High-Dimensional Analysis of Immune Cell Composition Predicts Periprosthetic Joint Infections and Dissects Its Pathophysiology

Staphylococcus epidermidis alters macrophage polarization and phagocytic uptake by extracellular DNA release in vitro

Biofilm formation shields Staphylococcus epidermidis from host defense mechanisms, contributing to chronic implant infections. Using wild-type S. epidermidis 1457, a PIA-negative mutant (1457-M10), and an eDNA-negative mutant (1457ΔatlE), this study examined the influence of biofilm matrix components on human monocyte-derived macrophage (hMDM) interactions. The wild-type strain was resistant to phagocytosis and induced an anti-inflammatory response in hMDMs, while both mutants were more susceptible to phagocytosis and triggered a pro-inflammatory response. Removing eDNA from the 1457 biofilm matrix increased hMDM uptake and a pro-inflammatory reaction, whereas adding eDNA to the 1457ΔatlE mutant reduced phagocytosis and promoted an anti-inflammatory response. Inhibiting TLR9 enhanced bacterial uptake and induced a pro-inflammatory response in hMDMs exposed to wild-type S. epidermidis. This study highlights the critical role of eDNA in immune evasion and the central role of TLR9 in modulating macrophage responses, advancing the understanding of implant infections.

Osteomyelitis is associated with increased anti-inflammatory response and immune exhaustion

Introduction

Osteomyelitis (OMS) is a bone infection causing bone pain and severe complications. A balanced immune response is critical to eradicate infection without harming the host, yet pathogens manipulate immunity to establish a chronic infection. Understanding OMS-driven inflammation is essential for disease management, but comprehensive data on immune profiles and immune cell activation during OMS are lacking.

Methods

Using high-dimensional flow cytometry, we investigated the detailed innate and adaptive systemic immune cell populations in OMS and age- and sex-matched controls.

Results

Our study revealed that OMS is associated with increased levels of immune regulatory cells, namely T regulatory cells, B regulatory cells, and T follicular regulatory cells. In addition, the expression of immune activation markers HLA-DR and CD86 was decreased in OMS, while the expression of immune exhaustion markers TIM-3, PD-1, PD-L1, and VISTA was increased. Members of the T follicular helper (Tfh) cell family as well as classical and typical memory B cells were significantly increased in OMS individuals. We also found a strong correlation between memory B cells and Tfh cells.

Discussion

We conclude that OMS skews the host immune system towards the immunomodulatory arm and that the Tfh memory B cell axis is evident in OMS. Therefore, immune-directed therapies may be a promising alternative for eradication and recurrence of infection in OMS, particularly in individuals and areas where antibiotic resistance is a major concern.

Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection

BACKGROUND

The immune response associated with periprosthetic joint infection (PJI) is an emerging but relatively unexplored topic. The aim of this study was to investigate immune cell infiltration in periprosthetic tissues and identify potential immune-related biomarkers.

METHODS

The GSE7103 dataset from the GEO database was selected as the data source. Differentially expressed genes (DEGs) and significant modular genes in weighted correlation network analysis (WGCNA) were identified. Functional enrichment analysis and transcription factor prediction were performed on the overlapping genes. Next, immune-related genes from the ImmPort database were matched. The protein-protein interaction (PPI) analysis was performed to identify hub genes. CIBERSORTx was used to evaluate the immune cell infiltration pattern. Spearman correlation analysis was used to evaluate the relationship between hub genes and immune cells.

RESULTS

A total of 667 DEGs were identified between PJI and control samples, and 1847 PJI-related module genes were obtained in WGCNA. Enrichment analysis revealed that the common genes were mainly enriched in immune and host defense-related terms. TFEC, SPI1, and TWIST2 were the top three transcription factors. Three hub genes, SDC1, MMP9, and IGF1, were identified in the immune-related PPI network. Higher levels of plasma cells, CD4+ memory resting T cells, follicular helper T cells, resting mast cells, and neutrophils were found in the PJI group, while levels of M0 macrophages were lower. Notably, the expression of all three hub genes correlated with the infiltration levels of seven types of immune cells.

