LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae.

Temperature is an important control factor for biologics biomanufacturing in precision fermentation. Here, we explored a highly responsive low temperature-inducible genetic system (LowTempGAL) in the model yeast Saccharomyces cerevisiae. Two temperature biosensors, a heat-inducible degron and a heat-inducible protein aggregation domain, were used to regulate the GAL activator Gal4p, rendering the leaky LowTempGAL systems. Boolean-type induction was achieved by implementing a second-layer control through low-temperature-mediated repression on GAL repressor gene GAL80, but suffered delayed response to low-temperature triggers and a weak response at 30°C. Application potentials were validated for protein and small molecule production. Proteomics analysis suggested that residual Gal80p and Gal4p insufficiency caused suboptimal induction. 'Turbo' mechanisms were engineered through incorporating a basal Gal4p expression and a galactose-independent Gal80p-supressing Gal3p mutant (Gal3Cp). Varying Gal3Cp configurations, we deployed the LowTempGAL systems capable for a rapid stringent high-level induction upon the shift from a high temperature (37-33°C) to a low temperature (≤30°C). Overall, we present a synthetic biology procedure that leverages 'leaky' biosensors to deploy highly responsive Boolean-type genetic circuits. The key lies in optimisation of the intricate layout of the multi-factor system. The LowTempGAL systems may be applicable in non-conventional yeast platforms for precision biomanufacturing.

Comparative constraint-based modelling of fruit development across species highlights nitrogen metabolism in the growth-defence trade-off.

Although primary metabolism is well conserved across species, it is useful to explore the specificity of its network to assess the extent to which some pathways may contribute to particular outcomes. Constraint-based metabolic modelling is an established framework for predicting metabolic fluxes and phenotypes and helps to explore how the plant metabolic network delivers specific outcomes from temporal series. After describing the main physiological traits during fruit development, we confirmed the correlations between fruit relative growth rate (RGR), protein content and time to maturity. Then a constraint-based method is applied to a panel of eight fruit species with a knowledge-based metabolic model of heterotrophic cells describing a generic metabolic network of primary metabolism. The metabolic fluxes are estimated by constraining the model using a large set of metabolites and compounds quantified throughout fruit development. Multivariate analyses showed a clear common pattern of flux distribution during fruit development with differences between fast- and slow-growing fruits. Only the latter fruits mobilise the tricarboxylic acid cycle in addition to glycolysis, leading to a higher rate of respiration. More surprisingly, to balance nitrogen, the model suggests, on the one hand, nitrogen uptake by nitrate reductase to support a high RGR at early stages of cucumber and, on the other hand, the accumulation of alkaloids during ripening of pepper and eggplant. Finally, building virtual fruits by combining 12 biomass compounds shows that the growth-defence trade-off is supported mainly by cell wall synthesis for fast-growing fruits and by total polyphenols accumulation for slow-growing fruits.

Deleterious variants in CRLS1 lead to cardiolipin deficiency and cause an autosomal recessive multi-system mitochondrial disease.

Mitochondrial diseases are a group of inherited diseases with highly varied and complex clinical presentations. Here, we report four individuals, including two siblings, affected by a progressive mitochondrial encephalopathy with biallelic variants in the cardiolipin biosynthesis gene CRLS1. Three affected individuals had a similar infantile presentation comprising progressive encephalopathy, bull's eye maculopathy, auditory neuropathy, diabetes insipidus, autonomic instability, cardiac defects and early death. The fourth affected individual presented with chronic encephalopathy with neurodevelopmental regression, congenital nystagmus with decreased vision, sensorineural hearing loss, failure to thrive and acquired microcephaly. Using patient-derived fibroblasts, we characterized cardiolipin synthase 1 (CRLS1) dysfunction that impaired mitochondrial morphology and biogenesis, providing functional evidence that the CRLS1 variants cause mitochondrial disease. Lipid profiling in fibroblasts from two patients further confirmed the functional defect demonstrating reduced cardiolipin levels, altered acyl-chain composition and significantly increased levels of phosphatidylglycerol, the substrate of CRLS1. Proteomic profiling of patient cells and mouse Crls1 knockout cell lines identified both endoplasmic reticular and mitochondrial stress responses, and key features that distinguish between varying degrees of cardiolipin insufficiency. These findings support that deleterious variants in CRLS1 cause an autosomal recessive mitochondrial disease, presenting as a severe encephalopathy with multi-systemic involvement. Furthermore, we identify key signatures in cardiolipin and proteome profiles across various degrees of cardiolipin loss, facilitating the use of omics technologies to guide future diagnosis of mitochondrial diseases.

multiTFA: a Python package for multi-variate thermodynamics-based flux analysis.

