Exploiting phenotypic heterogeneity to improve production of glutathione by yeast.

BACKGROUND: Gene expression noise (variation in gene expression among individual cells of a genetically uniform cell population) can result in heterogenous metabolite production by industrial microorganisms, with cultures containing both low- and high-producing cells. The presence of low-producing individuals may be a factor limiting the potential for high yields. This study tested the hypothesis that low-producing variants in yeast cell populations can be continuously counter-selected, to increase net production of glutathione (GSH) as an exemplar product. RESULTS: A counter-selection system was engineered in Saccharomyces cerevisiae based on the known feedback inhibition of gamma-glutamylcysteine synthetase (GSH1) gene expression, which is rate limiting for GSH synthesis: the GSH1 ORF and the counter-selectable marker GAP1 were expressed under control of the TEF1 and GSH-regulated GSH1 promoters, respectively. An 18% increase in the mean cellular GSH level was achieved in cultures of the engineered strain supplemented with D-histidine to counter-select cells with high GAP1 expression (i.e. low GSH-producing cells). The phenotype was non-heritable and did not arise from a generic response to D-histidine, unlike that with certain other test-constructs prepared with alternative markers. CONCLUSIONS: The results corroborate that the system developed here improves GSH production by targeting low-producing cells. This supports the potential for exploiting end-product/promoter interactions to enrich high-producing cells in phenotypically heterogeneous populations, in order to improve metabolite production by yeast.

Growth rate and nutrient limitation as key drivers of extracellular quorum sensing signal molecule accumulation in Pseudomonas aeruginosa.

In Pseudomonas aeruginosa, quorum sensing (QS) depends on an interconnected regulatory hierarchy involving the Las, Rhl and Pqs systems, which are collectively responsible for the co-ordinated synthesis of a diverse repertoire of N-acylhomoserine lactones (AHLs) and 2-alkyl-4-quinolones (AQs). Apparent population density-dependent phenomena such as QS may, however, be due to growth rate and/or nutrient exhaustion in batch culture. Using continuous culture, we show that growth rate and population density independently modulate the accumulation of AHLs and AQs such that the highest concentrations are observed at a slow growth rate and high population density. Carbon source (notably succinate), nutrient limitation (C, N, Fe, Mg) or growth at 25 °C generally reduces AHL and AQ levels, except for P and S limitation, which result in substantially higher concentrations of AQs, particularly AQ N-oxides, despite the lower population densities achieved. Principal component analysis indicates that ~26 % variation is due to nutrient limitation and a further 30 % is due to growth rate. The formation of N-(3-oxododecanoyl)-l-homoserine lactone (3OC12-HSL) turnover products such as the ring opened form and tetramic acid varies with the limiting nutrient limitation and anaerobiosis. Differential ratios of N-butanoyl-homoserine lactone (C4-HSL), 3OC12-HSL and the AQs as a function of growth environment are clearly apparent. Inactivation of QS by mutation of three key genes required for QS signal synthesis (lasI, rhlI and pqsA) substantially increases the concentrations of key substrates from the activated methyl cycle and aromatic amino acid biosynthesis, as well as ATP levels, highlighting the energetic drain that AHL and AQ synthesis and hence QS impose on P. aeruginosa.

A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications.

Exploiting biological processes to recycle renewable carbon into high value platform chemicals provides a sustainable and greener alternative to current reliance on petrochemicals. In this regard Cupriavidus necator H16 represents a particularly promising microbial chassis due to its ability to grow on a wide range of low-cost feedstocks, including the waste gas carbon dioxide, whilst also naturally producing large quantities of polyhydroxybutyrate (PHB) during nutrient-limited conditions. Understanding the complex metabolic behaviour of this bacterium is a prerequisite for the design of successful engineering strategies for optimising product yields. We present a genome-scale metabolic model (GSM) of C. necator H16 (denoted iCN1361), which is directly constructed from the BioCyc database to improve the readability and reusability of the model. After the initial automated construction, we have performed extensive curation and both theoretical and experimental validation. By carrying out a genome-wide essentiality screening using a Transposon-directed Insertion site Sequencing (TraDIS) approach, we showed that the model could predict gene knockout phenotypes with a high level of accuracy. Importantly, we indicate how experimental and computational predictions can be used to improve model structure and, thus, model accuracy as well as to evaluate potential false positives identified in the experiments. Finally, by integrating transcriptomics data with iCN1361 we create a condition-specific model, which, importantly, better reflects PHB production in C. necator H16. Observed changes in the omics data and in-silico-estimated alterations in fluxes were then used to predict the regulatory control of key cellular processes. The results presented demonstrate that iCN1361 is a valuable tool for unravelling the system-level metabolic behaviour of C. necator H16 and can provide useful insights for designing metabolic engineering strategies.

