Integrated host-microbe plasma metagenomics for sepsis diagnosis in a prospective cohort of critically ill adults

Metagenomic next-generation sequencing as a diagnostic tool in the clinical routine of an infectious diseases department: a retrospective cohort study

BACKGROUND

Metagenomic next-generation sequencing (mNGS) of circulating cell-free DNA from plasma is a hypothesis-independent broadband diagnostic method for identification of potential pathogens. So far, it has only been investigated in special risk populations (e.g. patients with neutropenic fever).

PURPOSE

To investigate the extent to which mNGS (DISQVER® platform) can be used in routine clinical practice.

METHODS

We collected whole blood specimens for mNGS testing, blood cultures (BC), and pathogen-specific PCR diagnostics. Clinical data and pathogen diagnostics were retrospectively reviewed by an infectious disease expert panel regarding the adjustment of anti-infective therapy.

RESULTS

In 55 selected patients (median age 53 years, 67% male) with heterogeneous diagnoses, a total of 66 different microorganisms and viruses were detected using mNGS (51% viruses, 38% bacteria, 8% fungi, 3% parasites). The overall positivity rate of mNGS was 53% (29/55). Fifty-two out of 66 (79%) potential pathogens detected by mNGS were found in patients with primary or secondary immunodeficiency. The concordance rates of BC and pathogen-specific PCR diagnostics with mNGS testing were 14% (4/28) and 36% (10/28), respectively (p < 0.001). An additional bacterial pathogen (Streptococcus agalactiae) could only be detected by BC. Therapeutic consequences regarding anti-infective therapy were drawn from 23 pathogens (35% of detections), with 18 of these detections occurring in patients with immunodeficiency.

CONCLUSIONS

We conclude that mNGS is a useful diagnostic tool, but should only be performed selectively in addition to routine diagnostics of infectious diseases. The limited number of patients and the retrospective study design do not allow any further conclusions.

Biomarkers in sepsis

Sepsis is a life-threatening condition characterized by dysregulated host response to infection leading to organ dysfunction. Despite advances in understanding its pathology, sepsis remains a global health concern and remains a major contributor to mortality. Timely identification is crucial for improving clinical outcomes, as delayed treatment significantly impacts survival. Accordingly, biomarkers play a pivotal role in diagnosis, risk stratification, and management. This review comprehensively discusses various biomarkers in sepsis and their potential application in antimicrobial stewardship and risk assessment. Biomarkers such as white blood cell count, neutrophil to lymphocyte ratio, erythrocyte sedimentation rate, C-reactive protein, interleukin-6, presepsin, and procalcitonin have been extensively studied for their diagnostic and prognostic value as well as in guiding antimicrobial therapy. Furthermore, this review explores the role of biomarkers in risk stratification, emphasizing the importance of identifying high-risk patients who may benefit from specific therapeutic interventions. Moreover, the review discusses the emerging field of transcriptional diagnostics and metagenomic sequencing. Advances in sequencing have enabled the identification of host response signatures and microbial genomes, offering insight into disease pathology and aiding species identification. In conclusion, this review provides a comprehensive overview of the current understanding and future directions of biomarker-based approaches in sepsis diagnosis, management, and personalized therapy.

A metabolomics pipeline highlights microbial metabolism in bloodstream infections

The growth of antimicrobial resistance (AMR) highlights an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe infections profoundly alter host metabolism, prior studies have largely ignored microbial metabolism in this context. Here, we describe an iterative, comparative metabolomics pipeline to uncover microbial metabolic features in the complex setting of a host and apply it to investigate gram-negative bloodstream infection (BSI) in patients. We find elevated levels of bacterially derived acetylated polyamines during BSI and discover the enzyme responsible for their production (SpeG). Blocking SpeG activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity also enhances bacterial membrane permeability and increases intracellular antibiotic accumulation, allowing us to overcome AMR in culture and in vivo. This study highlights how tools to study pathogen metabolism in the natural context of infection can reveal and prioritize therapeutic strategies for addressing challenging infections.

Enhancing sepsis biomarker development: key considerations from public and private perspectives

Implementation of biomarkers in sepsis and septic shock in emergency situations, remains highly challenging. This viewpoint arose from a public-private 3-day workshop aiming to facilitate the transition of sepsis biomarkers into clinical practice. The authors consist of international academic researchers and clinician-scientists and industry experts who gathered (i) to identify current obstacles impeding biomarker research in sepsis, (ii) to outline the important milestones of the critical path of biomarker development and (iii) to discuss novel avenues in biomarker discovery and implementation. To define more appropriately the potential place of biomarkers in sepsis, a better understanding of sepsis pathophysiology is mandatory, in particular the sepsis patient's trajectory from the early inflammatory onset to the late persisting immunosuppression phase. This time-varying host response urges to develop time-resolved test to characterize persistence of immunological dysfunctions. Furthermore, age-related difference has to be considered between adult and paediatric septic patients. In this context, numerous barriers to biomarker adoption in practice, such as lack of consensus about diagnostic performances, the absence of strict recommendations for sepsis biomarker development, cost and resources implications, methodological validation challenges or limited awareness and education have been identified. Biomarker-guided interventions for sepsis to identify patients that would benefit more from therapy, such as sTREM-1-guided Nangibotide treatment or Adrenomedullin-guided Enibarcimab treatment, appear promising but require further evaluation. Artificial intelligence also has great potential in the sepsis biomarker discovery field through capability to analyse high volume complex data and identify complex multiparametric patient endotypes or trajectories. To conclude, biomarker development in sepsis requires (i) a comprehensive and multidisciplinary approach employing the most advanced analytical tools, (ii) the creation of a platform that collaboratively merges scientific and commercial needs and (iii) the support of an expedited regulatory approval process.