CONCLUSION

The present study revealed immune infiltration signatures in the periprosthetic tissues of PJI patients. SDC1, MMP9, and IGF1 were potential immune-related biomarkers for PJI.

Periprosthetic joint infection and immunity: Current understanding of host-microbe interplay

Periprosthetic joint infection (PJI) is a major complication of total joint arthroplasty. Even with current treatments, failure rates are unacceptably high with a 5-year mortality rate of 26%. Majority of the literature in the field has focused on development of better biomarkers for diagnostics and treatment strategies including innovate antibiotic delivery systems, antibiofilm agents, and bacteriophages. Nevertheless, the role of the immune system, our first line of defense during PJI, is not well understood. Evidence of infection in PJI patients is found within circulation, synovial fluid, and tissue and include numerous cytokines, metabolites, antimicrobial peptides, and soluble receptors that are part of the PJI diagnosis workup. Macrophages, neutrophils, and myeloid-derived suppressor cells (MDSCs) are initially recruited into the joint by chemokines and cytokines produced by immune cells and bacteria and are activated by pathogen-associated molecular patterns. While these cells are efficient killers of planktonic bacteria by phagocytosis, opsonization, degranulation, and recruitment of adaptive immune cells, biofilm-associated bacteria are troublesome. Biofilm is not only a physical barrier for the immune system but also elicits effector functions. Additionally, bacteria have developed mechanisms to evade the immune system by inactivating effector molecules, promoting killing or anti-inflammatory effector cell phenotypes, and intracellular persistence and dissemination. Understanding these shortcomings and the mechanisms by which bacteria can subvert the immune system may open new approaches to better prepare our own immune system to combat PJI. Furthermore, preoperative immune system assessment and screening for dysregulation may aid in developing preventative interventions to decrease PJI incidence.

Mass spectrometry-based proteomic profiling of sonicate fluid differentiates Staphylococcus aureus periprosthetic joint infection from non-infectious failure: A pilot study

PURPOSE

This pilot study aimed to use proteomic profiling of sonicate fluid samples to compare host response during Staphylococcus aureus-associated periprosthetic joint infection (PJI) and non-infected arthroplasty failure (NIAF) and identify potential novel biomarkers differentiating the two.

EXPERIMENTAL DESIGN

In this pilot study, eight sonicate fluid samples (four from NIAF and four from S. aureus PJI) were studied. Samples were reduced, alkylated, and trypsinized overnight, followed by analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a high-resolution Orbitrap Eclipse mass spectrometer. MaxQuant software suite was used for protein identification, filtering, and label-free quantitation.

RESULTS

Principal component analysis of the identified proteins clearly separated S. aureus PJI and NIAF samples. Overall, 810 proteins were identified based on their detection in at least three out of four samples from each group; 35 statistically significant differentially abundant proteins (DAPs) were found (two-sample t-test p-values ≤0.05 and log2 fold-change values ≥2 or ≤-2). Gene ontology pathway analysis found that microbial defense responses, specifically those related to neutrophil activation, to be increased in S. aureus PJI compared to NIAF samples.

CONCLUSION AND CLINICAL RELEVANCE

Proteomic profiling of sonicate fluid using LC-MS/MS differentiated S. aureus PJI and NIAF in this pilot study. Further work is needed using a larger sample size and including non-S. aureus PJI and a diversty of NIAF-types.

Host Immune Regulation in Implant-Associated Infection (IAI): What Does the Current Evidence Provide Us to Prevent or Treat IAI?