Metabolic engineering of Cupriavidus necator H16 for heterotrophic and autotrophic production of 3-hydroxypropionic acid.

3-Hydroxypropionate (3-HP) is a versatile compound for chemical synthesis and a potential building block for biodegradable polymers. Cupriavidus necator H16, a facultative chemolithoautotroph, is an attractive production chassis and has been extensively studied as a model organism for biopolymer production. Here, we engineered C. necator H16 for 3-HP biosynthesis from its central metabolism. Wild type C. necator H16 can use 3-HP as a carbon source, a highly undesirable trait for a 3-HP production chassis. However, deletion of its three (methyl-)malonate semialdehyde dehydrogenases (mmsA1, mmsA2 and mmsA3) resulted in a strain that cannot grow on 3-HP as the sole carbon source, and this strain was selected as our production host. A stepwise approach was used to construct pathways for 3-HP production via ß-alanine. Two additional gene deletion targets were identified during the pathway construction process. Deletion of the 3-hydroxypropionate dehydrogenase, encoded by hpdH, prevented the re-consumption of the 3-HP produced by our engineered strains, while deletion of gdhA1, annotated as a glutamate dehydrogenase, prevented the utilization of aspartate as a carbon source, one of the key pathway intermediates. The final strain carrying these deletions was able to produce up to 8 mM 3-HP heterotrophically. Furthermore, an engineered strain was able to produce 0.5 mM 3-HP under autotrophic conditions, using CO2 as sole carbon source. These results form the basis for establishing C. necator H16 as an efficient platform for the production of 3-HP and 3-HP-containing polymers.

Required Gene Set for Autotrophic Growth of Clostridium autoethanogenum.

The majority of the genes present in bacterial genomes remain poorly characterized, with up to one-third of those that are protein encoding having no definitive function. Transposon insertion sequencing represents a high-throughput technique that can help rectify this deficiency. The technology, however, can only be realistically applied to those species in which high rates of DNA transfer can be achieved. Here, we have developed a number of approaches that overcome this barrier in the autotrophic species Clostridium autoethanogenum by using a mariner-based transposon system. The inherent instability of such systems in the Escherichia coli conjugation donor due to transposition events was counteracted through the incorporation of a conditionally lethal codA marker on the plasmid backbone. Relatively low frequencies of transformation of the plasmid into C. autoethanogenum were circumvented through the use of a plasmid that is conditional for replication coupled with the routine implementation of an Illumina library preparation protocol that eliminates plasmid-based reads. A transposon library was then used to determine the essential genes needed for growth using carbon monoxide as the sole carbon and energy source. IMPORTANCE Although microbial genome sequences are relatively easily determined, assigning gene function remains a bottleneck. Consequently, relatively few genes are well characterized, leaving the function of many as either hypothetical or entirely unknown. High-throughput transposon sequencing can help remedy this deficiency, but is generally only applicable to microbes with efficient DNA transfer procedures. These exclude many microorganisms of importance to humankind either as agents of disease or as industrial process organisms. Here, we developed approaches to facilitate transposon insertion sequencing in the acetogen Clostridium autoethanogenum, a chassis being exploited to convert single-carbon waste gases CO and CO2 into chemicals and fuels at an industrial scale. This allowed the determination of gene essentiality under heterotrophic and autotrophic growth, providing insights into the utilization of CO as a sole carbon and energy source. The strategies implemented are translatable and will allow others to apply transposon insertion sequencing to other microbes where DNA transfer has until now represented a barrier to progress.

Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions.

Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and 13C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between 13C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed.

RRNPP-type quorum sensing affects solvent formation and sporulation in Clostridium acetobutylicum.

