Conversion of Escherichia coli to Generate All Biomass Carbon from CO2.

The living world is largely divided into autotrophs that convert CO2 into biomass and heterotrophs that consume organic compounds. In spite of widespread interest in renewable energy storage and more sustainable food production, the engineering of industrially relevant heterotrophic model organisms to use CO2 as their sole carbon source has so far remained an outstanding challenge. Here, we report the achievement of this transformation on laboratory timescales. We constructed and evolved Escherichia coli to produce all its biomass carbon from CO2. Reducing power and energy, but not carbon, are supplied via the one-carbon molecule formate, which can be produced electrochemically. Rubisco and phosphoribulokinase were co-expressed with formate dehydrogenase to enable CO2 fixation and reduction via the Calvin-Benson-Bassham cycle. Autotrophic growth was achieved following several months of continuous laboratory evolution in a chemostat under intensifying organic carbon limitation and confirmed via isotopic labeling.

Sugar Synthesis from CO2 in Escherichia coli.

Can a heterotrophic organism be evolved to synthesize biomass from CO2 directly? So far, non-native carbon fixation in which biomass precursors are synthesized solely from CO2 has remained an elusive grand challenge. Here, we demonstrate how a combination of rational metabolic rewiring, recombinant expression, and laboratory evolution has led to the biosynthesis of sugars and other major biomass constituents by a fully functional Calvin-Benson-Bassham (CBB) cycle in E. coli. In the evolved bacteria, carbon fixation is performed via a non-native CBB cycle, while reducing power and energy are obtained by oxidizing a supplied organic compound (e.g., pyruvate). Genome sequencing reveals that mutations in flux branchpoints, connecting the non-native CBB cycle to biosynthetic pathways, are essential for this phenotype. The successful evolution of a non-native carbon fixation pathway, though not yet resulting in net carbon gain, strikingly demonstrates the capacity for rapid trophic-mode evolution of metabolism applicable to biotechnology. PAPERCLIP.

Evolthon: A community endeavor to evolve lab evolution.

In experimental evolution, scientists evolve organisms in the lab, typically by challenging them to new environmental conditions. How best to evolve a desired trait? Should the challenge be applied abruptly, gradually, periodically, sporadically? Should one apply chemical mutagenesis, and do strains with high innate mutation rate evolve faster? What are ideal population sizes of evolving populations? There are endless strategies, beyond those that can be exposed by individual labs. We therefore arranged a community challenge, Evolthon, in which students and scientists from different labs were asked to evolve Escherichia coli or Saccharomyces cerevisiae for an abiotic stress-low temperature. About 30 participants from around the world explored diverse environmental and genetic regimes of evolution. After a period of evolution in each lab, all strains of each species were competed with one another. In yeast, the most successful strategies were those that used mating, underscoring the importance of sex in evolution. In bacteria, the fittest strain used a strategy based on exploration of different mutation rates. Different strategies displayed variable levels of performance and stability across additional challenges and conditions. This study therefore uncovers principles of effective experimental evolutionary regimens and might prove useful also for biotechnological developments of new strains and for understanding natural strategies in evolutionary arms races between species. Evolthon constitutes a model for community-based scientific exploration that encourages creativity and cooperation.

Realistic head-shaped phantom with brain-mimicking metabolites for 7 T spectroscopy and spectroscopic imaging.

