Search

Aminotransferases (ATs) catalyze pyridoxal 5'-phosphate-dependent transamination reactions between amino donor and keto acceptor substrates and play central roles in nitrogen metabolism of all organisms. ATs are involved in the biosynthesis and degradation of both proteinogenic and nonproteinogenic amino acids and also carry out a wide variety of functions in photorespiration, detoxification, and secondary metabolism. Despite the importance of ATs, their functionality is poorly understood as only a small fraction of putative ATs, predicted from DNA sequences, are associated with experimental data. Even for characterized ATs, the full spectrum of substrate specificity, among many potential substrates, has not been explored in most cases. This is largely due to the lack of suitable high-throughput assays that can screen for AT activity and specificity at scale. Here we present a new high-throughput platform for screening AT activity using bioconjugate chemistry and mass spectrometry imaging-based analysis. Detection of AT reaction products is achieved by forming an oxime linkage between the ketone groups of transaminated amino donors and a probe molecule that facilitates mass spectrometry-based analysis using nanostructure-initiator mass spectrometry or MALDI-mass spectrometry. As a proof-of-principle, we applied the newly established method and found that a previously uncharacterized Arabidopsis thaliana tryptophan AT-related protein 1 is a highly promiscuous enzyme that can utilize 13 amino acid donors and three keto acid acceptors. These results demonstrate that this oxime-mass spectrometry imaging AT assay enables high-throughput discovery and comprehensive characterization of AT enzymes, leading to an accurate understanding of the nitrogen metabolic network.

Journal of the American Chemical Society : JACS 145(16), 8822-8832 (2023). doi:10.1021/jacs.2c11027, Published by American Chemical Society Publications, Washington, DC

Microbial soil communities form commensal relationships with plants to promote the growth of both parties. Optimization of plant-microbe interactions to advance sustainable agriculture is an important field in agricultural research. However, investigation in this field is hindered by a lack of model microbial community systems and efficient approaches for building these communities. Two key challenges in developing standardized model communities are maintaining community diversity over time and storing/resuscitating these communities after cryopreservation, especially considering the different growth rates of organisms. Here, a model community of 17 soil microorganisms commonly found in the rhizosphere of diverse plant species, isolated from soil surrounding a single switchgrass plant, has been developed and optimized for use with fabricated ecosystem devices (EcoFABs). EcoFABs allow reproducible research in model plant systems, with precise control of environmental conditions and easy measurement of plant-microbe metrics. The model soil community grows reproducibly in vitro between replicates and experiments, with high community α-diversity achieved through growth in low-nutrient media and adjustment of starting composition ratios for the growth of individual organisms. The community additionally grows in EcoFAB devices and regrows with a similar composition to unfrozen communities following cryopreservation with glycerol, allowing for dissemination of the model community. Our results demonstrate the generation of a stable microbial community that can be used with EcoFAB devices and shared between research groups for maximum reproducibility.ImportanceMicrobes associate with plants in distinct soil communities, to the benefit of both the soil microbes and the plant. Interactions between plants and these microbes can improve plant growth and health and are therefore a field of study in sustainable agricultural research. In this study, a model community of 17 soil bacteria has been developed to further reproducible study of plant-soil microbe interactions. Preservation of the microbial community has been optimized for dissemination to other research settings. Overall, this work will advance soil microbe research through optimization of a robust, reproducible model community.

High-throughput screening technologies are widely used for elucidating biological activities. These typically require trade-offs in assay specificity and sensitivity to achieve higher throughput. Microfluidic approaches enable rapid manipulation of small volumes and have found a wide range of applications in biotechnology providing improved control of reaction conditions, faster assays, and reduced reagent consumption. The integration of mass spectrometry with microfluidics has the potential to create high-throughput, sensitivity, and specificity assays. This review introduces the widely-used mass spectrometry ionization techniques that have been successfully integrated with microfluidics approaches such as continuous-flow system, microchip electrophoresis, droplet microfluidics, digital microfluidics, centrifugal microfluidics, and paper microfluidics. In addition, we discuss recent applications of microfluidics integrated with mass spectrometry in single-cell analysis, compound screening, and the study of microorganisms. Lastly, we provide future outlooks towards online coupling, improving the sensitivity and integration of multi-omics into a single platform., The integration of mass spectrometry with microfluidics has the potential to create high-throughput, sensitivity, and specificity assays.

Microalgae efficiently convert sunlight into lipids and carbohydrates, offering bio-based alternatives for energy and chemical production. Improving algal productivity and robustness against abiotic stress requires a systems level characterization enabled by functional genomics. Here, we characterize a halotolerant microalga Scenedesmus sp. NREL 46B-D3 demonstrating peak growth near 25 °C that reaches 30 g/m2/day and the highest biomass accumulation capacity post cell division reported to date for a halotolerant strain. Functional genomics analysis revealed that genes involved in lipid production, ion channels and antiporters are expanded and expressed. Exposure to temperature stress shifts fatty acid metabolism and increases amino acids synthesis. Co-expression analysis shows that many fatty acid biosynthesis genes are overexpressed with specific transcription factors under cold stress. These and other genes involved in the metabolic and regulatory response to temperature stress can be further explored for strain improvement., Sara Calhoun, Tisza Ann Szeremy Bell, Lukas Dahlin and colleagues characterize the growth and biomass accumulation of a halotolerant microalga Scenedesmus sp. NREL 46B-D3. They sequenced the genome and profiled the transcriptomic and metabolomic response of this strain under high and low-temperature stress, and shed light on the genes involved in the metabolic and regulatory response to temperature stress.

We described a mass spectrometry-based assay to rapidly quantify the production of primary alcohols directly from cell cultures. This novel assay used the combination of TEMPO-based oxidation chemistry and oxime ligation, followed by product analysis based on Nanostructure-Initiator Mass Spectrometry. This assay enables quantitative monitor both C5 to C18 alcohols as well as glucose and gluconate in the growth medium to support strain characterization and optimization. We find that this assay yields similar results to gas chromatography for isoprenol production but required much less acquisition time per sample. We applied this assay to gain new insights into P. Putida's utilization of alcohols and find that this strain largely could not grow on heptanol and octanol.

Dissolved exometabolites mediate algal interactions in aquatic ecosystems, but microalgal exometabolomes remain understudied. We conducted an untargeted metabolomic analysis of non-polar exometabolites exuded from four phylogenetically and ecologically diverse eukaryotic microalgal strains grown in the laboratory: freshwater Chlamydomonas reinhardtii, brackish Desmodesmus sp., marine Phaeodactylum tricornutum, and marine Microchloropsis salina, to identify released metabolites based on relative enrichment in the exometabolomes compared to cell pellet metabolomes. Exudates from the different taxa were distinct, but we did not observe clear phylogenetic patterns. We used feature based molecular networking to explore the identities of these metabolites, revealing several distinct di- and tripeptides secreted by each of the algae, lumichrome, a compound that is known to be involved in plant growth and bacterial quorum sensing, and novel prostaglandin-like compounds. We further investigated the impacts of exogenous additions of eight compounds selected based on exometabolome enrichment on algal growth. Of the these, five (lumichrome, 5’-S-methyl-5’-thioadenosine, 17-phenyl trinor prostaglandin A2, dodecanedioic acid, and aleuritic acid) impacted growth in at least one of the algal cultures. Two of these (dodecanedioic acid and aleuritic acid) produced contrasting results, increasing growth in some algae and decreasing growth in others. Together, our results reveal new groups of microalgal exometabolites, some of which could alter algal growth when provided exogenously, suggesting potential roles in allelopathy and algal interactions.IMPORTANCEMicroalgae are responsible for nearly half of primary production on earth and play an important role in global biogeochemical cycling as well as in a range of industrial applications. Algal exometabolites are important mediators of algal-algal and algal-bacterial interactions that ultimately affect algal growth and physiology. In this study we characterize exometabolomes across marine and freshwater algae to gain insights into the diverse metabolites they release into their environments (“exudates”). We observe that while phylogeny can play a role in exometabolome content, environmental conditions or habitat origin (freshwater vs marine) are also important. We also find that several of these compounds can influence algal growth (as measured by chlorophyll production) when provided exogenously, highlighting the importance of characterization of these novel compounds and their role in microalgal ecophysiology.

Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We show with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.

Light and nutrients are critical regulators of photosynthesis and metabolism in plants and algae. Many algae have the metabolic flexibility to grow photoautotrophically, heterotrophically, or mixotrophically. Here, we describe reversible Glc-dependent repression/activation of oxygenic photosynthesis in the unicellular green alga Chromochloris zofingiensis. We observed rapid and reversible changes in photosynthesis, in the photosynthetic apparatus, in thylakoid ultrastructure, and in energy stores including lipids and starch. Following Glc addition in the light, C. zofingiensis shuts off photosynthesis within days and accumulates large amounts of commercially relevant bioproducts, including triacylglycerols and the high-value nutraceutical ketocarotenoid astaxanthin, while increasing culture biomass. RNA sequencing reveals reversible changes in the transcriptome that form the basis of this metabolic regulation. Functional enrichment analyses show that Glc represses photosynthetic pathways while ketocarotenoid biosynthesis and heterotrophic carbon metabolism are upregulated. Because sugars play fundamental regulatory roles in gene expression, physiology, metabolism, and growth in both plants and animals, we have developed a simple algal model system to investigate conserved eukaryotic sugar responses as well as mechanisms of thylakoid breakdown and biogenesis in chloroplasts. Understanding regulation of photosynthesis and metabolism in algae could enable bioengineering to reroute metabolism toward beneficial bioproducts for energy, food, pharmaceuticals, and human health.

Significance Anaerobic gut fungi are important members of the gut microbiome of herbivores, yet they exist in small numbers relative to bacteria. Here, we show that these early-branching fungi produce a wealth of secondary metabolites (natural products) that may act to regulate the gut microbiome. We use an integrated 'omics'-based approach to classify the biosynthetic genes predicted from fungal genomes, determine transcriptionally active genes, and verify the presence of their enzymatic products. Our analysis reveals that anaerobic gut fungi are an untapped reservoir of bioactive compounds that could be harnessed for biotechnology., Anaerobic fungi (class Neocallimastigomycetes) thrive as low-abundance members of the herbivore digestive tract. The genomes of anaerobic gut fungi are poorly characterized and have not been extensively mined for the biosynthetic enzymes of natural products such as antibiotics. Here, we investigate the potential of anaerobic gut fungi to synthesize natural products that could regulate membership within the gut microbiome. Complementary 'omics' approaches were combined to catalog the natural products of anaerobic gut fungi from four different representative species: Anaeromyces robustus (A. robustus), Caecomyces churrovis (C. churrovis), Neocallimastix californiae (N. californiae), and Piromyces finnis (P. finnis). In total, 146 genes were identified that encode biosynthetic enzymes for diverse types of natural products, including nonribosomal peptide synthetases and polyketide synthases. In addition, N. californiae and C. churrovis genomes encoded seven putative bacteriocins, a class of antimicrobial peptides typically produced by bacteria. During standard laboratory growth on plant biomass or soluble substrates, 26% of total core biosynthetic genes in all four strains were transcribed. Across all four fungal strains, 30% of total biosynthetic gene products were detected via proteomics when grown on cellobiose. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) characterization of fungal supernatants detected 72 likely natural products from A. robustus alone. A compound produced by all four strains of anaerobic fungi was putatively identified as the polyketide-related styrylpyrone baumin. Molecular networking quantified similarities between tandem mass spectrometry (MS/MS) spectra among these fungi, enabling three groups of natural products to be identified that are unique to anaerobic fungi. Overall, these results support the finding that anaerobic gut fungi synthesize natural products, which could be harnessed as a source of antimicrobials, therapeutics, and other bioactive compounds.

With the advent of genome sequencing and mining technologies, secondary metabolite biosynthetic gene clusters (BGCs) within bacterial genomes are becoming easier to predict. For subsequent BGC characterization, clustered regularly interspaced short palindromic repeats (CRISPR) has contributed to knocking out target genes and/or modulating their expression; however, CRISPR is limited to strains for which robust genetic tools are available. Here we present a strategy that combines CRISPR with chassis-independent recombinase-assisted genome engineering (CRAGE), which enables CRISPR systems in diverse bacteria. To demonstrate CRAGE-CRISPR, we select 10 polyketide/non-ribosomal peptide BGCs in Photorhabdus luminescens as models and create their deletion and activation mutants. Subsequent loss- and gain-of-function studies confirm 22 secondary metabolites associated with the BGCs, including a metabolite from a previously uncharacterized BGC. These results demonstrate that the CRAGE-CRISPR system is a simple yet powerful approach to rapidly perturb expression of defined BGCs and to profile genotype-phenotype relationships in bacteria.

Lignocellulosic biomass is composed of three major biopolymers: cellulose, hemicellulose and lignin. Analytical tools capable of quickly detecting both glycan and lignin deconstruction are needed to support the development and characterization of efficient enzymes/enzyme cocktails. Previously we have described nanostructure-initiator mass spectrometry-based assays for the analysis of glycosyl hydrolase and most recently an assay for lignin modifying enzymes. Here we integrate these two assays into a single multiplexed assay against both classes of enzymes and use it to characterize crude commercial enzyme mixtures. Application of our multiplexed platform based on nanostructure-initiator mass spectrometry enabled us to characterize crude mixtures of laccase enzymes from fungi Agaricus bisporus (Ab) and Myceliopthora thermophila (Mt) revealing activity on both carbohydrate and aromatic substrates. Using time-series analysis we determined that crude laccase from Ab has the higher GH activity and that laccase from Mt has the higher activity against our lignin model compound. Inhibitor studies showed a significant reduction in Mt GH activity under low oxygen conditions and increased activities in the presence of vanillin (common GH inhibitor). Ultimately, this assay can help to discover mixtures of enzymes that could be incorporated into biomass pretreatments to deconstruct diverse components of lignocellulosic biomass.