MOTIVATION: We achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly reduces the uncertainty of thermodynamic variables. RESULTS: We present multiTFA, a Python implementation of our framework. We evaluated our application using the core Escherichia coli model and achieved a median reduction of 6.8 kJ/mol in reaction Gibbs free energy ranges, while three out of 12 reactions in glycolysis changed from reversible to irreversible. AVAILABILITY AND IMPLEMENTATION: Our framework along with documentation is available on https://github.com/biosustain/multitfa. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Awakening sleeping beauty: production of propionic acid in Escherichia coli through the sbm operon requires the activity of a methylmalonyl-CoA epimerase.

BACKGROUND: Propionic acid is used primarily as a food preservative with smaller applications as a chemical building block for the production of many products including fabrics, cosmetics, drugs, and plastics. Biological production using propionibacteria would be competitive against chemical production through hydrocarboxylation of ethylene if native producers could be engineered to reach near-theoretical yield and good productivity. Unfortunately, engineering propionibacteria has proven very challenging. It has been suggested that activation of the sleeping beauty operon in Escherichia coli is sufficient to achieve propionic acid production. Optimising E. coli production should be much easier than engineering propionibacteria if tolerance issues can be addressed. RESULTS: Propionic acid is produced in E. coli via the sleeping beauty mutase operon under anaerobic conditions in rich medium via amino acid degradation. We observed that the sbm operon enhances amino acids degradation to propionic acid and allows E. coli to degrade isoleucine. However, we show here that the operon lacks an epimerase reaction that enables propionic acid production in minimal medium containing glucose as the sole carbon source. Production from glucose can be restored by engineering the system with a methylmalonyl-CoA epimerase from Propionibacterium acidipropionici (0.23 ± 0.02 mM). 1-Propanol production was also detected from the promiscuous activity of the native alcohol dehydrogenase (AdhE). We also show that aerobic conditions are favourable for propionic acid production. Finally, we increase titre 65 times using a combination of promoter engineering and process optimisation. CONCLUSIONS: The native sbm operon encodes an incomplete pathway. Production of propionic acid from glucose as sole carbon source is possible when the pathway is complemented with a methylmalonyl-CoA epimerase. Although propionic acid via the restored succinate dissimilation pathway is considered a fermentative process, the engineered pathway was shown to be functional under anaerobic and aerobic conditions.

Adaptive laboratory evolution of Clostridium autoethanogenum to metabolize CO2 and H2 enhances growth rates in chemostat and unravels proteome and metabolome alterations.

Gas fermentation of CO2 and H2 is an attractive means to sustainably produce fuels and chemicals. Clostridium autoethanogenum is a model organism for industrial CO to ethanol and presents an opportunity for CO2-to-ethanol processes. As we have previously characterized its CO2/H2 chemostat growth, here we use adaptive laboratory evolution (ALE) with the aim of improving growth with CO2/H2. Seven ALE lineages were generated, all with improved specific growth rates. ALE conducted in the presence of 2% CO along with CO2/H2 generated Evolved lineage D, which showed the highest ethanol titres amongst all the ALE lineages during the fermentation of CO2/H2. Chemostat comparison against the parental strain shows no change in acetate or ethanol production, while Evolved D could achieve a higher maximum dilution rate. Multi-omics analyses at steady state revealed that Evolved D has widespread proteome and intracellular metabolome changes. However, the uptake and production rates and titres remain unaltered until investigating their maximum dilution rate. Yet, we provide numerous insights into CO2/H2 metabolism via these multi-omics data and link these results to mutations, suggesting novel targets for metabolic engineering in this bacterium.

A universal molecular control for DNA, mRNA and protein expression.