The number of orthopedic implants for bone fixation and joint arthroplasty has been steadily increasing over the past few years. However, implant-associated infection (IAI), a major complication in orthopedic surgery, impacts the quality of life and causes a substantial economic burden on patients and societies. While research and study on IAI have received increasing attention in recent years, the failure rate of IAI has still not decreased significantly. This is related to microbial biofilms and their inherent antibiotic resistance, as well as the various mechanisms by which bacteria evade host immunity, resulting in difficulties in diagnosing and treating IAIs. Hence, a better understanding of the complex interactions between biofilms, implants, and host immunity is necessary to develop new strategies for preventing and controlling these infections. This review first discusses the challenges in diagnosing and treating IAI, followed by an extensive review of the direct effects of orthopedic implants, host immune function, pathogenic bacteria, and biofilms. Finally, several promising preventive or therapeutic alternatives are presented, with the hope of mitigating or eliminating the threat of antibiotic resistance and refractory biofilms in IAI.

Profiling the Immune Response to Periprosthetic Joint Infection and Non-Infectious Arthroplasty Failure

Arthroplasty failure is a major complication of joint replacement surgery. It can be caused by periprosthetic joint infection (PJI) or non-infectious etiologies, and often requires surgical intervention and (in select scenarios) resection and reimplantation of implanted devices. Fast and accurate diagnosis of PJI and non-infectious arthroplasty failure (NIAF) is critical to direct medical and surgical treatment; differentiation of PJI from NIAF may, however, be unclear in some cases. Traditional culture, nucleic acid amplification tests, metagenomic, and metatranscriptomic techniques for microbial detection have had success in differentiating the two entities, although microbiologically negative apparent PJI remains a challenge. Single host biomarkers or, alternatively, more advanced immune response profiling-based approaches may be applied to differentiate PJI from NIAF, overcoming limitations of microbial-based detection methods and possibly, especially with newer approaches, augmenting them. In this review, current approaches to arthroplasty failure diagnosis are briefly overviewed, followed by a review of host-based approaches for differentiation of PJI from NIAF, including exciting futuristic combinational multi-omics methodologies that may both detect pathogens and assess biological responses, illuminating causes of arthroplasty failure.

Sonicate Fluid Cellularity Predicted by Transcriptomic Deconvolution Differentiates Infectious from Non-Infectious Arthroplasty Failure

BACKGROUND

Although cellularity is traditionally assessed morphologically, deep sequencing approaches being used for microorganism detection may be able to provide information about cellularity. We hypothesized that cellularity predicted using CIBERSORTx (Stanford University), a transcriptomic-based cellular deconvolution tool, would differentiate between infectious and non-infectious arthroplasty failure.

METHODS

CIBERSORTx-derived cellularity profiles of 93 sonicate fluid samples, including 53 from subjects who underwent failed arthroplasties due to periprosthetic joint infection (PJI) (abbreviated for the purpose of this study as PJIF) and 40 from subjects who had undergone non-infectious arthroplasty failure (abbreviated NIAF) that had been subjected to bulk RNA sequencing were evaluated.

RESULTS

Samples from PJIF and NIAF subjects were differentially clustered by principal component analysis based on the cellularity profile. Twelve of the 22 individual predicted cellular fractions were differentially expressed in the PJIF cases compared with the NIAF cases, including increased predicted neutrophils (mean and standard error, 9.73% ± 1.06% and 0.81% ± 0.60%), activated mast cells (17.12% ± 1.51% and 4.11% ± 0.44%), and eosinophils (1.96% ± 0.37% and 0.42% ± 0.21%), and decreased predicted M0 macrophages (21.33% ± 1.51% and 39.75% ± 2.45%), M2 macrophages (3.56% ± 0.52% and 8.70% ± 1.08%), and regulatory T cells (1.57% ± 0.23% and 3.20% ± 0.34%). The predicted total granulocyte fraction was elevated in the PJIF cases (32.97% ± 2.13% and 11.76% ± 1.61%), and the samples from the NIAF cases had elevated predicted total macrophage and monocyte (34.71% ± 1.71% and 55.34% ± 2.37%) and total B cell fractions (5.89% ± 0.30% and 8.62% ± 0.86%). Receiver operating characteristic curve analysis identified predicted total granulocytes, neutrophils, and activated mast cells as highly able to differentiate between the PJIF cases and the NIAF cases. Within the PJIF cases, the total granulocyte, total macrophage and monocyte, M0 macrophage, and M2 macrophage fractions were differentially expressed in Staphylococcus aureus compared with Staphylococcus epidermidis -associated samples. Within the NIAF cases, the predicted total B cell, naïve B cell, plasma cell, and M2 macrophage fractions were differentially expressed among different causes of failure.