Thermoflexus hugenholtzii JAD2T, the only cultured representative of the Chloroflexota order Thermoflexales, is abundant in Great Boiling Spring (GBS), NV, United States, and close relatives inhabit geothermal systems globally. However, no defined medium exists for T. hugenholtzii JAD2T and no single carbon source is known to support its growth, leaving key knowledge gaps in its metabolism and nutritional needs. Here, we report comparative genomic analysis of the draft genome of T. hugenholtzii JAD2T and eight closely related metagenome-assembled genomes (MAGs) from geothermal sites in China, Japan, and the United States, representing “Candidatus Thermoflexus japonica,” “Candidatus Thermoflexus tengchongensis,” and “Candidatus Thermoflexus sinensis.” Genomics was integrated with targeted exometabolomics and 13C metabolic probing of T. hugenholtzii. The Thermoflexus genomes each code for complete central carbon metabolic pathways and an unusually high abundance and diversity of peptidases, particularly Metallo- and Serine peptidase families, along with ABC transporters for peptides and some amino acids. The T. hugenholtzii JAD2T exometabolome provided evidence of extracellular proteolytic activity based on the accumulation of free amino acids. However, several neutral and polar amino acids appear not to be utilized, based on their accumulation in the medium and the lack of annotated transporters. Adenine and adenosine were scavenged, and thymine and nicotinic acid were released, suggesting interdependency with other organisms in situ. Metabolic probing of T. hugenholtzii JAD2T using 13C-labeled compounds provided evidence of oxidation of glucose, pyruvate, cysteine, and citrate, and functioning glycolytic, tricarboxylic acid (TCA), and oxidative pentose-phosphate pathways (PPPs). However, differential use of position-specific 13C-labeled compounds showed that glycolysis and the TCA cycle were uncoupled. Thus, despite the high abundance of Thermoflexus in sediments of some geothermal systems, they appear to be highly focused on chemoorganotrophy, particularly protein degradation, and may interact extensively with other microorganisms in situ.

Broad-specificity glycoside hydrolases (GHs) contribute to plant biomass hydrolysis by degrading a diverse range of polysaccharides, making them useful catalysts for renewable energy and biocommodity production. Discovery of new GHs with improved kinetic parameters or more tolerant substrate-binding sites could increase the efficiency of renewable bioenergy production even further. GH5 has over 50 subfamilies exhibiting selectivities for reaction with β-(1,4)-linked oligo- and polysaccharides. Among these, subfamily 4 (GH5_4) contains numerous broad-selectivity endoglucanases that hydrolyze cellulose, xyloglucan, and mixed-linkage glucans. We previously surveyed the whole subfamily and found over 100 new broad-specificity endoglucanases, although the structural origins of broad specificity remained unclear. A mechanistic understanding of GH5_4 substrate specificity would help inform the best protein design strategies and the most appropriate industrial application of broad-specificity endoglucanases. Here we report structures of 10 new GH5_4 enzymes from cellulolytic microbes and characterize their substrate selectivity using normalized reducing sugar assays and MS. We found that GH5_4 enzymes have the highest catalytic efficiency for hydrolysis of xyloglucan, glucomannan, and soluble β-glucans, with opportunistic secondary reactions on cellulose, mannan, and xylan. The positions of key aromatic residues determine the overall reaction rate and breadth of substrate tolerance, and they contribute to differences in oligosaccharide cleavage patterns. Our new composite model identifies several critical structural features that confer broad specificity and may be readily engineered into existing industrial enzymes. We demonstrate that GH5_4 endoglucanases can have broad specificity without sacrificing high activity, making them a valuable addition to the biomass deconstruction toolset.

Author(s): Morton, James T; McDonald, Daniel; Aksenov, Alexander A; Nothias, Louis Felix; Foulds, James R; Quinn, Robert A; Badri, Michelle H; Swenson, Tami L; Van Goethem, Marc W; Northen, Trent R; Vazquez-Baeza, Yoshiki; Wang, Mingxun; Bokulich, Nicholas A; Watters, Aaron; Song, Se Jin; Bonneau, Richard; Dorrestein, Pieter C; Knight, Rob

Cyanobacteria are important primary producers of organic matter in diverse environments on a global scale. While mechanisms of CO2 fixation are well understood, the distribution of the flow of fixed organic carbon within individual cells and complex microbial communities is less well characterized. To obtain a general overview of metabolism, we describe the use of deuterium oxide (D2O) to measure deuterium incorporation into the intracellular metabolites of two physiologically diverse cyanobacteria: a terrestrial filamentous strain (Microcoleus vaginatus PCC 9802) and a euryhaline unicellular strain (Synechococcus sp. PCC 7002). D2O was added to the growth medium during different phases of the diel cycle. Incorporation of deuterium into metabolites at nonlabile positions, an indicator of metabolite turnover, was assessed using liquid chromatography mass spectrometry. Expectedly, large differences in turnover among metabolites were observed. Some metabolites, such as fatty acids, did not show significant t...

Biological assays often require expensive reagents and tedious manipulations. These shortcomings can be overcome using digitally operated microfluidic devices that require reduced sample volumes to automate assays. One particular challenge is integrating bioassays with mass spectrometry based analysis. Towards this goal we have developed μNIMS, a highly sensitive and high throughput technique that integrates droplet microfluidics with nanostructure-initiator mass spectrometry (NIMS). Enzyme reactions are carried out in droplets that can be arrayed on discrete NIMS elements at defined time intervals for subsequent mass spectrometry analysis, enabling time resolved enzyme activity assay. We apply the μNIMS platform for kinetic characterization of a glycoside hydrolase enzyme (CelE-CMB3A), a chimeric enzyme capable of deconstructing plant hemicellulose into monosaccharides for subsequent conversion to biofuel. This study reveals NIMS nanostructures can be fabricated into arrays for microfluidic droplet deposition, NIMS is compatible with droplet and digital microfluidics, and can be used on-chip to assay glycoside hydrolase enzyme in vitro.

Assaying for enzymatic activity is a persistent bottleneck in biocatalyst and drug development. Existing high-throughput assays for enzyme activity tend to be applicable only to a narrow range of biochemical transformations, whereas universal enzyme characterization methods usually require chromatography to determine substrate turnover, greatly diminishing throughput. We present an enzyme activity assay which allows for the high-throughput mass-spectrometric detection of enzyme activity in complex matrices without the need for a chromatographic step. We demonstrate that this technology, which we call “Probing Enzymes with ‘Click’–Assisted NIMS” (PECAN), can detect the activity of medically and biocatalytically significant cytochrome P450s in cell lysate, microsomes, and bacterial cells. Using our approach, we successfully screened a cytochrome P450(BM3) mutant library for the ability to catalyze the oxidation of the sesquiterpene valencene.

The ability to link soil microbial diversity to soil processes requires technologies that differentiate active microbes from extracellular DNA and dormant cells. Here, we use BONCAT (bioorthogonal non-canonical amino acid tagging) to measure translationally active cells in soils. We compare the active population of two soil depths from Oak Ridge (Tennessee, USA) and find that a maximum of 25–70% of the extractable cells are active. Analysis of 16S rRNA sequences from BONCAT-positive cells recovered by fluorescence-activated cell sorting (FACS) reveals that the phylogenetic composition of the active fraction is distinct from the total population of extractable cells. Some members of the community are found to be active at both depths independently of their abundance rank, suggesting that the incubation conditions favor the activity of similar organisms. We conclude that BONCAT-FACS is effective for interrogating the active fraction of soil microbiomes in situ and provides a new approach for uncovering the links between soil processes and specific microbial groups., Standard DNA-based analyses of microbial communities cannot distinguish between active microbes and dead or dormant cells. Here, Couradeau et al. use BONCAT (bioorthogonal non-canonical amino acid tagging), flow cytometry, and 16S rRNA gene amplicon sequencing to identify active microbial cells in soils.

