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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

A cytosolic glyoxylate shunt complements the canonical photorespiratory pathway in Arabidopsis

Photorespiration functions in part to support photosynthetic performance, especially under stress such as high light, yet the underlying mechanisms are poorly understood. To identify modulators of photorespiration under high light, we have isolated genetic suppressors of the photorespiratory mutant hpr1 (hydroxypyruvate reductase 1) from Arabidopsis. A suppressor that partially rescues hpr1 is mapped to GLYR1, which encodes the cytosolic glyoxylate reductase 1 that converts glyoxylate to glycolate. Independent glyr1 mutants also partially rescue hpr1 and another photorespiratory mutant, catalase 2. Our genetic, transcriptomic and metabolic profiling analyses together reveal a connection between cytosolic glyoxylate and a non-canonical photorespiratory route mediated by HPR2, which we name the photorespiratory glyoxylate shunt. This shunt complements the canonical photorespiratory pathway and is especially critical when high photorespiratory fluxes are required and when the major photorespiratory pathway is deficient. Our findings support the metabolic flexibility of photorespiration and may help to improve crop performance under stress.

Light stress↗

Spatiotemporal metabolic responses to water deficit stress in distinct leaf cell-types of poplar

The impact of water-deficit (WD) stress on plant metabolism has been predominantly studied at the whole tissue level. However, plant tissues are made of several distinct cell types with unique and differentiated functions, which limits whole tissue ‘omics’-based studies to determine only an averaged molecular signature arising from multiple cell types. Advancements in spatial omics technologies provide an opportunity to understand the molecular mechanisms underlying plant responses to WD stress at distinct cell-type levels. Here, we studied the spatiotemporal metabolic responses of two poplar ( Populus tremula× P. alba ) leaf cell types -palisade and vascular cells- to WD stress using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI). We identified unique WD stress-mediated metabolic shifts in each leaf cell type when exposed to early and prolonged WD stresses and recovery from stress. During water-limited conditions, flavonoids and phenolic metabolites were exclusively accumulated in leaf palisade cells. However, vascular cells mainly accumulated sugars and fatty acids during stress and recovery conditions, respectively, highlighting the functional divergence of leaf cell types in response to WD stress. By comparing our MALDI-MSI metabolic data with whole leaf tissue gas chromatography-mass spectrometry (GC-MS)-based metabolic profile, we identified only a few metabolites including monosaccharides, hexose phosphates, and palmitic acid that showed a similar accumulation trend at both cell-type and whole leaf tissue levels. Overall, this work highlights the potential of the MSI approach to complement the whole tissue-based metabolomics techniques and provides a novel spatiotemporal understanding of plant metabolic responses to WD stress. This will help engineer specific metabolic pathways at a cellular level in strategic perennial trees like poplars to help withstand future aberrations in environmental conditions and to increase bioenergy sustainability.

59 BASIC BIOLOGICAL SCIENCES↗

Large-scale protein level comparison of Deltaproteobacteria reveals cohesive metabolic groups

Abstract Deltaproteobacteria, now proposed to be the phyla Desulfobacterota, Myxococcota, and SAR324, are ubiquitous in marine environments and play essential roles in global carbon, sulfur, and nutrient cycling. Despite their importance, our understanding of these bacteria is biased towards cultured organisms. Here we address this gap by compiling a genomic catalog of 1 792 genomes, including 402 newly reconstructed and characterized metagenome-assembled genomes (MAGs) from coastal and deep-sea sediments. Phylogenomic analyses reveal that many of these novel MAGs are uncultured representatives of Myxococcota and Desulfobacterota that are understudied. To better characterize Deltaproteobacteria diversity, metabolism, and ecology, we clustered ~1 500 genomes based on the presence/absence patterns of their protein families. Protein content analysis coupled with large-scale metabolic reconstructions separates eight genomic clusters of Deltaproteobacteria with unique metabolic profiles. While these eight clusters largely correspond to phylogeny, there are exceptions where more distantly related organisms appear to have similar ecological roles and closely related organisms have distinct protein content. Our analyses have identified previously unrecognized roles in the cycling of methylamines and denitrification among uncultured Deltaproteobacteria. This new view of Deltaproteobacteria diversity expands our understanding of these dominant bacteria and highlights metabolic abilities across diverse taxa.