CONCLUSIONS

CIBERSORTx can predict the cellularity of sonicate fluid using transcriptomic data, allowing for the evaluation of the underlying immune response during the PJIF and NIAF cases, without a need to phenotypically assess cell composition.

Cell-free Deoxyribonucleic Acid: A Potential Biomarker of Chronic Periprosthetic Knee Joint Infection

BACKGROUND

The correct diagnosis of a chronic periprosthetic joint infection (PJI) is a major challenge in clinical practice, with the "gold standard" for diagnosis yet to be established. Synovial fluid analysis has been proven to be a useful tool for that purpose. Cell-free DNA (cf-DNA) levels have been shown to be increased in several conditions such as cancer, trauma, and sepsis. Therefore, this study was designed to evaluate the potential of synovial fluid cf-DNA quantification for the diagnosis of chronic periprosthetic infections following total knee arthroplasty.

METHODS

A prospective study with patients undergoing total knee arthroplasty revision surgery for any indication was performed. PJI diagnosis was defined according to the Second International Consensus Meeting on Musculoskeletal Infection (2018) criteria. The study cohort consisted of 26 patients classified as infected and 40 as noninfected. Synovial fluid cf-DNA direct quantification by fluorescent staining was made. Sensitivity, specificity, and receiver operating characteristic curve were calculated.

RESULTS

The cf-DNA levels were significantly higher in patients who had PJIs (122.5 ± 57.2 versus 4.6 ± 2.8 ng/μL, P < .0001). With a cutoff of 15 ng/μL, the area under the receiver operating characteristic, sensitivity, and specificity of cf-DNA were 0.978, 96.2%, and 100%, respectively.

CONCLUSION

The present study has shown that cf-DNA is increased in synovial fluid of patients who have chronic PJIs. It is a promising biomarker for knee PJI diagnosis and further studies are needed to confirm its utility.

Soluble Pecam-1 as a Biomarker in Periprosthetic Joint Infection

A reliable workup with regard to a single diagnostic marker indicating periprosthetic joint infection (PJI) with sufficient sensitivity and specificity is still missing. The immunologically reactive molecule Pecam-1 is shed from the T-cell surface upon activation via proinflammatory signaling, e.g., triggered by specific pathogens. We hypothesized that soluble Pecam-1 (sPecam-1) can hence function as a biomarker of PJI. Fifty-eight patients were prospectively enrolled and assigned to one of the respective treatment groups (native knees prior to surgery, aseptic, and septic total knee arthroplasty (TKA) revision surgeries). Via synovial sample acquisition and ELISA testing, a database on local sPecam-1 levels was established. We observed a significantly larger quantity of sPecam-1 in septic (n = 22) compared to aseptic TKA revision surgeries (n = 20, p ≤ 0.001). Furthermore, a significantly larger amount of sPecam-1 was found in septic and aseptic revisions compared to native joints (n = 16, p ≤ 0.001). Benchmarking it to the gold standard showed a high predictive power for the detection of PJI. Local sPecam-1 levels correlated to the infection status of the implant, and thus bear a strong potential to act as a biomarker of PJI. While a clear role of sPecam-1 in infection could be demonstrated, the underlying mechanism of the molecule’s natural function needs to be further unraveled.