Emerging Technologies for Molecular Diagnosis of Sepsis

Suppression PCR-Based Selective Enrichment Sequencing for Pathogen and Antimicrobial Resistance Detection on Cell-Free DNA in Sepsis-A Targeted, Blood Culture-Independent Approach for Rapid Pathogen and Resistance Diagnostics in Septic Patients

Sepsis is a life-threatening syndrome triggered by infection and accompanied by high mortality, with antimicrobial resistances (AMRs) further escalating clinical challenges. The rapid and reliable detection of causative pathogens and AMRs are key factors for fast and appropriate treatment, in order to improve outcomes in septic patients. However, current sepsis diagnostics based on blood culture is limited by low sensitivity and specificity while current molecular approaches fail to enter clinical routine. Therefore, we developed a suppression PCR-based selective enrichment sequencing approach (SUPSETS), providing a molecular method combining multiplex suppression PCR with Nanopore sequencing to identify most common sepsis-causative pathogens and AMRs using plasma cell-free DNA. Applying only 1 mL of plasma, we targeted eight pathogens across three kingdoms and ten AMRs in a proof-of-concept study. SUPSETS was successfully tested in an experimental research study on the first ten clinical samples and revealed comparable results to clinical metagenomics while clearly outperforming blood culture. Several clinically relevant AMRs could be additionally detected. Furthermore, SUPSETS provided first pathogen and AMR-specific sequencing reads within minutes of starting sequencing, thereby potentially decreasing time-to-results to 11-13 h and suggesting diagnostic potential in sepsis.

Machine learning based DNA melt curve profiling enables automated novel genotype detection

Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic screening for novel genotypes remains challenging in part due to technological limitations. Towards addressing this challenge, we present an advancement in universal microbial high resolution melting (HRM) analysis that is capable of accomplishing both known genotype identification and novel genotype detection. Specifically, this novel surveillance functionality is achieved through time-series modeling of sequence-defined HRM curves, which is uniquely enabled by the large-scale melt curve datasets generated using our high-throughput digital HRM platform. Taking the detection of bacterial genotypes as a model application, we demonstrate that our algorithms accomplish an overall classification accuracy over 99.7% and perform novelty detection with a sensitivity of 0.96, specificity of 0.96 and Youden index of 0.92. Since HRM-based DNA profiling is an inexpensive and rapid technique, our results add support for the feasibility of its use in surveillance applications.

Universal digital high-resolution melting for the detection of pulmonary mold infections

Invasive mold infections (IMIs) are associated with high morbidity, particularly in immunocompromised patients, with mortality rates between 40% and 80%. Early initiation of appropriate antifungal therapy can substantially improve outcomes, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high-resolution melting (U-dHRM) analysis may enable rapid and robust diagnoses of IMI. A universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these pathogen curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons. U-dHRM achieved 97% overall fungal organism identification accuracy and a turnaround time of ~4 hrs. U-dHRM detected pathogenic molds (Aspergillus, Mucorales, Lomentospora, and Fusarium) in 73% of 30 samples classified as IMI, including mixed infections. Specificity was optimized by requiring the number of pathogenic mold curves detected in a sample to be >8 and a sample volume to be 1 mL, which resulted in 100% specificity in 21 at-risk patients without IMI. U-dHRM showed promise as a separate or combination diagnostic approach to standard mycological tests. U-dHRM's speed, ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples, and detect emerging opportunistic pathogens may aid treatment decisions, improving patient outcomes.

IMPORTANCE

Improvements in diagnostics for invasive mold infections are urgently needed. This work presents a new molecular detection approach that addresses technical and workflow challenges to provide fast pathogen detection, identification, and quantification that could inform treatment to improve patient outcomes.

Biomarkers in Sepsis: A Current Review of New Technologies

Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.

Universal Digital High-Resolution Melt Analysis for the Diagnosis of Bacteremia

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. We, therefore, assessed the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.

A Real-Time Automated Machine Learning Algorithm for Predicting Mortality in Trauma Patients: Survey Says it's Ready for Prime-Time

BACKGROUND

Though artificial intelligence ("AI") has been increasingly applied to patient care, many of these predictive models are retrospective and not readily available for real-time decision-making. This survey-based study aims to evaluate implementation of a new, validated mortality risk calculator (Parkland Trauma Index of Mortality, "PTIM") embedded in our electronic healthrecord ("EHR") that calculates hourly predictions of mortality with high sensitivity and specificity.

METHODS

This is a prospective, survey-based study performed at a level 1 trauma center. An anonymous survey was sent to surgical providers and regarding PTIM implementation. The PTIM score evaluates 23 variables including Glasgow Coma Score (GCS), vital signs, and laboratory data.

RESULTS

Of the 40 completed surveys, 35 reported using PTIM in decision-making. Prior to reviewing PTIM, providers identified perceived top 3 predictors of mortality, including GCS (22/38, 58%), age (18/35, 47%), and maximum heart rate (17/35, 45%). Most providers reported the PTIM assisted their treatment decisions (27/35, 77%) and timing of operative intervention (23/35, 66%). Many providers agreed that PTIM integrated into rounds and patient assessment (22/36, 61%) and that it improved efficiency in assessing patients' potential mortality (21/36, 58%).

CONCLUSIONS

Artificial intelligence algorithms are mostly retrospective and lag in real-time prediction of mortality. To our knowledge, this is the first real-time, automated algorithm predicting mortality in trauma patients. In this small survey-based study, we found PTIM assists in decision-making, timing of intervention, and improves accuracy in assessing mortality. Next steps include evaluating the short- and long-term impact on patient outcomes.

Propofol improves survival in a murine model of sepsis via inhibiting Rab5a-mediated intracellular trafficking of TLR4

BACKGROUND

Propofol is a widely used anesthetic and sedative, which has been reported to exert an anti-inflammatory effect. TLR4 plays a critical role in coordinating the immuno-inflammatory response during sepsis. Whether propofol can act as an immunomodulator through regulating TLR4 is still unclear. Given its potential as a sepsis therapy, we investigated the mechanisms underlying the immunomodulatory activity of propofol.

METHODS

The effects of propofol on TLR4 and Rab5a (a master regulator involved in intracellular trafficking of immune factors) were investigated in macrophage (from Rab5a-/- and WT mice) following treatment with lipopolysaccharide (LPS) or cecal ligation and puncture (CLP) in vitro and in vivo, and peripheral blood monocyte from sepsis patients and healthy volunteers.

RESULTS

We showed that propofol reduced membrane TLR4 expression on macrophages in vitro and in vivo. Rab5a participated in TLR4 intracellular trafficking and both Rab5a expression and the interaction between Rab5a and TLR4 were inhibited by propofol. We also showed Rab5a upregulation in peripheral blood monocytes of septic patients, accompanied by increased TLR4 expression on the cell surface. Propofol downregulated the expression of Rab5a and TLR4 in these cells.

