RESUMEN
Biomarkers of neurodegenerative disorders are needed to assist in diagnosis, to monitor disease progression and therapeutic interventions, and to provide insight into disease mechanisms. One route to identify such biomarkers is by proteomic and peptidomic analysis of cerebrospinal fluid (CSF). In the current study, we performed an in-depth analysis of the human CSF endopeptidome to establish an inventory that may serve as a basis for future targeted biomarker studies. High-pH RP HPLC was employed for off-line sample prefractionation followed by low-pH nano-LC-MS analysis. Different software programs and scoring algorithms for peptide identification were employed and compared. A total of 18 031 endogenous peptides were identified at a FDR of 1%, increasing the number of known endogenous CSF peptides 10-fold compared to previous studies. The peptides were derived from 2 053 proteins of which more than 60 have been linked to neurodegeneration. Notably, among the findings were six peptides derived from microtubule-associated protein tau, three of which span the diagnostically interesting threonine-181 (Tau-F isoform). Also, 213 peptides from amyloid precursor protein were identified, 58 of which were partially or completely within the sequence of amyloid ß 1-40/42, as well as 109 peptides from apolipoprotein E, spanning sequences that discriminate between the E2/E3/E4 isoforms of the protein.
Asunto(s)
Proteínas del Líquido Cefalorraquídeo/análisis , Péptidos/líquido cefalorraquídeo , Proteómica/métodos , Biomarcadores/líquido cefalorraquídeo , Cromatografía Liquida/métodos , Humanos , Espectrometría de Masas/métodos , Enfermedades Neurodegenerativas/líquido cefalorraquídeo , Programas InformáticosRESUMEN
Intestinal mucus barriers normally prevent microbial infections but are sensitive to diet-dependent changes in the luminal environment. Here we demonstrate that mice fed a Western-style diet (WSD) suffer regiospecific failure of the mucus barrier in the small intestinal jejunum caused by diet-induced mucus aggregation. Mucus barrier disruption due to either WSD exposure or chromosomal Muc2 deletion results in collapse of the commensal jejunal microbiota, which in turn sensitizes mice to atypical jejunal colonization by the enteric pathogen Citrobacter rodentium. We illustrate the jejunal mucus layer as a microbial habitat, and link the regiospecific mucus dependency of the microbiota to distinctive properties of the jejunal niche. Together, our data demonstrate a symbiotic mucus-microbiota relationship that normally prevents jejunal pathogen colonization, but is highly sensitive to disruption by exposure to a WSD.
Asunto(s)
Mucosa Intestinal , Yeyuno , Mucina 2 , Animales , Ratones , Dieta Occidental , Mucosa Intestinal/metabolismo , Mucosa Intestinal/microbiología , Intestino Delgado , Mucina 2/genética , Mucina 2/metabolismo , Moco , Citrobacter rodentium/fisiologíaRESUMEN
This protocol describes a method developed to identify endogenous peptides in human cerebrospinal fluid (CSF). For this purpose, a previously developed method based on molecular weight cut-off (MWCO) filtration and mass spectrometric analysis was combined with an offline high-pH reverse phase HPLC pre-fractionation step. Secretion into CSF is the main pathway for removal of molecules shed by cells of the central nervous system. Thus, many processes in the central nervous system are reflected in the CSF, rendering it a valuable diagnostic fluid. CSF has a complex composition, containing proteins that span a concentration range of 8 - 9 orders of magnitude. Besides proteins, previous studies have also demonstrated the presence of a large number of endogenous peptides. While less extensively studied than proteins, these may also hold potential interest as biomarkers. Endogenous peptides were separated from the CSF protein content through MWCO filtration. By removing a majority of the protein content from the sample, it is possible to increase the sample volume studied and thereby also the total amount of the endogenous peptides. The complexity of the filtrated peptide mixture was addressed by including a reverse phase (RP) HPLC pre-fractionation step at alkaline pH prior to LC-MS analysis. The fractionation was combined with a simple concatenation scheme where 60 fractions were pooled into 12, analysis time consumption could thereby be reduced while still largely avoiding co-elution. Automated peptide identification was performed by using three different peptide/protein identification software programs and subsequently combining the results. The different programs were complementary rather than comparable with less than 15% of the identifications overlapped between the three.