OptSSeq: High-Throughput Sequencing Readout of Growth Enrichment Defines Optimal Gene Expression Elements for Homoethanologenesis

Thermodynamics shape the in vivo enzyme burden of glycolytic pathways

Thermodynamically constrained reactions and pathways are hypothesized to impose greater protein demands on cells, requiring higher enzyme amounts to sustain a given flux compared to those with stronger thermodynamics. To test this, we quantified the absolute concentrations of glycolytic enzymes in three bacterial species - Zymomonas mobilis , Escherichia coli , and Clostridium thermocellum - which employ distinct glycolytic pathways with varying thermodynamic driving forces. By integrating enzyme concentration data with corresponding in vivo metabolic fluxes and ΔG measurements, we found that the highly favorable Entner-Doudoroff (ED) pathway in Z. mobilis requires only one-fourth the amount of enzymatic protein to sustain the same flux as the thermodynamically constrained pyrophosphate-dependent glycolytic pathway in C. thermocellum , with the Embden-Meyerhof-Parnas (EMP) pathway in E. coli exhibiting intermediate thermodynamic favorability and enzyme demand. Across all three pathways, early reactions with stronger thermodynamic driving forces generally required lower enzyme investment than later, less favorable steps. Additionally, reflecting differences in glycolytic strategies, the highly reversible ethanol fermentation pathway in C. thermocellum requires 10-fold more protein to maintain the same flux as the irreversible, forward-driven ethanol fermentation pathway in Z. mobilis . Thus, thermodynamic driving forces constitute a major in vivo determinant of the enzyme burden in metabolic pathways.

Deuterated water as a substrate-agnostic isotope tracer for investigating reversibility and thermodynamics of reactions in central carbon metabolism

Stable isotope tracers are a powerful tool for the quantitative analysis of microbial metabolism, enabling pathway elucidation, metabolic flux quantification, and assessment of reaction and pathway thermodynamics. 13C and 2H metabolic flux analysis commonly relies on isotopically labeled carbon substrates, such as glucose. However, the use of 2H-labeled nutrient substrates faces limitations due to their high cost and limited availability in comparison to 13C-tracers. Furthermore, isotope tracer studies in industrially relevant bacteria that metabolize complex substrates such as cellulose, hemicellulose, or lignocellulosic biomass, are challenging given the difficulty in obtaining these as isotopically labeled substrates. In this study, we examine the potential of deuterated water (2H2O) as an affordable, substrate-neutral isotope tracer for studying central carbon metabolism. We apply 2H2O labeling to investigate the reversibility of glycolytic reactions across three industrially relevant bacterial species -C. thermocellum, Z. mobilis, and E. coli-harboring distinct glycolytic pathways with unique thermodynamics. We demonstrate that 2H2O labeling recapitulates previous reversibility and thermodynamic findings obtained with established 13C and 2H labeled nutrient substrates. Furthermore, we exemplify the utility of this 2H2O labeling approach by applying it to high-substrate C. thermocellum fermentations -a setting in which the use of conventional tracers is impractical-thereby identifying the glycolytic enzyme phosphofructokinase as a major bottleneck during high-substrate fermentations and unveiling critical insights that will steer future engineering efforts to enhance ethanol production in this cellulolytic organism. This study demonstrates the utility of deuterated water as a substrate-agnostic isotope tracer for examining flux and reversibility of central carbon metabolic reactions, which yields biological insights comparable to those obtained using costly 2H-labeled nutrient substrates.