Microbiomes play critical roles in ecosystems and human health, yet in most cases scientists lack standardized and reproducible model microbial communities. The development of fabricated microbial ecosystems, which we term EcoFABs, will provide such model systems for microbiome studies.

© 2015. Mass spectrometry has become a choice method for broad-spectrum metabolite analysis in both fundamental and applied research. This can range from comprehensive analysis achieved through time-consuming chromatography to the rapid analysis of a few target metabolites without chromatography. In this review article, we highlight current high-throughput MS-based platforms and their potential application in metabolomics. Although current MS platforms can reach throughputs up to 0.5. seconds per sample, the metabolite coverage of these platforms are low compared to low-throughput, separation-based MS methods. High-throughput comes at a cost, as it's a trade-off between sample throughput and metabolite coverage. As we will discuss, promising emerging technologies, including microfluidics and miniaturization of separation techniques, have the potential to achieve both rapid and more comprehensive metabolite analysis.

Rapid genetic and phenotypic adaptation of the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough to salt stress was observed during experimental evolution. In order to identify key metabolites important for salt tolerance, a clone, ES10-5, which was isolated from population ES10 and allowed to experimentally evolve under salt stress for 5,000 generations, was analyzed and compared to clone ES9-11, which was isolated from population ES9 and had evolved under the same conditions for 1,200 generations. These two clones were chosen because they represented the best-adapted clones among six independently evolved populations. ES10-5 acquired new mutations in genes potentially involved in salt tolerance, in addition to the preexisting mutations and different mutations in the same genes as in ES9-11. Most basal abundance changes of metabolites and phospholipid fatty acids (PLFAs) were lower in ES10-5 than ES9-11, but an increase of glutamate and branched PLFA i17:1ω9c under high-salinity conditions was persistent. ES9-11 had decreased cell motility compared to the ancestor; in contrast, ES10-5 showed higher cell motility under both nonstress and high-salinity conditions. Both genotypes displayed better growth energy efficiencies than the ancestor under nonstress or high-salinity conditions. Consistently, ES10-5 did not display most of the basal transcriptional changes observed in ES9-11, but it showed increased expression of genes involved in glutamate biosynthesis, cation efflux, and energy metabolism under high salinity. These results demonstrated the role of glutamate as a key osmolyte and i17:1ω9c as the major PLFA for salt tolerance in D. vulgaris. The mechanistic changes in evolved genotypes suggested that growth energy efficiency might be a key factor for selection., IMPORTANCE High salinity (e.g., elevated NaCl) is a stressor that affects many organisms. Salt tolerance, a complex trait involving multiple cellular pathways, is attractive for experimental evolutionary studies. Desulfovibrio vulgaris Hildenborough is a model sulfate-reducing bacterium (SRB) that is important in biogeochemical cycling of sulfur, carbon, and nitrogen, potentially for bio-corrosion, and for bioremediation of toxic heavy metals and radionuclides. The coexistence of SRB and high salinity in natural habitats and heavy metal-contaminated field sites laid the foundation for the study of salt adaptation of D. vulgaris Hildenborough with experimental evolution. Here, we analyzed a clone that evolved under salt stress for 5,000 generations and compared it to a clone evolved under the same condition for 1,200 generations. The results indicated the key roles of glutamate for osmoprotection and of i17:1ω9c for increasing membrane fluidity during salt adaptation. The findings provide valuable insights about the salt adaptation mechanism changes during long-term experimental evolution.

Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist, yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. By using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.

Metabolomics is a widely used technology for obtaining direct measures of metabolic activities from diverse biological systems. However, ambiguous metabolite identifications are a common challenge and biochemical interpretation is often limited by incomplete and inaccurate genome-based predictions of enzyme activities (i.e. gene annotations). Metabolite, Annotation, and Gene Integration (MAGI) generates a metabolite-gene association score using a biochemical reaction network. This is calculated by a method that emphasizes consensus between metabolites and genes via biochemical reactions. To demonstrate the potential of this method, we applied MAGI to integrate sequence data and metabolomics data collected from Streptomyces coelicolor A3(2), an extensively characterized bacterium that produces diverse secondary metabolites. Our findings suggest that coupling metabolomics and genomics data by scoring consensus between the two increases the quality of both metabolite identifications and gene annotations in this organism. MAGI also made biochemical predictions for poorly annotated genes that were consistent with the extensive literature on this important organism. This limited analysis suggests that using metabolomics data has the potential to improve annotations in sequenced organisms and also provides testable hypotheses for specific biochemical functions. MAGI is freely available for academic use both as an online tool at https://magi.nersc.gov and with source code available at https://github.com/biorack/magi.

© 2017 by the author. Microbial consortia have the potential to perform complex, industrially important tasks. The design of microbial consortia requires knowledge of the substrate preferences and metabolic outputs of each member, to allow understanding of potential interactions such as competition and beneficial metabolic exchange. Here, we used exometabolite profiling to follow the resource processing by a microbial co-culture of two biotechnologically relevant microbes, the bacterial cellulose degrader Cellulomonas fimi, and the oleaginous yeast Yarrowia lipolytica. We characterized the substrate preferences of the two strains on compounds typically found in lignocellulose hydrolysates. This allowed prediction that specific sugars resulting from hemicellulose polysaccharide degradation by C. fimi may serve as a cross-feeding metabolites to Y. lipolytica in coculture. We also showed that products of ionic liquid-treated switchgrass lignocellulose degradation by C. fimi were channeled to Y. lipolytica in a co-culture. Additionally, we observed metabolites, such as shikimic acid accumulating in the co-culture supernatants, suggesting the potential for producing interesting co-products. Insights gained from characterizing the exometabolite profiles of individual and co-cultures of the two strains can help to refine this interaction, and guide strategies for making this an industrially viable co-culture to produce valuable products from lignocellulose material.

In Neurospora crassa, the transcription factor COL-26 functions as a regulator of glucose signaling and metabolism. Its loss leads to resistance to carbon catabolite repression. Here, we report that COL-26 is necessary for the expression of amylolytic genes in N. crassa and is required for the utilization of maltose and starch. Additionally, the Δcol-26 mutant shows growth defects on preferred carbon sources, such as glucose, an effect that was alleviated if glutamine replaced ammonium as the primary nitrogen source. This rescue did not occur when maltose was used as a sole carbon source. Transcriptome and metabolic analyses of the Δcol-26 mutant relative to its wild type parental strain revealed that amino acid and nitrogen metabolism, the TCA cycle and GABA shunt were adversely affected. Phylogenetic analysis showed a single col-26 homolog in Sordariales, Ophilostomatales, and the Magnaporthales, but an expanded number of col-26 homologs in other filamentous fungal species. Deletion of the closest homolog of col-26 in Trichoderma reesei, bglR, resulted in a mutant with similar preferred carbon source growth deficiency, and which was alleviated if glutamine was the sole nitrogen source, suggesting conservation of COL-26 and BglR function. Our finding provides novel insight into the role of COL-26 for utilization of starch and in integrating carbon and nitrogen metabolism for balanced metabolic activities for optimal carbon and nitrogen distribution., Author summary In nature, filamentous fungi sense nutrient availability in the surrounding environment and adjust their metabolism for optimal utilization, growth and reproduction. Carbon and nitrogen are two of major elements required for life. Within cells, signals from carbon and nitrogen catabolism are integrated, resulting in balanced metabolic activities for optimal carbon and nitrogen distribution. However, coordination of carbon and nitrogen metabolism is often missed in studies that are based on comparisons between single carbon or nitrogen sources. In this study, we performed systematic transcriptional profiling of Neurospora crassa on different components of starch and identified the transcription factor COL-26 to be an essential regulator for starch utilization and needed for coordinating carbon and nitrogen regulation and metabolism. Proteins with sequence similar to COL-26 widely exist among ascomycete fungi. Here we provide experimental evidence for shared function of a col-26 ortholog in Trichoderma reesei. Our finding provides novel insight into how the regulation of carbon and nitrogen metabolism can be integrated in filamentous fungi by the function of COL-26 and which may aid in the rational design of fungal strains for industrial purposes.

