Mortality Risk Profiling of Staphylococcus aureus Bacteremia by Multi-omic Serum Analysis Reveals Early Predictive and Pathogenic Signatures

Multi-omic signatures of host response associated with presence, type, and outcome of enterococcal bacteremia

Despite the prevalence and severity of enterococcal bacteremia (EcB), the mechanisms underlying systemic host responses to the disease remain unclear. Here, we present an extensive study that profiles molecular differences in plasma from EcB patients using an unbiased multi-omics approach. We performed shotgun proteomics and metabolomics on 105 plasma samples, including those from EcB patients and healthy volunteers. Comparison between healthy volunteer and EcB-infected patient samples revealed significant disparities in proteins and metabolites involved in the acute phase response, inflammatory processes, and cholestasis. Several features distinguish these two groups with remarkable accuracy. Cross-referencing EcB signatures with those of Staphylococcus aureus bacteremia revealed shared reductions in cholesterol metabolism proteins and differing responses in platelet alpha granule and neutrophil-associated proteins. Characterization of Enterococcus isolates derived from patients facilitated a nuanced comparison between EcB caused by Enterococcus faecalis and Enterococcus faecium, uncovering reduced immunoglobulin abundances in E. faecium cases and features capable of distinguishing the underlying microbe. Leveraging extensive patient metadata, we now have identified features associated with mortality or survival, revealing significant multi-omic differences and pinpointing histidine-rich glycoprotein and fetuin-B as features capable of distinguishing survival status with excellent accuracy. Altogether, this study aims to culminate in the creation of objective risk stratification algorithms-a pivotal step toward enhancing patient management and care. To facilitate the exploration of this rich data source, we provide a user-friendly interface at https://gonzalezlab.shinyapps.io/EcB_multiomics/.

IMPORTANCE

Enterococcus infections have emerged as the second most common nosocomial infection, with enterococcal bacteremia (EcB) contributing to thousands of patient deaths annually. To address a lack of detailed understanding regarding the specific systemic response to EcB, we conducted a comprehensive multi-omic evaluation of the systemic host response observed in patient plasma. Our findings reveal significant features in the metabolome and proteome associated with the presence of infection, species differences, and survival outcome. We identified features capable of discriminating EcB infection from healthy states and survival from mortality with excellent accuracy, suggesting potential practical clinical utility. However, our study also established that systemic features to distinguish Enterococcus faecalis from Enterococcus faecium EcB show only a moderate degree of discriminatory accuracy, unlikely to significantly improve upon current diagnostic methods. Comparisons of differences in the plasma proteome relative to healthy samples between bacteremia caused by Enterococcus and Staphylococcus aureus suggest the presence of bacteria-specific responses alongside conserved inflammatory reactions.

System-based insights into parasitological and clinical treatment failure in Chagas disease

Infectious disease treatment success requires symptom resolution (clinical treatment success), which often but not always involves pathogen clearance. Both of these treatment goals face disease-specific and general challenges. In this review, we summarize the current state of knowledge in mechanisms of clinical and parasitological treatment failure in the context of Chagas disease, a neglected tropical disease causing cardiac and gastrointestinal symptoms. Parasite drug resistance and persistence, drug pharmacokinetics and dynamics, as well as persistently altered host immune responses and tissue damage are the most common reasons for Chagas disease treatment failure. We discuss the therapeutics that failed before regulatory approval, limitations of current therapeutic options and new treatment strategies to overcome persistent parasites, inflammatory responses, and metabolic alterations. Large-scale omics analyses were critical in generating these insights and will continue to play a prominent role in addressing the challenges still facing Chagas disease drug treatment.

Combined urine proteomics and metabolomics analysis for the diagnosis of pulmonary tuberculosis

BACKGROUND

Tuberculosis (TB) diagnostic monitoring is paramount to clinical decision-making and the host biomarkers appears to play a significant role. The currently available diagnostic technology for TB detection is inadequate. In the present study, we aimed to identify biomarkers for diagnosis of pulmonary tuberculosis (PTB) using urinary metabolomic and proteomic analysis.

METHODS

In the study, urine from 40 PTB, 40 lung cancer (LCA), 40 community-acquired pneumonia (CAP) patients and 40 healthy controls (HC) was collected. Biomarker panels were selected based on random forest (RF) analysis.

RESULTS

A total of 3,868 proteins and 1,272 annotated metabolic features were detected using pairwise comparisons. Using AUC ≥ 0.80 as a cutoff value, we picked up five protein biomarkers for PTB diagnosis. The five-protein panel yielded an AUC for PTB/HC, PTB/CAP and PTB/LCA of 0.9840, 0.9680 and 0.9310, respectively. Additionally, five metabolism biomarkers were selected for differential diagnosis purpose. By employment of the five-metabolism panel, we could differentiate PTB/HC at an AUC of 0.9940, PTB/CAP of 0.8920, and PTB/LCA of 0.8570.

CONCLUSION

Our data demonstrate that metabolomic and proteomic analysis can identify a novel urine biomarker panel to diagnose PTB with high sensitivity and specificity. The receiver operating characteristic curve analysis showed that it is possible to perform non-invasive clinical diagnoses of PTB through these urine biomarkers.

Pathobiont-driven antibody sialylation through IL-10 undermines vaccination

The pathobiont Staphylococcus aureus (Sa) induces nonprotective antibody imprints that underlie ineffective staphylococcal vaccination. However, the mechanism by which Sa modifies antibody activity is not clear. Herein, we demonstrate that IL-10 is the decisive factor that abrogates antibody protection in mice. Sa-induced B10 cells drive antigen-specific vaccine suppression that affects both recalled and de novo developed B cells. Released IL-10 promotes STAT3 binding upstream of the gene encoding sialyltransferase ST3gal4 and increases its expression by B cells, leading to hyper-α2,3sialylation of antibodies and loss of protective activity. IL-10 enhances α2,3sialylation on cell-wall-associated IsdB, IsdA, and MntC antibodies along with suppression of the respective Sa vaccines. Consistent with mouse findings, human anti-Sa antibodies as well as anti-pseudomonal antibodies from cystic fibrosis subjects (high IL-10) are hypersialylated, compared with anti-Streptococcus pyogenes and pseudomonal antibodies from normal individuals. Overall, we demonstrate a pathobiont-centric mechanism that modulates antibody glycosylation through IL-10, leading to loss of staphylococcal vaccine efficacy.

Bioinspired peptide/polyamino acid assemblies as quorum sensing inhibitors for the treatment of bacterial infections

Insufficient development of new antibiotics and the rise in antimicrobial resistance are putting the world at risk of losing curative medicines against bacterial infection. Quorum sensing is a type of cellular signaling for cell-to-cell communication that plays critical roles in biofilm formation and antimicrobial resistance, and is expected to be a new type of effective target for drug resistant bacteria. In this review we highlight recent advances in bioinspired peptide/polyamino acid assemblies as quorum sensing inhibitors across various microbial communities. In addition, existing obstacles and future development directions of peptide/polyamino acid assemblies as quorum sensing inhibitors were proposed for broader clinical applications and translations. Overall, quorum sensing peptide/polyamino acid assemblies could be vital tools against bacterial infection and antimicrobial resistance.

Potential mechanism of CARD16 protein action and susceptibility to sepsis in the elderly infected population: Through transcriptome analysis of blood

As global aging accelerates, the super-elderly population is at higher risk of infectious diseases, especially sepsis, a condition that may be associated with declining immune system function and abnormal inflammatory responses. The aim of this study was to investigate the role of CARD16 protein in sepsis susceptibility in the elderly population and its potential mechanism, and to reveal the expression characteristics of CARD16-related genes through blood transcriptomic analysis. Transcriptome sequencing was conducted on peripheral blood samples obtained from patients suffering from senile sepsis, along with samples from a healthy elderly control group. To examine the differences in gene expression, bioinformatics techniques were employed to compare the expression levels of CARD16-related genes between the two groups. Additionally, a comprehensive analysis was performed on the downstream inflammatory pathways and cytokines that are regulated by CARD16.The findings from the transcriptome analysis indicated that the expression of CARD16 was markedly upregulated in the cohort of patients experiencing hypersenile sepsis. This upregulation was associated with an increase in a variety of pro-inflammatory factors. Further network analysis suggested that CARD16 may potentiate the inflammatory response by modulating the NF-κB signaling pathway, which could consequently heighten the patients' vulnerability to sepsis.In comparison to the healthy elderly control group, the levels of anti-inflammatory genes in the super-elderly cohort were found to be significantly diminished. This observation points to a notable imbalance in immune regulation, further emphasizing the altered immune response in individuals with senile sepsis.