The strictly anaerobic bacterium Clostridium acetobutylicum is well known for its ability to convert sugars into organic acids and solvents, most notably the potential biofuel butanol. However, the regulation of its fermentation metabolism, in particular the shift from acid to solvent production, remains poorly understood. The aim of this study was to investigate whether cell-cell communication plays a role in controlling the timing of this shift or the extent of solvent formation. Analysis of the available C. acetobutylicum genome sequences revealed the presence of eight putative RRNPP-type quorum-sensing systems, here designated qssA to qssH, each consisting of an RRNPP-type regulator gene followed by a small open reading frame encoding a putative signalling peptide precursor. The identified regulator and signal peptide precursor genes were designated qsrA to qsrH and qspA to qspH, respectively. Triplicate regulator mutants were generated in strain ATCC 824 for each of the eight systems and screened for phenotypic changes. The qsrB mutants showed increased solvent formation during early solventogenesis and hence the QssB system was selected for further characterization. Overexpression of qsrB severely reduced solvent and endospore formation and this effect could be overcome by adding short synthetic peptides to the culture medium representing a specific region of the QspB signalling peptide precursor. In addition, overexpression of qspB increased the production of acetone and butanol and the initial (48 h) titre of heat-resistant endospores. Together, these findings establish a role for QssB quorum sensing in the regulation of early solventogenesis and sporulation in C. acetobutylicum.

Gsmodutils: a python based framework for test-driven genome scale metabolic model development.

MOTIVATION: Genome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-state behaviour. Constraints based models of this form can include thousands of reactions and metabolites, with many crucial pathways that only become activated in specific simulation settings. However, despite their widespread use, power and the availability of tools to aid with the construction and analysis of large scale models, little methodology is suggested for their continued management. For example, when genome annotations are updated or new understanding regarding behaviour is discovered, models often need to be altered to reflect this. This is quickly becoming an issue for industrial systems and synthetic biotechnology applications, which require good quality reusable models integral to the design, build, test and learn cycle. RESULTS: As part of an ongoing effort to improve genome scale metabolic analysis, we have developed a test-driven development methodology for the continuous integration of validation data from different sources. Contributing to the open source technology based around COBRApy, we have developed the gsmodutils modelling framework placing an emphasis on test-driven design of models through defined test cases. Crucially, different conditions are configurable allowing users to examine how different designs or curation impact a wide range of system behaviours, minimizing error between model versions. AVAILABILITY AND IMPLEMENTATION: The software framework described within this paper is open source and freely available from http://github.com/SBRCNottingham/gsmodutils. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The carbonic anhydrase of Clostridium autoethanogenum represents a new subclass of ß-carbonic anhydrases.

Carbonic anhydrase catalyses the interconversion of carbon dioxide and water to bicarbonate and protons. It was unknown if the industrial-relevant acetogen Clostridium autoethanogenum possesses these enzymes. We identified two putative carbonic anhydrase genes in its genome, one of the ß class and one of the γ class. Carbonic anhydrase activity was found for the purified ß class enzyme, but not the γ class candidate. Functional complementation of an Escherichia coli carbonic anhydrase knock-out mutant showed that the ß class carbonic anhydrase could complement this activity, but not the γ class candidate gene. Phylogenetic analysis showed that the ß class carbonic anhydrase of Clostridium autoethanogenum represents a novel sub-class of ß class carbonic anhydrases that form the F-clade. The members of this clade have the shortest primary structure of any known carbonic anhydrase.

Engineering of vitamin prototrophy in Clostridium ljungdahlii and Clostridium autoethanogenum.

Clostridium autoethanogenum and Clostridium ljungdahlii are physiologically and genetically very similar strict anaerobic acetogens capable of growth on carbon monoxide as sole carbon source. While exact nutritional requirements have not been reported, we observed that for growth, the addition of vitamins to media already containing yeast extract was required, an indication that these are fastidious microorganisms. Elimination of complex components and individual vitamins from the medium revealed that the only organic compounds required for growth were pantothenate, biotin and thiamine. Analysis of the genome sequences revealed that three genes were missing from pantothenate and thiamine biosynthetic pathways, and five genes were absent from the pathway for biotin biosynthesis. Prototrophy in C. autoethanogenum and C. ljungdahlii for pantothenate was obtained by the introduction of plasmids carrying the heterologous gene clusters panBCD from Clostridium acetobutylicum, and for thiamine by the introduction of the thiC-purF operon from Clostridium ragsdalei. Integration of panBCD into the chromosome through allele-coupled exchange also conveyed prototrophy. C. autoethanogenum was converted to biotin prototrophy with gene sets bioBDF and bioHCA from Desulfotomaculum nigrificans strain CO-1-SRB, on plasmid and integrated in the chromosome. The genes could be used as auxotrophic selection markers in recombinant DNA technology. Additionally, transformation with a subset of the genes for pantothenate biosynthesis extended selection options with the pantothenate precursors pantolactone and/or beta-alanine. Similarly, growth was obtained with the biotin precursor pimelate combined with genes bioYDA from C. acetobutylicum. The work raises questions whether alternative steps exist in biotin and thiamine biosynthesis pathways in these acetogens.

