisting of Synechococcus elongatus cscB and Pseudomonas putida for the production of polyhydroxyalkanoates (PHA) from light and CO2. First, the process was improved by employing P. putida cscRABY, a strain with a higher metabolic activity towards sucrose. Next, the individual controllability of the co-culture partners was addressed by providing different nitrogen sources, each exclusively available for one strain. By this, the growth rate of the co-culture partners could be regulated individually, and defined conditions could be set. The molC/molN ratio, a key value for PHA accumulation, was estimated from the experimental data, and the necessary feeding rates to obtain a specific ratio could be predicted. This information was then implemented in the co-cultivation process, following the concept of a DBTL-cycle. In total, the streamlining of the process resulted in an increased maximal PHA titer of 393 mg/L and a PHA production rate of 42.1 mg/(L•day).

Higher-order interactions shape microbial interactions as microbial community complexity increases

Non-pairwise interactions, or higher-order interactions (HOIs), in microbial communities have been described as significant drivers of emergent features in microbiomes. Yet, the re-organization of microbial interactions between pairwise cultures and larger communities remains largely unexplored from a molecular perspective but is central to our understanding and further manipulation of microbial communities. Here, we used a bottom-up approach to investigate microbial interaction mechanisms from pairwise cultures up to 4-species communities from a simple microbiome (Hafnia alvei, Geotrichum candidum, Pencillium camemberti and Escherichia coli). Specifically, we characterized the interaction landscape for each species combination involving E. coli by identifying E. coli's interaction-associated mutants using an RB-TnSeq-based interaction assay. We observed a deep reorganization of the interaction-associated mutants, with very few 2-species interactions conserved all the way up to a 4-species community and the emergence of multiple HOIs. We further used a quantitative genetics strategy to decipher how 2-species interactions were quantitatively conserved in higher community compositions. Epistasis-based analysis revealed that, of the interactions that are conserved at all levels of complexity, 82% follow an additive pattern. Altogether, we demonstrate the complex architecture of microbial interactions even within a simple microbiome, and provide a mechanistic and molecular explanation of HOIs.

Carbon-negative synthetic biology: challenges and emerging trends of cyanobacterial technology

Global warming and climate instability have spurred interest in using renewable carbon resources for the sustainable production of chemicals. Cyanobacteria are ideal cellular factories for carbon-negative production of chemicals owing to their great potentials for directly utilizing light and CO₂ as sole energy and carbon sources, respectively. However, several challenges in adapting cyanobacterial technology to industry, such as low productivity, poor tolerance, and product harvesting difficulty, remain. Synthetic biology may finally address these challenges. Here, we summarize recent advances in the production of value-added chemicals using cyanobacterial cell factories, particularly in carbon-negative synthetic biology and emerging trends in cyanobacterial applications. We also propose several perspectives on the future development of cyanobacterial technology for commercialization.

Microalgae-based wastewater treatment - Microalgae-bacteria consortia, multi-omics approaches and algal stress response

Sustainable environmental management is one of the important aspects of sustainable development goals. Increasing amounts of wastewaters (WW) from exponential economic growth is a major challenge, and conventional treatment methods entail a huge carbon footprint in terms of energy use and GHG emissions. Microalgae-based WW treatment is a potential candidate for sustainable WW treatment. The nutrients which are otherwise unutilized in the conventional processes are recovered in the beneficial microalgal biomass. This review presents comprehensive information regarding the potential of microalgae as sustainable bioremediation agents. Microalgae-bacterial consortia play a critical role in synergistic nutrient removal, supported by the complex nutritional and metabolite exchange between microalgae and the associated bacteria. Design of effective microalgae-bacteria consortia either by screening or by recent technologies such as synthetic biology approaches are highly required for efficient WW treatment. Furthermore, this review discusses the crucial research gap in microalgal WW treatment - the application of a multi-omics platform for understanding microalgal response towards WW conditions and the design of effective microalgal or microalgae-bacteria consortia based on genetic information. While metagenomics helps in the identification and monitoring of the microbial community throughout the treatment process, transcriptomics, proteomics and metabolomics aid in studying the algal cellular response towards the nutrients and pollutants in WW. It has been established that the integration of microalgal processes into conventional WW treatment systems is feasible. In this direction, future research directions for microalgal WW treatment emphasize the need for identifying the niche in WW treatment, while highlighting the pilot sale plants in existence. Microalgae-based WW treatment could be a potential phase in the waste hierarchy of circular economy and sustainability, considering WWs are a rich secondary source of finite resources such as nitrogen and phosphorus.