Effective xanthine oxidase inhibitor urate lowering therapy in gout is linked to an emergent serum protein interactome of complement and inflammation modulators

Urate-lowering treatment (ULT) to target with xanthine oxidase inhibitors (XOIs) paradoxically causes early increase in gouty arthritis flares. Because delayed reduction in flare burden is mechanistically unclear, we tested for ULT inflammation responsiveness markers. Unbiased proteomics analyzed blood samples (baseline, 48 weeks ULT) in two, independent ULT out trial cohorts (n = 19, n = 30). STRING-db and multivariate analyses supplemented determinations of altered proteins via Wilcoxon matched pairs signed rank testing in XOI ULT responders. Mechanistic studies characterized proteomes of cultured XOI-treated murine bone marrow macrophages (BMDMs). At 48 weeks ULT, serum urate normalized in all gout patients, and flares declined in association with significantly altered proteins (p < 0.05) in clustering and proteome networks in sera and peripheral blood mononuclear cells. Sera demonstrated altered complement activation and regulatory gene ontology biologic processes. In both cohorts, a treatment-emergent serum interactome included key gouty inflammation mediators (C5, IL-1B, CXCL8, IL6). Last, febuxostat treatment decreased complement activation biologic process proteins in cultured BMDMs. Reduced gout flares are linked with a XOI treatment-emergent serum protein interactome that includes inflammation regulators, associated with altered complement activation and regulatory biologic processes. Serum and leukocyte proteomics could help identify when gouty inflammatory processes begin to subside in response to ULT.Trial Registration: ClinicalTrials.gov Identifier NCT02579096, posted October 19, 2015.

Shaping cardiac destiny: the role of post-translational modifications on endoplasmic reticulum - mitochondria crosstalk in cardiac remodeling

Cardiac remodeling is a shared pathological change in most cardiovascular diseases. Encompassing both adaptive physiological responses and decompensated pathological changes. Anatomically, atrial remodeling is primarily caused by atrial fibrillation, whereas ventricular remodeling is typically induced by myocardial infarction, hypertension, or cardiomyopathy. Mitochondria, the powerhouse of cardiomyocytes, collaborate with other organelles such as the endoplasmic reticulum to control a variety of pathophysiological processes such as calcium signaling, lipid transfer, mitochondrial dynamics, biogenesis, and mitophagy. This mechanism is proven to be essential for cardiac remodeling. Post-translational modifications can regulate intracellular signaling pathways, gene expression, and cellular stress responses in cardiac cells by modulating protein function, stability, and interactions, consequently shaping the myocardial response to injury and stress. These modifications, in particular phosphorylation, acetylation, and ubiquitination, are essential for the regulation of the complex molecular pathways that underlie cardiac remodeling. This review provides a comprehensive overview of the crosstalk between the endoplasmic reticulum and mitochondria during cardiac remodeling, focusing on the regulatory effects of various post-translational modifications on these interactions.

Metagenomic next generation sequencing of bronchoalveolar lavage fluids for the identification of pathogens in patients with pulmonary infection: A retrospective study

Due to the limitations of traditional laboratory methods (TMs), identification of causative pathogens of numerous pulmonary infections (PIs) remains difficult. This study evaluated the value of metagenomic next generation sequencing (mNGS) in the identification of various respiratory pathogens. A total of 207 patients with TMs and mNGS data were collected for this retrospective study. TMs included sputum culture, blood, and bronchoalveolar lavage fluid (BALF) analysis, or polymerase chain reaction analysis of throat swabs. Otherwise, BALF was collected and analyzed using mNGS. For bacterial pathogens, sensitivities of mNGS as compared to TMs were 76.74 % and 58.14 % (P=0.012). For fungal pathogens, the detection rate of mNGS sensitivity was higher as compared to that of TMs (93.68 % vs 22.11 %; P<0.001). The positive predictive value and negative predictive value were also greater for mNGS. Use of mNGS for BALF analysis offers good specificity and thus facilitates to the clinical diagnosis of PIs.

Factors Affecting Recurrent Staphylococcus aureus Bacteremia Among Older Patients in Rural Community Hospitals: A Retrospective Cohort Study

Introduction Staphylococcus aureus bacteremia (SAB) poses a significant health risk, particularly among adults over 65 years old, due to age-related vulnerabilities and comorbidities. Recurrent SAB is associated with increased morbidity, prolonged hospitalizations, and higher healthcare costs, necessitating the identification of risk factors that contribute to these recurrent infections. Methods A retrospective cohort study was conducted at a rural community hospital to identify factors associated with recurrent SAB in older patients. Data were extracted from electronic medical records of patients diagnosed with SAB between April 2016 and December 2023. Multivariate logistic regression was employed to analyze the relationship between recurrent SAB and potential risk factors, including age, sex, BMI, dependency on Japanese long-term health insurance, and comorbidities. Results Among 99 patients with SAB, 36 (36.4%) experienced recurrence. Higher BMI was significantly associated with recurrent SAB (OR: 1.15, 95% CI: 1.01-1.31, p = 0.036), while dependency on long-term care was associated with a lower risk of recurrence (OR: 0.20, 95% CI: 0.06-0.64, p = 0.007). Age and sex did not show significant associations with recurrence. Conclusion This study identified higher BMI as a risk factor for recurrent SAB in older patients, while dependency on long-term care was protective. These findings highlight the need for targeted management strategies for patients with higher BMI to prevent recurrent SAB. Further research is needed to explore these associations and confirm their relevance in other clinical settings.

Discovery of Antimicrobial Lysins from the "Dark Matter" of Uncharacterized Phages Using Artificial Intelligence

The rapid rise of antibiotic resistance and slow discovery of new antibiotics have threatened global health. While novel phage lysins have emerged as potential antibacterial agents, experimental screening methods for novel lysins pose significant challenges due to the enormous workload. Here, the first unified software package, namely DeepLysin, is developed to employ artificial intelligence for mining the vast genome reservoirs ("dark matter") for novel antibacterial phage lysins. Putative lysins are computationally screened from uncharacterized Staphylococcus aureus phages and 17 novel lysins are randomly selected for experimental validation. Seven candidates exhibit excellent in vitro antibacterial activity, with LLysSA9 exceeding that of the best-in-class alternative. The efficacy of LLysSA9 is further demonstrated in mouse bloodstream and wound infection models. Therefore, this study demonstrates the potential of integrating computational and experimental approaches to expedite the discovery of new antibacterial proteins for combating increasing antimicrobial resistance.

Nucleic acid-based nanotherapeutics for treating sepsis and associated organ injuries

In recent years, gene therapy has been made possible with the success of nucleic acid drugs against sepsis and its related organ dysfunction. Therapeutics based on nucleic acids such as small interfering RNAs (siRNAs), microRNAs (miRNAs), messenger RNAs (mRNAs), and plasmid DNAs (pDNAs) guarantee to treat previously undruggable diseases. The advantage of nucleic acid-based therapy against sepsis lies in the development of nanocarriers, achieving targeted and controlled gene delivery for improved efficacy with minimal adverse effects. Entrapment into nanocarriers also ameliorates the poor cellular uptake of naked nucleic acids. In this study, we discuss the current state of the art in nanoparticles for nucleic acid delivery to treat hyperinflammation and apoptosis associated with sepsis. The optimized design of the nanoparticles through physicochemical property modification and ligand conjugation can target specific organs-such as lung, heart, kidney, and liver-to mitigate multiple sepsis-associated organ injuries. This review highlights the nanomaterials designed for fabricating the anti-sepsis nanosystems, their physicochemical characterization, the mechanisms of nucleic acid-based therapy in working against sepsis, and the potential for promoting the therapeutic efficiency of the nucleic acids. The current investigations associated with nanoparticulate nucleic acid application in sepsis management are summarized in this paper. Noteworthily, the potential application of nanotherapeutic nucleic acids allows for a novel strategy to treat sepsis. Further clinical studies are required to confirm the findings in cell- and animal-based experiments. The capability of large-scale production and reproducibility of nanoparticle products are also critical for commercialization. It is expected that numerous anti-sepsis possibilities will be investigated for nucleic acid-based nanotherapeutics in the future.