A novel conjugal donor strain for improved DNA transfer into Clostridium spp.

Clostridium encompasses species which are relevant to human and animal disease as well as species which have industrial potential, for instance, as producers of chemicals and fuels or as tumour delivery vehicles. Genetic manipulation of these target organisms is critical for advances in these fields. DNA transfer efficiencies, however, vary between species. Low efficiencies can impede the progress of research efforts. A novel conjugal donor strain of Escherichia coli has been created which exhibits a greater than 10-fold increases in conjugation efficiency compared to the traditionally used CA434 strain in the three species tested; C. autoethanogenum DSM 10061, C. sporogenes NCIMB 10696 and C. difficile R20291. The novel strain, designated 'sExpress', does not methylate DNA at Dcm sites (CCWGG) which allows circumvention of cytosine-specific Type IV restriction systems. A robust protocol for conjugation is presented which routinely produces in the order of 105 transconjugants per millilitre of donor cells for C. autoethanogenum, 106 for C. sporogenes and 102 for C. difficile R20291. The novel strain created is predicted to be a superior conjugal donor in a wide range of species which possess Type IV restriction systems.

Quantitative Isotope-Dilution High-Resolution-Mass-Spectrometry Analysis of Multiple Intracellular Metabolites in Clostridium autoethanogenum with Uniformly 13C-Labeled Standards Derived from Spirulina.

We have investigated the applicability of commercially available lyophilized spirulina ( Arthrospira platensis), a microorganism uniformly labeled with 13C, as a readily accessible source of multiple 13C-labeled metabolites suitable as internal standards for the quantitative determination of intracellular bacterial metabolites. Metabolites of interest were analyzed by hydrophilic-interaction liquid chromatography coupled with high-resolution mass spectrometry. Multiple internal standards obtained from uniformly (U)-13C-labeled extracts from spirulina were used to enable isotope-dilution mass spectrometry (IDMS) in the identification and quantification of intracellular metabolites. Extraction of the intracellular metabolites of Clostridium autoethanogenum using 2:1:1 chloroform/methanol/water was found to be the optimal method in comparison with freeze-thaw, homogenization, and sonication methods. The limits of quantification were ≤1 µM with excellent linearity for all of the calibration curves ( R2 ≥ 0.99) for 74 metabolites. The precision and accuracy were found to be within relative standard deviations (RSDs) of 15% for 49 of the metabolites and within RSDs of 20% for all of the metabolites. The method was applied to study the effects of feeding different levels of carbon monoxide (as a carbon source) on the central metabolism and Wood-Ljungdahl pathway of C. autoethanogenum grown in continuous culture over 35 days. Using LC-IDMS with U-13C spirulina allowed the successful quantification of 52 metabolites in the samples, including amino acids, carboxylic acids, sugar phosphates, purines, and pyrimidines. The method provided absolute quantitative data on intracellular metabolites that was suitable for computational modeling to understand and optimize the C. autoethanogenum metabolic pathways active in gas fermentation.

Progress towards platform chemical production using Clostridium autoethanogenum.

Since 2013, there has been an explosion in the number of research articles published on Clostridium autoethanogenum, an acetogen capable of producing platform chemicals such as ethanol and 2,3-butanediol from greenhouse gases. However, no review focusing solely on C. autoethanogenum has appeared in the literature. This review outlines the research conducted into this organism in three broad categories (Enzymology, Genetics, and Systems Biology) and suggestions for future research are offered.

Functional Genetic Elements for Controlling Gene Expression in Cupriavidus necator H16.