CONCLUSIONS

We demonstrated that Rab5a regulates intracellular trafficking of TLR4 and that propofol reduces membrane TLR4 expression on macrophages by targeting Rab5a. Our study not only reveals a novel mechanism for the immunomodulatory effect of propofol but also indicates that Rab5a may be a potential therapeutic target against sepsis.

Short turnaround time of seven to nine hours from sample collection until informed decision for sepsis treatment using nanopore sequencing

Bloodstream infections (BSIs) and sepsis are major health problems, annually claiming millions of lives. Traditional blood culture techniques, employed to identify sepsis-causing pathogens and assess antibiotic susceptibility, usually take 2-4 days. Early and accurate antibiotic prescription is vital in sepsis to mitigate mortality and antibiotic resistance. This study aimed to reduce the wait time for sepsis diagnosis by employing shorter blood culture incubation times for BD BACTEC™ bottles using standard laboratory incubators, followed by real-time nanopore sequencing and data analysis. The method was tested on nine blood samples spiked with clinical isolates from the six most prevalent sepsis-causing pathogens. The results showed that pathogen identification was possible at as low as 102-104 CFU/mL, achieved after just 2 h of incubation and within 40 min of nanopore sequencing. Moreover, all the antimicrobial resistance genes were identified at 103-107 CFU/mL, achieved after incubation for 5 h and only 10 min to 3 h of sequencing. Therefore, the total turnaround time from sample collection to the information required for an informed decision on the right antibiotic treatment was between 7 and 9 h. These results hold significant promise for better clinical management of sepsis compared with current culture-based methods.

Spectral analysis and sorting of microbial organisms using a spectral sorter

This chapter discusses the problems related to the application of conventional flow cytometers to microbiology. To address some of those limitations, the concept of spectral flow cytometry is introduced and the advantages over conventional flow cytometry for bacterial sorting are presented. We demonstrate by using ThermoFisher's Bigfoot spectral sorter where the spectral signatures of different stains for staining bacteria are demonstrated with an example of performing unmixing on spectral datasets. In addition to the Bigfoot's spectral analysis, the special biosafety features of this instrument are discussed. Utilizing these biosafety features, the sorting and patterning at the single cell level is optimized using non-pathogenic bacteria. Finally, the chapter is concluded by presenting a novel, label free, non-destructive, and rapid phenotypic method called Elastic Light Scattering (ELS) technology for identification of the patterned bacterial cells based on their unique colony scatter patterns.

Development and proof-of-concept demonstration of a clinical metagenomics method for the rapid detection of bloodstream infection

BACKGROUND

The timely and accurate diagnosis of bloodstream infection (BSI) is critical for patient management. With longstanding challenges for routine blood culture, metagenomics is a promising approach to rapidly provide sequence-based detection and characterisation of bloodborne bacteria. Long-read sequencing technologies have successfully supported the use of clinical metagenomics for syndromes such as respiratory illness, and modified approaches may address two requisite factors for metagenomics to be used as a BSI diagnostic: depletion of the high level of host DNA to then detect the low abundance of microbes in blood.

METHODS

Blood samples from healthy donors were spiked with different concentrations of four prevalent causative species of BSI. All samples were then subjected to a modified saponin-based host DNA depletion protocol and optimised DNA extraction, whole genome amplification and debranching steps in preparation for sequencing, followed by bioinformatical analyses. Two related variants of the protocol are presented: 1mL of blood processed without bacterial enrichment, and 5mL of blood processed following a rapid bacterial enrichment protocol-SepsiPURE.

RESULTS

After first identifying that a large proportion of host mitochondrial DNA remained, the host depletion process was optimised by increasing saponin concentration to 3% and scaling the reaction to allow more sample volume. Compared to non-depleted controls, the 3% saponin-based depletion protocol reduced the presence of host chromosomal and mitochondrial DNA < 106 and < 103 fold respectively. When the modified depletion method was further combined with a rapid bacterial enrichment method (SepsiPURE; with 5mL blood samples) the depletion of mitochondrial DNA improved by a further > 10X while also increasing detectable bacteria by > 10X. Parameters during DNA extraction, whole genome amplification and long-read sequencing were also adjusted, and subsequently amplicons were detected for each input bacterial species at each of the spiked concentrations, ranging from 50-100 colony forming units (CFU)/mL to 1-5 CFU/mL.

CONCLUSION

In this proof-of-concept study, four prevalent BSI causative species were detected in under 12 h to species level (with antimicrobial resistance determinants) at concentrations relevant to clinical blood samples. The use of a rapid and precise metagenomic protocols has the potential to advance the diagnosis of BSI.

Comparison of pre-labelled primers and nucleotides as DNA labelling method for lateral flow detection of Legionella pneumophila amplicons

Labelling of nucleic acid amplicons during polymerase chain reaction (PCR) or isothermal techniques is possible by using both labelled primers and labelled nucleotides. While the former is the widely used method, the latter can offer significant advantages in terms of signal enhancement and improving the detection limit of an assay. Advantages and disadvantages of both methods depend on different factors, including amplification method, detection method and amplicon length. In this study, both methods for labelling PCR products for lateral flow assay (LFA) analysis (LFA-PCR) were analysed and compared. It was shown that labelling by means of nucleotides results in an increase in label incorporation rates. Nonetheless, this advantage is negated by the need for post-processing and competitive interactions. In the end, it was possible to achieve a detection limit of 3 cell equivalents for the detection of the Legionella-DNA used here via primer labelling. Labelling via nucleotides required genomic DNA of at least 3000 cell equivalents as starting material as well as an increased personnel and experimental effort.

Microfluidic systems for infectious disease diagnostics

Microorganisms, encompassing both uni- and multicellular entities, exhibit remarkable diversity as omnipresent life forms in nature. They play a pivotal role by supplying essential components for sustaining biological processes across diverse ecosystems, including higher host organisms. The complex interactions within the human gut microbiota are crucial for metabolic functions, immune responses, and biochemical signalling, particularly through the gut-brain axis. Viruses also play important roles in biological processes, for example by increasing genetic diversity through horizontal gene transfer when replicating inside living cells. On the other hand, infection of the human body by microbiological agents may lead to severe physiological disorders and diseases. Infectious diseases pose a significant burden on global healthcare systems, characterized by substantial variations in the epidemiological landscape. Fast spreading antibiotic resistance or uncontrolled outbreaks of communicable diseases are major challenges at present. Furthermore, delivering field-proven point-of-care diagnostic tools to the most severely affected populations in low-resource settings is particularly important and challenging. New paradigms and technological approaches enabling rapid and informed disease management need to be implemented. In this respect, infectious disease diagnostics taking advantage of microfluidic systems combined with integrated biosensor-based pathogen detection offers a host of innovative and promising solutions. In this review, we aim to outline recent activities and progress in the development of microfluidic diagnostic tools. Our literature research mainly covers the last 5 years. We will follow a classification scheme based on the human body systems primarily involved at the clinical level or on specific pathogen transmission modes. Important diseases, such as tuberculosis and malaria, will be addressed more extensively.