Dysregulated proteasome activity and steroid hormone biosynthesis are associated with mortality among patients with acute COVID-19

The persistence of coronavirus disease 2019 (COVID-19)-related hospitalization severely threatens medical systems worldwide and has increased the need for reliable detection of acute status and prediction of mortality. We applied a systems biology approach to discover acute-stage biomarkers that could predict mortality. A total 247 plasma samples were collected from 103 COVID-19 (52 surviving COVID-19 patients and 51 COVID-19 patients with mortality), 51 patients with other infectious diseases (IDCs) and 41 healthy controls (HCs). Paired plasma samples were obtained from survival COVID-19 patients within 1 day after hospital admission and 1-3 days before discharge. There were clear differences between COVID-19 patients and controls, as well as substantial differences between the acute and recovery phases of COVID-19. Samples from patients in the acute phase showed suppressed immunity and decreased steroid hormone biosynthesis, as well as elevated inflammation and proteasome activation. These findings were validated by enzyme-linked immunosorbent assays and metabolomic analyses in a larger cohort. Moreover, excessive proteasome activity was a prominent signature in the acute phase among patients with mortality, indicating that it may be a key cause of poor prognosis. Based on these features, we constructed a machine learning panel, including four proteins [C-reactive protein (CRP), proteasome subunit alpha type (PSMA)1, PSMA7, and proteasome subunit beta type (PSMB)1)] and one metabolite (urocortisone), to predict mortality among COVID-19 patients (area under the receiver operating characteristic curve: 0.976) on the first day of hospitalization. Our systematic analysis provides a novel method for the early prediction of mortality in hospitalized COVID-19 patients.

Integrative multi-omics analysis unravels the host response landscape and reveals a serum protein panel for early prognosis prediction for ARDS

BACKGROUND

The multidimensional biological mechanisms underpinning acute respiratory distress syndrome (ARDS) continue to be elucidated, and early biomarkers for predicting ARDS prognosis are yet to be identified.

METHODS

We conducted a multicenter observational study, profiling the 4D-DIA proteomics and global metabolomics of serum samples collected from patients at the initial stage of ARDS, alongside samples from both disease control and healthy control groups. We identified 28-day prognosis biomarkers of ARDS in the discovery cohort using the LASSO method, fold change analysis, and the Boruta algorithm. The candidate biomarkers were validated through parallel reaction monitoring (PRM) targeted mass spectrometry in an external validation cohort. Machine learning models were applied to explore the biomarkers of ARDS prognosis.

RESULTS

In the discovery cohort, comprising 130 adult ARDS patients (mean age 72.5, 74.6% male), 33 disease controls, and 33 healthy controls, distinct proteomic and metabolic signatures were identified to differentiate ARDS from both control groups. Pathway analysis highlighted the upregulated sphingolipid signaling pathway as a key contributor to the pathological mechanisms underlying ARDS. MAP2K1 emerged as the hub protein, facilitating interactions with various biological functions within this pathway. Additionally, the metabolite sphingosine 1-phosphate (S1P) was closely associated with ARDS and its prognosis. Our research further highlights essential pathways contributing to the deceased ARDS, such as the downregulation of hematopoietic cell lineage and calcium signaling pathways, contrasted with the upregulation of the unfolded protein response and glycolysis. In particular, GAPDH and ENO1, critical enzymes in glycolysis, showed the highest interaction degree in the protein-protein interaction network of ARDS. In the discovery cohort, a panel of 36 proteins was identified as candidate biomarkers, with 8 proteins (VCAM1, LDHB, MSN, FLG2, TAGLN2, LMNA, MBL2, and LBP) demonstrating significant consistency in an independent validation cohort of 183 patients (mean age 72.6 years, 73.2% male), confirmed by PRM assay. The protein-based model exhibited superior predictive accuracy compared to the clinical model in both the discovery cohort (AUC: 0.893 vs. 0.784; Delong test, P < 0.001) and the validation cohort (AUC: 0.802 vs. 0.738; Delong test, P  = 0.008).

INTERPRETATION

Our multi-omics study demonstrated the potential biological mechanism and therapy targets in ARDS. This study unveiled several novel predictive biomarkers and established a validated prediction model for the poor prognosis of ARDS, offering valuable insights into the prognosis of individuals with ARDS.

Tibial cortex transverse transport surgery improves wound healing in patients with severe type 2 DFUs by activating a systemic immune response: a cross-sectional study

BACKGROUND

Tibial cortex transverse transport (TTT) surgery has become an ideal treatment for patients with type 2 severe diabetic foot ulcerations (DFUs) while conventional treatments are ineffective. Based on our clinical practice experience, the protective immune response from TTT surgery may play a role against infections to promote wound healing in patients with DFUs. Therefore, this research aimed to systematically study the specific clinical efficacy and the mechanism of TTT surgery.

MATERIALS AND METHODS

Between June 2022 and September 2023, 68 patients with type 2 severe DFUs were enrolled and therapized by TTT surgery in this cross-sectional and experimental study. Major clinical outcomes including limb salvage rate and antibiotics usage rate were investigated. Ten clinical characteristics and laboratory features of glucose metabolism and kidney function were statistically analyzed. Blood samples from 6 key time points of TTT surgery were collected for label-free proteomics and clinical immune biomarker analysis. Besides, tissue samples from 3 key time points were for spatially resolved metabolomics and transcriptomics analysis, as well as applied to validate the key TTT-regulated molecules by RT-qPCR.

RESULTS

Notably, 64.7% of patients did not use antibiotics during the entire TTT surgery. TTT surgery can achieve a high limb salvage rate of 92.6% in patients with unilateral or bilateral DFUs. Pathway analysis of a total of 252 differentially expressed proteins (DEPs) from the proteomic revealed that the immune response induced by TTT surgery at different stages was first comprehensively verified through multi-omics combined with immune biomarker analysis. The function of upward transport was activating the systemic immune response, and wound healing occurs with downward transport. The spatial metabolic characteristics of skin tissue from patients with DFUs indicated downregulated levels of stearoylcarnitine and the glycerophospholipid metabolism pathway in skin tissue from patients with severe DFUs. Finally, the expressions of PRNP (prion protein) to activate the immune response, PLCB3 (PLCB3, phospholipase C beta 3) and VE-cadherin to play roles in neovascularization, and PPDPF (pancreatic progenitor cell differentiation and proliferation factor), LAMC2 (laminin subunit gamma 2) and SPRR2G (small proline rich protein 2G) to facilitate the developmental process mainly keratinocyte differentiation were statistically significant in skin tissues through transcriptomic and RT-qPCR analysis.

CONCLUSION

Tibial cortex transverse transport (TTT) surgery demonstrates favorable outcomes for patients with severe type 2 DFUs by activating a systemic immune response, contributing to anti-infection, ulcer recurrence, and the limb salvage rate for unilateral or bilateral DFUs. The specific clinical immune responses, candidate proteins, genes, and metabolic characteristics provide directions for in-depth mechanistic research on TTT surgery. Further research and public awareness are needed to optimize TTT surgery in patients with severe type 2 DFUs.

Multimodal nanoimmunotherapy engages neutrophils to eliminate Staphylococcus aureus infections

The increasing prevalence of antimicrobial resistance in Staphylococcus aureus necessitates alternative therapeutic approaches. Neutrophils play a crucial role in the fight against S. aureus but suffer from deficiencies in function leading to increased infection. Here we report a nanoparticle-mediated immunotherapy aimed at potentiating neutrophils to eliminate S. aureus. The nanoparticles consist of naftifine, haemoglobin (Hb) and a red blood cell membrane coating. Naftifine disrupts staphyloxanthin biosynthesis, Hb reduces bacterial hydrogen sulfide levels and the red blood cell membrane modifies bacterial lipid composition. Collectively, the nanoparticles can sensitize S. aureus to host oxidant killing. Furthermore, in the infectious microenvironment, Hb triggers lipid peroxidation in S. aureus, promoting neutrophil chemotaxis. Oxygen supplied by Hb can also significantly enhance the bactericidal capability of the recruited neutrophils by restoring neutrophil respiratory burst via hypoxia relief. This multimodal nanoimmunotherapy demonstrates excellent therapeutic efficacy in treating antimicrobial-resistant S. aureus persisters, biofilms and S. aureus-induced infection in mice.

