Lab

Precision Medicine and Metabolism LAB (https://www.omilletlab.com)

About the lab

Protein stability (thermodynamic and kinetic) drives the biophysical properties of the polypeptide chain (protein folding) and the protein's concentration in the cellular environment (protein homeostasis). It is the result of a delicate balance between inter- and intramolecular interactions, which can be easily altered by mutations and/or upon changes in the composition of the surrounding media. In this context, NMR spectroscopy offers a plethora of suitable experiments to investigate protein stability.

https://www.omilletlab.com/

Featured research (12)

Proton nuclear magnetic resonance (NMR) N-acetyl signals (Glyc) from glycoproteins and supramolecular phospholipids composite peak (SPC) from phospholipid quaternary nitrogen methyls in subcompartments of lipoprotein particles) can give important systemic metabolic information, but their absolute quantification is compromised by overlap with interfering resonances from lipoprotein lipids themselves. We present a J-Edited DIffusional (JEDI) proton NMR spectroscopic approach to selectively augment signals from the inflammatory marker peaks Glyc and SPCs in blood serum NMR spectra, which enables direct integration of peaks associated with molecules found in specific compartments. We explore a range of pulse sequences that allow editing based on peak J-modulation, translational diffusion, and T2 relaxation time and validate them for untreated blood serum samples from SARS-CoV-2 infected patients (n = 116) as well as samples from healthy controls and pregnant women with physiological inflammation and hyperlipidemia (n = 631). The data show that JEDI is an improved approach to selectively investigate inflammatory signals in serum and may have widespread diagnostic applicability to disease states associated with systemic inflammation.
COVID‐19 is a systemic infectious disease that may affect many organs, accompanied by a measurable metabolic dysregulation. The disease is also associated with significant mortality, particularly among the elderly, patients with comorbidities, and solid organ transplant recipients. Yet, the largest segment of the patient population is asymptomatic, and most other patients develop mild to moderate symptoms after SARS‐CoV‐2 infection. Here, we have used NMR metabolomics to characterize plasma samples from a cohort of the abovementioned group of COVID‐19 patients (n = 69), between 3 and 10 months after diagnosis, and compared them with a set of reference samples from individuals never infected by the virus (n = 71). Our results indicate that half of the patient population show abnormal metabolism including porphyrin levels and altered lipoprotein profiles six months after the infection, while the other half show little molecular record of the disease. Remarkably, most of these patients are asymptomatic or mild COVID‐19 patients, and we hypothesize that this is due to a metabolic reflection of the immune response stress. We have used NMR‐based metabolomics to characterize plasma samples from a cohort of recovered COVID‐19 patients, six months on average after diagnosis. Our results show that half the patient population have abnormal metabolism and altered lipoprotein profiles while the other moiety shows little molecular record of the disease.
BACKGROUND. Metabolic syndrome (MetS) is a multimorbid long-term condition without consensual medical definition and a diagnostic based on compatible symptomatology. Here we have investigated the molecular signature of MetS in urine. METHODS. We used NMR-based metabolomics to investigate a European cohort including urine samples from 11,754 individuals (18–75 years old, 41% females), designed to populate all the intermediate conditions in MetS, from subjects without any risk factor up to individuals with developed MetS (4–5%, depending on the definition). A set of quantified metabolites were integrated from the urine spectra to obtain metabolic models (one for each definition), to discriminate between individuals with MetS. RESULTS. MetS progression produces a continuous and monotonic variation of the urine metabolome, characterized by up- or down-regulation of the pertinent metabolites (19 in total, including glucose, lipids, aromatic amino acids, salicyluric acid, maltitol, trimethylamine N-oxide, and p-cresol sulfate) with some of the metabolites associated to MetS for the first time. This metabolic signature, based solely on information extracted from the urine spectrum, adds a molecular dimension to MetS definition and it was used to generate models that can identify subjects with MetS (AUROC values between 0.86 and 0.92). This signature is particularly suitable to add meaning to the conditions that are in the interface between healthy subjects and MetS patients. Aging and non-alcoholic fatty liver disease are also risk factors that may enhance MetS probability, but they do not directly interfere with the metabolic discrimination of the syndrome. CONCLUSIONS. Urine metabolomics, studied by NMR spectroscopy, unravelled a set of metabolites that concomitantly evolve with MetS progression, that were used to derive and validate a molecular definition of MetS and to discriminate the conditions that are in the interface between healthy individuals and the metabolic syndrome.
In glycoproteins, carbohydrates are responsible for the selective interaction and tight regulation of cellular processes, constituting the main information transducer interface in protein–glycoprotein interactions. Increasing experimental and computational evidence suggest that such interactions often induce allosteric changes in the host protein, underlining the importance of studying intact glycoproteins. Technical issues have precluded such studies for years but, nowadays, a promising era is emerging where NMR spectroscopy, among other techniques, allows the characterization of the composition, structure and segmental dynamics of glycoproteins. In this review, we discuss such advances and highlight some selected examples. This novel technology unravels multiple new functional mechanisms, subtly hidden within the sugar code.
Protein oligomerization processes are widespread and of crucial importance to understand degenerative diseases and healthy regulatory pathways. One particular case is the homo-oligomerization of folded domains involving domain swapping, often found as a part of the protein homeostasis in the crowded cytosol, composed by a complex mixture of cosolutes. Here, we have investigated the effect of a plethora of cosolutes of very diverse nature on the kinetics of a protein dimerization by domain swapping. In the absence of cosolutes, our system exhibits slow interconversion rates, with the reaction reaching the equilibrium within the average protein homeostasis timescale (24-48 h). In the presence of crowders, though, the oligomerization reaction in the same time frame will, depending on the protein's initial oligomeric state, either reach a pure equilibrium state or get kinetically trapped into an apparent equilibrium. Specifically, when the reaction is initiated from a large excess of dimer, it becomes unsensitive to the effect of cosolutes and reaches the same equilibrium populations as in the absence of cosolute. Conversely, when the reaction starts from a large excess of monomer, the reaction during the homeostatic timescale occurs under kinetic control and it is exquisitely sensitive to the presence and nature of the cosolute. In this scenario (the most habitual case in intracellular oligomerization processes), the effect of cosolutes on the intermediate conformation and diffusion-mediated encounters will dictate how the cellular milieu affect the domain-swapping reaction.

Lab head

Oscar Millet
Department
  • Structural Biology Unit

Members (16)

Fernando Lopitz-Otsoa
  • Center for Cooperative Research in Biosciences
David Fernández-Ramos
  • Center for Cooperative Research in Biosciences
Nieves Embade
  • Center for Cooperative Research in Biosciences
Virginia Gutiérrez
  • Center for Cooperative Research in Biosciences
Ganeko Bernardo-Seisdedos
  • ATLAS Molecular Pharma S.L.
Ana Laín
  • Center for Cooperative Research in Biosciences
Maider Bizkarguenaga-Uribiarte
  • Center for Cooperative Research in Biosciences
Rubén Gil-Redondo
  • Center for Cooperative Research in Biosciences
Tammo Diercks
Tammo Diercks
  • Not confirmed yet

Alumni (1)

Pedro Urquiza
  • Hospital Torrecárdenas, Almeria