From Shadows to Spotlight: Enhancing Bacterial DNA Detection in Blood Samples through Cutting-Edge Molecular Pre-Amplification

One of the greatest challenges to the use of molecular methods for diagnostic purposes is the detection of target DNA that is present only in low concentrations. One major factor that negatively impacts accuracy, diagnostic sensitivity, and specificity is the sample matrix, which hinders the attainment of the required detection limit due to the presence of residual background DNA. To address this issue, various methods have been developed to enhance sensitivity through targeted pre-amplification of marker sequences. Diagnostic sensitivity to the single molecular level is critical, particularly when identifying bloodstream infections. In cases of clinically manifest sepsis, the concentration of bacteria in the blood may reach as low as one bacterial cell/CFU per mL of blood. Therefore, it is crucial to achieve the highest level of sensitivity for accurate detection. In the present study, we have established a method that fills the analytical gap between low concentrations of molecular markers and the minimum requirements for molecular testing. For this purpose, a sample preparation of whole blood samples with a directly downstream pre-amplification was developed, which amplifies specific species and resistance markers in a multiplex procedure. When applying pre-amplification techniques, the sensitivity of the pathogen detection in whole blood samples was up to 100 times higher than in non-pre-amplified samples. The method was tested with blood samples that were spiked with several Gram-positive and Gram-negative bacterial pathogens. By applying this method to artificial spiked blood samples, it was possible to demonstrate a sensitivity of 1 colony-forming unit (CFU) per millilitre of blood for S. aureus and E. faecium. A detection limit of 28 and 383 CFU per ml of blood was achieved for E. coli and K. pneumoniae, respectively. If the sensitivity is also confirmed for real clinical blood samples from septic patients, the novel technique can be used for pathogen detection without cultivation, which might help to accelerate diagnostics and, thus, to decrease sepsis mortality rates.

Rapid nanopore sequencing and predictive susceptibility testing of positive blood cultures from intensive care patients with sepsis

We aimed to evaluate the performance of Oxford Nanopore Technologies (ONT) sequencing from positive blood culture (BC) broths for bacterial identification and antimicrobial susceptibility prediction. Patients with suspected sepsis in four intensive care units were prospectively enrolled. Human-depleted DNA was extracted from positive BC broths and sequenced using ONT (MinION). Species abundance was estimated using Kraken2, and a cloud-based system (AREScloud) provided in silico predictive antimicrobial susceptibility testing (AST) from assembled contigs. Results were compared to conventional identification and phenotypic AST. Species-level agreement between conventional methods and AST predicted from sequencing was 94.2% (49/52), increasing to 100% in monomicrobial infections. In 262 high-quality AREScloud AST predictions across 24 samples, categorical agreement (CA) was 89.3%, with major error (ME) and very major error (VME) rates of 10.5% and 12.1%, respectively. Over 90% CA was achieved for some taxa (e.g., Staphylococcus aureus) but was suboptimal for Pseudomonas aeruginosa. In 470 AST predictions across 42 samples, with both high quality and exploratory-only predictions, overall CA, ME, and VME rates were 87.7%, 8.3%, and 28.4%. VME rates were inflated by false susceptibility calls in a small number of species/antibiotic combinations with few representative resistant isolates. Time to reporting from sequencing could be achieved within 8-16 h from BC positivity. Direct sequencing from positive BC broths is feasible and can provide accurate predictive AST for some species. ONT-based approaches may be faster but significant improvements in accuracy are required before it can be considered for clinical use.IMPORTANCESepsis and bloodstream infections carry a high risk of morbidity and mortality. Rapid identification and susceptibility prediction of causative pathogens, using Nanopore sequencing direct from blood cultures, may offer clinical benefit. We assessed this approach in comparison to conventional phenotypic methods and determined the accuracy of species identification and susceptibility prediction from genomic data. While this workflow holds promise, and performed well for some common bacterial species, improvements in sequencing accuracy and more robust predictive algorithms across a diverse range of organisms are required before this can be considered for clinical use. However, results could be achieved in timeframes that are faster than conventional phenotypic methods.

A novel anoikis-related gene signature predicts prognosis in patients with sepsis and reveals immune infiltration

Sepsis is a common acute and severe medical condition with a high mortality rate. Anoikis, an emerging form of cell death, plays a significant role in various diseases. However, the role of anoikis in sepsis remains poorly understood. Based on the datasets from Gene Expression Omnibus and anoikis-related genes from GeneCards, the differentially expressed anoikis-related genes (DEARGs) were identified. Based on hub genes of DEARGs, a novel prognostic risk model was constructed, and the pattern of immune infiltration was investigated by CIBERSORT algorithm. And small molecule compounds targeting anoikis in sepsis were analyzed using Autodock. Of 23 DEARGs, CXCL8, CFLAR, FASLG and TP53 were significantly associated with the prognosis of sepsis (P < 0.05). Based on the prognostic risk model constructed with these four genes, high-risk population of septic patients had significant lower survival probability than low-risk population (HR = 3.30, P < 0.001). And the level of CFLAR was significantly correlated with the number of neutrophils in septic patients (r = 0.54, P < 0.001). Moreover, tozasertib had low binding energy with CXCL8, CFLAR, FASLG and TP53, and would be a potential compound for sepsis. Conclusively, our results identified a new prognostic model and potential therapeutic molecular for sepsis, providing new insights on mechanism and treatment of sepsis.

An overview of the mechanisms and potential roles of extracellular vesicles in septic shock

Septic shock, a subset of sepsis, is a fatal condition associated with high morbidity and mortality. However, the pathophysiology of septic shock is not fully understood. Moreover, the diagnostic markers employed for identifying septic shock lack optimal sensitivity and specificity. Current treatment protocols for septic shock have not been effective in lowering the mortality rate of patients. Most cells exhibit the capability to release extracellular vesicles (EVs), nanoscale vesicles that play a vital role in intercellular communication. In recent years, researchers have investigated the potential role of EVs in the pathogenesis, diagnosis, and treatment of different diseases, such as oncological, neurological, and cardiovascular diseases, as well as diabetes and septic shock. In this article, we present an overview of the inhibitory and facilitative roles that EVs play in the process of septic shock, the potential role of EVs in the diagnosis of septic shock, and the potential therapeutic applications of both native and engineered EVs in the management of septic shock.

Magnetic nanoparticles fabricated/integrated with microfluidics for biological applications: A review

Nanostructured materials have gained significant attention in recent years for their potential in biological applications, such as cell and biomolecular sorting, as well as early detection of metastatic cancer. Among these materials, magnetic nanoparticles (MNPs) stand out for their easy functionalization, high specific surface area, chemical stability, and superparamagnetic properties. However, conventional fabrication methods can lead to inconsistencies in MNPs' characteristics and performance, highlighting the need for a cost-effective, controllable, and reproducible synthesis approach. In this review, we will discuss the utilization of microfluidic technology as a cutting-edge strategy for the continuous and regulated synthesis of MNPs. This approach has proven effective in producing MNPs with a superior biomedical performance by offering precise control over particle size, shape, and surface properties. We will examine the latest research findings on developing and integrating MNPs synthesized through continuous microfluidic processes for a wide range of biological applications. By providing an overview of the current state of the field, this review aims to showcase the advantages of microfluidics in the fabrication and integration of MNPs, emphasizing their potential to revolutionize diagnostic and therapeutic methods within the realm of biotechnology.