Background Glycoside hydrolases (GHs) are enzymes that hydrolyze polysaccharides into simple sugars. To better understand the specificity of enzyme hydrolysis within the complex matrix of polysaccharides found in the plant cell wall, we studied the reactions of individual enzymes using glycome profiling, where a comprehensive collection of cell wall glycan-directed monoclonal antibodies are used to detect polysaccharide epitopes remaining in the walls after enzyme treatment and quantitative nanostructure initiator mass spectrometry (oxime-NIMS) to determine soluble sugar products of their reactions. Results Single, purified enzymes from the GH5_4, GH10, and GH11 families of glycoside hydrolases hydrolyzed hemicelluloses as evidenced by the loss of specific epitopes from the glycome profiles in enzyme-treated plant biomass. The glycome profiling data were further substantiated by oxime-NIMS, which identified hexose products from hydrolysis of cellulose, and pentose-only and mixed hexose-pentose products from the hydrolysis of hemicelluloses. The GH10 enzyme proved to be reactive with the broadest diversity of xylose-backbone polysaccharide epitopes, but was incapable of reacting with glucose-backbone polysaccharides. In contrast, the GH5 and GH11 enzymes studied here showed the ability to react with both glucose- and xylose-backbone polysaccharides. Conclusions The identification of enzyme specificity for a wide diversity of polysaccharide structures provided by glycome profiling, and the correlated identification of soluble oligosaccharide hydrolysis products provided by oxime-NIMS, offers a unique combination to understand the hydrolytic capabilities and constraints of individual enzymes as they interact with plant biomass. Electronic supplementary material The online version of this article (doi:10.1186/s13068-017-0703-6) contains supplementary material, which is available to authorized users.

Background Mixed cultures of different microbial species are increasingly being used to carry out a specific biochemical function in lieu of engineering a single microbe to do the same task. However, knowing how different species’ metabolisms will integrate to reach a desired outcome is a difficult problem that has been studied in great detail using steady-state models. However, many biotechnological processes, as well as natural habitats, represent a more dynamic system. Examining how individual species use resources in their growth medium or environment (exometabolomics) over time in batch culture conditions can provide rich phenotypic data that encompasses regulation and transporters, creating an opportunity to integrate the data into a predictive model of resource use by a mixed community. Results Here we use exometabolomic profiling to examine the time-varying substrate depletion from a mixture of 19 amino acids and glucose by two Pseudomonas and one Bacillus species isolated from ground water. Contrary to studies in model organisms, we found surprisingly few correlations between resource preferences and maximal growth rate or biomass composition. We then modeled patterns of substrate depletion, and used these models to examine if substrate usage preferences and substrate depletion kinetics of individual isolates can be used to predict the metabolism of a co-culture of the isolates. We found that most of the substrates fit the model predictions, except for glucose and histidine, which were depleted more slowly than predicted, and proline, glycine, glutamate, lysine and arginine, which were all consumed significantly faster. Conclusions Our results indicate that a significant portion of a model community’s overall metabolism can be predicted based on the metabolism of the individuals. Based on the nature of our model, the resources that significantly deviate from the prediction highlight potential metabolic pathways affected by species-species interactions, which when further studied can potentially be used to modulate microbial community structure and/or function. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1478-2) contains supplementary material, which is available to authorized users.

© 2017, Public Library of Science, All rights reserved. This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Lignin in plant biomass represents a target for engineering strategies towards the development of a sustainable bioeconomy. In addition to the conventional lignin monomers, namely p-coumaryl, coniferyl and sinapyl alcohols, tricin has been shown to be part of the native lignin polymer in certain monocot species. Because tricin is considered to initiate the polymerization of lignin chains, elucidating its biosynthesis and mechanism of export to the cell wall constitute novel challenges for the engineering of bioenergy crops. Late steps of tricin biosynthesis require two methylation reactions involving the pathway intermediate selgin. It has recently been demonstrated in rice and maize that caffeate O-methyltransferase (COMT) involved in the synthesis syringyl (S) lignin units derived from sinapyl alcohol also participates in the synthesis of tricin in planta. In this work, we validate in sorghum (Sorghum bicolor L.) that the O-methyltransferase responsible for the production of S lignin units (SbCOMT / Bmr12) is also involved in the synthesis of lignin-linked tricin. In particular, we show that biomass from the sorghum bmr12 mutant contains lower level of tricin incorporated into lignin, and that SbCOMT can methylate the tricin precursors luteolin and selgin. Our genetic and biochemical data point toward a general mechanism whereby COMT is involved in the synthesis of both tricin and S lignin units.

Long-chain fatty acids are internalized by receptor-mediated mechanisms or receptor-independent diffusion across cytoplasmic membranes and are utilized as nutrients, building blocks, and signaling intermediates. Here we describe how the association of long-chain fatty acids to a partially unfolded, extracellular protein can alter the presentation to target cells and cellular effects. HAMLET (human α-lactalbumin made lethal to tumor cells) is a tumoricidal complex of partially unfolded α-lactalbumin and oleic acid (OA). As OA lacks independent tumoricidal activity at concentrations equimolar to HAMLET, the contribution of the lipid has been debated. We show by natural abundance (13)C NMR that the lipid in HAMLET is deprotonated and by chromatography that oleate rather than oleic acid is the relevant HAMLET constituent. Compared with HAMLET, oleate (175 μm) showed weak effects on ion fluxes and gene expression. Unlike HAMLET, which causes metabolic paralysis, fatty acid metabolites were less strongly altered. The functional overlap increased with higher oleate concentrations (500 μm). Cellular responses to OA were weak or absent, suggesting that deprotonation favors cellular interactions of fatty acids. Fatty acids may thus exert some of their essential effects on host cells when in the deprotonated state and when presented in the context of a partially unfolded protein.

A recent metagenomic analysis sequenced a switchgrass-adapted compost community to identify enzymes from microorganisms that were specifically adapted to switchgrass under thermophilic conditions. These enzymes are being examined as part of the pretreatment process for the production of "second-generation" biofuels. Among the enzymes discovered was JMB19063, a novel three-domain β-glucosidase that belongs to the GH3 (glycoside hydrolase 3) family. Here, we report the structure of JMB19063 in complex with glucose and the catalytic variant D261N crystallized in the presence of cellopentaose. JMB19063 is first structure of a dimeric member of the GH3 family, and we demonstrate that dimerization is required for catalytic activity. Arg-587 and Phe-598 from the C-terminal domain of the opposing monomer are shown to interact with bound ligands in the D261N structure. Enzyme assays confirmed that these residues are absolutely essential for full catalytic activity.

