Cysteine and iron accelerate the formation of ribose-5-phosphate, providing insights into the evolutionary origins of the metabolic network structure.

The structure of the metabolic network is highly conserved, but we know little about its evolutionary origins. Key for explaining the early evolution of metabolism is solving a chicken-egg dilemma, which describes that enzymes are made from the very same molecules they produce. The recent discovery of several nonenzymatic reaction sequences that topologically resemble central metabolism has provided experimental support for a "metabolism first" theory, in which at least part of the extant metabolic network emerged on the basis of nonenzymatic reactions. But how could evolution kick-start on the basis of a metal catalyzed reaction sequence, and how could the structure of nonenzymatic reaction sequences be imprinted on the metabolic network to remain conserved for billions of years? We performed an in vitro screening where we add the simplest components of metabolic enzymes, proteinogenic amino acids, to a nonenzymatic, iron-driven reaction network that resembles glycolysis and the pentose phosphate pathway (PPP). We observe that the presence of the amino acids enhanced several of the nonenzymatic reactions. Particular attention was triggered by a reaction that resembles a rate-limiting step in the oxidative PPP. A prebiotically available, proteinogenic amino acid cysteine accelerated the formation of RNA nucleoside precursor ribose-5-phosphate from 6-phosphogluconate. We report that iron and cysteine interact and have additive effects on the reaction rate so that ribose-5-phosphate forms at high specificity under mild, metabolism typical temperature and environmental conditions. We speculate that accelerating effects of amino acids on rate-limiting nonenzymatic reactions could have facilitated a stepwise enzymatization of nonenzymatic reaction sequences, imprinting their structure on the evolving metabolic network

Evolutionary Descent of Prion Genes from the ZIP Family of Metal Ion Transporters

In the more than twenty years since its discovery, both the phylogenetic origin and cellular function of the prion protein (PrP) have remained enigmatic. Insights into a possible function of PrP may be obtained through the characterization of its molecular neighborhood in cells. Quantitative interactome data demonstrated the spatial proximity of two metal ion transporters of the ZIP family, ZIP6 and ZIP10, to mammalian prion proteins in vivo. A subsequent bioinformatic analysis revealed the unexpected presence of a PrP-like amino acid sequence within the N-terminal, extracellular domain of a distinct sub-branch of the ZIP protein family that includes ZIP5, ZIP6 and ZIP10. Additional structural threading and orthologous sequence alignment analyses argued that the prion gene family is phylogenetically derived from a ZIP-like ancestral molecule. The level of sequence homology and the presence of prion protein genes in most chordate species place the split from the ZIP-like ancestor gene at the base of the chordate lineage. This relationship explains structural and functional features found within mammalian prion proteins as elements of an ancient involvement in the transmembrane transport of divalent cations. The phylogenetic and spatial connection to ZIP proteins is expected to open new avenues of research to elucidate the biology of the prion protein in health and disease

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

Specific interactions of Bi(III) with Cys-Xaa-Cys unit of a peptide sequence

The medicinal application of bismuth compounds is focused in two fields: antimicrobial and anticancer. Bi(III) complexes have been used in medicine as an effective treatment of microbial infections, such as peptic ulcers, diarrhoea, gastritis and syphilis. 212Bi and 213Bi are strong a-particle emitters, which, bound to specific ligands, could be promising targeted radio-therapeutic agents for the treatment of cancer. In this work, the coordination of bismuth to three peptides with the Cys-Xaa-Cys motif was studied by potentiometric, spectroscopic, mass spectrometric and NMR methods. We have shown, that sulfur atoms from cysteines are critical donors for the coordination of Bi(III). Our investigation provides insight towards an understanding of the chemistry of bismuth-containing complexes and may lead to the further application of this metal in medicine

Heteronuclear and homonuclear Cu2+ and Zn2+ complexes with multihistidine peptides based on zebrafish prion-like protein

The homeostasis of metal ions, especially copper and zinc, is a major factor that may influence the prion diseases and the biological function of prion protein (PrP). The His-rich regions are basic sites for metal binding and antioxidant activity of the PrP structures. Animal prion-like proteins contain also His-rich domains, and their coordination chemistry may provide better insight into the chemistry and biology of PrP structures and related diseases. Herein, we report an equilibrium study on heteronuclear Zn2+-Cu2+ complexes with zrel-PrP fragments from zebrafish. Potentiometric, spectroscopic, and mass spectrometric methods showed that the binding of copper is much more effective than the binding of zinc. At physiological pH, both metals bind to the histidine imidazole N donors of the studied peptides

Copper(II) coordination outside the tandem repeat region of an unstructured domain of chicken prion protein

Combined potentiometric, calorimetric and spectroscopic methods were used to investigate the Cu2+ binding ability and coordination behaviour of some peptide fragments related to the neurotoxic region of chicken Prion Protein. The systems studied were the following protein fragments: chPrP106–114, chPrP119–126, chPrP108–127, chPrP105–127 and chPrP105–133. The complex formation always starts around pH 4 with the coordination of an imidazole nitrogen, followed by the deprotonation and binding of amide nitrogens from the peptidic backbone. At neutral pH, the {Nim, 3N−} binding mode is the preferred one. The amide nitrogens participating in the binding to the Cu2+ ion derive from residues from the N-terminus side, with the formation of a six-membered chelate ring with the imidazolic side chain. Comparison of thermodynamic data for the two histydyl binding domains (around His-110 and His-124), clearly indicates that the closest to the hexarepeat domain (His-110) has the highest ability to bind Cu2+ ions, although both of them have the same coordination mode. Conversely, in the case of the human neurotoxic peptide region, between the two binding sites, located at His-96 and His-111, the farthest from the tandem repeat region is the strongest one. Finally, thermodynamic data show that chicken peptide is a distinctly better ligand for coordination of copper ions with respect to the human fragment

Imaging of intracellular fatty acids by scanning X-ray fluorescence microscopy

International audienceFatty acids are taken up by cells and incorporated into complex lipids such as neutral lipids and glycerophospholipids. Glycerophospholipids are major constituents of cellular membranes. More than 1000 mol. species of glycerophospholipids differ in their polar head groups and fatty acid compns. They are related to cellular functions and diseases and have beenwell analyzed by mass spectrometry. However, intracellular imaging of fatty acids and glycerophospholipids has not been successful due to insufficient resoln. using conventional methods. Here, we developed a method for labeling fatty acids with bromine (Br) and applied scanning X-​ray fluorescence microscopy (SXFM) to obtain intracellular Br mapping data with submicrometer resoln. Mass spectrometry showed that cells took up Br-​labeled fatty acids andmetabolized them mainly into glycerophospholipids in CHO cells. Most Br signals obsd. by SXFM were in the perinuclear region. Higher resoln. revealed a spot-​like distributionofBr inthe cytoplasm.The current method enabled successful visualization of intracellular Br-​labeled fatty acids. Single-​element labeling combined with SXFM technol. facilitates the intracellular imaging of fatty acids, which provides a new tool to det. dynamic changes in fatty acids and their derivs. at the single-​cell level