Langwig, Marguerite V. (ORCID:0000000202472816)↗

Metabolomics of related C3 and C4 Flaveria species indicate differences in the operation of photorespiration under fluctuating light

C 3 photosynthesis can be complemented with a C 4 carbon concentrating mechanism (CCM) to minimize photorespiratory losses. C 4 photosynthesis is often more efficient than C 3 under steady-state conditions. However, the C 4 CCM depends on inter-cellular metabolite concentration gradients, which must increase following increases in light intensity and could decrease rates of C 4 photosynthesis under fluctuating light. Additionally, incomplete flux through photorespiration could prove beneficial to C 4 assimilation during light induction of the CCM. Here, we compare metabolic profiles in the closely related C 3 Flaveria robusta and C 4 Flaveria bidentis during a light transient from low to high light to determine if these non-steady state accumulation patterns provide insight to the induction of the metabolite gradients needed to drive C 4 intermediate transport and if there is incomplete cycling of photorespiratory intermediates. In these C 3 and C 4 species, metabolite steady-state pool sizes suggest that C 4 transport acids maintain concentration gradients across the bundle sheath and mesophyll cell types under these light fluctuations. However, there was incomplete flux through photorespiration in the C 4 F. bidentis, which could reduce photorespiratory CO 2 loss via glycine decarboxylation and help maintain higher rates of assimilation during following induction periods.

59 BASIC BIOLOGICAL SCIENCES↗

Maize Terpene Synthase 8 (ZmTPS8) Contributes to a Complex Blend of Fungal-Elicited Antibiotics

In maize (Zea mays), fungal-elicited immune responses include the accumulation of terpene synthase (TPS) and cytochrome P450 monooxygenases (CYP) enzymes resulting in complex antibiotic arrays of sesquiterpenoids and diterpenoids, including α/β-selinene derivatives, zealexins, kauralexins and dolabralexins. To uncover additional antibiotic families, we conducted metabolic profiling of elicited stem tissues in mapping populations, which included B73 × M162W recombinant inbred lines and the Goodman diversity panel. Five candidate sesquiterpenoids associated with a chromosome 1 locus spanning the location of ZmTPS27 and ZmTPS8. Heterologous enzyme co-expression studies of ZmTPS27 in Nicotiana benthamiana resulted in geraniol production while ZmTPS8 yielded α-copaene, δ-cadinene and sesquiterpene alcohols consistent with epi-cubebol, cubebol, copan-3-ol and copaborneol matching the association mapping efforts. ZmTPS8 is an established multiproduct α-copaene synthase; however, ZmTPS8-derived sesquiterpene alcohols are rarely encountered in maize tissues. A genome wide association study further linked an unknown sesquiterpene acid to ZmTPS8 and combined ZmTPS8-ZmCYP71Z19 heterologous enzyme co-expression studies yielded the same product. To consider defensive roles for ZmTPS8, in vitro bioassays with cubebol demonstrated significant antifungal activity against both Fusarium graminearum and Aspergillus parasiticus. As a genetically variable biochemical trait, ZmTPS8 contributes to the cocktail of terpenoid antibiotics present following complex interactions between wounding and fungal elicitation.

59 BASIC BIOLOGICAL SCIENCES↗

The AML microenvironment catalyzes a step-wise evolution to gilteritinib resistance

This study reports a stepwise evolution of gilteritinib resistance in acute myeloid leukemia (AML) relapse, and identifies therapeutic vulnerabilities that could be exploited. Our in vitro model demonstrates that extrinsic microenvironmental factors within the bone marrow nurture the growth of residual cells that underlie early gilteritinib resistance. These early resistant cells exhibit a dependency upon Aurora B (AURKB) and undergo dynamic metabolic adaptations that fostered their transition to late resistance. In line with clinical observations of gilteritinib resistance, late resistant cells displayed an expansion of NRAS mutant subclones and a unique metabolic profile that originated during early resistance. Pharmacological inhibition of AURKB resensitized early resistant cells to gilteritinib. Early resistant cells from AML patients were found to display exquisite sensitivitye to AURKB inhibition. Together, our findings support that eradication of early resistant AML cells may increase the efficacy and durability of gilteritinib.