Type I modular polyketide synthases (PKSs) are polymerases that utilize acyl-CoAs as substrates. Each polyketide elongation reaction is catalyzed by a set of protein domains called a module. Each module usually contains an acyltransferase (AT) domain, which determines the specific acyl-CoA incorporated into each condensation reaction. Although a successful exchange of individual AT domains can lead to the biosynthesis of a large variety of novel compounds, hybrid PKS modules often show significantly decreased activities. Using monomodular PKSs as models, we have systematically analyzed the segments of AT domains and associated linkers in AT exchanges in vitro and have identified the boundaries within a module that can be used to exchange AT domains while maintaining protein stability and enzyme activity. Importantly, the optimized domain boundary is highly conserved, which facilitates AT domain replacements in most type I PKS modules. To further demonstrate the utility of the optimized AT domain boundary, we have constructed hybrid PKSs to produce industrially important short-chain ketones. Our in vitro and in vivo analysis demonstrated production of predicted ketones without significant loss of activities of the hybrid enzymes. These results greatly enhance the mechanistic understanding of PKS modules and prove the benefit of using engineered PKSs as a synthetic biology tool for chemical production.

Glycoside hydrolases (GHs) are key enzymes in the depolymerization of plant-derived cellulose, a process central to the global carbon cycle and the conversion of plant biomass to fuels and chemicals. A limited number of GH families hydrolyze crystalline cellulose, often by a processive mechanism along the cellulose chain. During cultivation of thermophilic cellulolytic microbial communities, substantial differences were observed in the crystalline cellulose saccharification activities of supernatants recovered from divergent lineages. Comparative community proteomics identified a set of cellulases from a population closely related to actinobacterium Thermobispora bispora that were highly abundant in the most active consortium. Among the cellulases from T. bispora, the abundance of a GH family 12 (GH12) protein correlated most closely with the changes in crystalline cellulose hydrolysis activity. This result was surprising since GH12 proteins have been predominantly characterized as enzymes active on soluble polysaccharide substrates. Heterologous expression and biochemical characterization of the suite of T. bispora hydrolytic cellulases confirmed that the GH12 protein possessed the highest activity on multiple crystalline cellulose substrates and demonstrated that it hydrolyzes cellulose chains by a predominantly random mechanism. This work suggests that the role of GH12 proteins in crystalline cellulose hydrolysis by cellulolytic microbes should be reconsidered., IMPORTANCE Cellulose is the most abundant organic polymer on earth, and its enzymatic hydrolysis is a key reaction in the global carbon cycle and the conversion of plant biomass to biofuels. The glycoside hydrolases that depolymerize crystalline cellulose have been primarily characterized from isolates. In this study, we demonstrate that adapting microbial consortia from compost to grow on crystalline cellulose generated communities whose soluble enzymes exhibit differential abilities to hydrolyze crystalline cellulose. Comparative proteomics of these communities identified a protein of glycoside hydrolase family 12 (GH12), a family of proteins previously observed to primarily hydrolyze soluble substrates, as a candidate that accounted for some of the differences in hydrolytic activities. Heterologous expression confirmed that the GH12 protein identified by proteomics was active on crystalline cellulose and hydrolyzed cellulose by a random mechanism, in contrast to most cellulases that act on the crystalline polymer in a processive mechanism.

Microorganisms are typically found as complex microbial communities that altogether govern global biogeochemical cycles. Microbes have developed highly regulated metabolic capabilities to efficiently use available substrates including preferential substrate usage that can result in diauxic shifts. This and other metabolic behaviors have been discovered in studies of microbes in monoculture when grown on low-complexity (e.g.two-component) mixtures of substrates, however, little is known about how species partition environmental substrates through substrate competition in more complex substrate mixtures. Here we use exometabolomic profiling to examine the time-varying substrate depletion from a mixture of 19 amino acids and glucose by twoPseudomonadsand oneBacillusspecies isolated from ground water. We examine if the first substrates depleted result in maximal growth rate, or relate to growth medium or biomass composition and find surprisingly few correlations. Patterns of substrate depletion are modeled, and these models are used to examine if substrate usage preferences and substrate depletion kinetics of three microbial isolates can be used to predict the metabolism of the pooled isolates in co-culture. We find that most of the substrates fit the model predictions, indicating that the microbes are not altering their behaviors for these substrates in the presence of competitors. Glucose and histidine were depleted more slowly than predicted, while proline, glycine, glutamate, lysine, and arginine were all consumed significantly faster; these compounds highlight substrates that could be involved in species-species interactions within the consortium.Author ContributionsOE, TRN conceived and designed the experimentsOE, BPB, SMK, SJ, RL performed the experimentsOE, BPB, SJ, TRN analyzed the dataOE, TRN wrote the manuscriptTRN contributed materials and analysis tools

Mass spectrometry imaging (MSI) has emerged as a powerful technique enabling spatially defined imaging of metabolites within microbial biofilms. Here, we extend this approach to enable differentiation of newly synthesized versus pre-existing metabolites across a co-culture. This is accomplished by MS imaging two soil microbes, Shewanella oneidensis MR1 and Pseudomonas stutzeri RCH2, that were administered heavy water (D2O) during growth on agar plates. For two species-specific diglyceride (DG) lipids, isotopic analysis was performed on each spectra collected across the co-culture to determine the relative amount of newly synthesized versus pre-existing lipid. Here, highest levels of new synthesis of RCH2 lipid was localized to border regions adjacent to S. oneidensis MR1, while the MR1 lipid showed highest levels in regions further from RCH2. Interestingly, regions of high lipid abundance did not correspond to the regions with highest new lipid biosynthesis. Given the simplicity and generality of using D2O as a stable isotopic probe combined with the accessibility of kMSI to a range of MSI instrumentation, this approach has broad application for improving our understanding of how microbial interactions influence metabolite biosynthesis.

Natural microbial communities are extremely diverse and contain uncharacterized but functionally important small molecules. By coupling a deuterium (D) labeling technique to high mass accuracy untargeted liquid chromatography-electrospray ionization-mass spec- trometry (LC-ESI-MS) metabolomic analysis, we found that natural acidophilic microbial biofilms dominated by bacteria of the genus Leptospirillum contained unusual lyso phosphatidylethanolamine (PE) lipids in high abundance (more than 10 nmol/mg of dry biomass). The unusual polar head group structure of these lipids is similar to lipids found in phylogenetically unrelated acidophilic chemo- autolithotrophs and may be related to the affinity of these lipids for iron and calcium ions. Correlations of lyso phospholipid and proteome abundance patterns suggest a link between the lyso phospholipids and the UBA-type substrain of Leptospirillum group II. By combining untar- geted metabolomics with D exchange we demonstrate the ability to identify cryptic but biologically functional small molecules in mixed microbial communities.