Liquid Biopsy Based on Cell-Free DNA and RNA

This review delves into the rapidly evolving landscape of liquid biopsy technologies based on cell-free DNA (cfDNA) and cell-free RNA (cfRNA) and their increasingly prominent role in precision medicine. With the advent of high-throughput DNA sequencing, the use of cfDNA and cfRNA has revolutionized noninvasive clinical testing. Here, we explore the physical characteristics of cfDNA and cfRNA, present an overview of the essential engineering tools used by the field, and highlight clinical applications, including noninvasive prenatal testing, cancer testing, organ transplantation surveillance, and infectious disease testing. Finally, we discuss emerging technologies and the broadening scope of liquid biopsies to new areas of diagnostic medicine.

Biological effects of corticosteroids on pneumococcal pneumonia in Mice-translational significance

BACKGROUND

Streptococcus pneumoniae is the most common bacterial cause of community acquired pneumonia and the acute respiratory distress syndrome (ARDS). Some clinical trials have demonstrated a beneficial effect of corticosteroid therapy in community acquired pneumonia, COVID-19, and ARDS, but the mechanisms of this benefit remain unclear. The primary objective of this study was to investigate the effects of corticosteroids on the pulmonary biology of pneumococcal pneumonia in a mouse model. A secondary objective was to identify shared transcriptomic features of pneumococcal pneumonia and steroid treatment in the mouse model and clinical samples.

METHODS

We carried out comprehensive physiologic, biochemical, and histological analyses in mice to identify the mechanisms of lung injury in Streptococcus pneumoniae with and without adjunctive steroid therapy. We also studied lower respiratory tract gene expression from a cohort of 15 mechanically ventilated patients (10 with Streptococcus pneumoniae and 5 controls) to compare with the transcriptional studies in the mice.

RESULTS

In mice with pneumonia, dexamethasone in combination with ceftriaxone reduced (1) pulmonary edema formation, (2) alveolar protein permeability, (3) proinflammatory cytokine release, (4) histopathologic lung injury score, and (5) hypoxemia but did not increase bacterial burden. Transcriptomic analyses identified effects of steroid therapy in mice that were also observed in the clinical samples.

CONCLUSIONS

In combination with appropriate antibiotic therapy in mice, treatment of pneumococcal pneumonia with steroid therapy reduced hypoxemia, pulmonary edema, lung permeability, and histologic criteria of lung injury, and also altered inflammatory responses at the protein and gene expression level. The transcriptional studies in patients suggest that the mouse model replicates some of the features of pneumonia in patients with Streptococcus pneumoniae and steroid treatment. Overall, these studies provide evidence for the mechanisms that may explain the beneficial effects of glucocorticoid therapy in patients with community acquired pneumonia from Streptococcus Pneumoniae.

Biological basis of critical illness subclasses: from the bedside to the bench and back again

Critical illness syndromes including sepsis, acute respiratory distress syndrome, and acute kidney injury (AKI) are associated with high in-hospital mortality and long-term adverse health outcomes among survivors. Despite advancements in care, clinical and biological heterogeneity among patients continues to hamper identification of efficacious therapies. Precision medicine offers hope by identifying patient subclasses based on clinical, laboratory, biomarker and 'omic' data and potentially facilitating better alignment of interventions. Within the previous two decades, numerous studies have made strides in identifying gene-expression based endotypes and clinico-biomarker based phenotypes among critically ill patients associated with differential outcomes and responses to treatment. In this state-of-the-art review, we summarize the biological similarities and differences across the various subclassification schemes among critically ill patients. In addition, we highlight current translational gaps, the need for advanced scientific tools, human-relevant disease models, to gain a comprehensive understanding of the molecular mechanisms underlying critical illness subclasses.

A Comprehensive Review on Circulating cfRNA in Plasma: Implications for Disease Diagnosis and Beyond

Circulating cfRNA in plasma has emerged as a fascinating area of research with potential applications in disease diagnosis, monitoring, and personalized medicine. Circulating RNA sequencing technology allows for the non-invasive collection of important information about the expression of target genes, eliminating the need for biopsies. This comprehensive review aims to provide a detailed overview of the current knowledge and advancements in the study of plasma cfRNA, focusing on its diverse landscape and biological functions, detection methods, its diagnostic and prognostic potential in various diseases, challenges, and future perspectives.

Cell-free RNA Liquid Biopsy to Monitor Hematopoietic Stem Cell Transplantation

Hematopoietic Stem Cell Transplantation (HSCT) is one of the oldest and most successful immunotherapies. Yet, despite long-standing success in the use of HSCT for the treatment of blood cancers and severe immune disorders, monitoring post-transplant complications remains a challenge due to a lack of informative diagnostic tests. Here, we investigate the utility of cell-free RNA (cfRNA) in plasma as a liquid biopsy to monitor allogeneic HSCT recipients during and after treatment. We assayed longitudinal samples from 92 HSCT recipients by cfRNA sequencing and show that cfRNA provides insight into treatment and recovery trajectories, immune dynamics in response to transplantation, infection, and solid-tissue injury associated with Graft-Versus-Host Disease. Collectively, our results provide support for the use of plasma cfRNA profiling to monitor complications of HSCT.

