Integrated pH Measurement during Reaction Monitoring with Dual-Reception 1H-31P NMR Spectroscopy

6-Phosphogluconolactonase is critical for the efficient functioning of the pentose phosphate pathway

The metabolic networks of microorganisms are remarkably robust to genetic and environmental perturbations. This robustness stems from redundancies such as gene duplications, isoenzymes, alternative metabolic pathways, and also from non-enzymatic reactions. In the oxidative branch of the pentose phosphate pathway (oxPPP), 6-phosphogluconolactone hydrolysis into 6-phosphogluconate is catalysed by 6-phosphogluconolactonase (Pgl) but in the absence of the latter, the oxPPP flux is thought to be maintained by spontaneous hydrolysis. However, in Δpgl Escherichia coli, an extracellular pathway can also contribute to pentose phosphate synthesis. This raises question as to whether the intracellular non-enzymatic reaction can compensate for the absence of 6-phosphogluconolactonase and, ultimately, on the role of 6-phosphogluconolactonase in central metabolism. Our results validate that the bypass pathway is active in the absence of Pgl, specifically involving the extracellular spontaneous hydrolysis of gluconolactones to gluconate. Under these conditions, metabolic flux analysis reveals that this bypass pathway accounts for the entire flux into the oxPPP. This alternative metabolic route-partially extracellular-sustains the flux through the oxPPP necessary for cell growth, albeit at a reduced rate in the absence of Pgl. Importantly, these findings imply that intracellular non-enzymatic hydrolysis of 6-phosphogluconolactone does not compensate for the absence of Pgl. This underscores the crucial role of Pgl in ensuring the efficient functioning of the oxPPP.

Exploring the pH dependence of an improved PETase

Enzymatic recycling of plastic and especially of polyethylene terephthalate (PET) has shown great potential to reduce its negative impact on our society. PET hydrolases (PETases) have been optimized using rational design and machine learning, but the mechanistic details of the PET depolymerization process remain unclear. Belonging to the carboxylic-ester hydrolase family with a canonical Ser-His-Asp catalytic triad, their observed alkaline pH optimum is generally thought to be related to the protonation state of the catalytic His. Here, we explore this aspect in the context of LCCICCG, an optimized PETase, derived from the leaf-branch compost cutinase enzyme. We use NMR to identify the dominant tautomeric structure of the six histidines. Five show surprisingly low pKa values below 4.0, whereas the catalytic H242 in the active enzyme displays a pKa value that varies from 4.9 to 4.7 when temperatures increase from 30°C to 50°C. Whereas the hydrolytic activity of the enzyme toward a soluble substrate can be modeled by the corresponding protonation/deprotonation curve, an important discrepancy is found when the substrate is the solid plastic. This opens the way to further mechanistic understanding of the PETase activity and underscores the importance of studying the enzyme at the liquid-solid interface.

The combination of inorganic phosphate and pyrophosphate 31 P-NMR for the electrodeless pH determination in the 5-12 range

Potentiometry is the primary pH measurement method, but alternatives are sought beyond glass electrodes operative limitations. In nuclear magnetic resonance (NMR) experiments, electrodeless pH sensing is important to track changes along titrations, during chemical reactions or inside compartmentalized environments inaccessible to electrodes, for instance. Although several interesting NMR pH indicators have been already presented, the potential of inorganic phosphate is overlooked, despite its common presence in NMR samples as the buffer main component. Its use for electrodeless pH determination can be expanded by exploiting all its three proton dissociations. This study was aimed at verifying the use of inorganic phosphate 31 P chemical shift to sense pH variations, and at exploring the complementary use of pyrophosphate ions to cover a wide pH range. A simple set of equations is presented to utilize both phosphate and pyrophosphate 31 P chemical shift in combination for accurate pH determination without a glass electrode over the 5-12 pH range, and without affecting the spectrum of other nuclei. The present study demonstrated an average deviation of 0.09 (maximum <0.2) pH unit from glass electrode measurements. The trimethylphosphate can be used as a suitable chemical shift reference for both 31 P and 1 H (also 13 C), with its hydrolysis being significant only at pH > 12. The method was also demonstrated by determining the pKa of three distinct molecules in a mixture and by comparing the results to those obtained when the glass electrode was used to measure the pH. The approach shown here can be easily tuned to different experimental conditions.

Advances in the Synthesis and Analysis of Biologically Active Phosphometabolites

Phosphorus-containing metabolites cover a large molecular diversity and represent an important domain of small molecules which are highly relevant for life and represent essential interfaces between biology and chemistry, between the biological and abiotic world. The large but not unlimited amount of phosphate minerals on our planet is a key resource for living organisms on our planet, while the accumulation of phosphorus-containing waste is associated with negative effects on ecosystems. Therefore, resource-efficient and circular processes receive increasing attention from different perspectives, from local and regional levels to national and global levels. The molecular and sustainability aspects of a global phosphorus cycle have become of much interest for addressing the phosphorus biochemical flow as a high-risk planetary boundary. Knowledge of balancing the natural phosphorus cycle and the further elucidation of metabolic pathways involving phosphorus is crucial. This requires not only the development of effective new methods for practical discovery, identification, and high-information content analysis, but also for practical synthesis of phosphorus-containing metabolites, for example as standards, as substrates or products of enzymatic reactions, or for discovering novel biological functions. The purpose of this article is to review the advances which have been achieved in the synthesis and analysis of phosphorus-containing metabolites which are biologically active.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

In-cell NMR: Why and how?

NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.

Potential of multiparametric characterization of foodstuffs by nuclear magnetic resonance to better predict microbial behavior

Numerous predictive microbiology models have been proposed to describe bacterial population behaviors in foodstuffs. These models depict the growth kinetics of particular bacterial strains based on key physico-chemical parameters of food matrices and their storage temperature. In this context, there is a prominent issue to accurately characterize these parameters, notably pH, water activity (a_w ), and NaCl and organic acid concentrations. Usually, all these product features are determined using one destructive analysis per parameter at macroscale (>5 g). Such approach prevents an overall view of these characteristics on a single sample. Besides, it does not take into account the intra-product microlocal variability of these parameters within foods. Nuclear magnetic resonance (NMR) is a versatile non-invasive spectroscopic technique. Experiments can be recorded successively on a same collected sample without damaging it. In this work, we designed a dedicated NMR approach to characterize the microenvironment of foods using 10-mg samples. The multiparametric mesoscopic-scale approach was validated on four food matrices: a smear soft cheese, cooked peeled shrimps, cold-smoked salmon, and smoked ham. Its implementation in situ on salmon fillets enabled to observe the intra-product heterogeneity and to highlight the impact of process on the spatial distribution of pH, NaCl, and organic acids. This analytical development and its successful application can help address the shortcomings of monoparametric methods traditionally used for predictive microbiology purposes.

In-Cell Structural Biology by NMR: The Benefits of the Atomic Scale

In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.

Improved NMR Detection of Phospho-Metabolites in a Complex Mixture

Phosphorylated metabolites are omnipresent in cells, but their analytical characterization faces several technical hurdles. Here, we detail an improved NMR workflow aimed at assigning the high-resolution subspectrum of the phospho-metabolites in a complex mixture. Combining a pure absorption J-resolved spectrum (Pell, A. J.; J. Magn. Reson. 2007, 189 (2), 293-299) with alternate on- and off-switching of the ³¹P coupling interaction during the t₁ evolution with a pure in-phase (PIP) HSQMBC experiment (Castañar, L.; Angew. Chem., Int. Ed. 2014, 53 (32), 8379-8382) without or with total correlation spectroscopy (TOCSY) transfer during the insensitive nuclei enhancement by polarization transfer (INEPT) gives access to selective identification of the individual subspectra of the phosphorylated metabolites. Returning to the initial J-res spectra, we can extract with optimal resolution the full trace for the individual phospho-metabolites, which can then be transposed on the high-resolution quantitative one dimensional spectrum.

Probing Microenvironmental Acidity in Lyophilized Protein and Vaccine Formulations Using Solid-state NMR Spectroscopy

Biophysical and biochemical instability of therapeutic proteins in the solution state may necessitate the development of products in the solid form, due to their enhanced stability. Lyophilization is a widely used method to ensure dry state stabilization of biological products. A commonly encountered issue is the pH shifts that can occur due to undesired crystallization of a buffer component, resulting in loss of protein activities. However, it is technically challenging to noninvasively investigate the physicochemical environment in the lyophile matrix. In this work, we demonstrate an approach based on solid-state NMR to investigate the microenvironmental acidity in lyophilized protein formulations, using histidine, a commonly used buffer agent, as a molecular probe. The solid-state acidity in the lyophilized matrix can be assessed by monitoring the chemical shift changes of histidine. The protonation and tautomeric states of histidine lyophilized at a range of pH values from 4.5 to 11.0 were identified from full ¹³C and ¹⁵N resonance assignments in one-dimensional and two-dimensional NMR experiments. The results demonstrated a pH-dependence of histidine chemical shift in the amorphous state. Moreover, we successfully applied this protocol to investigate the microenvironmental pH in lyophilized formulations of the HPV vaccine and lactate dehydrogenase protein.

Tuning the catalytic activity and selectivity of water-soluble bimetallic RuPt nanoparticles by modifying their surface metal distribution

Bimetallic ruthenium-platinum nanoparticles (RuPt NPs) of different surface distributions and stabilized by using a sulfonated N-heterocyclic carbene ligand (1-(2,6-diisopropylphenyl)-3-(3-potassium sulfonatopropyl)-imidazol-2-ylidene) were prepared from Ru(COD)(COT) (COD = cyclooctadiene and COT = cyclooctatriene), and platinum precursors having various decomposition rates (Pt(NBE)₃, NBE = norbornene, Pt(CH₃)₂(COD) and Pt₂(DBA)₃, DBA = dibenzylideneacetone). Structural and surface studies by FT-IR and solid-state MAS NMR, using carbon monoxide as a probe molecule, revealed the presence of different structures and surface compositions for different nanoparticles of similar sizes, which principally depend on the decomposition rate of the organometallic precursors used during the synthesis. Specifically, the slower the decomposition rate of the platinum precursor, the higher the number of Pt atoms at the NP surface. The different bimetallic RuPt NPs, as well as their monometallic equivalents (Pt and Ru NPs), were used in isotopic H/D exchange through C-H activation on l-lysine. Interestingly, the activity and selectivity of the direct C-H deuteration were dependent on the NP surface composition at the α position but not on that at the ε position. Chemical shift perturbation (CSP) experiments revealed that the difference in reactivity at the α position is due to a Pt-carboxylate interaction, which hinders the H/D exchange.