Multidrug-Resistant Sepsis: A Critical Healthcare Challenge

Sepsis globally accounts for an alarming annual toll of 48.9 million cases, resulting in 11 million deaths, and inflicts an economic burden of approximately USD 38 billion on the United States healthcare system. The rise of multidrug-resistant organisms (MDROs) has elevated the urgency surrounding the management of multidrug-resistant (MDR) sepsis, evolving into a critical global health concern. This review aims to provide a comprehensive overview of the current epidemiology of (MDR) sepsis and its associated healthcare challenges, particularly in critically ill hospitalized patients. Highlighted findings demonstrated the complex nature of (MDR) sepsis pathophysiology and the resulting immune responses, which significantly hinder sepsis treatment. Studies also revealed that aging, antibiotic overuse or abuse, inadequate empiric antibiotic therapy, and underlying comorbidities contribute significantly to recurrent sepsis, thereby leading to septic shock, multi-organ failure, and ultimately immune paralysis, which all contribute to high mortality rates among sepsis patients. Moreover, studies confirmed a correlation between elevated readmission rates and an increased risk of cognitive and organ dysfunction among sepsis patients, amplifying hospital-associated costs. To mitigate the impact of sepsis burden, researchers have directed their efforts towards innovative diagnostic methods like point-of-care testing (POCT) devices for rapid, accurate, and particularly bedside detection of sepsis; however, these methods are currently limited to detecting only a few resistance biomarkers, thus warranting further exploration. Numerous interventions have also been introduced to treat MDR sepsis, including combination therapy with antibiotics from two different classes and precision therapy, which involves personalized treatment strategies tailored to individual needs. Finally, addressing MDR-associated healthcare challenges at regional levels based on local pathogen resistance patterns emerges as a critical strategy for effective sepsis treatment and minimizing adverse effects.

Molecular antimicrobial susceptibility testing in sepsis

Rapidly detecting and identifying pathogens is crucial for appropriate antimicrobial therapy in patients with sepsis. Conventional diagnostic methods have been a great asset to medicine, though they are time consuming and labor intensive. This work will enable healthcare professionals to understand the bacterial community better and enhance their diagnostic capacity by using novel molecular methods that make obtaining quicker, more precise results possible. The authors discuss and critically assess the merits and drawbacks of molecular testing and the added value of these tests, including the shift turnaround time, the implication for clinicians' decisions, gaps in knowledge, future research directions and novel insights or innovations. The field of antimicrobial molecular testing has seen several novel insights and innovations to improve the diagnosis and management of infectious diseases.

Pneumonia in the first week after polytrauma is associated with reduced blood levels of soluble herpes virus entry mediator

Background

Pneumonia develops frequently after major surgery and polytrauma and thus in the presence of systemic inflammatory response syndrome (SIRS) and organ dysfunction. Immune checkpoints balance self-tolerance and immune activation. Altered checkpoint blood levels were reported for sepsis. We analyzed associations of pneumonia incidence in the presence of SIRS during the first week of critical illness and trends in checkpoint blood levels.

Materials and methods

Patients were studied from day two to six after admission to a surgical intensive care unit (ICU). Blood was sampled and physician experts retrospectively adjudicated upon the presence of SIRS and Sepsis-1/2 every eight hours. We measured the daily levels of immune checkpoints and inflammatory markers by bead arrays for polytrauma patients developing pneumonia. Immune checkpoint time series were additionally determined for clinically highly similar polytrauma controls remaining infection-free during follow-up. We performed cluster analyses. Immune checkpoint time trends in cases and controls were compared with hierarchical linear models. For patients with surgical trauma and with and without sepsis, selected immune checkpoints were determined in study baseline samples.

Results

In polytrauma patients with post-injury pneumonia, eleven immune checkpoints dominated subcluster 3 that separated subclusters 1 and 2 of myeloid markers from subcluster 4 of endothelial activation, tissue inflammation, and adaptive immunity markers. Immune checkpoint blood levels were more stable in polytrauma cases than controls, where they trended towards an increase in subcluster A and a decrease in subcluster B. Herpes virus entry mediator (HVEM) levels (subcluster A) were lower in cases throughout. In unselected surgical patients, sepsis was not associated with altered HVEM levels at the study baseline.

Conclusion

Pneumonia development after polytrauma until ICU-day six was associated with decreased blood levels of HVEM. HVEM signaling may reduce pneumonia risk by strengthening myeloid antimicrobial defense and dampening lymphoid-mediated tissue damage. Future investigations into the role of HVEM in pneumonia and sepsis development and as a predictive biomarker should consider the etiology of critical illness and the site of infection.

Metagenomic identification of pathogens and antimicrobial-resistant genes in bacterial positive blood cultures by nanopore sequencing

Nanopore sequencing workflows have attracted increasing attention owing to their fast, real-time, and convenient portability. Positive blood culture samples were collected from patients with bacterial bloodstream infection and tested by nanopore sequencing. This study compared the sequencing results for pathogen taxonomic profiling and antimicrobial resistance genes to those of species identification and phenotypic drug susceptibility using traditional microbiology testing. A total of 37 bacterial positive blood culture results of strain genotyping by nanopore sequencing were consistent with those of mass spectrometry. Among them, one mixed infection of bacteria and fungi was identified using nanopore sequencing and confirmatory quantitative polymerase chain reaction. The amount of sequencing data was 21.89 ± 8.46 MB for species identification, and 1.0 MB microbial strain data enabled accurate determination. Data volumes greater than or equal to 94.6 MB nearly covered all the antimicrobial resistance genes of the bacteria in our study. In addition, the results of the antimicrobial resistance genes were compared with those of phenotypic drug susceptibility testing for Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus. Therefore, the nanopore sequencing platform for rapid identification of causing pathogens and relevant antimicrobial resistance genes complementary to conventional blood culture outcomes may optimize antimicrobial stewardship management for patients with bacterial bloodstream infection.