The expression of genes encompasses their transcription into mRNA followed by translation into protein. In recent years, next-generation sequencing and mass spectrometry methods have profiled DNA, RNA and protein abundance in cells. However, there are currently no reference standards that are compatible across these genomic, transcriptomic and proteomic methods, and provide an integrated measure of gene expression. Here, we use synthetic biology principles to engineer a multi-omics control, termed pREF, that can act as a universal molecular standard for next-generation sequencing and mass spectrometry methods. The pREF sequence encodes 21 synthetic genes that can be in vitro transcribed into spike-in mRNA controls, and in vitro translated to generate matched protein controls. The synthetic genes provide qualitative controls that can measure sensitivity and quantitative accuracy of DNA, RNA and peptide detection. We demonstrate the use of pREF in metagenome DNA sequencing and RNA sequencing experiments and evaluate the quantification of proteins using mass spectrometry. Unlike previous spike-in controls, pREF can be independently propagated and the synthetic mRNA and protein controls can be sustainably prepared by recipient laboratories using common molecular biology techniques. Together, this provides a universal synthetic standard able to integrate genomic, transcriptomic and proteomic methods.

Quantitative subcellular reconstruction reveals a lipid mediated inter-organelle biogenesis network.

The structures and functions of organelles in cells depend on each other but have not been systematically explored. We established stable knockout cell lines of peroxisomal, Golgi and endoplasmic reticulum genes identified in a whole-genome CRISPR knockout screen for inducers of mitochondrial biogenesis stress, showing that defects in peroxisome, Golgi and endoplasmic reticulum metabolism disrupt mitochondrial structure and function. Our quantitative total-organelle profiling approach for focussed ion beam scanning electron microscopy revealed in unprecedented detail that specific organelle dysfunctions precipitate multi-organelle biogenesis defects, impair mitochondrial morphology and reduce respiration. Multi-omics profiling showed a unified proteome response and global shifts in lipid and glycoprotein homeostasis that are elicited when organelle biogenesis is compromised, and that the resulting mitochondrial dysfunction can be rescued with precursors for ether-glycerophospholipid metabolic pathways. This work defines metabolic and morphological interactions between organelles and how their perturbation can cause disease.

Copy number variation in tRNA isodecoder genes impairs mammalian development and balanced translation.

The number of tRNA isodecoders has increased dramatically in mammals, but the specific molecular and physiological reasons for this expansion remain elusive. To address this fundamental question we used CRISPR editing to knockout the seven-membered phenylalanine tRNA gene family in mice, both individually and combinatorially. Using ATAC-Seq, RNA-seq, ribo-profiling and proteomics we observed distinct molecular consequences of single tRNA deletions. We show that tRNA-Phe-1-1 is required for neuronal function and its loss is partially compensated by increased expression of other tRNAs but results in mistranslation. In contrast, the other tRNA-Phe isodecoder genes buffer the loss of each of the remaining six tRNA-Phe genes. In the tRNA-Phe gene family, the expression of at least six tRNA-Phe alleles is required for embryonic viability and tRNA-Phe-1-1 is most important for development and survival. Our results reveal that the multi-copy configuration of tRNA genes is required to buffer translation and viability in mammals.

An integrated systems biology approach reveals differences in formate metabolism in the genus Methanothermobacter.

Methanogenesis allows methanogenic archaea to generate cellular energy for their growth while producing methane. Thermophilic hydrogenotrophic species of the genus Methanothermobacter have been recognized as robust biocatalysts for a circular carbon economy and are already applied in power-to-gas technology with biomethanation, which is a platform to store renewable energy and utilize captured carbon dioxide. Here, we generated curated genome-scale metabolic reconstructions for three Methanothermobacter strains and investigated differences in the growth performance of these same strains in chemostat bioreactor experiments with hydrogen and carbon dioxide or formate as substrates. Using an integrated systems biology approach, we identified differences in formate anabolism between the strains and revealed that formate anabolism influences the diversion of carbon between biomass and methane. This finding, together with the omics datasets and the metabolic models we generated, can be implemented for biotechnological applications of Methanothermobacter in power-to-gas technology, and as a perspective, for value-added chemical production.

Multi-omic profiling reveals an RNA processing rheostat that predisposes to prostate cancer.