The Complex Intracellular Lifecycle of Staphylococcus aureus Contributes to Reduced Antibiotic Efficacy and Persistent Bacteremia

Staphylococcus aureus bacteremia continues to be associated with significant morbidity and mortality, despite improvements in diagnostics and management. Persistent infections pose a major challenge to clinicians and have been consistently shown to increase the risk of mortality and other infectious complications. S. aureus, while typically not considered an intracellular pathogen, has been proven to utilize an intracellular niche, through several phenotypes including small colony variants, as a means for survival that has been linked to chronic, persistent, and recurrent infections. This intracellular persistence allows for protection from the host immune system and leads to reduced antibiotic efficacy through a variety of mechanisms. These include antimicrobial resistance, tolerance, and/or persistence in S. aureus that contribute to persistent bacteremia. This review will discuss the challenges associated with treating these complicated infections and the various methods that S. aureus uses to persist within the intracellular space.

Effective xanthine oxidase inhibitor urate lowering therapy in gout is linked to an emergent serum protein interactome of complement activation and inflammation modulators

Background

Urate-lowering treatment (ULT) to target with xanthine oxidase inhibitors (XOIs) paradoxically causes early increase in gouty arthritis flares. Because delayed reduction in flare burden is mechanistically unclear, we tested for ULT inflammation responsiveness markers.

Methods

Unbiased proteomics analyzed blood samples (baseline, 48 weeks ULT) in two, independent ULT out trial cohorts (n = 19, n = 30). STRING-db and multivariate analyses supplemented determinations of altered proteins via Wilcoxon matched pairs signed rank testing in XOI ULT responders. Mechanistic studies characterized proteomes of cultured XOI-treated murine bone marrow macrophages (BMDMs).

Results

At 48 weeks ULT, serum urate normalized in all gout patients, and flares declined, with significantly altered proteins (p < 0.05) in clustering and proteome networks in sera and peripheral blood mononuclear cells. Serum proteome changes included decreased complement C8 heterotrimer C8A and C8G chains and chemokine PPBP/CXCL7, and increased urate crystal phagocytosis inhibitor sCD44. In both cohorts, a treatment-emergent serum interactome included key gouty inflammation mediators (C5, IL-1B, CXCL8, IL6). Last, febuxostat inhibited complement activation pathway proteins in cultured BMDMs.

Conclusions

Reduced gout flares are kinked with a XOI-treatment emergent complement- and inflammation-regulatory serum protein interactome. Serum and leukocyte proteomes could help identify onset of anti-inflammatory responsiveness to ULT in gout.

Trial registration

ClinicalTrials.gov Identifier: NCT02579096, posted October 19, 2015.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Targeting staphylococcal enterotoxin B binding to CD28 as a new strategy for dampening superantigen-mediated intestinal epithelial barrier dysfunctions

Staphylococcus aureus is a gram-positive bacterium that may cause intestinal inflammation by secreting enterotoxins, which commonly cause food-poisoning and gastrointestinal injuries. Staphylococcal enterotoxin B (SEB) acts as a superantigen (SAg) by binding in a bivalent manner the T-cell receptor (TCR) and the costimulatory receptor CD28, thus stimulating T cells to produce large amounts of inflammatory cytokines, which may affect intestinal epithelial barrier integrity and functions. However, the role of T cell-mediated SEB inflammatory activity remains unknown. Here we show that inflammatory cytokines produced by T cells following SEB stimulation induce dysfunctions in Caco-2 intestinal epithelial cells by promoting actin cytoskeleton remodelling and epithelial cell-cell junction down-regulation. We also found that SEB-activated inflammatory T cells promote the up-regulation of epithelial-mesenchymal transition transcription factors (EMT-TFs) in a nuclear factor-κB (NF-κB)- and STAT3-dependent manner. Finally, by using a structure-based design approach, we identified a SEB mimetic peptide (pSEB116-132) that, by blocking the binding of SEB to CD28, dampens inflammatory-mediated dysregulation of intestinal epithelial barrier.

Clinical practice of sepsis-induced immunosuppression: Current immunotherapy and future options

Sepsis is a potentially fatal condition characterized by the failure of one or more organs due to a disordered host response to infection. The development of sepsis is closely linked to immune dysfunction. As a result, immunotherapy has gained traction as a promising approach to sepsis treatment, as it holds the potential to reverse immunosuppression and restore immune balance, thereby improving the prognosis of septic patients. However, due to the highly heterogeneous nature of sepsis, it is crucial to carefully select the appropriate patient population for immunotherapy. This review summarizes the current and evolved treatments for sepsis-induced immunosuppression to enhance clinicians' understanding and practical application of immunotherapy in the management of sepsis.

Peptidomic analysis of endogenous and bacterial protease activity in human plasma and wound fluids

Endogenous and bacterial proteases play important roles in wound healing and infection. Analysis of alterations in the low-molecular-weight peptidome by individual enzymes could therefore provide insight into proteolytic events occurring in wounds and may aid in the discovery of biomarkers. Using liquid chromatography with tandem mass spectrometry, we characterized the peptidome of plasma and acute wound fluids digested ex vivo with human (neutrophil elastase and cathepsin G) and bacterial proteases (Pseudomonas aeruginosa LasB and Staphyloccocus aureus V8). We identified over 100 protein targets for each enzyme and characterized enzyme specific peptides and cleavage patterns. Moreover, we found unique peptide regions in V8 digested samples that were also present in dressing extracts from S. aureus infected wounds. Finally, the work indicates that peptidomic analysis of qualitative differences of proteolytic activity of individual enzymes may aid in the discovery of potential diagnostic biomarkers for wound healing status.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Study Highlights

The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

Bacteriophage therapy for drug-resistant Staphylococcus aureus infections

Drug-resistant Staphylococcus aureus stands as a prominent pathogen in nosocomial and community-acquired infections, capable of inciting various infections at different sites in patients. This includes Staphylococcus aureus bacteremia (SaB), which exhibits a severe infection frequently associated with significant mortality rate of approximately 25%. In the absence of better alternative therapies, antibiotics is still the main approach for treating infections. However, excessive use of antibiotics has, in turn, led to an increase in antimicrobial resistance. Hence, it is imperative that new strategies are developed to control drug-resistant S. aureus infections. Bacteriophages are viruses with the ability to infect bacteria. Bacteriophages, were used to treat bacterial infections before the advent of antibiotics, but were subsequently replaced by antibiotics due to limited theoretical understanding and inefficient preparation processes at the time. Recently, phages have attracted the attention of many researchers again because of the serious problem of antibiotic resistance. This article provides a comprehensive overview of phage biology, animal models, diverse clinical case treatments, and clinical trials in the context of drug-resistant S. aureus phage therapy. It also assesses the strengths and limitations of phage therapy and outlines the future prospects and research directions. This review is expected to offer valuable insights for researchers engaged in phage-based treatments for drug-resistant S. aureus infections.

MOCCal: A Multiomic CCS Calibrator for Traveling Wave Ion Mobility Mass Spectrometry

Ion mobility mass spectrometry (IM-MS) is a rapid, gas-phase separation technology that can resolve ions on the basis of their size-to-charge and mass-to-charge ratios. Since each class of biomolecule has a unique relationship between size and mass, IM-MS spectra of complex biological samples are organized into trendlines that each contain one type of biomolecule (i.e., lipid, peptide, metabolite). These trendlines can aid in the identification of unknown ions by providing a general classification, while more specific identifications require the conversion of IM arrival times to collision cross section (CCS) values to minimize instrument-to-instrument variability. However, the process of converting IM arrival times to CCS values varies between the different IM devices. Arrival times from traveling wave ion mobility (TWIM) devices must undergo a calibration process to obtain CCS values, which can impart biases if the calibrants are not structurally similar to the analytes. For multiomic mixtures, several different types of calibrants must be used to obtain the most accurate CCS values from TWIM platforms. Here we describe the development of a multiomic CCS calibration tool, MOCCal, to automate the assignment of unknown features to the power law calibration that provides the most accurate CCS value. MOCCal calibrates every experimental arrival time with up to three class-specific calibration curves and uses the difference (in Å2) between the calibrated TWCCSN2 value and DTCCSN2 vs m/z regression lines to determine the best calibration curve. Using real and simulated multiomic samples, we demonstrate that MOCCal provides accurately calibrated TWCCSN2 values for small molecules, lipids, and peptides.