AML, Proteomics↗

Engineered Endosymbionts that Modulate Primary Macrophage Function and Attenuate Tumor Growth by Shifting the Tumor Microenvironment

Modulating gene expression in macrophages can be used to improve tissue regeneration and redirect tumor microenvironments (TMEs) toward positive therapeutic outcomes. We have developed Bacillus subtilis as an engineered endosymbiont (EES) capable of residing inside the eukaryotic host cell cytoplasm and controlling the fate of macrophages. Secretion of mammalian transcription factors (TFs) from B. subtilis that expresses listeriolysin O (LLO; allowing the EES to escape destruction by the macrophage) modulated expression of surface markers, cytokines, and chemokines, indicating functional changes in a macrophage/monocyte cell line. The engineered B. subtilis LLO TF strains were evaluated in murine bone marrow-derived macrophages (BMDMs) by flow cytometry, chemokine/cytokine profiling, metabolic assays, and RNA-Seq delivery of TFs by the EES shifted BMDM gene expression, production of cytokine and chemokines, and metabolic patterns, indicating that the TF strains could guide primary macrophage function. Thereafter, the ability of the TF strains to alter the TME was characterized in vivo in an orthotopic murine model of triple-negative breast cancer to assess therapeutic effects. The TF strains altered the TME by shifting immune cell composition and attenuating tumor growth. Additionally, multiple doses of the TF strains were well-tolerated by the mice. The use of B. subtilis LLO TF strains as EES showed promise as a unique cancer immunotherapy by directing the immune function intracellularly. The uses of EES could be expanded to modulate other mammalian cells over a range of biomedical applications.

60 APPLIED LIFE SCIENCES↗

A Fast-Pass, Desorption Electrospray Ionization Mass Spectrometry Strategy for Untargeted Metabolic Phenotyping

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) provides direct analytical readouts of small molecules that can be used to characterize the metabolic phenotypes of genetically engineered bacteria. In an effort to accelerate the time frame associated with the screening of mutant libraries, we have developed a high-throughput DESI-MSI analytical workflow implementing a single raster line-scan strategy that facilitates the collection of location-resolved molecular information from engineered strains on a subminute time scale. Evaluation of this “Fast-Pass” DESI-MSI phenotyping workflow on analytical standards demonstrated the capability of acquiring full metabolic profiling information with a throughput of ~40 s per sample. This Fast-Pass strategy was implemented in the analysis of genetically edited Escherichia coli strains that have been engineered to produce various free-fatty acids (FFAs) for applications relevant to biofuels. Due to the untargeted nature of DESI-MSI, the investigation of these strains yielded molecular information for both global metabolites and targeted detection of accumulated bioproducts, allowing simultaneous readouts of strain-specific chemical profiles and comparative measurements of FFA production levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DRAM for distilling microbial metabolism to automate the curation of microbiome function

Abstract Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

59 BASIC BIOLOGICAL SCIENCES↗

A Role for the Plastidial GPT2 Translocator in the Modulation of Lignin Biosynthesis

ABSTRACT Engineering plants with reduced lignin content can result in pleiotropic growth defects. In stems of Arabidopsis plants with reduced expression of hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase (HCT), the plastidial glucose 6‐phosphate: phosphate co‐transporter GPT2 is highly overexpressed, and this coincides with reduced lignin levels and extensive transcriptional and metabolic reprogramming. To explore the potential relationship between GPT2 expression and lignin accumulation, GPT2 transcript levels were evaluated in a suite ofArabidopsis thalianaandMedicago truncatulalignin‐defective lines. We also examined lignin levels and composition, and transcriptomic and metabolic profiles in GPT2 loss‐of‐function, GPT2 overexpression, and wild‐type Arabidopsis plants. Loss of GPT2 had no effect on lignin, but its overexpression caused a decrease in stem lignin levels due to reduced accumulation of both guaiacyl and syringyl lignins and their associated monolignol pools.HCTtranscript levels were diminished in 35S‐GPT2 lines, indicating a potential transcriptional regulatory connection between lignin biosynthesis and GPT2. Based on our transcriptomic and metabolomic analyses, we suggest that GPT2 operates to balance the flux between the biosynthesis of lignin and light‐protective phenylpropanoid derivatives.

