Identification of Molecular Marker of Coagulase-negative Staphylococci for the Diagnosis of Prosthetic Joint Infections

One of the major causes of prosthetic joint failure is infection. Recently, coagulase-negative Staphylococci (CoNS) have been identified as emergent, nosocomial pathogens involved in subclinical prosthetic joint infections (PJIs). The diagnosis of PJIs mediated by CoNS is complex and demanding due to the absence of clear clinical signs derived from the host immune system response. In this scenario, the key to successful surgical treatment is the capability to differentiate between aseptic implant loosening and septic failure. Hence, the central hypothesis of this study is that proteomic analysis of the secretome of CoNS clinical isolates associated with the characterization of patient synovial fluids will reveal a panel of putative biomarkers tightly linked to PJIs. The confirmation of the presence of bacterial PJI biomarkers in synovial fluids of infected patients will pave the way for the development of a new reliable test capable of aiding in the diagnosis of subclinical PJIs.

Task 1.1: Synovial fluids will be collected from 60 patients referred to IRCCS Galeazzi Orthopedic Institute for the revision of a septic prosthesis and from 40 patients undergoing revision due to aseptic failure. The collected synovial fluids will be stored at -80°C until analysis.

According to MSIS guidelines, the measurement of CRP and ESR levels, synovial WBC count, and the microbiological culture of the explanted device and periprosthetic tissue will be conducted following routine protocols. Only synovial fluid collected from patients of the infected group diagnosed with a PJI mediated by CoNS will be eligible for subsequent proteomic analyses. Task 1.2: The secretome of at least 10 isolates of the retrieved species of CoNS will be characterized. In particular, CoNS clinical isolates will be cultured in a drip flow reactor to induce the production of biofilm and the secretome analyzed to perform the first selection of proteins of interest.

Task 2.1: Proteins extracted from the synovial fluids of patients with or without PJI will be carbamidomethylated and digested by trypsin. Thereafter, peptide mixtures will be analyzed by nano liquid chromatography coupled to tandem mass spectrometry (nano LC-MS/MS). Label-free quantifications (LFQ) will be applied to assess the levels of proteins expressed by bacteria and secreted in patient synovial fluids.

Task 2.2: Using proteomic software (i.e. MaxQuant, Perseus, etc.), the bioinformatic analysis will be performed to determine a pool of proteins of interest present only in samples belonging to the infected group of patients which would be closely related to the presence of bacteria.

Task 3.1: Proteins of interest identified in Task 1.2 and Task 2.2 as putative biomarkers related to CoNS-mediated PJIs will be selected for targeted proteomic analyses by means of additional bioinformatic analyses.

Task 3.2: To confirm the presence of putative biomarkers defined in Task 3.1 in synovial fluid of enrolled patients, targeted proteomic analysis will be performed on all the infected/not infected samples collected in Task 1.1. Prototypic peptides for each putative biomarker will be selected by Skyline software. Ionization and fragmentation behaviors of all candidate peptides will be studied.

Task 3.3: Finally, the information from the targeted proteomic analysis will be correlated to the outcomes of the diagnosis formulated following the MSIS guidelines in order to evaluate the diagnostic value of each selected biomarker.

Eligibility Criteria:
Inclusion Criteria:

* ≥ 18 years old patients
* Patients subjected to a revision of the articular prosthesis due to bacterial infection mediated by coagulase-negative Staphylococci (CoNS) or to an aseptic failure of the implant
* Collection of a sufficient volume of synovial fluid
* Patient consent by signing an informed consent form

Exclusion Criteria:

* Patients not fulfilling the inclusion criteria
* Collection of a hemolytic sample