Use of Transcriptional Signatures to Differentiate Pathogen-Specific and Treatment-Specific Host Responses in Patients With Bacterial Bloodstream Infections

BACKGROUND

Clinical outcomes in bacterial bloodstream infections (BSIs) are influenced by bacterial species, host immunity, and antibiotic therapy. The mechanisms by which such factors influence outcomes are poorly understood. We aimed to identify bacterial- and antibiotic-specific host transcriptional signatures in patients with bacterial BSI.

METHODS

RNA sequencing was performed on blood samples from patients with BSI due to gram-negative (GN) versus gram-positive (GP) pathogens: Escherichia coli (n = 30) or Klebsiella pneumoniae (n = 28) versus methicillin-susceptible Staphylococcus aureus (MSSA) (n = 24) or methicillin-resistant S. aureus (MRSA) (n = 58). Patients were matched by age, sex, and race.

RESULTS

No significant host transcriptome differences were detected in patients with E. coli versus K. pneumoniae BSI, so these were considered together as GN BSI. Relative to S. aureus BSI, patients with GN BSI had increased activation of the classic complement system. However, the most significant signal was a reduction in host transcriptional signatures involving mitochondrial energy transduction and oxidative burst in MRSA versus MSSA. This attenuated host transcriptional signature remained after controlling for antibiotic therapy.

CONCLUSIONS

Given the importance of immune cellular energetics and reactive oxygen species in eliminating hematogenous or intracellular MRSA, these findings may offer insights into its persistence relative to other bacterial BSIs.

Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID pipeline

Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the CZ ID AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.

Prognostic value of poly-microorganisms detected by droplet digital PCR and pathogen load kinetics in sepsis patients: a multi-center prospective cohort study

This study aimed to investigate the prognostic value of a novel droplet digital polymerase chain reaction (DDPCR) assay in sepsis patients. In this prospective cohort study, univariable and multivariable Cox regressions were used to assess risk factors for 28-day mortality. We also monitored pathogen load together with clinical indicators in a subgroup of the cohort. A total of 107 sepsis patients with positive baseline DDPCR results were included. Detection of poly-microorganisms [adjusted hazard ratio (HR) = 3.19; 95% confidence interval (CI) = 1.34-7.62; P = 0.009], high Charlson Comorbidity Index (CCI) score (adjusted HR = 1.14; 95% CI = 1.01-1.29; P = 0.041), and Sequential Organ Failure Assessment (SOFA) score (adjusted HR = 1.18; 95% CI = 1.05-1.32; P = 0.005) at baseline were independent risk factors for 28-day mortality while initial pathogen load was not associated (adjusted HR = 1.17; 95% CI = 0.82-1.66; P = 0.385). Among 63 patients with serial DDPCR results, an increase in pathogen load at days 6-8 compared to baseline was a risk factor for 28-day mortality (P = 0.008). Also, pathogen load kinetics were significantly different between day-28 survivors and nonsurvivors (P = 0.022), with a decline overtime only in survivors and an increase from days 3 and 4 to days 6-8 in nonsurvivors. Using DDPCR technique, we found that poly-microorganisms detected and increased pathogen load a week after sepsis diagnosis were associated with poor prognosis.IMPORTANCEThis prospective study was initiated to explore the prognostic implications of a novel multiplex PCR assay in sepsis. Notably, our study was the largest cohort of sepsis with droplet digital polymerase chain reaction pathogen monitoring to date, allowing for a comprehensive evaluation of the prognostic significance of both pathogen species and load. We found that detection of poly-microorganisms was an independent risk factors for 28-day mortality. Also, pathogen load increase 1 week after sepsis diagnosis was a risk factor for 28-day mortality, and differential pathogen load kinetics were identified between day-28 survivors and nonsurvivors. Overall, this study demonstrated that pathogen species and load were highly correlated with sepsis prognosis. Patients exhibiting conditions mentioned above face a more adverse prognosis, suggesting the potential need for an escalation of antimicrobial therapy.Registered at ClinicalTrials.gov (NCT05190861).

Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID pipeline

Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the Chan Zuckerberg ID (CZ ID) AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.

Host-microbe multiomic profiling reveals age-dependent immune dysregulation associated with COVID-19 immunopathology

Age is a major risk factor for severe coronavirus disease 2019 (COVID-19), yet the mechanisms behind this relationship have remained incompletely understood. To address this, we evaluated the impact of aging on host immune response in the blood and the upper airway, as well as the nasal microbiome in a prospective, multicenter cohort of 1031 vaccine-naïve patients hospitalized for COVID-19 between 18 and 96 years old. We performed mass cytometry, serum protein profiling, anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody assays, and blood and nasal transcriptomics. We found that older age correlated with increased SARS-CoV-2 viral abundance upon hospital admission, delayed viral clearance, and increased type I interferon gene expression in both the blood and upper airway. We also observed age-dependent up-regulation of innate immune signaling pathways and down-regulation of adaptive immune signaling pathways. Older adults had lower naïve T and B cell populations and higher monocyte populations. Over time, older adults demonstrated a sustained induction of pro-inflammatory genes and serum chemokines compared with younger individuals, suggesting an age-dependent impairment in inflammation resolution. Transcriptional and protein biomarkers of disease severity differed with age, with the oldest adults exhibiting greater expression of pro-inflammatory genes and proteins in severe disease. Together, our study finds that aging is associated with impaired viral clearance, dysregulated immune signaling, and persistent and potentially pathologic activation of pro-inflammatory genes and proteins.