Expanded Multiplexing on Sensor-Constrained Microfluidic Partitioning Systems

Microfluidics can split samples into thousands or millions of partitions, such as droplets or nanowells. Partitions capture analytes according to a Poisson distribution, and in diagnostics, the analyte concentration is commonly inferred with a closed-form solution via maximum likelihood estimation (MLE). Here, we present a new scalable approach to multiplexing analytes. We generalize MLE with microfluidic partitioning and extend our previously developed Sparse Poisson Recovery (SPoRe) inference algorithm. We also present the first in vitro demonstration of SPoRe with droplet digital PCR (ddPCR) toward infection diagnostics. Digital PCR is intrinsically highly sensitive, and SPoRe helps expand its multiplexing capacity by circumventing its channel limitations. We broadly amplify bacteria with 16S ddPCR and assign barcodes to nine pathogen genera by using five nonspecific probes. Given our two-channel ddPCR system, we measured two probes at a time in multiple groups of droplets. Although individual droplets are ambiguous in their bacterial contents, we recover the concentrations of bacteria in the sample from the pooled data. We achieve stable quantification down to approximately 200 total copies of the 16S gene per sample, enabling a suite of clinical applications given a robust upstream microbial DNA extraction procedure. We develop a new theory that generalizes the application of this framework to many realistic sensing modalities, and we prove scaling rules for system design to achieve further expanded multiplexing. The core principles demonstrated here could impact many biosensing applications with microfluidic partitioning.

Exploring the Utility of Multiplex Infectious Disease Panel Testing for Diagnosis of Infection in Different Body Sites: A Joint Report of the Association for Molecular Pathology, American Society for Microbiology, Infectious Diseases Society of America, and Pan American Society for Clinical Virology

The use of clinical molecular diagnostic methods for detecting microbial pathogens continues to expand and, in some cases, supplant conventional identification methods in various scenarios. Analytical and clinical benefits of multiplex molecular panels for the detection of respiratory pathogens have been demonstrated in various studies. The use of these panels in managing different patient populations has been incorporated into clinical guidance documents. The Association for Molecular Pathology's Infectious Diseases Multiplex Working Group conducted a review of the current benefits and challenges to using multiplex PCR for the detection of pathogens from gastrointestinal tract, central nervous system, lower respiratory tract, and joint specimens. The Working Group also discusses future directions and novel approaches to detection of pathogens in alternate specimen types, and outlines challenges associated with implementation of these multiplex PCR panels.

A broad-based probe-free qPCR assay for detection and discrimination of three human herpes viruses

Primary infection or reactivation of latent human cytomegalovirus (HCMV) or herpes simplex viruses (HSV) 1 or 2 during pregnancy can transmit the virus in utero or during natural childbirth to the fetus. The majority of these infections are asymptomatic at birth but may present later with potentially lethal disseminated infection or meningitis (HSV), or long-term neurodevelopmental sequelae including sensorineural hearing loss or neurodevelopmental impairments (HCMV). Unfortunately, early signs and symptoms of disseminated viral infections may be misdiagnosed as bacterial sepsis. Therefore, immediate testing for viral etiologies may not be ordered or even considered by skilled clinicians. In asymptomatic HCMV infections, early detection is necessary to monitor for and treat future neurologic sequelae. In acutely ill-appearing infants, specific detection of viruses against other disease-causing agents is vital to inform correct patient management, including early administration of the correct antimicrobial(s). An ideal test should be rapid, inexpensive, require low sample volumes, and demonstrate efficacy in multiple tissue matrices to aid in timely clinical decision-making for neonatal infections. This work discusses the development of a rapid probe-free qPCR assay for HSV and HCMV that enables early and specific detection of these viruses in neonates. The assay's probe free chemistry would allow easier extension to a broad-based multiplexed pathogenic panel as compared to assays utilizing sequence-specific probes or nested PCR.

Clinical application of amplification-based versus amplification-free metagenomic next-generation sequencing test in infectious diseases

Background

Recently, metagenomic next-generation sequencing (mNGS) has been used in the diagnosis of infectious diseases (IDs) as an emerging and powerful tool. However, whether the complicated methodological variation in mNGS detections makes a difference in their clinical performance is still unknown. Here we conducted a method study on the clinical application of mNGS tests in the DNA detection of IDs.

Methods

We analyzed the effect of several potential factors in the whole process of mNGS for DNA detection on microorganism identification in 98 samples of suspected ID patients by amplification-based mNGS. The amplification-based and amplification-free mNGS tests were successfully performed in 41 samples. Then we compared the clinical application of the two mNGS methods in the DNA detection of IDs.

Results

We found that a higher concentration of extracted nucleic acid was more conducive to detecting microorganisms. Other potential factors, such as read depth and proportion of human reads, might not be attributed to microorganism identification. The concordance rate of amplification-based and amplification-free mNGS results was 80.5% (33/41) in the patients with suspected IDs. Amplification-based mNGS showed approximately 16.7% higher sensitivity than amplification-free mNGS. However, 4 cases with causative pathogens only detected by amplification-based mNGS were finally proved false-positive. In addition, empirical antibiotic treatments were adjusted in 18 patients following mNGS testing with unexpected pathogens.

Conclusions

Amplification-based and amplification-free mNGS tests showed their specific advantages and disadvantages in the diagnosis of IDs. The clinical application of mNGS still needs more exploration from a methodological perspective. With advanced technology and standardized procedure, mNGS will play a promising role in the diagnosis of IDs and help guide the use of antibiotics.

Universal Digital High Resolution Melt for the detection of pulmonary mold infections

Background

Invasive mold infections (IMIs) such as aspergillosis, mucormycosis, fusariosis, and lomentosporiosis are associated with high morbidity and mortality, particularly in immunocompromised patients, with mortality rates as high as 40% to 80%. Outcomes could be substantially improved with early initiation of appropriate antifungal therapy, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high resolution melting analysis (U-dHRM) may enable rapid and robust diagnosis of IMI. This technology aims to accomplish timely pathogen detection at the single genome level by conducting broad-based amplification of microbial barcoding genes in a digital polymerase chain reaction (dPCR) format, followed by high-resolution melting of the DNA amplicons in each digital reaction to generate organism-specific melt curve signatures that are identified by machine learning.

Methods

A universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these 19 fungal melt curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage (BAL) samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons.

Results

U-dHRM achieved an average of 97% fungal organism identification accuracy and a turn-around-time of 4hrs. Pathogenic molds (Aspergillus, Mucorales, Lomentospora and Fusarium) were detected by U-dHRM in 73% of BALF samples suspected of IMI. Mixtures of pathogenic molds were detected in 19%. U-dHRM demonstrated good sensitivity for IMI, as defined by current diagnostic criteria, when clinical findings were also considered.

Conclusions

U-dHRM showed promising performance as a separate or combination diagnostic approach to standard mycological tests. The speed of U-dHRM and its ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples as well as detect emerging opportunistic pathogens may provide information that could aid in treatment decisions and improve patient outcomes.

Unleashing the power of artificial intelligence for diagnosing and treating infectious diseases: A comprehensive review

Infectious diseases present a global challenge, requiring accurate diagnosis, effective treatments, and preventive measures. Artificial intelligence (AI) has emerged as a promising tool for analysing complex molecular data and improving the diagnosis, treatment, and prevention of infectious diseases. Computer-aided detection (CAD) using convolutional neural networks (CNN) has gained prominence for diagnosing tuberculosis (TB) and other infectious diseases such as COVID-19, HIV, and viral pneumonia. The review discusses the challenges and limitations associated with AI in this field and explores various machine-learning models and AI-based approaches. Artificial neural networks (ANN), recurrent neural networks (RNN), support vector machines (SVM), multilayer neural networks (MLNN), CNN, long short-term memory (LSTM), and random forests (RF) are among the models discussed. The review emphasizes the potential of AI to enhance the accuracy and efficiency of diagnosis, treatment, and prevention of infectious diseases, highlighting the need for further research and development in this area.