Light-Driven Synthetic Biology: Progress in Research and Industrialization of Cyanobacterial Cell Factory

Light-driven synthetic biology refers to an autotrophic microorganisms-based research platform that remodels microbial metabolism through synthetic biology and directly converts light energy into bio-based chemicals. This technology can help achieve the goal of carbon neutrality while promoting green production. Cyanobacteria are photosynthetic microorganisms that use light and CO₂ for growth and production. They thus possess unique advantages as "autotrophic cell factories". Various fuels and chemicals have been synthesized by cyanobacteria, indicating their important roles in research and industrial application. This review summarized the progresses and remaining challenges in light-driven cyanobacterial cell factory. The choice of chassis cells, strategies used in metabolic engineering, and the methods for high-value CO₂ utilization will be discussed.

Copper Effect on Microalgae: Toxicity and Bioremediation Strategies

Microalgae are increasingly recognised as suitable microorganisms for heavy metal (HM) removal, since they are able to adsorb them onto their cell wall and, in some cases, compartmentalise them inside organelles. However, at relatively high HM concentrations, they could also show signs of stress, such as organelle impairments and increased activities of antioxidant enzymes. The main aim of this review is to report on the mechanisms adopted by microalgae to counteract detrimental effects of high copper (Cu) concentrations, and on the microalgal potential for Cu bioremediation of aquatic environments. Studying the delicate balance between beneficial and detrimental effects of Cu on microalgae is of particular relevance as this metal is widely present in aquatic environments facing industrial discharges. This metal often induces chloroplast functioning impairment, generation of reactive oxygen species (ROS) and growth rate reduction in a dose-dependent manner. However, microalgae also possess proteins and small molecules with protective role against Cu and, in general, metal stress, which increase their resistance towards these pollutants. Our critical literature analysis reveals that microalgae can be suitable indicators of Cu pollution in aquatic environments, and could also be considered as components of eco-sustainable devices for HM bioremediation in association with other organisms.

Bacterial species metabolic interaction network for deciphering the lignocellulolytic system in fungal cultivating termite gut microbiota

Fungus-cultivating termite Odontotermes badius developed a mutualistic association with Termitomyces fungi for the plant material decomposition and providing a food source for the host survival. The mutualistic relationship sifted the microbiome composition of the termite gut and Termitomyces fungal comb. Symbiotic bacterial communities in the O. badius gut and fungal comb have been studied extensively to identify abundant bacteria and their lignocellulose degradation capabilities. Despite several metagenomic studies, the species-wide metabolic interaction pattern of bacterial communities in termite gut and fungal comb remains unclear. The bacterial species metabolic interaction network (BSMIN) has been constructed with 230 bacteria identified from the O. badius gut and fungal comb microbiota. The network portrayed the metabolic map of the entire microbiota and highlighted several inter-species biochemical interactions like cross-feeding, metabolic interdependency, and competition. Further, the reconstruction and analysis of the bacterial influence network (BIN) quantified the positive and negative pairwise influences in the termite gut and fungal comb microbial communities. Several key macromolecule degraders and fermentative microbial entities have been identified by analyzing the BIN. The mechanistic interplay between these influential microbial groups and the crucial glycoside hydrolases (GH) enzymes produced by the macromolecule degraders execute the community-wide functionality of lignocellulose degradation and subsequent fermentation. The metabolic interaction pattern between the nine influential microbial species has been determined by considering them growing in a synthetic microbial community. Competition (30%), parasitism (47%), and mutualism (17%) were predicted to be the major mode of metabolic interaction in this synthetic microbial community. Further, the antagonistic metabolic effect was found to be very high in the metabolic-deprived condition, which may disrupt the community functionality. Thus, metabolic interactions of the crucial bacterial species and their GH enzyme cocktail identified from the O. badius gut and fungal comb microbiota may provide essential knowledge for developing a synthetic microcosm with efficient lignocellulolytic machinery.