A novel method for simultaneous detection of hematological tumors and infectious pathogens by metagenomic next generation sequencing of plasma

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is valuable for pathogen identification; however, distinguishing between infectious diseases and conditions with potentially similar clinical manifestations, including malignant tumors, is challenging. Therefore, we developed a method for simultaneous detection of infectious pathogens and cancer in blood samples.

METHODS

Plasma samples (n = 244) were collected from 150 and 94 patients with infections and hematological malignancies, respectively, and analyzed by mNGS for pathogen detection, alongside human tumor chromosomal copy number variation (CNV) analysis (≥5Mbp or 10Mbp CNV region). Further, an evaluation set, comprising 87 plasma samples, was analyzed by mNGS and human CNV analysis, to validate the feasibility of the method.

RESULTS

Among 94 patients with hematological malignancy, sensitivity values of CNV detection for tumor diagnosis were 69.15 % and 32.98 % for CNV region 5Mbp and 10Mbp, respectively, with corresponding specificities of 92.62 % and 100 % in the infection group. Area under the ROC curve (AUC) values for 5Mbp and 10Mbp region were 0.825 and 0.665, respectively, which was a significant difference of 0.160 (95 % CI: 0.110-0.210; p < 0.001), highlighting the superiority of 5Mbp output region data. Six patients with high-risk CNV results were identified in the validation study: three with history of tumor treatment, two eventually newly-diagnosed with hematological malignancies, and one with indeterminate final diagnosis.

CONCLUSIONS

Concurrent CNV analysis alongside mNGS for infection diagnosis is promising for detecting malignant tumors. We recommend adopting a CNV region of 10Mbp over 5Mbp for our model, because of the lower false-positive rate (FPR).

Profiling the dysregulated immune response in sepsis: overcoming challenges to achieve the goal of precision medicine

Sepsis is characterised by a dysregulated host immune response to infection. Despite recognition of its significance, immune status monitoring is not implemented in clinical practice due in part to the current absence of direct therapeutic implications. Technological advances in immunological profiling could enhance our understanding of immune dysregulation and facilitate integration into clinical practice. In this Review, we provide an overview of the current state of immune profiling in sepsis, including its use, current challenges, and opportunities for progress. We highlight the important role of immunological biomarkers in facilitating predictive enrichment in current and future treatment scenarios. We propose that multiple immune and non-immune-related parameters, including clinical and microbiological data, be integrated into diagnostic and predictive combitypes, with the aid of machine learning and artificial intelligence techniques. These combitypes could form the basis of workable algorithms to guide clinical decisions that make precision medicine in sepsis a reality and improve patient outcomes.

Host and Microbe Blood Metagenomics Reveals Key Pathways Characterizing Critical Illness Phenotypes

Rationale: Two molecular phenotypes of sepsis and acute respiratory distress syndrome, termed hyperinflammatory and hypoinflammatory, have been consistently identified by latent class analysis in numerous cohorts, with widely divergent clinical outcomes and differential responses to some treatments; however, the key biological differences between these phenotypes remain poorly understood.Objectives: We used host and microbe metagenomic sequencing data from blood to deepen our understanding of biological differences between latent class analysis-derived phenotypes and to assess concordance between the latent class analysis-derived phenotypes and phenotypes reported by other investigative groups (e.g., Sepsis Response Signature [SRS1-2], molecular diagnosis and risk stratification of sepsis [MARS1-4], reactive and uninflamed).Methods: We analyzed data from 113 patients with hypoinflammatory sepsis and 76 patients with hyperinflammatory sepsis enrolled in a two-hospital prospective cohort study. Molecular phenotypes had been previously assigned using latent class analysis.Measurements and Main Results: The hyperinflammatory and hypoinflammatory phenotypes of sepsis had distinct gene expression signatures, with 5,755 genes (31%) differentially expressed. The hyperinflammatory phenotype was associated with elevated expression of innate immune response genes, whereas the hypoinflammatory phenotype was associated with elevated expression of adaptive immune response genes and, notably, T cell response genes. Plasma metagenomic analysis identified differences in prevalence of bacteremia, bacterial DNA abundance, and composition between the phenotypes, with an increased presence and abundance of Enterobacteriaceae in the hyperinflammatory phenotype. Significant overlap was observed between these phenotypes and previously identified transcriptional subtypes of acute respiratory distress syndrome (reactive and uninflamed) and sepsis (SRS1-2). Analysis of data from the VANISH trial indicated that corticosteroids might have a detrimental effect in patients with the hypoinflammatory phenotype.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have distinct transcriptional and metagenomic features that could be leveraged for precision treatment strategies.

Plasma Cell-free RNA Signatures of Inflammatory Syndromes in Children

Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circulating cell-free RNA (cfRNA) in plasma as an analyte for the differential diagnosis and characterization of pediatric inflammatory syndromes. We profiled cfRNA in 370 plasma samples from pediatric patients with a range of inflammatory conditions, including Kawasaki disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), viral infections and bacterial infections. We developed machine learning models based on these cfRNA profiles, which effectively differentiated KD from MIS-C - two conditions presenting with overlapping symptoms - with high performance (Test Area Under the Curve (AUC) = 0.97). We further extended this methodology into a multiclass machine learning framework that achieved 81% accuracy in distinguishing among KD, MIS-C, viral, and bacterial infections. We further demonstrated that cfRNA profiles can be used to quantify injury to specific tissues and organs, including the liver, heart, endothelium, nervous system, and the upper respiratory tract. Overall, this study identified cfRNA as a versatile analyte for the differential diagnosis and characterization of a wide range of pediatric inflammatory syndromes.