PURPOSE: Moving to ultra-high fields (≥7 T), the inhomogeneity of both RF (B1 ) and static (B0 ) magnetic fields increases, which further motivates us to design a realistic head-shaped phantom, especially for spectroscopic imaging. Such phantoms provide images similar to the human brain and serve as a reliable tool for developing and examining methods in MRI. This study aims to develop and characterize a realistic head-shaped phantom filled with brain-mimicking metabolites for MRS and magnetic resonance spectroscopic imaging in a 7 T MRI scanner. METHODS: A 3D head-shaped container with three sections-mimicking brain, muscle and precranial lipid-was constructed. The phantom was designed to provide robustness to heating, mechanical damage and leakage, with easy refilling. The head's shape and the agarose mixture were optimized to provide B0 and B1 distributions and T1 /T2 relaxation values similar to those of human brain. Eight brain-tissue-mimicking metabolites were included for spectroscopy. The phantom was evaluated for localized spectroscopy, fast spectroscopic imaging and fat suppression. RESULTS: The B0 and B1 maps showed distribution similar to that of human brain, with increased B0 inhomogeneity near the nasal and ear areas and reduced B1 in the temporal lobe and brain stem regions, as expected in vivo. The metabolites' concentrations were verified by single-voxel spectroscopy, showing an average deviation of 11%. Fast spectroscopic imaging and imaging with fat suppression were demonstrated. CONCLUSION: A 3D head-shaped phantom for human brain imaging and spectroscopic imaging in 7 T MRI was demonstrated, making it a realistic phantom for methodology development at 7 T.

Noise in gene expression is coupled to growth rate.

Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications.

Heterosis as a consequence of regulatory incompatibility.

BACKGROUND: The merging of genomes in inter-specific hybrids can result in novel phenotypes, including increased growth rate and biomass yield, a phenomenon known as heterosis. Heterosis is typically viewed as the opposite of hybrid incompatibility. In this view, the superior performance of the hybrid is attributed to heterozygote combinations that compensate for deleterious mutations accumulating in each individual genome, or lead to new, over-dominating interactions with improved performance. Still, only fragmented knowledge is available on genes and processes contributing to heterosis. RESULTS: We describe a budding yeast hybrid that grows faster than both its parents under different environments. Phenotypically, the hybrid progresses more rapidly through cell cycle checkpoints, relieves the repression of respiration in fast growing conditions, does not slow down its growth when presented with ethanol stress, and shows increased signs of DNA damage. A systematic genetic screen identified hundreds of S. cerevisiae alleles whose deletion reduced growth of the hybrid. These growth-affecting alleles were condition-dependent, and differed greatly from alleles that reduced the growth of the S. cerevisiae parent. CONCLUSIONS: Our results define a budding yeast hybrid that is perturbed in multiple regulatory processes but still shows a clear growth heterosis. We propose that heterosis results from incompatibilities that perturb regulatory mechanisms, which evolved to protect cells against damage or prepare them for future challenges by limiting cell growth.

Following Metabolism in Living Microorganisms by Hyperpolarized (1)H NMR.

Dissolution dynamic nuclear polarization (dDNP) is used to enhance the sensitivity of nuclear magnetic resonance (NMR), enabling monitoring of metabolism and specific enzymatic reactions in vivo. dDNP involves rapid sample dissolution and transfer to a spectrometer/scanner for subsequent signal detection. So far, most biologically oriented dDNP studies have relied on hyperpolarizing long-lived nuclear spin species such as (13)C in small molecules. While advantages could also arise from observing hyperpolarized (1)H, short relaxation times limit the utility of prepolarizing this sensitive but fast relaxing nucleus. Recently, it has been reported that (1)H NMR peaks in solution-phase experiments could be hyperpolarized by spontaneous magnetization transfers from bound (13)C nuclei following dDNP. This work demonstrates the potential of this sensitivity-enhancing approach to probe the enzymatic process that could not be suitably resolved by (13)C dDNP MR. Here we measured, in microorganisms, the action of pyruvate decarboxylase (PDC) and pyruvate formate lyase (PFL)-enzymes that catalyze the decarboxylation of pyruvate to form acetaldehyde and formate, respectively. While (13)C NMR did not possess the resolution to distinguish the starting pyruvate precursor from the carbonyl resonances in the resulting products, these processes could be monitored by (1)H NMR at 500 MHz. These observations were possible in both yeast and bacteria in minute-long kinetic measurements where the hyperpolarized (13)C enhanced, via (13)C → (1)H cross-relaxation, the signals of protons binding to the (13)C over the course of enzymatic reactions. In addition to these spontaneous heteronuclear enhancement experiments, single-shot acquisitions based on J-driven (13)C → (1)H polarization transfers were also carried out. These resulted in higher signal enhancements of the (1)H resonances but were not suitable for multishot kinetic studies. The potential of these (1)H-based approaches for measurements in vivo is briefly discussed.