Neutrophil-targeted combinatorial nanosystems for suppressing bacteremia-associated hyperinflammation and MRSA infection to improve survival rates

There is currently no specific and effective treatment for bacteremia-mediated sepsis. Hence, this study engineered a combinatorial nanosystem containing neutrophil-targeted roflumilast-loaded nanocarriers and non-targeted fusidic acid-loaded nanoparticles to enable the dual mitigation of bacteremia-associated inflammation and methicillin-resistant Staphylococcus aureus (MRSA) infection. The targeted nanoparticles were developed by conjugating anti-lymphocyte antigen 6 complex locus G6D (Ly6G) antibody fragment on the nanoparticulate surface. The particle size and zeta potential of the as-prepared nanosystem were about 200 nm and -25 mV, respectively. The antibody-conjugated nanoparticles showed a three-fold increase in neutrophil internalization compared to the unfunctionalized nanoparticles. As a selective phosphodiesterase (PDE) 4 inhibitor, the roflumilast in the nanocarriers largely inhibited cytokine/chemokine release from the activated neutrophils. The fusidic acid-loaded nanocarriers were vital to eliminate biofilm MRSA colony by 3 log units. The nanoparticles drastically decreased the intracellular bacterial count compared to the free antibiotic. The in vivo mouse bioimaging demonstrated prolonged retention of the nanosystem in the circulation with limited organ distribution and liver metabolism. In the mouse bacteremia model, the multifunctional nanosystem produced a 1‒2 log reduction of MRSA burden in peripheral organs and blood. The functionalized nanosystem arrested the cytokine/chemokine overexpression greater than the unfunctionalized nanocarriers and free drugs. The combinatory nanosystem also extended the median survival time from 50 to 103 h. No toxicity from the nanoformulation was found based on histology and serum biochemistry. Furthermore, our data proved that the active neutrophil targeting by the versatile nanosystem efficiently alleviated MRSA infection and organ dysfunction caused by bacteremia. STATEMENT OF SIGNIFICANCE: Bacteremia-mediated sepsis poses a significant challenge in clinical practice, as there is currently no specific and effective treatment available. In our study, we have developed a novel combinatorial nanosystem to address this issue. Our nanosystem consists of neutrophil-targeted roflumilast-loaded nanocarriers and non-targeted fusidic acid-loaded nanoparticles, enabling the simultaneous mitigation of bacteremia-associated inflammation and MRSA infection. Our nanosystem demonstrated the decreased neutrophil activation, effective inhibition of cytokine release, elimination of MRSA biofilm colonies, and reduced intracellular bacterial counts. In vivo experiments showed prolonged circulation, limited organ distribution, and increased survival rates in a mouse bacteremia model. Importantly, our nanosystem exhibited no toxicity based on comprehensive assessments.

Sustained xanthine oxidase inhibitor treat to target urate lowering therapy rewires a tight inflammation serum protein interactome

Background

Effective xanthine oxidoreductase inhibition (XOI) urate-lowering treatment (ULT) to target significantly reduces gout flare burden and synovitis between 1-2 years therapy, without clearing all monosodium urate crystal deposits. Paradoxically, treat to target ULT is associated with increased flare activity for at least 1 year in duration on average, before gout flare burden decreases. Since XOI has anti-inflammatory effects, we tested for biomarkers of sustained, effective ULT that alters gouty inflammation.

Methods

We characterized the proteome of febuxostat-treated murine bone marrow macrophages. Blood samples (baseline and 48 weeks ULT) were analyzed by unbiased proteomics in febuxostat and allopurinol ULT responders from two, independent, racially and ethnically distinct comparative effectiveness trial cohorts (n=19, n=30). STRING-db and multivariate analyses supplemented determinations of significantly altered proteins via Wilcoxon matched pairs signed rank testing.

Results

The proteome of cultured IL-1b-stimulated macrophages revealed febuxostat-induced anti-inflammatory changes, including for classical and alternative pathway complement activation pathways. At 48 weeks ULT, with altered purine metabolism confirmed by serum metabolomics, serum urate dropped >30%, to normal (<6.8 mg/dL) in all the studied patients. Overall, flares declined from baseline. Treated gout patient sera and peripheral blood mononuclear cells (PBMCs) showed significantly altered proteins (p<0.05) in clustering and proteome networks. CRP was not a useful therapy response biomarker. By comparison, significant serum proteome changes included decreased complement C8 heterotrimer C8A and C8G chains essential for C5b-9 membrane attack complex assembly and function; increase in the NLRP3 inflammasome activation promoter vimentin; increased urate crystal phagocytosis inhibitor sCD44; increased gouty inflammation pro-resolving mediator TGFB1; decreased phagocyte-recruiting chemokine PPBP/CXCL7, and increased monocyte/macrophage-expressed keratin-related proteins (KRT9,14,16) further validated by PBMC proteomics. STRING-db analyses of significantly altered serum proteins from both cohorts revealed a tight interactome network including central mediators of gouty inflammation (eg, IL-1B, CXCL8, IL6, C5).

Conclusions

Rewiring of inflammation mediators in a tight serum protein interactome was a biomarker of sustained XOI-based ULT that effectively reduced serum urate and gout flares. Monitoring of the serum and PBMC proteome, including for changes in the complement pathway could help determine onset and targets of anti-inflammatory changes in response to effective, sustained XOI-based ULT.Trial Registration: ClinicalTrials.gov Identifier: NCT02579096.

Bioprospecting the Skin Microbiome: Advances in Therapeutics and Personal Care Products

Bioprospecting is the discovery and exploration of biological diversity found within organisms, genetic elements or produced compounds with prospective commercial or therapeutic applications. The human skin is an ecological niche which harbours a rich and compositional diversity microbiome stemming from the multifactorial interactions between the host and microbiota facilitated by exploitable effector compounds. Advances in the understanding of microbial colonisation mechanisms alongside species and strain interactions have revealed a novel chemical and biological understanding which displays applicative potential. Studies elucidating the organismal interfaces and concomitant understanding of the central processes of skin biology have begun to unravel a potential wealth of molecules which can exploited for their proposed functions. A variety of skin-microbiome-derived compounds display prospective therapeutic applications, ranging from antioncogenic agents relevant in skin cancer therapy to treatment strategies for antimicrobial-resistant bacterial and fungal infections. Considerable opportunities have emerged for the translation to personal care products, such as topical agents to mitigate various skin conditions such as acne and eczema. Adjacent compound developments have focused on cosmetic applications such as reducing skin ageing and its associated changes to skin properties and the microbiome. The skin microbiome contains a wealth of prospective compounds with therapeutic and commercial applications; however, considerable work is required for the translation of in vitro findings to relevant in vivo models to ensure translatability.

Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics

Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.

Characteristics of Virulent ST5-SCCmec II Methicillin-Resistant Staphylococcus aureus Prevalent in a Surgery Ward

Objective

To investigate the transmission pathway of a MRSA prevalence in a pancreatic surgery ward in a Chinese teaching hospital.

Methods

Molecular epidemiology investigations were carried out combined PFGE, MLST, SCCmec typing and whole-genome sequencing for 20 successive MRSA isolates (2 isolates from the ward environment). Resistance and virulence genes were detected using specific PCR. Bacterial identification and AST were performed using the Vitek 2 Compact System. Clinical data of enrolled cases were retrieved from electronic case records.

Results

From January 2020 to May 2020, successive isolated 20 MRSA strains were clarified to 2 PFGE patterns (A = 19, B = 1) in the ward. Both isolates from environment and patients belonged to sequence type ST5-SCCmec II-spa type t311. MRSA-related resistance genes mecA, blaZ, ermA, ant(4')-Ia and norA were found in each clone. All 20 isolates carried tst, hlg, hla, eta, eap, fnbA and seo virulence genes, other virulence genes such as sea, sec, seb, seg, sei, sem, sen, ebpS and fnbB were also found in partial stains. All patients had fever symptom, 27.8% were accompanied by diarrhea, 88.9% had undergone surgery or invasive procedures within 30 days. Finally, 94.4% of these patients recovered.