Metabolite profiling using mass spectrometry provides an attractive approach for the interrogation of cellular metabolic capabilities. Untargeted metabolite profiling has the potential to identify numerous novel metabolites; however, de novo identification of metabolites from spectral features remains a challenge. Here we present an integrated workflow for metabolite identification using uniform stable isotope labeling. Metabolite profiling of cell and growth media extracts of unlabeled control, (15)N, and (13)C-labeled cultures of the cyanobacterium, Synechococcus sp. PCC 7002 was performed using normal phase liquid chromatography coupled to mass spectrometry (LC-MS). Visualization of three-way comparisons of raw data sets highlighted characteristic labeling patterns for metabolites of biological origin allowing exhaustive identification of corresponding spectral features. Additionally, unambiguous assignment of chemical formulas was greatly facilitated by the use of stable isotope labeling. Chemical formulas of metabolites responsible for redundant spectral features were determined and fragmentation (MS/MS) spectra for these metabolites were collected. Analysis of acquired MS/MS spectra against spectral database records led to the identification of a number of metabolites absent not only from the reconstructed draft metabolic network of Synechococcus sp. PCC 7002 but not included in databases of metabolism (MetaCyc or KEGG).

Alga-derived lipids represent an attractive potential source of biofuels. However, lipid accumulation in algae is a stress response tightly coupled to growth arrest, thereby imposing a major limitation on productivity. To identify transcriptional regulators of lipid accumulation, we performed an integrative chromatin signature and transcriptomic analysis to decipher the regulation of lipid biosynthesis in the alga Chlamydomonas reinhardtii. Genome-wide histone modification profiling revealed remarkable differences in functional chromatin states between the algae and higher eukaryotes and uncovered regulatory components at the core of lipid accumulation pathways. We identified the transcription factor, PSR1, as a pivotal switch that triggers cytosolic lipid accumulation. Dissection of the PSR1-induced lipid profiles corroborates its role in coordinating multiple lipid-inducing stress responses. The comprehensive maps of functional chromatin signatures in a major clade of eukaryotic life and the discovery of a transcriptional regulator of algal lipid metabolism will facilitate targeted engineering strategies to mediate high lipid production in microalgae.

Background Carbohydrate binding modules (CBMs) bind polysaccharides and help target glycoside hydrolases catalytic domains to their appropriate carbohydrate substrates. To better understand how CBMs can improve cellulolytic enzyme reactivity, representatives from each of the 18 families of CBM found in Ruminoclostridiumthermocellum were fused to the multifunctional GH5 catalytic domain of CelE (Cthe_0797, CelEcc), which can hydrolyze numerous types of polysaccharides including cellulose, mannan, and xylan. Since CelE is a cellulosomal enzyme, none of these fusions to a CBM previously existed. Results CelEcc_CBM fusions were assayed for their ability to hydrolyze cellulose, lichenan, xylan, and mannan. Several CelEcc_CBM fusions showed enhanced hydrolytic activity with different substrates relative to the fusion to CBM3a from the cellulosome scaffoldin, which has high affinity for binding to crystalline cellulose. Additional binding studies and quantitative catalysis studies using nanostructure-initiator mass spectrometry (NIMS) were carried out with the CBM3a, CBM6, CBM30, and CBM44 fusion enzymes. In general, and consistent with observations of others, enhanced enzyme reactivity was correlated with moderate binding affinity of the CBM. Numerical analysis of reaction time courses showed that CelEcc_CBM44, a combination of a multifunctional enzyme domain with a CBM having broad binding specificity, gave the fastest rates for hydrolysis of both the hexose and pentose fractions of ionic-liquid pretreated switchgrass. Conclusion We have shown that fusions of different CBMs to a single multifunctional GH5 catalytic domain can increase its rate of reaction with different pure polysaccharides and with pretreated biomass. This fusion approach, incorporating domains with broad specificity for binding and catalysis, provides a new avenue to improve reactivity of simple combinations of enzymes within the complexity of plant biomass. Electronic supplementary material The online version of this article (doi:10.1186/s13068-015-0402-0) contains supplementary material, which is available to authorized users.

International audience; Mass spectrometry-based metabolomics has become a powerful tool for the detection of metabolites in complex biological systems and for the identification of novel metabolites. We previously identified a number of unexpected metabolites in the cyanobacterium Synechococcus sp. PCC 7002, such as histidine betaine, its derivatives and several unusual oligosaccharides. To test for the presence of these compounds and to assess the diversity of small polar metabolites in other cyanobacteria, we profiled cell extracts of nine strains representing much of the morphological and evolutionary diversification of this phylum. Spectral features in raw metabolite profiles obtained by normal phase liquid chromatography coupled to mass spectrometry (MS) were manually curated so that chemical formulae of metabolites could be assigned. For putative identification, retention times and MS/MS spectra were cross-referenced with those of standards or available sprectral library records. Overall, we detected 264 distinct metabolites. These included indeed different betaines, oligosaccharides as well as additional unidentified metabolites with chemical formulae not present in databases of metabolism. Some of these metabolites were detected only in a single strain, but some were present in more than one. Genomic OPEN ACCESS Mar. Drugs 2013, 11 3618 interrogation of the strains revealed that generally, presence of a given metabolite corresponded well with the presence of its biosynthetic genes, if known. Our results show the potential of combining metabolite profiling and genomics for the identification of novel biosynthetic genes.

The fractionation of hydrogen stable isotopes during lipid biosynthesis is larger in autotrophic than in heterotrophic microorganisms, possibly due to selective incorporation of hydrogen from water into NAD(P)H, resulting in D-depleted lipids. An analogous fractionation should occur during amino acid biosynthesis. Whereas these effects are traditionally measured using gas-phase isotope ratio on 1H-1H and 1H-2H, using an electrospray mass spectrometry-based technique on the original biomolecular structure and fitting of isotopic patterns we measured the hydrogen isotope compositions of proteins from an acidophilic microbial community with organism specificity and compared values with those for lipids. We showed that lipids were isotopically light by -260 ‰ relative to water in the growth solution; alternatively protein isotopic composition averaged -370 ‰. This difference suggests that steps in addition to NAD(P)H formation contribute to D/H fractionation. Further, autotrophic bacteria sharing 94% 16S rRNA gene sequence identity displayed statistically significant differences in protein hydrogen isotope fractionation, suggesting different metabolic traits consistent with distinct ecological niches or incorrectly annotated gene function. In addition, it was found that heterotrophic, archaeal members of the community had isotopically light protein (-323 ‰) relative to growth water and were significantly different from coexisting bacteria. This could be attributed to metabolite transfer from autotrophs and unknown aspects of fractionation associated with iron reduction. Differential fractionation of hydrogen stable isotopes into metabolites and proteins may reveal trophic levels of members of microbial communities. The approach developed here provided insights into the metabolic characteristics of organisms in natural communities and may be applied to analyze other systems.

Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities., IMPORTANCE Microbial communities are central to many critical global processes and yet remain enigmatic largely due to their complex and distributed metabolic interactions. Metabolomics has the possibility of providing mechanistic insights into the function and ecology of microbial communities. However, our limited knowledge of microbial metabolites, the difficulty of identifying metabolites from complex samples, and the inability to link metabolites directly to community members have proven to be major limitations in developing advances in systems interactions. Here, we show that combining stable-isotope-enabled metabolomics with genomics, transcriptomics, and proteomics can illuminate the ecology of microorganisms at the community scale.