Characterization and Amelioration of Filtration Difficulties Encountered in Metabolomic Studies of Clostridium thermocellum at Elevated Sugar Concentrations

Clostridium thermocellum, a promising candidate for consolidated bioprocessing, has been subjected to numerous engineering strategies for enhanced bioethanol production. Measurements of intracellular metabolites at substrate concentrations high enough (>50 g/L) to allow the production of industrially relevant titers of ethanol would inform efforts toward this end but have been difficult due to the production of a viscous substance that interferes with the filtration and quenching steps during metabolite extraction. To determine whether this problem is unique to C. thermocellum, we performed filtration experiments with other organisms that have been engineered for high-titer ethanol production, including Escherichia coli and Thermoanaerobacterium saccharolyticum. We addressed the problem through a series of improvements, including active pH control (to reduce problems with viscosity), investigation of different filter materials and pore sizes (to increase the filtration capacity), and correction for extracellular metabolite concentrations, and we developed a technique for more accurate intracellular metabolite measurements at elevated substrate concentrations. IMPORTANCE The accurate measurement of intracellular metabolites (metabolomics) is an integral part of metabolic engineering for the enhanced production of industrially important compounds and a useful technique to understand microbial physiology. Previous work tended to focus on model organisms under laboratory conditions. As we try to perform metabolomic studies with a wider range of organisms under conditions that more closely represent those found in nature or industry, we have found limitations in existing techniques. For example, fast filtration is an important step in quenching metabolism in preparation for metabolite extraction; however, it does not work for cultures of C. thermocellum at high substrate concentrations. In this work, we characterize the extent of the problem and develop techniques to overcome it.

Escherichia coli Leucine-Responsive Regulatory Protein Bridges DNA In Vivo and Tunably Dissociates in the Presence of Exogenous Leucine

Feast-famine response proteins are a widely conserved class of global regulators in prokaryotes, the most highly studied of which is the Escherichia coli leucine-responsive regulatory protein (Lrp). Lrp senses the environmental nutrition status and subsequently regulates up to one-third of the genes in E. coli, either directly or indirectly. Lrp exists predominantly as octamers and hexadecamers (16mers), where leucine is believed to shift the equilibrium toward the octameric state. In this study, we analyzed the effects of three oligomerization state mutants of Lrp in terms of their ability to bind to DNA and regulate gene expression in response to exogenous leucine. We find that oligomerization beyond dimers is required for Lrp's regulatory activity and that, contrary to previous speculation, exogenous leucine modulates Lrp activity at its target promoters exclusively by inhibiting Lrp binding to DNA. We also show evidence that Lrp binding bridges DNA over length scales of multiple kilobases, revealing a new range of mechanisms for Lrp-mediated transcriptional regulation. IMPORTANCE Leucine-responsive regulatory protein (Lrp) is one of the most impactful regulators in E. coli and other bacteria. Lrp senses nutrient conditions and responds by controlling strategies for virulence, cellular motility, and nutrient acquisition. Despite its importance and being evolutionarily highly conserved across bacteria and archaea, several mysteries remain regarding Lrp, including how it actually responds to leucine to change its regulation of targets. Previous studies have led to the hypothesis that Lrp switches between two states, an octamer (8 Lrp molecules together) and a hexadecamer (16 Lrp molecules together), upon exposure to leucine; these are referred to as different oligomerization states. Here, we show that contrary to previous expectations, it is Lrp's propensity to bind DNA, rather than its oligomerization state, that is directly affected by leucine in the cell's environment. Our new understanding of Lrp activity will aid in identifying and disrupting pathways used by bacteria to cause disease.

RfaH Counter-Silences Inhibition of Transcript Elongation by H-NS-StpA Nucleoprotein Filaments in Pathogenic Escherichia coli