Conclusion

This study confirmed a prevalence of ST5-MRSA-II-t311 clone in a surgery ward, indicated MRSA is a risk factor for post-surgery nosocomial infection and hand hygiene and environmental surveillance should not be ignored.

Integration of metabolomics and peptidomics reveals distinct molecular landscape of human diabetic kidney disease

Diabetic kidney disease (DKD) is the most common microvascular complication of diabetes, and there is an urgent need to discover reliable biomarkers for early diagnosis. Here, we established an effective urine multi-omics platform and integrated metabolomics and peptidomics to investigate the biological changes during DKD pathogenesis. Methods: Totally 766 volunteers (221 HC, 198 T2DM, 175 early DKD, 125 overt DKD, and 47 grey-zone T2DM patients with abnormal urinary mALB concentration) were included in this study. Non-targeted metabolic fingerprints of urine samples were acquired on matrix-free LDI-MS platform by the tip-contact extraction method using fluorinated ethylene propylene coated silicon nanowires chips (FEP@SiNWs), while peptide profiles hidden in urine samples were uncovered by MALDI-TOF MS after capturing urine peptides by porous silicon microparticles. Results: After multivariate analysis, ten metabolites and six peptides were verified to be stepwise regulated in different DKD stages. The altered metabolic pathways and biological processes associated with the DKD pathogenesis were concentrated in amino acid metabolism and cellular protein metabolic process, which were supported by renal transcriptomics. Interestingly, multi-omics significantly increased the diagnostic accuracy for both early DKD diagnosis and DKD status discrimination. Combined with machine learning, a stepwise prediction model was constructed and 89.9% of HC, 75.5% of T2DM, 69.6% of early DKD and 75.7% of overt DKD subjects in the external validation cohort were correctly classified. In addition, 87.5% of grey-zone patients were successfully distinguished from T2DM patients. Conclusion: This multi-omics platform displayed a satisfactory ability to explore molecular information and provided a new insight for establishing effective DKD management.

Bivalent binding of staphylococcal superantigens to the TCR and CD28 triggers inflammatory signals independently of antigen presenting cells

Staphylococcus aureus superantigens (SAgs) such as staphylococcal enterotoxin A (SEA) and B (SEB) are potent toxins stimulating T cells to produce high levels of inflammatory cytokines, thus causing toxic shock and sepsis. Here we used a recently released artificial intelligence-based algorithm to better elucidate the interaction between staphylococcal SAgs and their ligands on T cells, the TCR and CD28. The obtained computational models together with functional data show that SEB and SEA are able to bind to the TCR and CD28 stimulating T cells to activate inflammatory signals independently of MHC class II- and B7-expressing antigen presenting cells. These data reveal a novel mode of action of staphylococcal SAgs. By binding to the TCR and CD28 in a bivalent way, staphylococcal SAgs trigger both the early and late signalling events, which lead to massive inflammatory cytokine secretion.

Amplification of Inflammation by Lubricin Deficiency Implicated in Incident, Erosive Gout Independent of Hyperuricemia

OBJECTIVE

In gout, hyperuricemia promotes urate crystal deposition, which stimulates the NLRP3 inflammasome and interleukin-1β (IL-1β)-mediated arthritis. Incident gout without background hyperuricemia is rarely reported. To identify hyperuricemia-independent mechanisms driving gout incidence and progression, we characterized erosive urate crystalline inflammatory arthritis in a young female patient with normouricemia diagnosed as having sufficient and weighted classification criteria for gout according to the American College of Rheumatology (ACR)/EULAR gout classification criteria (the proband).

METHODS

We conducted whole-genome sequencing, quantitative proteomics, whole-blood RNA-sequencing analysis using serum samples from the proband. We used a mouse model of IL-1β-induced knee synovitis to characterize proband candidate genes, biomarkers, and pathogenic mechanisms of gout.

RESULTS

Lubricin level was attenuated in human proband serum and associated with elevated acute-phase reactants and inflammatory whole-blood transcripts and transcriptional pathways. The proband had predicted damaging gene variants of NLRP3 and of inter-α trypsin inhibitor heavy chain 3, an inhibitor of lubricin-degrading cathepsin G. Changes in the proband's serum protein interactome network supported enhanced lubricin degradation, with cathepsin G activity increased relative to its inhibitors, SERPINB6 and thrombospondin 1. Activation of Toll-like receptor 2 (TLR-2) suppressed levels of lubricin mRNA and lubricin release in cultured human synovial fibroblasts (P < 0.01). Lubricin blunted urate crystal precipitation and IL-1β induction of xanthine oxidase and urate in cultured macrophages (P < 0.001). In lubricin-deficient mice, injection of IL-1β in knees increased xanthine oxidase-positive synovial resident M1 macrophages (P < 0.05).

CONCLUSION

Our findings linked normouricemic erosive gout to attenuated lubricin, with impaired control of cathepsin G activity, compounded by deleterious NLRP3 variants. Lubricin suppressed monosodium urate crystallization and blunted IL-1β-induced increases in xanthine oxidase and urate in macrophages. The collective activities of articular lubricin that could limit incident and erosive gouty arthritis independently of hyperuricemia are subject to disruption by inflammation, activated cathepsin G, and synovial fibroblast TLR-2 signaling.

Feature-Based Molecular Networking Facilitates the Comprehensive Identification of Differential Metabolites in Diabetic Cognitive Dysfunction Rats

Cognitive dysfunction is a frequent complication of type 2 diabetes mellitus (T2DM), usually accompanied by metabolic disorders. However, the metabolic changes in diabetic cognitive dysfunction (DCD) patients, especially compared to T2DM groups, are not fully understood. Due to the subtle differences in metabolic alterations between DCD groups and T2DM groups, the comprehensive detection of the untargeted metabolic profiles of hippocampus and urine samples of rats was conducted by LC-MS, considering the different ionization modes and polarities of the examined compounds, and feature-based molecular networking (FBMN) was performed to help identify differential metabolites from a comprehensive perspective in this study. In addition, an association analysis of the differential metabolites in hippocampus and urine was conducted by the O2PLS model. Finally, a total of 71 hippocampal tissue differential metabolites and 179 urine differential metabolites were identified. The pathway enrichment results showed that glutamine and glutamate metabolism, alanine, aspartate, and glutamate metabolism, glycerol phospholipid metabolism, TCA cycle, and arginine biosynthesis in the hippocampus of DCD animals were changed. Seven metabolites (AUC > 0.9) in urine appeared as key differential metabolites that might reflect metabolic changes in the target tissue of DCD rats. This study showed that FBMN facilitated the comprehensive identification of differential metabolites in DCD rats. The differential metabolites may suggest an underlying DCD and be considered as potential biomarkers for DCD. Large samples and clinical experiments are needed for the subsequent elucidation of the possible mechanisms leading to these alterations and the verification of potential biomarkers.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Metabolomics meets systems immunology

Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

Deep Learning of Dual Plasma Fingerprints for High-Performance Infection Classification

Infection classification is the key for choosing the proper treatment plans. Early determination of the causative agents is critical for disease control. Host responses analysis can detect variform and sensitive host inflammatory responses to ascertain the presence and type of the infection. However, traditional host-derived inflammatory indicators are insufficient for clinical infection classification. Fingerprints-based omic analysis has attracted increasing attention globally for analyzing the complex host systemic immune response. A single type of fingerprints is not applicable for infection classification (area under curve (AUC) of 0.550-0.617). Herein, an infection classification platform based on deep learning of dual plasma fingerprints (DPFs-DL) is developed. The DPFs with high reproducibility (coefficient of variation <15%) are obtained at low sample consumption (550 nL native plasma) using inorganic nanoparticle and organic matrix assisted laser desorption/ionization mass spectrometry. A classifier (DPFs-DL) for viral versus bacterial infection discrimination (AUC of 0.775) and coronavirus disease 2019 (COVID-2019) diagnosis (AUC of 0.917) is also built. Furthermore, a metabolic biomarker panel of two differentially regulated metabolites, which may serve as potential biomarkers for COVID-19 management (AUC of 0.677-0.883), is constructed. This study will contribute to the development of precision clinical care for infectious diseases.