Combined Treatment of an Amyotrophic Lateral Sclerosis Rat Model with Recombinant GOT1 and Oxaloacetic Acid: A Novel Neuroprotective Treatment.

BACKGROUND/AIM: The sporadic form of the disease affects the majority of amyotrophic lateral sclerosis (ALS) patients. The role of glutamate (Glu) excitotoxicity in ALS has been extensively documented and remains one of the prominent hypotheses of ALS pathogenesis. In light of this evidence, the availability of a method to remove excess Glu from brain and spinal cord extracellular fluids without the need to deliver drugs across the blood-brain barrier and with minimal or no adverse effects may provide a major therapeutic asset, which is the primary aim of this study. METHODS: The therapeutic efficacy of the combined treatment with recombinant Glu-oxaloacetate-transaminase (rGOT) and its co-factor oxaloacetic acid (OxAc) has been tested in an animal model of sporadic ALS. RESULTS: We found that OxAc/rGOT treatment provides significant neuroprotection to spinal cord motor neurons. It also slows down the development of motor weakness and prolongs survival. CONCLUSION: In this study we bring evidence that the administration of Glu scavengers to rats with sporadic ALS inhibited the massive death of spinal cord motor neurons, slowed the onset of motor weakness and prolonged survival. This treatment may be of high clinical significance for the future treatment of chronic neurodegenerative diseases.

Autotrophic growth of Escherichia coli is achieved by a small number of genetic changes.

Synthetic autotrophy is a promising avenue to sustainable bioproduction from CO2. Here, we use iterative laboratory evolution to generate several distinct autotrophic strains. Utilising this genetic diversity, we identify that just three mutations are sufficient for Escherichia coli to grow autotrophically, when introduced alongside non-native energy (formate dehydrogenase) and carbon-fixing (RuBisCO, phosphoribulokinase, carbonic anhydrase) modules. The mutated genes are involved in glycolysis (pgi), central-carbon regulation (crp), and RNA transcription (rpoB). The pgi mutation reduces the enzyme's activity, thereby stabilising the carbon-fixing cycle by capping a major branching flux. For the other two mutations, we observe down-regulation of several metabolic pathways and increased expression of native genes associated with the carbon-fixing module (rpiB) and the energy module (fdoGH), as well as an increased ratio of NADH/NAD+ - the cycle's electron-donor. This study demonstrates the malleability of metabolism and its capacity to switch trophic modes using only a small number of genetic changes and could facilitate transforming other heterotrophic organisms into autotrophs.

Competitive fungal commensalism mitigates candidiasis pathology.

The mycobiota are a critical part of the gut microbiome, but host-fungal interactions and specific functional contributions of commensal fungi to host fitness remain incompletely understood. Here, we report the identification of a new fungal commensal, Kazachstania heterogenica var. weizmannii, isolated from murine intestines. K. weizmannii exposure prevented Candida albicans colonization and significantly reduced the commensal C. albicans burden in colonized animals. Following immunosuppression of C. albicans colonized mice, competitive fungal commensalism thereby mitigated fatal candidiasis. Metagenome analysis revealed K. heterogenica or K. weizmannii presence among human commensals. Our results reveal competitive fungal commensalism within the intestinal microbiota, independent of bacteria and immune responses, that could bear potential therapeutic value for the management of C. albicans-mediated diseases.

Host gene targets for novel influenza therapies elucidated by high-throughput RNA interference screens.

Influenza virus encodes only 11 viral proteins but replicates in a broad range of avian and mammalian species by exploiting host cell functions. Genome-wide RNA interference (RNAi) has proven to be a powerful tool for identifying the host molecules that participate in each step of virus replication. Meta-analysis of findings from genome-wide RNAi screens has shown influenza virus to be dependent on functional nodes in host cell pathways, requiring a wide variety of molecules and cellular proteins for replication. Because rapid evolution of the influenza A viruses persistently complicates the effectiveness of vaccines and therapeutics, a further understanding of the complex host cell pathways coopted by influenza virus for replication may provide new targets and strategies for antiviral therapy. RNAi genome screening technologies together with bioinformatics can provide the ability to rapidly identify specific host factors involved in resistance and susceptibility to influenza virus, allowing for novel disease intervention strategies.

Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays.

We developed a new DNA microarray-based technology, called protein binding microarrays (PBMs), that allows rapid, high-throughput characterization of the in vitro DNA binding-site sequence specificities of transcription factors in a single day. Using PBMs, we identified the DNA binding-site sequence specificities of the yeast transcription factors Abf1, Rap1 and Mig1. Comparison of these proteins' in vitro binding sites with their in vivo binding sites indicates that PBM-derived sequence specificities can accurately reflect in vivo DNA sequence specificities. In addition to previously identified targets, Abf1, Rap1 and Mig1 bound to 107, 90 and 75 putative new target intergenic regions, respectively, many of which were upstream of previously uncharacterized open reading frames. Comparative sequence analysis indicated that many of these newly identified sites are highly conserved across five sequenced sensu stricto yeast species and, therefore, are probably functional in vivo binding sites that may be used in a condition-specific manner. Similar PBM experiments should be useful in identifying new cis regulatory elements and transcriptional regulatory networks in various genomes.

gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution.

Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones' relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system's application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.

Global analysis of protein phosphorylation in yeast.

Protein phosphorylation is estimated to affect 30% of the proteome and is a major regulatory mechanism that controls many basic cellular processes. Until recently, our biochemical understanding of protein phosphorylation on a global scale has been extremely limited; only one half of the yeast kinases have known in vivo substrates and the phosphorylating kinase is known for less than 160 phosphoproteins. Here we describe, with the use of proteome chip technology, the in vitro substrates recognized by most yeast protein kinases: we identified over 4,000 phosphorylation events involving 1,325 different proteins. These substrates represent a broad spectrum of different biochemical functions and cellular roles. Distinct sets of substrates were recognized by each protein kinase, including closely related kinases of the protein kinase A family and four cyclin-dependent kinases that vary only in their cyclin subunits. Although many substrates reside in the same cellular compartment or belong to the same functional category as their phosphorylating kinase, many others do not, indicating possible new roles for several kinases. Furthermore, integration of the phosphorylation results with protein-protein interaction and transcription factor binding data revealed novel regulatory modules. Our phosphorylation results have been assembled into a first-generation phosphorylation map for yeast. Because many yeast proteins and pathways are conserved, these results will provide insights into the mechanisms and roles of protein phosphorylation in many eukaryotes.

Blood Glutamate Scavenger as a Novel Neuroprotective Treatment in Spinal Cord Injury.

Neurotrauma causes immediate elevation of extracellular glutamate (Glu) levels, which creates excitotoxicity and facilitates inflammation, glial scar formation, and consequently neuronal death. Finding factors that reduce the inflammatory response and glial scar formation, and increase neuronal survival and neurite outgrowth, are of major importance for improving the outcome after spinal cord injury (SCI). In the present study, we evaluated a new treatment aiming to remove central nervous system (CNS) Glu into the systemic blood circulation by intravenous (IV) administration of blood Glu scavengers (BGS) such as the enzyme recombinant glutamate-oxaloacetate transaminase 1 (rGOT1) and its co-substrate. In this study we induced in mice an SCI (hemisection), and 1 h post-injury started administering BGS treatment for 5 consecutive days. The treatment reduced the expression levels of p-p38, which regulates apoptosis and increased the expression of p-Akt, which mediates cell survival. Moreover, this treatment decreased pro-inflammatory cytokine expression and microglia activation, reduced astrocytes' reactivity, and facilitated expression of radial glia markers such as Pax6 and nestin. BGS treatment increased the survival of neurons at lesion site and enabled axonal regeneration into the injury site. These effects were correlated with improved functional recovery of the left paretic hindlimb. Thus, early pharmacological intervention with BGS following SCI may be neuroprotective and create a pro-regenerative environment by modulating glia cell response. In light of our results, the availability of the method to remove excess Glu from CNS without the need to deliver drugs across the blood-brain barrier (BBB) and with minimal or no adverse effects may provide a major therapeutic asset.