Time to embrace sepsis pathways and antibiotic prescribing decision support in the emergency department: Observations from a retrospective single site clinical audit

OBJECTIVE

To compare clinician documentation of sepsis for infective presentations in the ED against a formal sepsis pathway in the ED and to assess appropriateness of the initial parenteral antibiotic prescription for adult patients in ED.

METHODS

A retrospective, clinical audit of adult patients who received at least one parenteral antibiotic in ED over a 10-week period in 2018. Documented initial clinical impression was compared with an approved sepsis pathway. Antibiotic appropriateness was assessed using National Antimicrobial Prescribing Survey definitions. Assessment was carried out by an infectious diseases pharmacist, with input from an infectious diseases physician.

RESULTS

Two hundred and nineteen infective presentations were included in the analysis. There was a discordance between the initial documented clinical impression compared with the classification when a sepsis pathway was applied. An initial documented clinical impression of sepsis and septic shock was present in 38 (60.3%) of the presentations compared to 63 presentations when a formal sepsis pathway was applied as a screening tool. There was a significant difference in the proportion of patients in each diagnostic group (infection, sepsis and septic shock) according to documented clinical impression versus sepsis pathway classification (P = 0.0002). There were 386 prescriptions for antibiotics as part of the initial management. Antibiotic appropriateness for the initial prescription was assessed as 63.7% appropriate, 27.2% inappropriate and 9.1% not assessable.

CONCLUSION

Our observations demonstrate that use of a formal sepsis pathway may improve the screening and early diagnosis of sepsis and septic shock and that there is a need for antibiotic prescribing guidance in the ED.

Universal digital high resolution melt analysis for the diagnosis of bacteremia

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires ∼15 hours to detect the presence of a pathogen. Here, we assess the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 21 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 90.5% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1 mL sample input and sample-to-answer time of 6 hrs. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.

Universal digital high resolution melt analysis for the diagnosis of bacteremia

April Aralar, Tyler Goshia, Nanda Ramchandar, Shelley M. Lawrence, Aparajita Karmakar, Ankit Sharma, Mridu Sinha, David Pride, Peiting Kuo, Khrissa Lecrone, Megan Chiu, Karen Mestan, Eniko Sajti, Michelle Vanderpool, Sarah Lazar, Melanie Crabtree, Yordanos Tesfai, Stephanie I. Fraley.

A PCR-Reverse Dot Blot Hybridization Based Microfluidics Detection System for the Rapid Identification of 13 Fungal Pathogens Directly After Blood Cultures Over a Period of Time

Introduction

It is time-consuming to identify fungal pathogens from positive blood cultures using the standard culture-based method. And delayed diagnosis of bloodstream infection leads to significantly increased mortality.

Methods

We developed a PCR-reverse dot blot hybridization combined with microfluidic chip techniques to rapidly identify 13 fungal pathogens within 3-4 h using the sample of blood cultured over a period of time.

Results

We performed clinical validation using 43 blood culture-positive samples with a sensitivity of 96.7%, a specificity of 100%, and a concordance rate of 97.7%. Samples with different culture durations were evaluated using our approach, showing a detection rate of 85.2% at 16 h and 96.3% at 24 h; the platform could reach a detection limit of 103cfu/mL for the Candida spp. and 103 copies/mL for Aspergillus spp.

Discussion

The detection rate of the platform is much higher than the positive rates of concurrent blood cultures. This method bears substantial clinical application potential as it incorporates the microfluidic platform with low reagent consumption, automation, and low cost (about 10 dollars).

Phage diversity in cell-free DNA identifies bacterial pathogens in human sepsis cases

Bacteriophages, viruses that infect bacteria, have great specificity for their bacterial hosts at the strain and species level. However, the relationship between the phageome and associated bacterial population dynamics is unclear. Here we generated a computational pipeline to identify sequences associated with bacteriophages and their bacterial hosts in cell-free DNA from plasma samples. Analysis of two independent cohorts, including a Stanford Cohort of 61 septic patients and 10 controls and the SeqStudy cohort of 224 septic patients and 167 controls, reveals a circulating phageome in the plasma of all sampled individuals. Moreover, infection is associated with overrepresentation of pathogen-specific phages, allowing for identification of bacterial pathogens. We find that information on phage diversity enables identification of the bacteria that produced these phages, including pathovariant strains of Escherichia coli. Phage sequences can likewise be used to distinguish between closely related bacterial species such as Staphylococcus aureus, a frequent pathogen, and coagulase-negative Staphylococcus, a frequent contaminant. Phage cell-free DNA may have utility in studying bacterial infections.

An update on current and novel molecular diagnostics for the diagnosis of invasive fungal infections

BACKGROUND

Invasive fungal infections cause millions of infections annually, but diagnosis remains challenging. There is an increased need for low-cost, easy to use, highly sensitive and specific molecular assays that can differentiate between colonized and pathogenic organisms from different clinical specimens.

AREAS COVERED

We reviewed the literature evaluating the current state of molecular diagnostics for invasive fungal infections, focusing on current and novel molecular tests such as polymerase chain reaction (PCR), digital PCR, high-resolution melt (HRM), and metagenomics/next generation sequencing (mNGS).

EXPERT OPINION

PCR is highly sensitive and specific, although performance can be impacted by prior/concurrent antifungal use. PCR assays can identify mutations associated with antifungal resistance, non-Aspergillus mold infections, and infections from endemic fungi. HRM is a rapid and highly sensitive diagnostic modality that can identify a wide range of fungal pathogens, including down to the species level, but multiplex assays are limited and HRM is currently unavailable in most healthcare settings, although universal HRM is working to overcome this limitation. mNGS offers a promising approach for rapid and hypothesis-free diagnosis of a wide range of fungal pathogens, although some drawbacks include limited access, variable performance across platforms, the expertise and costs associated with this method, and long turnaround times in real-world settings.

