Bevezetés: A periprotetikus infekciók ellátása jelentős kihívás elé állítja az operáló orvost, mind diagnosztikai, mind terápiás tekintetben. Az utóbbi években a mozgásszervi kutatások során egyre növekvő figyelmet kaptak az extracellularis vesiculák. Az extracellularis vesiculák által szállított fehérjék tömegspektrometrián alapuló azonosítása fontos lépés, mely segíthet megérteni a védekezési folyamatban betöltött biológiai funkcióikat. Célkitűzés: Vizsgálatunk célja volt az akut és a krónikus fertőzött mintákból izolált extracellularis vesiculák fehérjetartalmának megismerése, azonosságok és különbségek keresése – az „egy legjobb biomarker” megtalálása helyett a lehető legtöbb, detektálható mennyiségben jelen lévő extracellularis vesiculába zárt fehérje vizsgálata és biológiai folyamatokba illesztése. Módszer: Prospektív, monocentrikus vizsgálatot végeztünk, a beválasztási kritériumok a 2018-as MSIS-kritériumokon alapultak. A vizsgálatba 13 (n = 13) beteget vontunk be, minden beteg periprotetikus infekció miatt került műtétre. 6 (n = 6) betegnél akut purulens (akut csoport) folyamatot, míg 7 (n = 7) betegnél ’low-grade’ infekciót (krónikus csoport) igazoltunk. Az extracellularis vesiculák izolálása minden esetben a protézist körülvevő synovialis folyadékból történt. A tömegspektrometriai vizsgálattal azonosított fehérjék funkcionális alapú klaszterezésére a STRING, KEGG, Gene Ontology adatbázisokat használtuk. A végleges vizualizáció Cytoscape 3.9.1. szoftverrel történt. Eredmények: Az extracellularis vesiculák feltárása után 222 db fehérjét azonosítottunk, melyek vagy az akut, vagy a krónikus minták valamelyikének több mint felében fordultak elő. Csak az akut minták több mint felében 50 db fehérjét; csak a krónikus minták több mint felében 33 db fehérjét; egyszerre mindkét csoport több mint felében 86 db fehérjét azonosítottunk. Ezek alapján készültek a funkcionális klaszterek. Megbeszélés: A protézisfertőzések diagnosztikájában régóta megvan a törekvés, hogy megtalálják az „egy legjobb biomarkert”, amely biztosan különbséget tud tenni fertőzött és nem fertőzött protézislazulás között. Következtetés: Vizsgálatunk célja nem egy újabb biomarker kiválasztása volt, hanem az extracellularis vesiculákban szállított fehérjék biológiai folyamatokban betöltött szerepének ábrázolása, leírása, amellyel jobban betekinthetünk a periprotetikus infekció során zajló folyamatokba. Orv Hetil. 2024; 165(3): 98–109.
Introduction: The management of periprosthetic infections is a major challenge for the operating surgeon, both diagnostically and therapeutically. In recent years, extracellular vesicles have received increasing attention in musculoskeletal research. Mass spectrometry-based identification of proteins transported by extracellular vesicles is an important step towards understanding their biological functions in the defence process. Objective: The aim of our study was to investigate the protein content of extracellular vesicles isolated from acute and chronic infected samples, to search for identities and differences – instead of finding “the single best biomarker”, to investigate the proteins encapsulated in extracellular vesicles present in as many detectable amounts as possible and to integrate them into biological processes. Method: Prospective monocentric study was performed, inclusion criteria were based on the 2018 MSIS criteria. 13 (n = 13) patients were included in the study, all patients underwent surgery for periprosthetic infection. 6 (n = 6) patients were confirmed to have an acute purulent (acute group) process, while 7 (n = 7) patients were confirmed to have a low-grade infection (chronic group). Extracellularis vesicles were isolated from the synovial fluid surrounding the prosthesis in all cases. STRING, KEGG, Gene Ontology databases were used for function-based clustering of proteins identified by mass spectrometry analysis. Final visualization was performed using Cytoscape 3.9.1 software. Results: 222 proteins were identified after extracellular vesicles were detected and were present in more than half of the acute or chronic samples. In more than half of the acute samples alone, 50 proteins were identified; in more than half of the chronic samples alone, 33 proteins were identified; in more than half of both groups simultaneously, 86 proteins were identified. These were used to construct functional clusters. Discussion: There has been a long-standing effort in the diagnostics of prosthetic infection to find “the single best biomarker” that can distinguish with certainty between infected and non-infected prosthetic loosening. Conclusion: The aim of our study was not to select a new biomarker, but to describe the role of proteins transported in extracellularis vesicles in biological processes, which will give us a better insight into the processes involved in periprosthetic infection. Orv Hetil. 2024; 165(3): 98–109.
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