A robust and predictable control of gene expression plays an important role in synthetic biology and biotechnology applications. Development and quantitative evaluation of functional genetic elements, such as constitutive and inducible promoters as well as ribosome binding sites (RBSs), are required. In this study, we designed, built, and tested promoters and RBSs for controlling gene expression in the model lithoautotroph Cupriavidus necator H16. A series of variable-strength, insulated, constitutive promoters exhibiting predictable activity within a >700-fold dynamic range was compared to the native P phaC , with the majority of promoters displaying up to a 9-fold higher activity. Positively (AraC/P araBAD -l-arabinose and RhaRS/P rhaBAD -l-rhamnose) and negatively (AcuR/P acuRI -acrylate and CymR/P cmt -cumate) regulated inducible systems were evaluated. By supplying different concentrations of inducers, a >1,000-fold range of gene expression levels was achieved. Application of inducible systems for controlling expression of the isoprene synthase gene ispS led to isoprene yields that exhibited a significant correlation to the reporter protein synthesis levels. The impact of designed RBSs and other genetic elements, such as mRNA stem-loop structure and A/U-rich sequence, on gene expression was also evaluated. A second-order polynomial relationship was observed between the RBS activities and isoprene yields. This report presents quantitative data on regulatory genetic elements and expands the genetic toolbox of C. necatorIMPORTANCE This report provides tools for robust and predictable control of gene expression in the model lithoautotroph C. necator H16. To address a current need, we designed, built, and tested promoters and RBSs for controlling gene expression in C. necator H16. To answer a question on how existing and newly developed inducible systems compare, two positively (AraC/P araBAD -l-arabinose and RhaRS/P rhaBAD -l-rhamnose) and two negatively (AcuR/P acuRI -acrylate and CymR/P cmt -cumate) regulated inducible systems were quantitatively evaluated and their induction kinetics analyzed. To establish if gene expression can be further improved, the effect of genetic elements, such as mRNA stem-loop structure and A/U-rich sequence, on gene expression was evaluated. Using isoprene production as an example, the study investigated if and to what extent chemical compound yield correlates to the level of gene expression of product-synthesizing enzyme.

Metabolic engineering of Clostridium autoethanogenum for selective alcohol production.

Gas fermentation using acetogenic bacteria such as Clostridium autoethanogenum offers an attractive route for production of fuel ethanol from industrial waste gases. Acetate reduction to acetaldehyde and further to ethanol via an aldehyde: ferredoxin oxidoreductase (AOR) and alcohol dehydrogenase has been postulated alongside the classic pathway of ethanol formation via a bi-functional aldehyde/alcohol dehydrogenase (AdhE). Here we demonstrate that AOR is critical to ethanol formation in acetogens and inactivation of AdhE led to consistently enhanced autotrophic ethanol production (up to 180%). Using ClosTron and allelic exchange mutagenesis, which was demonstrated for the first time in an acetogen, we generated single mutants as well as double mutants for both aor and adhE isoforms to confirm the role of each gene. The aor1+2 double knockout strain lost the ability to convert exogenous acetate, propionate and butyrate into the corresponding alcohols, further highlighting the role of these enzymes in catalyzing the thermodynamically unfavourable reduction of carboxylic acids into alcohols.

Mathematical modelling of clostridial acetone-butanol-ethanol fermentation.

Clostridial acetone-butanol-ethanol (ABE) fermentation features a remarkable shift in the cellular metabolic activity from acid formation, acidogenesis, to the production of industrial-relevant solvents, solventogensis. In recent decades, mathematical models have been employed to elucidate the complex interlinked regulation and conditions that determine these two distinct metabolic states and govern the transition between them. In this review, we discuss these models with a focus on the mechanisms controlling intra- and extracellular changes between acidogenesis and solventogenesis. In particular, we critically evaluate underlying model assumptions and predictions in the light of current experimental knowledge. Towards this end, we briefly introduce key ideas and assumptions applied in the discussed modelling approaches, but waive a comprehensive mathematical presentation. We distinguish between structural and dynamical models, which will be discussed in their chronological order to illustrate how new biological information facilitates the 'evolution' of mathematical models. Mathematical models and their analysis have significantly contributed to our knowledge of ABE fermentation and the underlying regulatory network which spans all levels of biological organization. However, the ties between the different levels of cellular regulation are not well understood. Furthermore, contradictory experimental and theoretical results challenge our current notion of ABE metabolic network structure. Thus, clostridial ABE fermentation still poses theoretical as well as experimental challenges which are best approached in close collaboration between modellers and experimentalists.

A genetic assay for gene essentiality in Clostridium.

Essential genes of pathogens are potential therapeutic targets, but are difficult to verify. Here, gene essentiality was determined by targeted knockout following engineered gene duplication. Null mutants of candidate essential genes of Clostridium difficile were viable only in the presence of a stable second copy of the gene.