Staphylococcus aureus host interactions and adaptation

Invasive Staphylococcus aureus infections are common, causing high mortality, compounded by the propensity of the bacterium to develop drug resistance. S. aureus is an excellent case study of the potential for a bacterium to be commensal, colonizing, latent or disease-causing; these states defined by the interplay between S. aureus and host. This interplay is multidimensional and evolving, exemplified by the spread of S. aureus between humans and other animal reservoirs and the lack of success in vaccine development. In this Review, we examine recent advances in understanding the S. aureus-host interactions that lead to infections. We revisit the primary role of neutrophils in controlling infection, summarizing the discovery of new immune evasion molecules and the discovery of new functions ascribed to well-known virulence factors. We explore the intriguing intersection of bacterial and host metabolism, where crosstalk in both directions can influence immune responses and infection outcomes. This Review also assesses the surprising genomic plasticity of S. aureus, its dualism as a multi-mammalian species commensal and opportunistic pathogen and our developing understanding of the roles of other bacteria in shaping S. aureus colonization.

Metabolomics as a Critical Tool for Studying Clinical Surgery

Metabolomics enables the analysis of metabolites within an organism, which offers the closest direct measurement of the physiological activity of the organism, and has advanced efforts to characterize metabolic states, identify biomarkers, and investigate metabolic pathways. A high degree of innovation in analytical techniques has promoted the application of metabolomics, especially in the study of clinical surgery. Metabolomics can be employed as a clinical testing method to maximize therapeutic outcomes, and has been applied in rapid diagnosis of diseases, timely postoperative monitoring, prognostic assessment, and personalized medicine. This review focuses on the use of mass spectrometry and nuclear magnetic resonance-based metabolomics in clinical surgery, including identifying metabolic changes before and after surgery, finding disease-associated biomarkers, and exploring the potential of personalized therapy. Challenges and opportunities of metabolomics in organ transplantation are also discussed, with a particular emphasis on metabolomics in donor organ evaluation and protection, prognostic outcome prediction, as well as postoperative adverse reaction monitoring. In the end, current limitations of metabolomics in clinical surgery and future research directions are presented.

Intracellular infection-responsive release of NO and peptides for synergistic bacterial eradication

Bacteria have the ability to invade and survive in host cells to form intracellular bacteria (ICBs), and challenges remain in the intracellular delivery of sufficient antibiotics to remove ICBs. Herein, antimicrobial peptide of epsilon-poly-l-lysine (ePL) and nitric oxide (NO) donors are integrated into nanoparticles (NPs) for ICB treatment without using any antibiotics. ePL was grafted with dodecyl alcohol through ethyl dichlorophosphate to prepare ePL-C₁₂, followed by conjugation of nitrate-functionalized NO donors to obtain ePL-C₁₂NO. PNO/C NPs were prepared from mixtures of ePL-C₁₂NO and ePL-C₁₂ and the optimal ePL-C₁₂NO ratio was 7% in terms of bactericidal effect and macrophage toxicity. Once being engulfed by bacteria-infected macrophages (BIMs), NPs are disintegrated when encountering with ICB-secreted phosphatase, and the NP degradation accelerates intracellular NO release in response to the elevated glutathione levels in BIMs. The selective and abrupt release of NO and ePL with different antimicrobial mechanisms exhibits synergistic eradication of ICBs and no apparent toxicity to macrophages. ICB-infected mice show persistent weight loss and 100% of mortality rate after treatment with ePL-C₁₂ NPs for 7 days, while PNO/C treatment causes entire survival of infected mice and full recovery of body weights to normal values. ICB-infected mice are also accompanied with apparent hepatomegaly and splenomegaly, which are only eliminated by PNO/C treatment without associated any pathological abnormality. PNO/C treatment reduces bacterial burdens in livers (2.45 log), spleens (2.16 log) and kidneys (3.46 log) and restores hepatic and renal function to normal levels. Thus, this study provides a feasible strategy to selectively release NO and cationic peptides in response to intracellular infection-derived signals, achieving synergistic eradication of ICBs and function restoration of the main tissues.

Persistent Methicilin-Resistant Staphylococcus aureus Bacteremia: Resetting the Clock for Optimal Management

A positive follow-up blood culture for methicillin-resistant Staphylococcus aureus (MRSA) while on seemingly appropriate therapy is a common and ominous development. However, the definition and management of persistent MRSA bacteremia is unstandardized. In this Opinion Paper, we identify the presence of bacteremia for > 1 calendar day as a "worry point" that should trigger an intensive diagnostic evaluation to identify metastatic infection sites. Next, we define the duration of MRSA bacteremia that likely constitutes antibiotic failure and outline a potential management algorithm for such patients. Finally, we propose pragmatic clinical trial designs to test treatment strategies for persistent MRSA bacteremia.

IDSL.UFA Assigns High-Confidence Molecular Formula Annotations for Untargeted LC/HRMS Data Sets in Metabolomics and Exposomics

Untargeted liquid chromatography/high-resolution mass spectrometry (LC/HRMS) assays in metabolomics and exposomics aim to characterize the small molecule chemical space in a biospecimen. To gain maximum biological insights from these data sets, LC/HRMS peaks should be annotated with chemical and functional information including molecular formula, structure, chemical class, and metabolic pathways. Among these, molecular formulas may be assigned to LC/HRMS peaks through matching theoretical and observed isotopic profiles (MS1) of the underlying ionized compound. For this, we have developed the Integrated Data Science Laboratory for Metabolomics and Exposomics-United Formula Annotation (IDSL.UFA) R package. In the untargeted metabolomics validation tests, IDSL.UFA assigned 54.31-85.51% molecular formula for true positive annotations as the top hit and 90.58-100% within the top five hits. Molecular formula annotations were also supported by tandem mass spectrometry data. We have implemented new strategies to (1) generate formula sources and their theoretical isotopic profiles, (2) optimize the formula hits ranking for the individual and aligned peak lists, and (3) scale IDSL.UFA-based workflows for studies with larger sample sizes. Annotating the raw data for a publicly available pregnancy metabolome study using IDSL.UFA highlighted hundreds of new pregnancy-related compounds and also suggested the presence of chlorinated perfluorotriether alcohols (Cl-PFTrEAs) in human specimens. IDSL.UFA is useful for human metabolomics and exposomics studies where we need to minimize the loss of biological insights in untargeted LC/HRMS data sets. The IDSL.UFA package is available in the R CRAN repository https://cran.r-project.org/package=IDSL.UFA. Detailed documentation and tutorials are also provided at www.ufa.idsl.me.

Vascular Proteome Responses Precede Organ Dysfunction in a Murine Model of Staphylococcus aureus Bacteremia

Vascular dysfunction and organ failure are two distinct, albeit highly interconnected, clinical outcomes linked to morbidity and mortality in human sepsis. The mechanisms driving vascular and parenchymal damage are dynamic and display significant molecular cross talk between organs and tissues. Therefore, assessing their individual contribution to disease progression is technically challenging. Here, we hypothesize that dysregulated vascular responses predispose the organism to organ failure. To address this hypothesis, we have evaluated four major organs in a murine model of Staphylococcus aureus sepsis by combining in vivo labeling of the endothelial cell surface proteome, data-independent acquisition (DIA) mass spectrometry, and an integrative computational pipeline. The data reveal, with unprecedented depth and throughput, that a septic insult evokes organ-specific proteome responses that are highly compartmentalized, synchronously coordinated, and significantly correlated with the progression of the disease. These responses include abundant vascular shedding, dysregulation of the intrinsic pathway of coagulation, compartmentalization of the acute phase response, and abundant upregulation of glycocalyx components. Vascular cell surface proteome changes were also found to precede bacterial invasion and leukocyte infiltration into the organs, as well as to precede changes in various well-established cellular and biochemical correlates of systemic coagulopathy and tissue dysfunction. Importantly, our data suggest a potential role for the vascular proteome as a determinant of the susceptibility of the organs to undergo failure during sepsis. IMPORTANCE Sepsis is a life-threatening response to infection that results in immune dysregulation, vascular dysfunction, and organ failure. New methods are needed for the identification of diagnostic and therapeutic targets. Here, we took a systems-wide approach using data-independent acquisition (DIA) mass spectrometry to track the progression of bacterial sepsis in the vasculature leading to organ failure. Using a murine model of S. aureus sepsis, we were able to quantify thousands of proteins across the plasma and parenchymal and vascular compartments of multiple organs in a time-resolved fashion. We showcase the profound proteome remodeling triggered by sepsis over time and across these compartments. Importantly, many vascular proteome alterations precede changes in traditional correlates of organ dysfunction, opening a molecular window for the discovery of early markers of sepsis progression.