Prostate cancer is the most commonly diagnosed malignancy and the third leading cause of cancer deaths. GWAS have identified variants associated with prostate cancer susceptibility; however, mechanistic and functional validation of these mutations is lacking. We used CRISPR-Cas9 genome editing to introduce a missense variant identified in the ELAC2 gene, which encodes a dually localised nuclear and mitochondrial RNA processing enzyme, into the mouse Elac2 gene as well as to generate a prostate-specific knockout of Elac2. These mutations caused enlargement and inflammation of the prostate and nodule formation. The Elac2 variant or knockout mice on the background of the transgenic adenocarcinoma of the mouse prostate (TRAMP) model show that Elac2 mutation with a secondary genetic insult exacerbated the onset and progression of prostate cancer. Multiomic profiling revealed defects in energy metabolism that activated proinflammatory and tumorigenic pathways as a consequence of impaired noncoding RNA processing and reduced protein synthesis. Our physiologically relevant models show that the ELAC2 variant is a predisposing factor for prostate cancer and identify changes that underlie the pathogenesis of this cancer.

A Genome-Scale Metabolic Model of Methanoperedens nitroreducens: Assessing Bioenergetics and Thermodynamic Feasibility.

Methane is an abundant low-carbon fuel that provides a valuable energy resource, but it is also a potent greenhouse gas. Therefore, anaerobic oxidation of methane (AOM) is an essential process with central features in controlling the carbon cycle. Candidatus 'Methanoperedens nitroreducens' (M. nitroreducens) is a recently discovered methanotrophic archaeon capable of performing AOM via a reverse methanogenesis pathway utilizing nitrate as the terminal electron acceptor. Recently, reverse methanogenic pathways and energy metabolism among anaerobic methane-oxidizing archaea (ANME) have gained significant interest. However, the energetics and the mechanism for electron transport in nitrate-dependent AOM performed by M. nitroreducens is unclear. This paper presents a genome-scale metabolic model of M. nitroreducens, iMN22HE, which contains 813 reactions and 684 metabolites. The model describes its cellular metabolism and can quantitatively predict its growth phenotypes. The essentiality of the cytoplasmic heterodisulfide reductase HdrABC in the reverse methanogenesis pathway is examined by modeling the electron transfer direction and the specific energy-coupling mechanism. Furthermore, based on better understanding electron transport by modeling, a new energy transfer mechanism is suggested. The new mechanism involves reactions capable of driving the endergonic reactions in nitrate-dependent AOM, including the step reactions in reverse canonical methanogenesis and the novel electron-confurcating reaction HdrABC. The genome metabolic model not only provides an in silico tool for understanding the fundamental metabolism of ANME but also helps to better understand the reverse methanogenesis energetics and its thermodynamic feasibility.

A Pan-Genome Guided Metabolic Network Reconstruction of Five Propionibacterium Species Reveals Extensive Metabolic Diversity.

Propionibacteria have been studied extensively since the early 1930s due to their relevance to industry and importance as human pathogens. Still, their unique metabolism is far from fully understood. This is partly due to their signature high GC content, which has previously hampered the acquisition of quality sequence data, the accurate annotation of the available genomes, and the functional characterization of genes. The recent completion of the genome sequences for several species has led researchers to reassess the taxonomical classification of the genus Propionibacterium, which has been divided into several new genres. Such data also enable a comparative genomic approach to annotation and provide a new opportunity to revisit our understanding of their metabolism. Using pan-genome analysis combined with the reconstruction of the first high-quality Propionibacterium genome-scale metabolic model and a pan-metabolic model of current and former members of the genus Propionibacterium, we demonstrate that despite sharing unique metabolic traits, these organisms have an unexpected diversity in central carbon metabolism and a hidden layer of metabolic complexity. This combined approach gave us new insights into the evolution of Propionibacterium metabolism and led us to propose a novel, putative ferredoxin-linked energy conservation strategy. The pan-genomic approach highlighted key differences in Propionibacterium metabolism that reflect adaptation to their environment. Results were mathematically captured in genome-scale metabolic reconstructions that can be used to further explore metabolism using metabolic modeling techniques. Overall, the data provide a platform to explore Propionibacterium metabolism and a tool for the rational design of strains.

Genome-scale model guided design of Propionibacterium for enhanced propionic acid production.

Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs) to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP), Zwf (glucose-6-phosphate 1-dehydrogenase) and Pgl (6-phosphogluconolactonase). Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK) and sodium-pumping methylmalonyl-CoA decarboxylase (MMD) was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in Propionibacterium. We also describe the benefit of carbon dioxide to propionibacteria growth, substrate conversion and propionate yield.