Chemo Markers as Biomarkers in Septic Shock: A Comprehensive Review of Their Utility and Clinical Applications

Sepsis is a life-threatening condition characterized by a dysregulated host response to infection, often leading to septic shock. Early diagnosis and prompt intervention are crucial for improving patient outcomes. Chemo markers, which are measurable biological substances associated with the pathophysiology of septic shock, have emerged as potential biomarkers for the identification, risk stratification, and management of this condition. This comprehensive review aims to thoroughly evaluate the utility and clinical applications of chemo markers in septic shock. The review begins by discussing the criteria for ideal chemo markers, including specificity, sensitivity, dynamic range, stability, non-invasiveness, and prognostic value. These characteristics ensure accurate diagnosis, early detection, effective monitoring, and prediction of clinical outcomes. Furthermore, the review explores the role of chemo markers in monitoring treatment response and disease progression, highlighting their ability to serve as objective indicators for assessing the effectiveness of interventions and making timely adjustments in management strategies. Moreover, the prognostic value of chemo markers in predicting outcomes is discussed, emphasizing their association with mortality, hospital stays, and the development of complications. Integration of chemo markers into prognostic models or scoring systems enhances risk stratification and informs therapeutic decisions. The review also delves into recent advances in chemo marker research and technology, emphasizing the potential for discovering novel chemo markers with enhanced diagnostic and prognostic capabilities. It highlights the use of high-throughput proteomics, genomics, and transcriptomics in identifying specific molecular signatures associated with septic shock. This contributes to a deeper understanding of the complex immune and inflammatory responses involved. In conclusion, chemo markers have emerged as valuable biomarkers in septic shock, offering potential utility in diagnosis, risk stratification, treatment monitoring, and prediction of outcomes. Continued research, validation, and integration into clinical practice are necessary to fully realize their potential in improving patient care and outcomes in septic shock.

Six potential biomarkers in septic shock: a deep bioinformatics and prospective observational study

Background

Septic shock occurs when sepsis is related to severe hypotension and leads to a remarkable high number of deaths. The early diagnosis of septic shock is essential to reduce mortality. High-quality biomarkers can be objectively measured and evaluated as indicators to accurately predict disease diagnosis. However, single-gene prediction efficiency is inadequate; therefore, we identified a risk-score model based on gene signature to elevate predictive efficiency.

Methods

The gene expression profiles of GSE33118 and GSE26440 were downloaded from the Gene Expression Omnibus (GEO) database. These two datasets were merged, and the differentially expressed genes (DEGs) were identified using the limma package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed. Subsequently, Lasso regression and Boruta feature selection algorithm were combined to identify the hub genes of septic shock. GSE9692 was then subjected to weighted gene co-expression network analysis (WGCNA) to identify the septic shock-related gene modules. Subsequently, the genes within such modules that matched with septic shock-related DEGs were identified as the hub genes of septic shock. To further understand the function and signaling pathways of hub genes, we performed gene set variation analysis (GSVA) and then used the CIBERSORT tool to analyze the immune cell infiltration pattern of diseases. The diagnostic value of hub genes in septic shock was determined using receiver operating characteristic (ROC) analysis and verified using quantitative PCR (qPCR) and Western blotting in our hospital patients with septic shock.

Results

A total of 975 DEGs in the GSE33118 and GSE26440 databases were obtained, of which 30 DEGs were remarkably upregulated. With the use of Lasso regression and Boruta feature selection algorithm, six hub genes (CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4) with expression differences in septic shock were screened as potential diagnostic markers for septic shock among the significant DEGs and were further validated in the GSE9692 dataset. WGCNA was used to identify the co-expression modules and module-trait correlation. Enrichment analysis showed significant enrichment in the reactive oxygen species pathway, hypoxia, phosphatidylinositol 3-kinases (PI3K)/Protein Kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling, nuclear factor-κβ/tumor necrosis factor alpha (NF-κβ/TNF-α), and interleukin-6 (IL-6)/Janus Kinase (JAK)/Signal Transducers and Activators of Transcription 3 (STAT3) signaling pathways. The receiver operating characteristic curve (ROC) of these signature genes was 0.938, 0.914, 0.939, 0.956, 0.932, and 0.914, respectively. In the immune cell infiltration analysis, the infiltration of M0 macrophages, activated mast cells, neutrophils, CD8 T cells, and naive B cells was more significant in the septic shock group. In addition, higher expression levels of CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 messenger RNA (mRNA) were observed in peripheral blood mononuclear cells (PBMCs) isolated from septic shock patients than from healthy donors. Higher expression levels of CD177 and MMP8 proteins were also observed in the PBMCs isolated from septic shock patients than from control participants.

Conclusions

CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 were identified as hub genes, which were of considerable value in the early diagnosis of septic shock patients. These preliminary findings are of great significance for studying immune cell infiltration in the pathogenesis of septic shock, which should be further validated in clinical studies and basic studies.

Electrochemical point-of-care devices for the diagnosis of sepsis

Sepsis is a life-threatening dysfunction of organ systems caused by a dysregulated immune system because of an infectious process. It remains one of the leading causes of hospital mortality and of hospital readmissions in the United States. Mortality from sepsis increases with each hour of delayed treatment, therefore, diagnostic devices that can reduce the time from the onset of a patient's infection to the delivery of appropriate therapy are urgently needed. Likewise, tools that are capable of high-frequency testing of clinically relevant biomarkers are required to study disease progression. Electrochemical biosensors offer important advantages such as high sensitivity, fast response, miniaturization, and low cost that can be adapted to clinical needs. In this review paper, we discuss the current state, limitations, and future directions of electrochemical-based point-of-care detection platforms that contribute to the diagnosis and monitoring of sepsis.

Predictive value of cell population data with Sysmex XN-series hematology analyzer for culture-proven bacteremia

Background

Cell population data (CPD) parameters related to neutrophils, such as fluorescent light intensity (NE-SFL) and fluorescent light distribution width index (NE-WY), have emerged as potential biomarkers for sepsis. However, the diagnostic implication in acute bacterial infection remains unclear. This study assessed the diagnostic value of NE-WY and NE-SFL for bacteremia in patients with acute bacterial infections, and those associations with other sepsis biomarkers.

Methods

Patients with acute bacterial infections were enrolled in this prospective observational cohort study. For all patients, a blood sample, with at least two sets of blood cultures, were collected at the onset of infection. Microbiological evaluation included examination of the blood bacterial load using PCR. CPD was assessed using Automated Hematology analyzer Sysmex series XN-2000. Serum levels of procalcitonin (PCT), interleukin-6 (IL-6), presepsin, and CRP were also assessed.

Results

Of 93 patients with acute bacterial infection, 24 developed culture-proven bacteremia and 69 did not. NE-SFL and NE-WY were significantly higher in patients with bacteremia than in those without bacteremia (p < 0.005, respectively), and were significantly correlated with the bacterial load determined by PCR (r = 0.384 and r = 0.374, p < 0.005, respectively). To assess the diagnostic value for bacteremia, receiver operating characteristic curve analysis was used. NE-SFL and NE-WY showed an area under the curve of 0.685 and 0.708, respectively, while those of PCT, IL-6, presepsin, and CRP were 0.744, 0.778, 0.685, and 0.528, respectively. Correlation analysis showed that the levels of NE-WY and NE-SFL were strongly correlated with PCT and IL-6 levels.

Conclusion

This study demonstrated that NE-WY and NE-SFL could predict bacteremia in a manner that may be different from that of other indicators. These findings suggest there are potential benefits of NE-WY/NE-SFL in predicting severe bacterial infections.

