RESUMEN
Metabolic syndrome (MetS) is a complex metabolic disorder with a global prevalence of 20%-25%. Early identification and intervention would help minimize the global burden on healthcare systems. Here, we measured over 400 proteins from â¼20,000 proteomes using data-independent acquisition mass spectrometry for 7,890 serum samples from a longitudinal cohort of 3,840 participants with two follow-up time points over 10 years. We then built a machine-learning model for predicting the risk of developing MetS within 10 years. Our model, composed of 11 proteins and the age of the individuals, achieved an area under the curve of 0.774 in the validation cohort (n = 242). Using linear mixed models, we found that apolipoproteins, immune-related proteins, and coagulation-related proteins best correlated with MetS development. This population-scale proteomics study broadens our understanding of MetS and may guide the development of prevention and targeted therapies for MetS.
Asunto(s)
Síndrome Metabólico , Humanos , Síndrome Metabólico/diagnóstico , Síndrome Metabólico/epidemiología , Pronóstico , Proteómica , Proteoma , Aprendizaje AutomáticoRESUMEN
Estimates of quantitative proteomic distance between populations have not been reported to date. Here, quantitative proteomic distances between three Spanish bovine breeds (Asturiana de los Valles, AV; Retinta, RE; and Rubia Gallega, RG) were estimated from two-dimensional electrophoresis profiles of meat samples of longissimus thoracis muscle at 2 h post-mortem. Statistically significant distances were detected between AV/RG and the most genetically different RE breed, using the novel QD measure of quantitative proteomic distance. In total, 18 differentially abundant myofibrillar and sarcoplasmic proteins/isoforms contributing to proteomic distances between breeds were confidently identified by tandem mass spectrometry. The fast skeletal myosin regulatory light chain 2 followed by other five interacting proteins exhibited the most pronounced relative change between breeds. In addition, most differentially represented proteins could be associated with variations in meat tenderness. Therefore, they could be candidate biomarkers for molecular breeding programs and authentication of the three Spanish beef breeds.
Asunto(s)
Carne Roja/análisis , Animales , Cruzamiento , Bovinos , Análisis de los Alimentos , Músculo Esquelético/metabolismo , ProteómicaRESUMEN
Quantitative proteomics was used to reveal biochemical differences in kidneys of marine and freshwater three-spined sticklebacks. More than 1500 unambiguous proteins were identified, 106 of which are robustly co-translationally modified. Amino-terminal acetylation sites for 94 and proline hydroxylation sites for 12 proteins, including 4 protein disulfide isomerases having the consensus motif APWCGHCK, were determined. More than 1500 proteins were quantified by LC-MS/MS yielding 120 proteins with consistent population-specific abundance differences. Twenty-five of these were selected for validation by data-independent acquisition (DIA) and spectral library based MS2 quantitation. A dense biochemical network was revealed, which promotes the synthesis of the organic osmolytes betaine, sorbitol, trimethylamine oxid (TMAO), and urea. It contains 33 of 49 proteins that are elevated in marine compared to freshwater sticklebacks, including the most highly elevated proteins (dimethylaniline monooxygenase, alanine-glyoxylate aminotransferase, glycine N-methyltransferase). Freshwater stickleback kidneys contain elevated levels of proteolytic, cytoskeletal, extracellular matrix, and calcium signaling proteins. Proteins that are most elevated in freshwater sticklebacks are ES1 protein homolog, apoptosis-associated speck-like protein containing a CARD and caspase 1. Protein-abundance network analysis demonstrates significantly higher levels of synchronized abundance control in marine sticklebacks. The significance of these findings for biochemical diversification of renal function in marine and FW sticklebacks is discussed.
Asunto(s)
Organismos Acuáticos/metabolismo , Proteínas de Peces/metabolismo , Riñón/metabolismo , Proteoma/metabolismo , Proteómica , Smegmamorpha/metabolismo , Animales , Especificidad de la EspecieRESUMEN
Understanding the forces that shape eco-evolutionary patterns often requires linking phenotypes to genotypes, allowing characterization of these patterns at the molecular level. DNA-based markers are less informative in this aim compared to markers associated with gene expression and, more specifically, with protein quantities. The characterization of eco-evolutionary patterns also usually requires the analysis of large sample sizes to accurately estimate interindividual variability. However, the methods used to characterize and compare protein samples are generally expensive and time-consuming, which constrains the size of the produced data sets to few individuals. We present here a method that estimates the interindividual variability of protein quantities based on a global, semi-automatic analysis of 1D electrophoretic profiles, opening the way to rapid analysis and comparison of hundreds of individuals. The main original features of the method are the in silico normalization of sample protein quantities using pictures of electrophoresis gels at different staining levels, as well as a new method of analysis of electrophoretic profiles based on a median profile. We demonstrate that this method can accurately discriminate between species and between geographically distant or close populations, based on interindividual variation in venom protein profiles from three endoparasitoid wasps of two different genera (Psyttalia concolor, Psyttalia lounsburyi and Leptopilina boulardi). Finally, we discuss the experimental designs that would benefit from the use of this method.
Asunto(s)
Electroforesis en Gel de Poliacrilamida/métodos , Proteoma/análisis , Ponzoñas/química , Avispas/clasificación , Animales , Automatización de Laboratorios/métodosRESUMEN
Comparing populations residing in contrasting environments is an efficient way to decipher how organisms modulate their physiology. Here we present the proteomic signatures of two populations in a non-model marine species, the great scallop Pecten maximus, living in the northern (Hordaland, Norway) and in the center (Brest, France) of this species' latitudinal distribution range. The results showed 38 protein spots significantly differentially accumulated in mantle tissues between the two populations. We could unambiguously identify 11 of the protein spots by Maldi TOF-TOF mass spectrometry. Eight proteins corresponded to different isoforms of actin, two were identified as filamin, another protein related to the cytoskeleton structure, and one was the protease elastase. Our results suggest that scallops from the two populations assayed may modulate their cytoskeleton structures through regulation of intracellular pools of actin and filamin isoforms to better adapt to their environment. BIOLOGICAL SIGNIFICANCE: Marine mollusks are non-model organisms that have been poorly studied at the proteomic level, and this article is the first studying the great scallop (P. maximus) at this level. Furthermore, it addresses population proteomics, a new promising field, especially in environmental sciences. This article is part of a Special Issue entitled: Proteomics of non-model organisms.