Progress of engineered bacteria for tumor therapy

Recently, with the rapid development of bioengineering technology and nanotechnology, natural bacteria were modified to change their physiological activities and therapeutic functions for improved therapeutic efficiency of diseases. These engineered bacteria were equipped to achieve directed genetic reprogramming, selective functional reorganization and precise spatio-temporal control. In this review, research progress in the basic modification methodologies of engineered bacteria were summarized, and representative researches about their therapeutic performances for tumor treatment were illustrated. Moreover, the strategies for the construction of engineered colonies based on engineering of individual bacteria were summarized, providing innovative ideas for complex functions and efficient anti-tumor treatment. Finally, current limitation and challenges of tumor therapy utilizing engineered bacteria were discussed.

Applications of synthetic light-driven microbial consortia for biochemicals production

Synthetic microbial consortia provide a versatile and efficient platform for biochemicals production through the labor division. Especially, microbial communities composed of phototrophs and heterotrophs offer a promising alternative, as they can directly convert carbon dioxide (CO₂) into chemicals. Within this system, photoautotrophic microbes can convert CO₂ into organic carbon for microbial growth and metabolites synthesis by the heterotrophic partners. In return, heterotrophs can provide additional CO₂ to support the growth of photoautotrophic microbes. However, the unmatched growing conditions, low stability and production efficiency of synthetic microbial consortia hinder their further applications. Thus, design and construction of mutualistic and stable synthetic light-driven microbial consortia are urgently needed. In this review, the progress of synthetic light-driven microbial consortia for chemicals production was comprehensively summarized. In addition, space-efficient synthetic light-driven microbial consortia in hydrogel system were reviewed. Perspectives on orderly distribution of light-driven microbial consortia associated with 3D printing technology in biomanufacturing were also addressed.

Recent Biotechnology Advances in Bio-Conversion of Lignin to Lipids by Bacterial Cultures

The complexity and recalcitrance of the lignin structure is a major barrier to its efficient utilization and commercial production of high-value products. In recent years, the “bio-funneling” transformation ability of microorganisms has provided a significant opportunity for lignin conversion and integrated biorefinery. Based on the chemical structure of lignin, this mini-review introduces the recent advances of lignin depolymerization by bacterial strains and the application of microbial lignin degradation in lipids production. Furthermore, the current challenges, future trends and perspectives for microbe-based lignin conversion to lipids are discussed.

Interactions of E. coli with algae and aquatic vegetation in natural waters

Both algae and bacteria are essential inhabitants of surface waters. Their presence is of ecological significance and sometimes of public health concern triggering various control actions. Interactions of microalgae, macroalgae, submerged aquatic vegetation, and bacteria appear to be important phenomena necessitating a deeper understanding by those involved in research and management of microbial water quality. Given the long-standing reliance on Escherichia coli as an indicator of the potential presence of pathogens in natural waters, understanding its biology in aquatic systems is necessary. The major effects of algae and aquatic vegetation on E. coli growth and survival, including changes in the nutrient supply, modification of water properties and constituents, impact on sunlight radiation penetration, survival as related to substrate attachment, algal mediation of secondary habitats, and survival inhibition due to the release of toxic substances and antibiotics, are discussed in this review. An examination of horizontal gene transfer and antibiotic resistance potential, strain-specific interactions, effects on the microbial, microalgae, and grazer community structure, and hydrodynamic controls is given. Outlooks due to existing and expected consequences of climate change and advances in observation technologies via high-resolution satellite imaging, unmanned aerial vehicles (drones), and mathematical modeling are additionally covered. The multiplicity of interactions among bacteria, algae, and aquatic vegetation as well as multifaceted impacts of these interactions, create a wide spectrum of research opportunities and technology developments.

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g., genomics, metabolomics, and transcriptomics). In this review, we analyze the available Big Data useful for metabolic modeling and compile the available GEM reconstruction tools that integrate Big Data. We also discuss recent applications in industry and research that include predicting phenotypes, elucidating metabolic pathways, producing industry-relevant chemicals, identifying drug targets, and generating knowledge to better understand host-associated diseases. In addition to the up-to-date review of GEMs currently available, we assessed a plethora of tools for developing new GEMs that include macromolecular expression and dynamic resolution. Finally, we provide a perspective in emerging areas, such as annotation, data managing, and machine learning, in which GEMs will play a key role in the further utilization of Big Data.