[High-throughput sequencing for infectious disease diagnoses: Example of shotgun metagenomics in central nervous system infections]

The advent of high-throughput sequencing in clinical microbiology is opening the way to new diagnostic and prognostic approaches in infectious diseases. Detection, identification and characterisation of pathogenic microorganisms are essential steps in diagnosis and implementation of appropriate antimicrobial therapy. However, standard methods of microbiological diagnosis are failing in some cases. In addition, the emergence of new infections, facilitated by international travel and global warming, requires the implementation of innovative diagnostic methods. Among the different strategies used in clinical microbiology and reviewed in this article, shotgun metagenomics is the only technique that allows today a panpathogenic and unbiased detection of all microorganisms potentially responsible for an infectious disease, including those still unknown. The aims of this article are to present the different possible strategies of high-throughput sequencing used in the microbiological diagnosis of infectious diseases and to highlight the diagnostic contribution of shotgun metagenomics in the field of central nervous system infections.

The Report Says What?: How the Medical Microbiologist can aid in the Interpretation of Next-Generation Sequencing Results

The applications of next-generation sequencing (NGS) in the clinical microbiology laboratory are expanding at a rapid pace. The medical microbiologist thus plays a key role in translating the results of these emerging technologies to the practicing clinician. Here we discuss the factors to consider to successfully develop standardized reporting for microbial targeted or metagenomic NGS testing in the clinical laboratory.

Biological Effects of Corticosteroids on Pneumococcal Pneumonia in Mice and Humans

Background

Streptococcus pneumoniae is the most common bacterial cause of community acquired pneumonia and the acute respiratory distress syndrome (ARDS). Some clinical trials have demonstrated a beneficial effect of corticosteroid therapy in community acquired pneumonia, COVID-19, and ARDS, but the mechanisms of this benefit remain unclear. The objective of this study was to investigate the effects of corticosteroids on the pulmonary biology of pneumococcal pneumonia in an observational cohort of mechanically ventilated patients and in a mouse model of bacterial pneumonia with Streptococcus pneumoniae.

Methods

We studied gene expression with lower respiratory tract transcriptomes from a cohort of mechanically ventilated patients and in mice. We also carried out comprehensive physiologic, biochemical, and histological analyses in mice to identify the mechanisms of lung injury in Streptococcus pneumoniae with and without adjunctive steroid therapy.

Results

Transcriptomic analysis identified pleiotropic effects of steroid therapy on the lower respiratory tract in critically ill patients with pneumococcal pneumonia, findings that were reproducible in mice. In mice with pneumonia, dexamethasone in combination with ceftriaxone reduced (1) pulmonary edema formation, (2) alveolar protein permeability, (3) proinflammatory cytokine release, (4) histopathologic lung injury score, and (5) hypoxemia but did not increase bacterial burden.

Conclusions

The gene expression studies in patients and in the mice support the clinical relevance of the mouse studies, which replicate several features of pneumococcal pneumonia and steroid therapy in humans. In combination with appropriate antibiotic therapy in mice, treatment of pneumococcal pneumonia with steroid therapy reduced hypoxemia, pulmonary edema, lung permeability, and histologic criteria of lung injury, and also altered inflammatory responses at the protein and gene expression level. The results from these studies provide evidence for the mechanisms that may explain the beneficial effects of glucocorticoid therapy in patients with community acquired pneumonia from Streptococcus Pneumoniae.

Host-Microbe Multiomic Profiling Reveals Age-Dependent COVID-19 Immunopathology

Age is a major risk factor for severe coronavirus disease-2019 (COVID-19), yet the mechanisms responsible for this relationship have remained incompletely understood. To address this, we evaluated the impact of aging on host and viral dynamics in a prospective, multicenter cohort of 1,031 patients hospitalized for COVID-19, ranging from 18 to 96 years of age. We performed blood transcriptomics and nasal metatranscriptomics, and measured peripheral blood immune cell populations, inflammatory protein expression, anti-SARS-CoV-2 antibodies, and anti-interferon (IFN) autoantibodies. We found that older age correlated with an increased SARS-CoV-2 viral load at the time of admission, and with delayed viral clearance over 28 days. This contributed to an age-dependent increase in type I IFN gene expression in both the respiratory tract and blood. We also observed age-dependent transcriptional increases in peripheral blood IFN-γ, neutrophil degranulation, and Toll like receptor (TLR) signaling pathways, and decreases in T cell receptor (TCR) and B cell receptor signaling pathways. Over time, older adults exhibited a remarkably sustained induction of proinflammatory genes (e.g., CXCL6) and serum chemokines (e.g., CXCL9) compared to younger individuals, highlighting a striking age-dependent impairment in inflammation resolution. Augmented inflammatory signaling also involved the upper airway, where aging was associated with upregulation of TLR, IL17, type I IFN and IL1 pathways, and downregulation TCR and PD-1 signaling pathways. Metatranscriptomics revealed that the oldest adults exhibited disproportionate reactivation of herpes simplex virus and cytomegalovirus in the upper airway following hospitalization. Mass cytometry demonstrated that aging correlated with reduced naïve T and B cell populations, and increased monocytes and exhausted natural killer cells. Transcriptional and protein biomarkers of disease severity markedly differed with age, with the oldest adults exhibiting greater expression of TLR and inflammasome signaling genes, as well as proinflammatory proteins (e.g., IL6, CXCL8), in severe COVID-19 compared to mild/moderate disease. Anti-IFN autoantibody prevalence correlated with both age and disease severity. Taken together, this work profiles both host and microbe in the blood and airway to provide fresh insights into aging-related immune changes in a large cohort of vaccine-naïve COVID-19 patients. We observed age-dependent immune dysregulation at the transcriptional, protein and cellular levels, manifesting in an imbalance of inflammatory responses over the course of hospitalization, and suggesting potential new therapeutic targets.