A Bacterial Growth Law out of Steady State.

Bacterial growth follows simple laws in constant conditions. However, bacteria in nature often face fluctuating environments. We therefore ask whether there are growth laws that apply to changing environments. We derive a law for upshifts using an optimal resource-allocation model: the post-shift growth rate equals the geometrical mean of the pre-shift growth rate and the growth rate on saturating carbon. We test this using chemostat and batch culture experiments, as well as previous data from several species. The increase in growth rate after an upshift indicates that ribosomes have spare capacity (SC). We demonstrate theoretically that SC has the cost of slow steady-state growth but is beneficial after an upshift because it prevents large overshoots in intracellular metabolites and allows rapid response to change. We also provide predictions for downshifts. The present study quantifies the optimal degree of SC, which rises the slower the growth rate, and suggests that SC can be precisely regulated.

The Cost of Protein Production.

The economy of protein production is central to cell physiology, being intimately linked with cell division rate and cell size. Attempts to model cellular physiology are limited by the scarcity of experimental data defining the molecular processes limiting protein expression. Here, we distinguish the relative contribution of gene transcription and protein translation to the slower proliferation of budding yeast producing excess levels of unneeded proteins. In contrast to widely held assumptions, rapidly growing cells are not universally limited by ribosome content. Rather, transcription dominates cost under some conditions (e.g., low phosphate), translation in others (e.g., low nitrogen), and both in other conditions (e.g., rich media). Furthermore, cells adapted to enforced protein production by becoming larger and increasing their endogenous protein levels, suggesting limited competition for common resources. We propose that rapidly growing cells do not exhaust their resources to maximize growth but maintain sufficient reserves to accommodate changing requirements.

Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools.

One of the key applications of next-generation sequencing (NGS) technologies is RNA-Seq for transcriptome genome-wide analysis. Although multiple studies have evaluated and benchmarked RNA-Seq tools dedicated to gene level analysis, few studies have assessed their effectiveness on the transcript-isoform level. Alternative splicing is a naturally occurring phenomenon in eukaryotes, significantly increasing the biodiversity of proteins that can be encoded by the genome. The aim of this study was to assess and compare the ability of the bioinformatics approaches and tools to assemble, quantify and detect differentially expressed transcripts using RNA-Seq data, in a controlled experiment. To this end, in vitro synthesized mouse spike-in control transcripts were added to the total RNA of differentiating mouse embryonic bodies, and their expression patterns were measured. This novel approach was used to assess the accuracy of the tools, as established by comparing the observed results versus the results expected of the mouse controlled spiked-in transcripts. We found that detection of differential expression at the gene level is adequate, yet on the transcript-isoform level, all tools tested lacked accuracy and precision.

Global analysis of protein function using protein microarrays.

Protein microarrays containing thousands of proteins arrayed at high density can be prepared and probed for a wide variety of activities, thereby allowing the large scale analysis of many proteins simultaneously. In addition to identifying the activities of many previously uncharacterized proteins, protein microarrays can reveal new activities of well-characterized proteins, thus providing new insights about the functions of these proteins. Below, we describe the construction and use of protein microarrays and their applications using yeast as a model system.

Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples.

Metagenomic sequencing increased our understanding of the role of the microbiome in health and disease, yet it only provides a snapshot of a highly dynamic ecosystem. Here, we show that the pattern of metagenomic sequencing read coverage for different microbial genomes contains a single trough and a single peak, the latter coinciding with the bacterial origin of replication. Furthermore, the ratio of sequencing coverage between the peak and trough provides a quantitative measure of a species' growth rate. We demonstrate this in vitro and in vivo, under different growth conditions, and in complex bacterial communities. For several bacterial species, peak-to-trough coverage ratios, but not relative abundances, correlated with the manifestation of inflammatory bowel disease and type II diabetes.