Expression of virulence genes in pathogenic Escherichia coli is controlled in part by the transcription silencer H-NS and its paralogs (e.g., StpA), which sequester DNA in multi-kb nucleoprotein filaments to inhibit transcription initiation, elongation, or both. Some activators counter-silence initiation by displacing H-NS from promoters, but how H-NS inhibition of elongation is overcome is not understood. In uropathogenic E. coli (UPEC), elongation regulator RfaH aids expression of some H-NS-silenced pathogenicity operons (e.g., hlyCABD encoding hemolysin). RfaH associates with elongation complexes (ECs) via direct contacts to a transiently exposed, nontemplate DNA strand sequence called operon polarity suppressor (ops). RfaH-ops interactions establish long-lived RfaH-EC contacts that allow RfaH to recruit ribosomes to the nascent mRNA and to suppress transcriptional pausing and termination. Using ChIP-seq, we mapped the genome-scale distributions of RfaH, H-NS, StpA, RNA polymerase (RNAP), and σ⁷⁰ in the UPEC strain CFT073. We identify eight RfaH-activated operons, all of which were bound by H-NS and StpA. Four are new additions to the RfaH regulon. Deletion of RfaH caused premature termination, whereas deletion of H-NS and StpA allowed elongation without RfaH. Thus, RfaH is an elongation counter-silencer of H-NS. Consistent with elongation counter-silencing, deletion of StpA alone decreased the effect of RfaH. StpA increases DNA bridging, which inhibits transcript elongation via topological constraints on RNAP. Residual RfaH effect when both H-NS and StpA were deleted was attributable to targeting of RfaH-regulated operons by a minor H-NS paralog, Hfp. These operons have evolved higher levels of H-NS-binding features, explaining minor-paralog targeting. IMPORTANCE Bacterial pathogens adapt to hosts and host defenses by reprogramming gene expression, including by H-NS counter-silencing. Counter-silencing turns on transcription initiation when regulators bind to promoters and rearrange repressive H-NS nucleoprotein filaments that ordinarily block transcription. The specialized NusG paralog RfaH also reprograms virulence genes but regulates transcription elongation. To understand how elongation regulators might affect genes silenced by H-NS, we mapped H-NS, StpA (an H-NS paralog), RfaH, σ⁷⁰, and RNA polymerase (RNAP) locations on DNA in the uropathogenic E. coli strain CFT073. Although H-NS-StpA filaments bind only 18% of the CFT073 genome, all loci at which RfaH binds RNAP are also bound by H-NS-StpA and are silenced when RfaH is absent. Thus, RfaH represents a distinct class of counter-silencer that acts on elongating RNAP to enable transcription through repressive nucleoprotein filaments. Our findings define a new mechanism of elongation counter-silencing and explain how RfaH functions as a virulence regulator.

Novel computational and experimental approaches for investigating the thermodynamics of metabolic networks

Thermodynamic analysis of metabolic networks has emerged as a useful new tool for pathway design and metabolic engineering. Understanding the relationship between the thermodynamic driving force of biochemical reactions and metabolic flux has generated new insights regarding the design principles of microbial carbon metabolism. This review summarizes the various lessons that can be obtained from the thermodynamic analysis of metabolic pathways, illustrates concepts of computational thermodynamic tools, and highlights recent applications of thermodynamic analysis to pathway design in industrially relevant microbes.

Inferring Protein Sequence-Function Relationships with Large-Scale Positive-Unlabeled Learning

Machine learning can infer how protein sequence maps to function without requiring a detailed understanding of the underlying physical or biological mechanisms. It is challenging to apply existing supervised learning frameworks to large-scale experimental data generated by deep mutational scanning (DMS) and related methods. DMS data often contain high-dimensional and correlated sequence variables, experimental sampling error and bias, and the presence of missing data. Notably, most DMS data do not contain examples of negative sequences, making it challenging to directly estimate how sequence affects function. Here, we develop a positive-unlabeled (PU) learning framework to infer sequence-function relationships from large-scale DMS data. Our PU learning method displays excellent predictive performance across ten large-scale sequence-function datasets, representing proteins of different folds, functions, and library types. The estimated parameters pinpoint key residues that dictate protein structure and function. Finally, we apply our statistical sequence-function model to design highly stabilized enzymes.

In Vivo Thermodynamic Analysis of Glycolysis in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum Using 13C and 2H Tracers

Thermodynamics constitutes a key determinant of flux and enzyme efficiency in metabolic networks. Here, we provide new insights into the divergent thermodynamics of the glycolytic pathways of C. thermocellum and T. saccharolyticum, two industrially relevant thermophilic bacteria whose metabolism still is not well understood. We report that while the glycolytic pathway in T. saccharolyticum is as thermodynamically favorable as that found in model organisms, such as E. coli or Saccharomyces cerevisiae, the glycolytic pathway of C. thermocellum operates near equilibrium. The use of a near-equilibrium glycolytic pathway, with potentially increased ATP yield, by this cellulolytic microbe may represent an evolutionary adaptation to growth on cellulose, but it has the drawback of being highly susceptible to product feedback inhibition. The results of this study will facilitate future engineering of high-performance strains capable of transforming cellulosic biomass to biofuels at high yields and titers.