Plant Sciences↗

Metabolic activity and community structure of prokaryotes associated with particles in the twilight zone of the South China Sea

The twilight zone is an important depth of the ocean where particulate organic matter (POM) remineralization takes place, and prokaryotes contribute to more than 70% of the estimated remineralization. However, little is known about the microbial community and metabolic activity associated with different particles in the twilight zone. The composition and distribution of particle-attached prokaryotes in the twilight zone of the South China Sea (SCS) were investigated using high-throughput sequencing and quantitative PCR, together with the Biolog Ecoplate™ microplates culture to analyze the microbial metabolic activity. We found that α- and γ-Proteobacteria dominating at the lower and upper boundary of the twilight zone, respectively; Methanosarcinales and Halobacteriales of the Euyarchaeota occupied in the larger particles at the upper boundary. Similar microbial community existed between euphotic layer and the upper boundary. Higher amount of shared Operational Taxonomic Units (OTUs) in the larger particles along the water depths, might be due to the fast sinking and major contribution of carbon flux of the larger particles from the euphotic layer. In addition to polymers as the major carbon source, carbohydrates and amino acids were preferentially used by microbial community at the upper and lower boundary, respectively. This could potentially be attributed to the metabolic capabilities of attached microbial groups in different particles, and reflected the initial preference of the carbon source by the natural microbes in the twilight zone as well. The microbial structure and carbon metabolic profiles could be complemented with metatranscriptomic analysis in future studies to augment the understanding of the complex carbon cycling pathways in the twilight zone.

Liu, Hao↗

Downregulation of barley ferulate 5-hydroxylase dramatically alters straw lignin structure without impact on mechanical properties

Barley is a major cereal crop for temperate climates, and a diploid genetic model for polyploid wheat. Cereal straw biomass is an attractive source of feedstock for green technologies but lignin, a key determinant of feedstock recalcitrance, complicates bio-conversion processes. However, manipulating lignin content to improve the conversion process could negatively affect agronomic traits. An alternative approach is to manipulate lignin composition which influences the physical and chemical properties of straw. This study validates the function of a barley ferulate 5-hydroxylase gene and demonstrates that its downregulation using the RNA-interference approach substantially impacts lignin composition. We identified five barley genes having putative ferulate 5-hydroxylase activity. Downregulation of HvF5H1 substantially reduced the lignin syringyl/guaiacyl (S/G) ratio in straw while the lignin content, straw mechanical properties, plant growth habit, and grain characteristics all remained unaffected. Metabolic profiling revealed significant changes in the abundance of 173 features in the HvF5H1-RNAi lines. The drastic changes in the lignin polymer of transgenic lines highlight the plasticity of barley lignification processes and the associated potential for manipulating and improving lignocellulosic biomass as a feedstock for green technologies. On the other hand, our results highlight some differences between the lignin biosynthetic pathway in barley, a temperate climate grass, and the warm climate grass, rice, and underscore potential diversity in the lignin biosynthetic pathways in grasses.

59 BASIC BIOLOGICAL SCIENCES↗

Ultra-high Information-content Chemical Imaging with Broadband Coherent Anti-Stokes Raman and Two-photon Fluorescence Lifetime Microscopy