Bone morphogenetic protein 9 is a candidate prognostic biomarker and host-directed therapy target for sepsis

Defining next-generation immune therapeutics for the treatment of sepsis will involve biomarker-based therapeutic decision-making. Bone morphogenetic protein 9 (BMP9) is a cytokine in the transforming growth factor-β superfamily. Here, circulating BMP9 concentrations were quantified in two independent cohorts of patients with sepsis. Decreased concentrations of serum BMP9 were observed in the patients with sepsis at the time of admission as compared with healthy controls. Concentrations of BMP9 at the time of admission were also associated with 28-day mortality, because patients with sepsis at a higher risk of death had lower BMP9 concentrations. The mechanism driving the contribution of BMP9 to host immunity was further investigated using in vivo murine sepsis models and in vitro cell models. We found that BMP9 treatment improved outcome in mice with experimental sepsis. BMP9-treated mice exhibited increased macrophage influx into the peritoneal cavity and more efficient bacterial clearance than untreated mice. In vitro, BMP9 promoted macrophage recruitment, phagocytosis, and subsequent bacterial killing. We further found that deletion of the type 1 BMP receptor ALK1 in macrophages abolished BMP9-mediated protection against polymicrobial sepsis in vivo. Further experiments indicated that the regulation of macrophage activation by the BMP9-ALK1 axis was mainly mediated through the suppressor of mother against decapentaplegic 1/5 signaling pathway. Together, these results suggest that BMP9 can both serve as a biomarker for patient stratification with an independent prognostic value and be developed as a host-directed therapy for sepsis.

Quantification of bacterial DNA in blood using droplet digital PCR: a pilot study

We used droplet digital PCR (ddPCR) assays to detect/quantify DNA from Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Enterococcus spp. in blood samples. Bacterial DNA from clinical strains (4 < n < 12) was extracted, quantified and diluted (10-0.0001 ng/µL) and ddPCR assays were performed in triplicate. These ddPCR assays showed low replication variability, low detection limit (1-0.1 pg/µL), and genus/species specificity. ddPCR assays were also used to quantify bacterial DNA obtained from spiked blood (1 × 104-1 CFU/mL) of each bacterial genus/species. Comparison between ddPCR assays and bacterial culture was performed by Pearson correlation. There was an almost perfect correlation (r ≥ 0.997, P ≤ 0.001) between the number of CFU/mL from bacterial culture and the number of gene copies/mL detected by ddPCR. The time from sample preparation to results was determined to be 3.5 to 4 hours. The results demonstrated the quantification capacity and specificity of the ddPCR assays to detect/quantify 4 of the most important bloodstream infection (BSI) bacterial pathogens directly from blood. SIGNIFICANCE AND IMPACT: This pilot study results support the potential of ddPCR for the diagnosis and/or severity stratification of BSI. Applied to patients' blood samples it can improve diagnosis and diminish sample-to-results time, improving patient care.

Noninvasive diagnosis of secondary infections in COVID-19 by sequencing of plasma microbial cell-free DNA

Secondary infection (SI) diagnosis in severe COVID-19 remains challenging. We correlated metagenomic sequencing of plasma microbial cell-free DNA (mcfDNA-Seq) with clinical SI assessment, immune response, and outcomes. We classified 42 COVID-19 inpatients as microbiologically confirmed-SI (Micro-SI, n = 8), clinically diagnosed-SI (Clinical-SI, n = 13, i.e., empiric antimicrobials), or no-clinical-suspicion-for-SI (No-Suspected-SI, n = 21). McfDNA-Seq was successful in 73% of samples. McfDNA detection was higher in Micro-SI (94%) compared to Clinical-SI (57%, p = 0.03), and unexpectedly high in No-Suspected-SI (83%), similar to Micro-SI. We detected culture-concordant mcfDNA species in 81% of Micro-SI samples. McfDNA correlated with LRT 16S rRNA bacterial burden (r = 0.74, p = 0.02), and biomarkers (white blood cell count, IL-6, IL-8, SPD, all p < 0.05). McfDNA levels were predictive of worse 90-day survival (hazard ratio 1.30 [1.02-1.64] for each log10 mcfDNA, p = 0.03). High mcfDNA levels in COVID-19 patients without clinical SI suspicion may suggest SI under-diagnosis. McfDNA-Seq offers a non-invasive diagnostic tool for pathogen identification, with prognostic value on clinical outcomes.