Kinetic, metabolic, and statistical analytics: addressing metabolic transport limitations among organelles and microbial communities

Microbial organisms engage in a variety of metabolic interactions. A crucial part of these interactions is the exchange of molecules between different organelles, cells, and the environment. The main forces mediating this metabolic exchange are transporters. This transport can be difficult to measure experimentally because several transport mechanisms remain opaque. However, theoretical calculations about the inputs and outputs of cells via metabolic exchanges have enabled the successful inference of the workings of intra-organismal and inter-organismal systems. Kinetic, metabolic, and statistical modeling approaches in combination with omics data are enhancing our knowledge and understanding about metabolic exchange and mass resource allocation. This model-driven analytics approach can guide effective experimental design and yield new insights into biological function and control.

Challenges and opportunities in biological funneling of heterogeneous and toxic substrates beyond lignin

Significant developments in the understanding and manipulation of microbial metabolism have enabled the use of engineered biological systems toward a more sustainable energy and materials economy. While developments in metabolic engineering have primarily focused on the conversion of carbohydrates, substantial opportunities exist for using these same principles to extract value from more heterogeneous and toxic waste streams, such as those derived from lignin, biomass pyrolysis, or industrial waste. Funneling heterogeneous substrates from these streams toward valuable products, termed biological funneling, presents new challenges in balancing multiple catabolic pathways competing for shared cellular resources and engineering against perturbation from toxic substrates. Solutions to many of these challenges have been explored within the field of lignin valorization. This perspective aims to extend beyond lignin to highlight the challenges and discuss opportunities for use of biological systems to upgrade previously inaccessible waste streams.

Mechanistic models of microbial community metabolism

Microbial communities affect many facets of human health and well-being. Naturally occurring bacteria, whether in nature or the human body, rarely exist in isolation. A deeper understanding of the metabolic functions of these communities is now possible with emerging computational models. In this review, we summarize frameworks for constructing mechanistic models of microbial community metabolism and discuss available algorithms for model analysis. We highlight essential decision points that greatly influence algorithm selection, as well as model analysis. Polymicrobial metabolic models can be utilized to gain insights into host-pathogen interactions, bacterial engineering, and many more translational applications.

Biotechnology for secure biocontainment designs in an emerging bioeconomy

Genetically modified organisms (GMOs) have emerged as an integral component of a sustainable bioeconomy, with an array of applications in agriculture, bioenergy, and biomedicine. However, the rapid development of GMOs and associated synthetic biology approaches raises a number of biosecurity concerns related to environmental escape of GMOs, detection thereof, and impact upon native ecosystems. A myriad of genetic safeguards have been deployed in diverse microbial hosts, ranging from classical auxotrophies to global genome recoding. However, to realize the full potential of microbes as biocatalytic platforms in the bioeconomy, a deeper understanding of the fundamental principles governing microbial responsiveness to biocontainment constraints, and interactivity of GMOs with the environment, is required. Herein, we review recent analytical biotechnological advances and strategies to assess biocontainment and microbial bioproductivity, as well as opportunities for predictive systems biodesigns towards securing a viable bioeconomy.

Interactions of microalgae-bacteria consortia for nutrient removal from wastewater: A review

Nitrogen and phosphorus pollution can cause eutrophication, resulting in ecosystem disruption. Wastewater treatment systems employing microalgae-bacteria consortia have the potential to enhance the nutrient removal efficiency from wastewater through mutual interaction and synergetic effects. The knowledge and control of the mechanisms involved in microalgae-bacteria interaction could improve the system's ability to transform and recover nutrients. In this review, a critical evaluation of recent literature was carried out to synthesize knowledge related to mechanisms of interaction between microalgae and bacteria consortia for nutrient removal from wastewater. It is now established that microalgae can produce oxygen through photosynthesis for bacteria and, in turn, bacteria supply the required metabolites and inorganic carbon source for algae growth. Here we highlight how the interaction between microalgae and bacteria is highly dependent on the nitrogen species in the wastewater. When the nitrogen source is ammonium, the generated oxygen by microalgae has a positive influence on nitrifying bacteria. When the nitrogen source is nitrate, the oxygen can have an inhibitory effect on denitrifying bacteria. However, some strains of microalgae have the capability to supply hydrogen gas for hydrogenotrophic denitrifiers as an energy source. Recent literature on biogranulation of microalgae and bacteria and its application for nutrient removal and biomass recovery is also discussed as a promising approach. Significant research challenges remain for the integration of microalgae-bacteria consortia into wastewater treatment processes including microbial community control and process stability over long time horizons.