Raman fingerprint spectroscopy and fluorescence lifetime imaging are emerging tools for studying metabolic profiles of biological specimens. While Raman fingerprint spectroscopy detects intrinsic molecular vibrations that reflect the molecular composition and chemical environment of a sample, fluorescence lifetime imaging measures changes in the excited-state lifetime of fluorophores that are sensitive to their microenvironments. Here, we present a multimodal imaging platform combining broadband coherent anti-Stokes Raman scattering (BCARS) and two-photon fluorescence lifetime imaging (2p-FLIM) microscopy that can acquire biologically relevant Raman fingerprint spectra and fluorescence lifetime signals in vivo and simultaneously. The tremendous chemical information obtained from spatially co-registered BCARS and 2p-FLIM images allows us to characterize the subtle differences between sub-cellular compartments and verify the potential false-positive results generated by fluorescence imaging alone. This is demonstrated by directly comparing the BCARS, 2p-FLIM, and two-photon excitation fluorescence(TPEF) signals simultaneously obtained from the same dye-stained organelle in the live, intact C. elegans expressing a green fluorescent protein (GFP) marker. In this work, we introduce the BCARS/2p-FLIM/TPEF setup scheme, the image acquisition steps, data processing, and representative results showing that the cross-modality imaging method enables rigorous characterization and in vivo detection at sub-cellular resolution. Furthermore, this protocol provides a framework for simultaneous chemical and fluorescence lifetime imaging to improve the accuracy of biological interpretation in complex living systems.

Xu, Haoyu [Georgia Institute of Technology, Atlant↗

HAMscope: a snapshot Hyperspectral Autofluorescence Miniscope for real-time molecular imaging

We introduce HAMscope, a compact, snapshot hyperspectral autofluorescence miniscope that enables real-time, label-free molecular imaging in a wide range of biological systems. By integrating a thin polymer diffuser into a widefield miniscope, HAMscope spectrally encodes each frame and employs a probabilistic deep learning framework to reconstruct 30-channel hyperspectral stacks (452-703 nm) or directly infer molecular composition maps from single images. A scalable multi-pass U-Net architecture with transformer-based attention and per pixel uncertainty estimation enables high spatio-spectral fidelity (mean absolute error ∼0.0048) at video rates. While initially demonstrated in plant systems, including lignin, chlorophyll, and suberin imaging in intact poplar and cork tissues, the platform is readily adaptable to other applications such as neural activity mapping, metabolic profiling, and histopathology. We show that the system generalizes to out-of-distribution tissue types and supports direct molecular mapping without the need for spectral unmixing. HAMscope establishes a general framework for compact, uncertainty-aware spectral imaging that combines minimal optics with advanced deep learning, offering broad utility for real-time biochemical imaging across neuroscience, environmental monitoring, and biomedicine.

59 BASIC BIOLOGICAL SCIENCES↗

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes

Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.

59 BASIC BIOLOGICAL SCIENCES↗

CAZyme domain architectures suggest fine-scale functional differentiation among anaerobic fungi and bacteria during lignocellulose conversion to volatile fatty acids

Anaerobic fermentation with microbial communities (microbiomes) is an emerging platform for conversion of lignocellulosic biomass to biofuels and bioproducts. The process relies on diverse anaerobic microbes that interact to deconstruct and convert lignocellulosic biomass into a range of products, such as volatile fatty acids (VFAs), which can be achieved by arresting methanogenesis during fermentation. However, defining the distinct functional roles played by various fungi and bacteria during anaerobic biodegradation remains poorly understood. Here, we performed parallel enrichment experiments from cow faeces, goat faeces, and anaerobic digester sludge, selecting for fungal or bacterial dominated communities that convert sorghum biomass into VFAs. Subsequently we reconstructed metabolic networks across these enrichments based on recovered bacterial metagenome-assembled genomes (MAGs) and fungal isolate genomes and profiled their metabolic activity using metatranscriptomics to identify potential functional niches. Our findings implicate diverse bacteria affiliated with the Bacteroidales and Lachnospiraceae in the direct conversion of lignocellulosic biomass to propionate and butyrate, respectively, whereas Neocallimastix-dominated fungal enrichments converted lignocellulose to lactate, acetate and formate. Analysis of carbohydrate-active enzymes (CAZymes) revealed fine-scale differences between microbes that expressed unique multi-functional enzymes linking two or more CAZymes together with distinct carbohydrate binding motifs, implicating lignocellulose structure as a key driver of selection and niche differentiation. Most of these multi-functional enzymes localized complementary degradation functions together, likely conferring synergistic degradation effects within and between microbiome members. We anticipate that these findings will help inform efforts to develop synthetic microbiomes with tailored functionality for low-cost conversion of lignocellulosic biomass to fuels and bio-based chemicals.

Lawson, Christopher E [University of Toronto;]↗