Identification and targeting of microbial putrescine acetylation in bloodstream infections

The growth of antimicrobial resistance (AMR) has highlighted an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe bacterial infections profoundly alter host metabolism, prior studies have largely ignored alterations in microbial metabolism in this context. Performing metabolomics on patient and mouse plasma samples, we identify elevated levels of bacterially-derived N-acetylputrescine during gram-negative bloodstream infections (BSI), with higher levels associated with worse clinical outcomes. We discover that SpeG is the bacterial enzyme responsible for acetylating putrescine and show that blocking its activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity enhances bacterial membrane permeability and results in increased intracellular accumulation of antibiotics, allowing us to overcome AMR of clinical isolates both in culture and in vivo. This study highlights how studying pathogen metabolism in the natural context of infection can reveal new therapeutic strategies for addressing challenging infections.

Use of Electronic Clinical Data to Track Incidence and Mortality for SARS-CoV-2-Associated Sepsis

Importance

Efforts to quantify the burden of SARS-CoV-2-associated sepsis have been limited by inconsistent definitions and underrecognition of viral sepsis.

Objective

To describe the incidence and outcomes of SARS-CoV-2-associated sepsis vs presumed bacterial sepsis using objective electronic clinical criteria.

Design, Setting, and Participants

This retrospective cohort study included adults hospitalized at 5 Massachusetts hospitals between March 2020 and November 2022.

Exposures

SARS-CoV-2-associated sepsis was defined as a positive SARS-CoV-2 polymerase chain reaction test and concurrent organ dysfunction (ie, oxygen support above simple nasal cannula, vasopressors, elevated lactate level, rise in creatine or bilirubin level, and/or decline in platelets). Presumed bacterial sepsis was defined by modified US Centers for Disease Control and Prevention adult sepsis event criteria (ie, blood culture order, sustained treatment with antibiotics, and organ dysfunction using identical thresholds as for SARS-CoV-2-associated sepsis).

Main Outcomes and Measures

Trends in the quarterly incidence (ie, proportion of hospitalizations) and in-hospital mortality for SARS-CoV-2-associated and presumed bacterial sepsis were assessed using negative binomial and logistic regression models.

Results

This study included 431 017 hospital encounters from 261 595 individuals (mean [SD] age 57.9 [19.8] years, 241 131 (55.9%) females, 286 397 [66.5%] from academic hospital site). Of these encounters, 23 276 (5.4%) were from SARS-CoV-2, 6558 (1.5%) had SARS-CoV-2-associated sepsis, and 30 604 patients (7.1%) had presumed bacterial sepsis without SARS-CoV-2 infection. Crude in-hospital mortality for SARS-CoV-2-associated sepsis declined from 490 of 1469 (33.4%) in the first quarter to 67 of 450 (14.9%) in the last (adjusted odds ratio [aOR], 0.88 [95% CI, 0.85-0.90] per quarter). Crude mortality for presumed bacterial sepsis was 4451 of 30 604 patients (14.5%) and stable across quarters (aOR, 1.00 [95% CI, 0.99-1.01]). Medical record reviews of 200 SARS-CoV-2-positive hospitalizations confirmed electronic health record (EHR)-based SARS-CoV-2-associated sepsis criteria performed well relative to sepsis-3 criteria (90.6% [95% CI, 80.7%-96.5%] sensitivity; 91.2% [95% CI, 85.1%-95.4%] specificity).

Conclusions and Relevance

In this retrospective cohort study of hospitalized adults, SARS-CoV-2 accounted for approximately 1 in 6 cases of sepsis during the first 33 months of the COVID-19 pandemic. In-hospital mortality rates for SARS-CoV-2-associated sepsis were high but declined over time and ultimately were similar to presumed bacterial sepsis. These findings highlight the high burden of SARS-CoV-2-associated sepsis and demonstrate the utility of EHR-based algorithms to conduct surveillance for viral and bacterial sepsis.

One biomarker does not fit all: tailoring anti-infective therapy through utilization of procalcitonin and other specific biomarkers

INTRODUCTION

Considering the ongoing increase in antibiotic resistance, the importance of judicious use of antibiotics through reduction of exposure is crucial. Adding procalcitonin (PCT) and other biomarkers to pathogen-specific tests may help to further improve antibiotic therapy algorithms and advance antibiotic stewardship programs to achieve these goals.

AREAS COVERED

In recent years, several trials have investigated the inclusion of biomarkers such as PCT into clinical decision-making algorithms. For adult patients, findings demonstrated improvements in the individualization of antibiotic treatment, particularly for patients with respiratory tract infections and sepsis. While most trials were performed in hospitals with central laboratories, point-of-care testing might further advance the field by providing a cost-effective and rapid diagnostic tool in upcoming years. Furthermore, novel biomarkers including CD-64, presepsin, Pancreatic stone and sTREM-1, have all shown promising results for increased accuracy of sepsis diagnosis. Availability of these markers however is currently still limited and there is insufficient evidence for their routine use in clinical care.

EXPERT OPINION

In addition to new host-response markers, combining such biomarkers with pathogen-directed diagnostics present a promising strategy to increase algorithm accuracy in differentiating between bacterial and viral infections. Recent advances in microbiologic testing using PCR or nucleic amplification tests may further improve the diagnostic yield and promote more targeted pathogen-specific antibiotic therapy.