Mass spectrometry based technologies are promising as generalizable high-throughput assays for enzymatic activity. In one such technology, a specialized enzyme substrate probe is presented to a biological mixture potentially exhibiting enzymatic activity, followed by an in situ enrichment step using fluorous interactions and nanostructure-initiator mass spectrometry. This technology, known as Nimzyme, shows great potential but is limited by the need to synthesize custom substrate analogs. We describe a synthetic route that simplifies the production of these probes by fashioning their perfluorinated invariant portion as an alkylating agent. This way, a wide variety of compounds can be effectively transformed into enzyme activity probes. As a proof of principle, a chloramphenicol analog synthesized according to this methodology was used to detect chloramphenicol acetyltransferase activity in cell lysate. This verifies the validity of the synthetic strategy employed and constitutes the first reported application of Nimzyme to a non-carbohydrate-active enzyme. The simplified synthetic approach presented here may help advance the application of mass spectrometry to high-throughput enzyme activity determination. Figure The Nimzyme high-throughput enzyme activity assay allows for the detection of enzyme activity in cell lysate. Fluorous interactions between a specialized substrate probe and a nanostructure-initiator mass spectrometry surface allow for in situ cleanup and the subsequent collection of unambiguous mass spectra. One of the main hurdles that prevents the widespread adoption of this technology is the need to chemically synthesize the required probes. Here, we present a simplified route to derive Nimzyme probes from a wide variety of biologically interesting substrates. Electronic supplementary material The online version of this article (doi:10.1007/s00216-013-6888-z) contains supplementary material, which is available to authorized users.

The discrepancy between the pace of sequencing and functional characterization of genomes is a major challenge in understanding complex microbial metabolic processes and metabolic interactions in the environment. Here, we identified and validated genes related to the utilization of specific metabolites in bacteria by profiling metabolite utilization in libraries of mutant strains. Untargeted mass spectrometry based metabolomics was used to identify metabolites utilized by Escherichia coli and Shewanella oneidensis MR-1. Targeted high-throughput metabolite profiling of spent media of 8042 individual mutant strains was performed to link utilization to specific genes. Using this approach we identified genes of known function as well as novel transport proteins and enzymes required for the utilization of tested metabolites. Specific examples include two subunits of a predicted ABC transporter encoded by the genes SO1043 and SO1044 required for the utilization of citrulline and a predicted histidase encoded by the gene SO3057 required for the utilization of ergothioneine by S. oneidensis. In vitro assays with purified proteins showed substrate specificity of SO3057 toward ergothioneine and histidine betaine in contrast to substrate specificity of a paralogous histidase SO0098 toward histidine. This generally applicable, high-throughput workflow has the potential both to discover novel metabolic capabilities of microorganisms and to identify the corresponding genes.

Mass spectrometry (MS)-based enzyme assay has been shown to be a useful tool for screening enzymatic activities from environmental samples. Recently, reported approaches for high-specificity multiplexed characterization of enzymatic activities allow for providing detailed information on the range of enzymatic products and monitoring multiple enzymatic reactions. However, the throughput has been limited by the slow liquid-liquid handling and manual analysis. This rapid communication demonstrates the integration of acoustic sample deposition with nanostructure initiator mass spectrometry (NIMS) imaging to provide reproducible measurements of multiple enzymatic reactions at a throughput that is tenfold to 100-fold faster than conventional MS-based enzyme assay. It also provides a simple means for the visualization of multiple reactions and reaction pathways.

We describe a Nanostructure-Initiator Mass Spectrometry (NIMS) enzymatic (Nimzyme) assay in which enzyme substrates are immobilized on the mass spectrometry surface by using fluorous-phase interactions. This “soft” immobilization allows efficient desorption/ionization while also enabling the use of surface-washing steps to reduce signal suppression from complex biological samples, which results from the preferential retention of the tagged products and reactants. The Nimzyme assay is sensitive to subpicogram levels of enzyme, detects both addition and cleavage reactions (sialyltransferase and galactosidase), is applicable over a wide range of pHs and temperatures, and can measure activity directly from crude cell lysates. The ability of the Nimzyme assay to analyze complex mixtures is illustrated by identifying and directly characterizing β-1,4-galactosidase activity from a thermophilic microbial community lysate. The optimal enzyme temperature and pH were found to be 65°C and 5.5, respectively, and the activity was inhibited by both phenylethyl-β- d -thiogalactopyranoside and deoxygalactonojirimycin. Metagenomic analysis of the community suggests that the activity is from an uncultured, unsequenced γ-proteobacterium. In general, this assay provides an efficient method for detection and characterization of enzymatic activities in complex biological mixtures prior to sequencing or cloning efforts. More generally, this approach may have important applications for screening both enzymatic and inhibitor libraries, constructing and screening glycan microarrays, and complementing fluorous-phase organic synthesis.

Specific cell types are critically implicated in a variety of neuropathologies that exhibit region-specific susceptibility. Neuronal and glial function is impaired in a host of neurodegenerative diseases. Previous reports suggest that mass spectrometry imaging has the potential to resolve cell-specific enrichment in brain regions; however, individual ions cannot resolve glial and neuronal cells within the complex structure of brain tissue. Here, we utilized a matrix-free surface mass spectrometry approach, nanostructure initiator mass spectrometry (NIMS) to determine if multiple lipid ions can be used as a ‘fingerprint’ to discriminate between neuronal- and glial-enriched brain regions and between glial cells in different regions of the brain, such as the cortex and the cerebellum. This is accomplished by using established stains to define glial cell enrichment (GFAP) and NIMS imaging on adjacent serial sections to measure phospholipid distributions. Identifications were made using QTOF analysis of whole-brain extracts and comparison with previous reports. From these identifications, it was found that utilization of multiple lipids can indeed resolve glial and neuronal cell enriched brain regions in the imaged brain section. The resolution of brain regions and cell populations is greatly enhanced through application of multivariate statistical analysis (Nonnegative Matrix Factorization) of the 18 dominant potassium adducts of phospholipids. Strikingly, this analysis resolves other brain regions that are difficult to distinguish using conventional stains but known to have distinct physiological functions. For example, this method could accurately distinguish the frontal (or somatomotor) and dorsal (or retrosplenial) regions of the cortex, which have important functional differences, from each other and from the pons region. This work suggests that using this approach with inclusion of larger numbers of lipids has the potential to greatly improve our understanding of regional and cell type specific variation in the brain.

The enzymatic hydrolysis of polysaccharides into fermentable sugars is a crucial step in the conversion of biomass to lignocellulosic biofuels. An efficient hydrolysis is highly dependent on the identification and characterization of optimal glycoside hydrolases. However, existing techniques for characterizing activity are limited by the range of reaction conditions that can be used, sample complexity, and throughput. The method we present is a multiplexed approach based on nanostructure-initiator mass spectrometry (NIMS) that allows for the rapid analysis of several glycolytic activities in parallel under diverse assay conditions. By forming colloids, it was possible to perform aqueous reactions in tubes and microwell plates despite the substrate analogs' hydrophobic perfluorinated tags. This method was validated by analyzing standard enzymatic parameters (temperature, pH, and kinetics) of β-glucosidase and β-xylosidase in separate setups. The multiplexity of this assay system was demonstrated by the simultaneous analysis of β-glucosidase and β-xylosidase activities, which was then used to profile environmental samples. Enzymes secreted by microbial communities within these samples were extracted by washing the sample with buffer. Enzymatic activities were directly detected within this crude extract without any further sample pretreatment steps. The multiplexed analysis of β-glucosidase, exo-/endoglucanase, and xylanase activities was applied for a detailed characterization of previously unknown glycoside hydrolase activities. The results show the suitability of the described method for the rapid screening of crude environmental samples under a wide range of conditions to determine enzyme activities from the microbial communities present within these samples.