Clostridium thermocellum and Thermoanaerobacterium saccharolyticum are thermophilic anaerobic bacteria with complementary metabolic capabilities that utilize distinct glycolytic pathways for the conversion of cellulosic sugars to biofuels. We integrated quantitative metabolomics with ²H and ¹³C metabolic flux analysis to investigate the in vivo reversibility and thermodynamics of the central metabolic networks of these two microbes. We found that the glycolytic pathway in C. thermocellum operates remarkably close to thermodynamic equilibrium, with an overall drop in Gibbs free energy 5-fold lower than that of T. saccharolyticum or anaerobically grown Escherichia coli. The limited thermodynamic driving force of glycolysis in C. thermocellum could be attributed in large part to the small free energy of the phosphofructokinase reaction producing fructose bisphosphate. The ethanol fermentation pathway was also substantially more reversible in C. thermocellum than in T. saccharolyticum. These observations help explain the comparatively low ethanol titers of C. thermocellum and suggest engineering interventions that can be used to increase its ethanol productivity and glycolytic rate. In addition to thermodynamic analysis, we used our isotope tracer data to reconstruct the T. saccharolyticum central metabolic network, revealing exclusive use of the Embden-Meyerhof-Parnas (EMP) pathway for glycolysis, a bifurcated tricarboxylic acid (TCA) cycle, and a sedoheptulose bisphosphate bypass active within the pentose phosphate pathway.

IMPORTANCE Thermodynamics constitutes a key determinant of flux and enzyme efficiency in metabolic networks. Here, we provide new insights into the divergent thermodynamics of the glycolytic pathways of C. thermocellum and T. saccharolyticum, two industrially relevant thermophilic bacteria whose metabolism still is not well understood. We report that while the glycolytic pathway in T. saccharolyticum is as thermodynamically favorable as that found in model organisms, such as E. coli or Saccharomyces cerevisiae, the glycolytic pathway of C. thermocellum operates near equilibrium. The use of a near-equilibrium glycolytic pathway, with potentially increased ATP yield, by this cellulolytic microbe may represent an evolutionary adaptation to growth on cellulose, but it has the drawback of being highly susceptible to product feedback inhibition. The results of this study will facilitate future engineering of high-performance strains capable of transforming cellulosic biomass to biofuels at high yields and titers.

A Regulatory NADH/NAD+ Redox Biosensor for Bacteria

NADH and NAD+ cofactors drive hundreds of biochemical reactions, and their ratio is a key metabolic marker of cellular state. Traditional assays to measure the NADH/NAD+ ratio is laborious, prone to inaccuracies, and not suitable for high-throughput screening. We report a genetically encoded ratiometric biosensor for NADH/NAD+ based on redox-responsive bacterial transcription factor Rex that overcomes these limitations. We engineered a Rex-regulated E. coli promoter with improved biosensor characteristics by tuning the affinity of Rex and the operator site. Since NADH is oxidized during aerobic respiration, we used the biosensor-reporter to investigate the effect of removing respiratory chain enzymes on NADH/NAD+ ratio during aerobiosis. We found that the NADH/NAD+ signal increased in five of the nine mutants by over 3-fold compared to wildtype, including an NADH dehydrogenase double mutant with 6-fold elevation. We also found that among several common carbon sources, E. coli grown on acetate exhibited higher NADH/NAD+ compared to E. coli grown on glucose. As a proof-of-concept for high-throughput redox screening, we were able to enrich high NADH mutants present at 1 in 10 000 among wildtype cells by biosensor-guided pooled screen. Thus, our Rex biosensor-reporter enables facile, noninvasive, high-throughput redox measurement to understand and engineer redox metabolism.