ConSIG: consistent discovery of molecular signature from OMIC data

The discovery of proper molecular signature from OMIC data is indispensable for determining biological state, physiological condition, disease etiology, and therapeutic response. However, the identified signature is reported to be highly inconsistent, and there is little overlap among the signatures identified from different biological datasets. Such inconsistency raises doubts about the reliability of reported signatures and significantly hampers its biological and clinical applications. Herein, an online tool, ConSIG, was constructed to realize consistent discovery of gene/protein signature from any uploaded transcriptomic/proteomic data. This tool is unique in a) integrating a novel strategy capable of significantly enhancing the consistency of signature discovery, b) determining the optimal signature by collective assessment, and c) confirming the biological relevance by enriching the disease/gene ontology. With the increasingly accumulated concerns about signature consistency and biological relevance, this online tool is expected to be used as an essential complement to other existing tools for OMIC-based signature discovery. ConSIG is freely accessible to all users without login requirement at https://idrblab.org/consig/.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

Review of immunological plasma markers for longitudinal analysis of inflammation and infection in rat models

Disease or trauma of orthopedic tissues, including osteomyelitis, osteoporosis, arthritis, and fracture, results in a complex immune response, leading to a change in the concentration and milieu of immunological cells and proteins in the blood. While C-reactive protein levels and white blood cell counts are used to track inflammation and infection clinically, controlled longitudinal studies of disease/injury progression are limited. Thus, the use of clinically-relevant animal models can enable a more in-depth understanding of disease/injury progression and treatment efficacy. Though longitudinal tracking of immunological markers has been performed in rat models of various inflammatory and infectious diseases, currently there is no consensus on which markers are sensitive and reliable for tracking levels of inflammation and/or infection. Here, we discuss the blood markers that are most consistent with other outcome measures of the immune response in the rat, by reviewing their utility for longitudinal tracking of infection and/or inflammation in the following types of models: localized inflammation/arthritis, injury, infection, and injury + infection. While cytokines and acute phase proteins such as haptoglobin, fibrinogen, and α₂ -macroglobulin demonstrate utility for tracking immunological response in many inflammation and infection models, there is likely not a singular superior marker for all rat models. Instead, longitudinal characterization of these models may benefit from evaluation of a collection of cytokines and/or acute phase proteins. Identification of immunological plasma markers indicative of the progression of a pathology will allow for the refinement of animal models for understanding, diagnosing, and treating inflammatory and infectious diseases of orthopedic tissues.

Coagulation factor protein abundance in the pre-septic state predicts coagulopathic activities that arise during late-stage murine sepsis

BACKGROUND

Although sepsis accounts for 1 in 5 deaths globally, few molecular therapies exist for this condition. The development of effective biomarkers and treatments for sepsis requires a more complete understanding of host responses and pathogenic mechanisms at early stages of disease to minimize host-driven pathology.

METHODS

An alternative to the current symptom-based approach used to diagnose sepsis is a precise assessment of blood proteomic changes during the onset and progression of Salmonella Typhimurium (ST) murine sepsis.

FINDINGS

A distinct pattern of coagulation factor protein abundance was identified in the pre-septic state- prior to overt disease symptoms or bacteremia- that was predictive of the dysregulation of fibrinolytic and anti-coagulant activities and resultant consumptive coagulopathy during ST murine sepsis. Moreover, the changes in protein abundance observed generally have the same directionality (increased or decreased abundance) reported for human sepsis. Significant overlap of ST coagulopathic activities was observed in Gram-negative Escherichia coli- but not in Gram-positive staphylococcal or pneumococcal murine sepsis models. Treatment with matrix metalloprotease inhibitors prevented aberrant inflammatory and coagulopathic activities post-ST infection and increased survival. Antibiotic treatment regimens initiated after specific changes arise in the plasma proteome post-ST infection were predictive of an increase in disease relapse and death after cessation of antibiotic treatment.

INTERPRETATION

Altered blood proteomics provides a platform to develop rapid and easy-to-perform tests to predict sepsis for early intervention via biomarker incorporation into existing blood tests prompted by patient presentation with general malaise, and to stratify Gram-negative and Gram-positive infections for appropriate treatment. Antibiotics are less effective in microbial clearance when initiated after the onset of altered blood proteomics as evidenced by increased disease relapse and death after termination of antibiotic therapy. Treatment failure is potentially due to altered bacterial / host-responses and associated increased host-driven pathology, providing insight into why delays in antibiotic administration in human sepsis are associated with increased risk for death. Delayed treatment may thus require prolonged therapy for microbial clearance despite the prevailing notion of antibiotic de-escalation and shortened courses of antibiotics to improve drug stewardship.

FUNDING

National Institutes of Health, U.S. Army.

Infection Biomarkers Based on Metabolomics

Current infection biomarkers are highly limited since they have low capability to predict infection in the presence of confounding processes such as in non-infectious inflammatory processes, low capability to predict disease outcomes and have limited applications to guide and evaluate therapeutic regimes. Therefore, it is critical to discover and develop new and effective clinical infection biomarkers, especially applicable in patients at risk of developing severe illness and critically ill patients. Ideal biomarkers would effectively help physicians with better patient management, leading to a decrease of severe outcomes, personalize therapies, minimize antibiotics overuse and hospitalization time, and significantly improve patient survival. Metabolomics, by providing a direct insight into the functional metabolic outcome of an organism, presents a highly appealing strategy to discover these biomarkers. The present work reviews the desired main characteristics of infection biomarkers, the main metabolomics strategies to discover these biomarkers and the next steps for developing the area towards effective clinical biomarkers.

Molecular networking in infectious disease models

Small molecule metabolites are the product of many enzymatic reactions. Metabolomics thus opens a window into enzyme activity and function, integrating effects at the post-translational, proteome, transcriptome and genome level. In addition, small molecules can themselves regulate enzyme activity, expression and function both via substrate availability mechanisms and through allosteric regulation. Metabolites are therefore at the nexus of infectious diseases, regulating nutrient availability to the pathogen, immune responses, tropism, and host disease tolerance and resilience. Analysis of metabolomics data is however complex, particularly in terms of metabolite annotation. An emerging valuable approach to extend metabolite annotations beyond existing compound libraries and to identify infection-induced chemical changes is molecular networking. In this chapter, we discuss the applications of molecular networking in the context of infectious diseases specifically, with a focus on considerations relevant to these biological systems.

Multi-omics of human plasma reveals molecular features of dysregulated inflammation and accelerated aging in schizophrenia

Schizophrenia is a devastating psychiatric illness that detrimentally affects a significant portion of the worldwide population. Aging of schizophrenia patients is associated with reduced longevity, but the potential biological factors associated with aging in this population have not yet been investigated in a global manner. To address this gap in knowledge, the present study assesses proteomics and metabolomics profiles in the plasma of subjects afflicted with schizophrenia compared to non-psychiatric control patients over six decades of life. Global, unbiased analyses of circulating blood plasma can provide knowledge of prominently dysregulated molecular pathways and their association with schizophrenia, as well as features of aging and gender in this disease. The resulting data compiled in this study represent a compendium of molecular changes associated with schizophrenia over the human lifetime. Supporting the clinical finding of schizophrenia's association with more rapid aging, both schizophrenia diagnosis and age significantly influenced the plasma proteome in subjects assayed. Schizophrenia was broadly associated with prominent dysregulation of inflammatory and metabolic system components. Proteome changes demonstrated increased abundance of biomarkers for risk of physiologic comorbidities of schizophrenia, especially in younger individuals. These findings advance our understanding of the molecular etiology of schizophrenia and its associated comorbidities throughout the aging process.