Whole genome sequence and manual annotation of Clostridium autoethanogenum, an industrially relevant bacterium.

BACKGROUND: Clostridium autoethanogenum is an acetogenic bacterium capable of producing high value commodity chemicals and biofuels from the C1 gases present in synthesis gas. This common industrial waste gas can act as the sole energy and carbon source for the bacterium that converts the low value gaseous components into cellular building blocks and industrially relevant products via the action of the reductive acetyl-CoA (Wood-Ljungdahl) pathway. Current research efforts are focused on the enhancement and extension of product formation in this organism via synthetic biology approaches. However, crucial to metabolic modelling and directed pathway engineering is a reliable and comprehensively annotated genome sequence. RESULTS: We performed next generation sequencing using Illumina MiSeq technology on the DSM10061 strain of Clostridium autoethanogenum and observed 243 single nucleotide discrepancies when compared to the published finished sequence (NCBI: GCA_000484505.1), with 59.1 % present in coding regions. These variations were confirmed by Sanger sequencing and subsequent analysis suggested that the discrepancies were sequencing errors in the published genome not true single nucleotide polymorphisms. This was corroborated by the observation that over 90 % occurred within homopolymer regions of greater than 4 nucleotides in length. It was also observed that many genes containing these sequencing errors were annotated in the published closed genome as encoding proteins containing frameshift mutations (18 instances) or were annotated despite the coding frame containing stop codons, which if genuine, would severely hinder the organism's ability to survive. Furthermore, we have completed a comprehensive manual curation to reduce errors in the annotation that occur through serial use of automated annotation pipelines in related species. As a result, different functions were assigned to gene products or previous functional annotations rejected because of missing evidence in various occasions. CONCLUSIONS: We present a revised manually curated full genome sequence for Clostridium autoethanogenum DSM10061, which provides reliable information for genome-scale models that rely heavily on the accuracy of annotation, and represents an important step towards the manipulation and metabolic modelling of this industrially relevant acetogen.

Glutamate enrichment as new diagnostic opportunity in breast cancer.

Exogenous glutamine is an important source of energy and molecular building blocks for many tumors. There is a renewed interest in therapeutically targeting glutamine metabolism due to the recent discovery of two novel glutaminase inhibitors. To quantify the dysregulation of the glutamate-glutamine equilibrium in breast cancer, metabolomics analysis of 270 clinical breast cancer samples and 97 normal breast samples was carried out using gas chromatography combined with time-of-flight mass spectrometry. Positive correlation between glutamate and glutamine in normal breast tissues switched to negative correlation between glutamate and glutamine in breast cancer tissues. Compared with the ratio of glutamate to glutamine in normal tissues, we found 56% of the ER+ tumor tissues and 88% of the ER- tumor tissues glutamate-enriched. The glutamate-to-glutamine ratio (GGR) significantly correlated with ER status (p = 8.0E-09) and with tumor grade (p = 3.3E-05). Higher levels of GGR were associated with prolonged overall survival in univariate analysis (HR = 0.77, p = 0.027) and in multivariate analysis (HR = 0.73, p = 0.038). GGR levels were reflected in an unsupervised clustering of metabolomics profiles. In a supervised analysis of metabolomics data and of genome-wide expression data, replacement of GGR by metabolite surrogate markers was feasible, while replacement of GGR by RNA markers had a limited accuracy. Functional analysis of the gene expression data showed negative correlation between glutamate enrichment and activation of peroxisome proliferator-activated receptor (PPAR) pathway. Our findings may have important implications for patient stratification related to utilization of glutaminase inhibitors.

Bacteria-instructed synthesis of polymers for self-selective microbial binding and labelling.

The detection and inactivation of pathogenic strains of bacteria continues to be an important therapeutic goal. Hence, there is a need for materials that can bind selectively to specific microorganisms for diagnostic or anti-infective applications, but that can be formed from simple and inexpensive building blocks. Here, we exploit bacterial redox systems to induce a copper-mediated radical polymerization of synthetic monomers at cell surfaces, generating polymers in situ that bind strongly to the microorganisms that produced them. This 'bacteria-instructed synthesis' can be carried out with a variety of microbial strains, and we show that the polymers produced are self-selective binding agents for the 'instructing' cell types. We further expand on the bacterial redox chemistries to 'click' fluorescent reporters onto polymers directly at the surfaces of a range of clinical isolate strains, allowing rapid, facile and simultaneous binding and visualization of pathogens.