The ecology of wine fermentation: a model for the study of complex microbial ecosystems

The general interest in microbial ecology has skyrocketed over the past decade, driven by technical advances and by the rapidly increasing appreciation of the fundamental services that these ecosystems provide. In biotechnology, ecosystems have many more functionalities than single species, and, if properly understood and harnessed, will be able to deliver better outcomes for almost all imaginable applications. However, the complexity of microbial ecosystems and of the interactions between species has limited their applicability. In research, next generation sequencing allows accurate mapping of the microbiomes that characterise ecosystems of biotechnological and/or medical relevance. But the gap between mapping and understanding, to be filled by "functional microbiomics", requires the collection and integration of many different layers of complex data sets, from molecular multi-omics to spatial imaging technologies to online ecosystem monitoring tools. Holistically, studying the complexity of most microbial ecosystems, consisting of hundreds of species in specific spatial arrangements, is beyond our current technical capabilities, and simpler model systems with fewer species and reduced spatial complexity are required to establish the fundamental rules of ecosystem functioning. One such ecosystem, the ecosystem responsible for natural alcoholic fermentation, can provide an excellent tool to study evolutionarily relevant interactions between multiple species within a relatively easily controlled environment. This review will critically evaluate the approaches that are currently implemented to dissect the cellular and molecular networks that govern this ecosystem. KEY POINTS: • Evolutionarily isolated fermentation ecosystem can be used as an ecological model. • Experimental toolbox is gearing towards mechanistic understanding of this ecosystem. • Integration of multidisciplinary datasets is key to predictive understanding.

The sum is greater than the parts: exploiting microbial communities to achieve complex functions

Multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology. The rational intervention of microbial communities for the purpose of improved function has been facilitated in part by developments in multi-omics approaches, synthetic biology, and computational methods. Recent studies have demonstrated the benefits of rational interventions to human and animal health as well as agricultural productivity. Emergent technologies, such as in situ modification of complex microbial community and community metabolic modeling, represent an avenue to engineer sustainable microbial communities. In this opinion, we review relevant computational and experimental approaches to study and engineer microbial communities and discuss their potential for biotechnological applications.

Degradation of organic pollutants by intimately coupling photocatalytic materials with microbes: a review

With the rapid development of industry and agriculture, large amounts of organic pollutants have been released into the environment. Consequently, the degradation of refractory organic pollutants has become one of the toughest challenges in remediation. To solve this problem, intimate coupling of photocatalysis and biodegradation (ICPB) technology, which allows the simultaneous action of photocatalysis and biodegradation and thus integrates the advantages of photocatalytic reactions and biological treatments, was developed recently. ICPB consists mainly of porous carriers, photocatalysts, biofilms, and an illuminated reactor. Under illumination, photocatalysts on the surface of the carriers convert refractory pollutants into biodegradable products through photocatalytic reactions, after which these products are completely degraded by the biofilms cultivated in the carriers. Additionally, the biofilms are protected by the carriers from the harmful light and free radicals generated by the photocatalyst. Compared with traditional technologies, ICPB remarkably improves the degradation efficiency and reduces the cost of bioremediation. In this review, we introduce the origin and mechanisms of ICPB, discuss the development of reactors, carriers, photocatalysts, and biofilms used in ICPB, and summarize the applications of ICPB to treat organic pollutants. Finally, gaps in this research as well as future perspectives are discussed.

The Expanding Computational Toolbox for Engineering Microbial Phenotypes at the Genome Scale

Microbial strains are being engineered for an increasingly diverse array of applications, from chemical production to human health. While traditional engineering disciplines are driven by predictive design tools, these tools have been difficult to build for biological design due to the complexity of biological systems and many unknowns of their quantitative behavior. However, due to many recent advances, the gap between design in biology and other engineering fields is closing. In this work, we discuss promising areas of development of computational tools for engineering microbial strains. We define five frontiers of active research: (1) Constraint-based modeling and metabolic network reconstruction, (2) Kinetics and thermodynamic modeling, (3) Protein structure analysis, (4) Genome sequence analysis, and (5) Regulatory network analysis. Experimental and machine learning drivers have enabled these methods to improve by leaps and bounds in both scope and accuracy. Modern strain design projects will require these tools to be comprehensively applied to the entire cell and efficiently integrated within a single workflow. We expect that these frontiers, enabled by the ongoing revolution of big data science, will drive forward more advanced and powerful strain engineering strategies.