Differentiating infection, colonisation, and sterile inflammation in critical illness: the emerging role of host-response profiling

Infection results when a pathogen produces host tissue damage and elicits an immune response. Critically ill patients experience immune activation secondary to both sterile and infectious insults, with overlapping clinical phenotypes and underlying immunological mechanisms. Patients also undergo a shift in microbiota with the emergence of pathogen-dominant microbiomes. Whilst the combination of inflammation and microbial shift has long challenged intensivists in the identification of true infection, the advent of highly sensitive molecular diagnostics has further confounded the diagnostic dilemma as the number of microbial detections increases. Given the key role of the host immune response in the development and definition of infection, profiling the host response offers the potential to help unravel the conundrum of distinguishing colonisation and sterile inflammation from true infection. This narrative review provides an overview of current approaches to distinguishing colonisation from infection using routinely available techniques and proposes matrices to support decision-making in this setting. In searching for new tools to better discriminate these states, the review turns to the understanding of the underlying pathobiology of the host response to infection. It then reviews the techniques available to assess this response in a clinically applicable context. It will cover techniques including profiling of transcriptome, protein expression, and immune functional assays, detailing the current state of knowledge in diagnostics along with the challenges and opportunities. The ultimate infection diagnostic tool will likely combine an assessment of both host immune response and sensitive pathogen detection to improve patient management and facilitate antimicrobial stewardship.

Clinical metagenomics-challenges and future prospects

Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.

Cancer and sepsis

Sepsis is one of the leading causes of death worldwide. While mortality is high regardless of inciting infection or comorbidities, mortality in patients with cancer and sepsis is significantly higher than mortality in patients with sepsis without cancer. Cancer patients are also significantly more likely to develop sepsis than the general population. The mechanisms underlying increased mortality in cancer and sepsis patients are multifactorial. Cancer treatment alters the host immune response and can increase susceptibility to infection. Preclinical data also suggests that cancer, in and of itself, increases mortality from sepsis with dysregulation of the adaptive immune system playing a key role. Further, preclinical data demonstrate that sepsis can alter subsequent tumor growth while tumoral immunity impacts survival from sepsis. Checkpoint inhibition is a well-accepted treatment for many types of cancer, and there is increasing evidence suggesting this may be a useful strategy in sepsis as well. However, preclinical studies of checkpoint inhibition in cancer and sepsis demonstrate results that could not have been predicted by examining either variable in isolation. As sepsis management transitions from a 'one size fits all' model to a more individualized approach, understanding the mechanistic impact of cancer on outcomes from sepsis represents an important strategy towards delivering on the promise of precision medicine in the intensive care unit.

[Relevant biomarkers in infectiology]

A biomarker in infectiology should ideally be able to identify infectious agents, monitor clinical response and determine the duration of treatment. This article answers the question to what extent C-reactive protein and procalcitonin meet these requirements and reports on the search for further biomarkers - e.g. with the help of "omics"-based technologies and the integration of artificial intelligence.

Viewing both sides of the coin for infectious disease diagnosis

Optimal management of lower respiratory tract infection relies on distinguishing infectious from noninfectious etiologies and identifying the microbiologic cause if applicable. This process is complicated by overlapping clinical symptoms and the colonizing lung microbiota. In a recent issue of the JCI, Mick, Tsitsiklis, and colleagues apply RNA-Seq to tracheal aspirates from critically ill children and demonstrate how integration of the host response with microbial identification results in a harmonious and accurate diagnostic classifier. Though promising, there are numerous barriers to realizing a combined host and pathogen diagnostic.

Metagenomic Sequencing in the ICU for Precision Diagnosis of Critical Infectious Illnesses

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Utility of metagenomics next-generation sequencing in the diagnosis and treatment of severe infectious diseases in the intensive care unit

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is a new method that combines high-throughput sequencing and bioinformatics analysis. However, it has not become as popular due to the limited testing equipment and high costs and lack of family awareness with not much relevant intensive care unit (ICU) research data.

OBJECTIVE

To explore the clinical use and value of metagenomics next-generation sequencing (mNGS) in patients with sepsis in the ICU.

METHODS

We conducted a retrospective analysis of 102 patients with sepsis admitted to the ICU of Peking University International Hospital from January 2018 to January 2022. Based on whether mNGS was performed, the identified patients were divided into the observation group (n= 51) and the control group (n= 51), respectively. Routine laboratory tests, including routine blood test, C-reactive protein, procalcitonin, and culture of suspicious lesion specimens were performed in both groups within 2 hours after admission to the ICU, while mNGS tests were performed in the observation group. Patients in both groups were routinely given initial anti-infective, anti-shock, and organ support treatment. Antibiotic regimens were optimized in a timely manner according to the etiological results. Relevant clinical data were collected.

RESULTS

The testing cycle of mNGS was shorter than that of the conventional culture (30.79 ± 4.01 h vs. 85.38 ± 9.94 h, P< 0.001), while the positive rate of mNGS was higher than that of the conventional culture (82.35% vs. 45.1%, P< 0.05), with obvious superiority in the detection of viruses and fungus. There were significant differences in the optimal time of antibiotics (48 h vs.100 h) and length of ICU stay (11 d vs. 16 d) between the observation group and control group (P< 0.01) respectively, with no difference in 28-day mortality (33.3% vs. 41.2%, P> 0.05).

CONCLUSION

mNGS is useful in the detection of sepsis-causing pathogens in the ICU with the advantages of short testing time and high positive rate. There was no difference in the 28-day outcome between the two groups, which may be related to other confounding factors such as small sample size. Additional studies with extended sample size are needed.