Antimicrobial resistance and machine learning: past, present, and future

Machine learning has become ubiquitous across all industries, including the relatively new application of predicting antimicrobial resistance. As the first bibliometric review in this field, we expect it to inspire further research in this area. The review employs standard bibliometric indicators such as article count, citation count, and the Hirsch index (H-index) to evaluate the relevance and impact of the leading countries, organizations, journals, and authors in this field. VOSviewer and Biblioshiny programs are utilized to analyze citation and co-citation networks, collaboration networks, keyword co-occurrence, and trend analysis. The United States has the highest contribution with 254 articles, accounting for over 37.57% of the total corpus, followed by China (103) and the United Kingdom (78). Among 58 publishers, the top four publishers account for 45% of the publications, with Elsevier leading with 15% of the publications, followed by Springer Nature (12%), MDPI, and Frontiers Media SA with 9% each. Frontiers in Microbiology is the most frequent publication source (33 articles), followed by Scientific Reports (29 articles), PLoS One (17 articles), and Antibiotics (16 articles). The study reveals a substantial increase in research and publications on the use of machine learning to predict antibiotic resistance. Recent research has focused on developing advanced machine learning algorithms that can accurately forecast antibiotic resistance, and a range of algorithms are now being used to address this issue.

Deep Learning-Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification

Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the bloodstream and may induce systemic immune responses. Early and appropriate antibiotic usage is crucial to effectively treating BSI. However, conventional culture-based microbiological diagnostics are time-consuming and cannot provide timely bacterial identification for subsequent antimicrobial susceptibility test (AST) and clinical decision-making. To address this issue, modern microbiological diagnostics have been developed, such as surface-enhanced Raman scattering (SERS), which is a sensitive, label-free, and quick bacterial detection method measuring specific bacterial metabolites. In this study, we aim to integrate a new deep learning (DL) method, Vision Transformer (ViT), with bacterial SERS spectral analysis to build the SERS-DL model for rapid identification of Gram type, species, and resistant strains. To demonstrate the feasibility of our approach, we used 11,774 SERS spectra obtained directly from eight common bacterial species in clinical blood samples without artificial introduction as the training dataset for the SERS-DL model. Our results showed that ViT achieved excellent identification accuracy of 99.30% for Gram type and 97.56% for species. Moreover, we employed transfer learning by using the Gram-positive species identifier as a pre-trained model to perform the antibiotic-resistant strain task. The identification accuracy of methicillin-resistant and -susceptible Staphylococcus aureus (MRSA and MSSA) can reach 98.5% with only 200-dataset requirement. In summary, our SERS-DL model has great potential to provide a quick clinical reference to determine the bacterial Gram type, species, and even resistant strains, which can guide early antibiotic usage in BSI.

Pathology stewardship in emergency departments: a single-site, retrospective, cohort study of the value of C-reactive protein in patients with suspected sepsis

Increasing awareness of the importance of pathology stewardship in reducing low value care has led to scrutiny of appropriate laboratory test ordering. The objective of this study is to investigate the value of a commonly ordered laboratory test, the C-reactive protein (CRP), in decisions regarding diagnosis, management and disposition of emergency department (ED) patients with suspected sepsis. Retrospective chart reviews were performed on 1716 adult patients with suspected sepsis presenting to the Townsville University Hospital ED between 1 January 2021 and 30 June 2021. Suspected sepsis was defined as the emergency clinicians' decision to perform a blood culture. A CRP value of 10 mg/L or higher was defined as an elevated CRP. The primary outcome of interest was commencement of antibiotics in ED. Secondary outcomes include hospital admission (ward and ICU), hospital length of stay, mortality, documentation of indication for CRP testing, test parameters of CRP in detecting culture-positive bacteraemia and rates of bacteraemia with presumptive ED diagnosis. This study found no significant association between CRP values and antibiotic commencement (p=0.222), ward admission (p=0.071), ICU admission (p=0.248), hospital length of stay (p=0.164) or mortality (p=1.000). CRP had an area under the curve of 0.58 (95% CI 0.51-0.66) for detecting culture-positive bacteraemia. Sensitivity and specificity of CRP were 62.5% and 47.7%, respectively, at a threshold of 46 mg/dL. CRP testing is of little value in ED patients with suspected sepsis as it does not influence decision making about diagnosis, management, or disposition. Avoiding CRP testing in this patient cohort can contribute to pathology stewardship and optimal use of finite healthcare resources.

Modular Engineering of a DNA Tetrahedron-Based Nanomachine for Ultrasensitive Detection of Intracellular Bioactive Small Molecules

Bioactive small molecules serve as invaluable biomarkers for recognizing modulated organismal metabolism in correlation with numerous diseases. Therefore, sensitive and specific molecular biosensing and imaging in vitro and in vivo are particularly critical for the diagnosis and treatment of a large group of diseases. Herein, a modular DNA tetrahedron-based nanomachine was engineered for the ultrasensitive detection of intracellular small molecules. The nanomachine was composed of three self-assembled modules: an aptamer for target recognition, an entropy-driven unit for signal reporting, and a tetrahedral oligonucleotide for the transportation of the cargo (e.g., the nanomachine and fluorescent markers). Adenosine triphosphate (ATP) was used as the molecular model. Once the target ATP bonded with the aptamer module, an initiator was released from the aptamer module to activate the entropy-driven module, ultimately activating the ATP-responsive signal output and subsequent signal amplification. The performance of the nanomachine was validated by delivering it to living cells with the aid of the tetrahedral module to demonstrate the possibility of executing intracellular ATP imaging. This innovative nanomachine displays a linear response to ATP in the 1 pM to 10 nM concentration range and demonstrates high sensitivity with a low detection limit of 0.40 pM. Remarkably, our nanomachine successfully executes endogenous ATP imaging and is able to distinguish tumor cells from normal ones based on the ATP level. Overall, the proposed strategy opens up a promising avenue for bioactive small molecule-based detection/diagnostic assays.

Application of a sepsis flow chip (SFC) assay for the molecular diagnosis of paediatric sepsis

A delay in detecting sepsis pathogens is a problematic issue for determining definitive antibiotic therapy for the causative pathogens. The gold standard method for sepsis is blood culture but this requires 3 days to detect the definitive pathogen. Molecular methods offer rapid identification of pathogens. We evaluated the use of sepsis flow chip (SFC) assay for identifying pathogens from children with sepsis. Blood samples from children with sepsis were collected and incubated in a culture device. Positive samples were subjected to amplification-hybridization using SFC assay and culture. A total of 94 samples from 47 patients were recovered, from which 25 isolates were recovered, including Klebsiella pneumoniae (11) and Staphylococcus epidermidis (6). From 25 positive blood culture bottles subjected to SFC assay, 24 genus/species and 18 resistance genes were detected. The sensitivity, specificity and conformity was 80, 94.2 and 94.68 % respectively. SFC assay offers promise to identify pathogens from positive blood culture in paediatric patients with sepsis and may support the antimicrobial stewardship programme in hospitals.

The Role of Coagulase-Negative Staphylococci Biofilms on Late-Onset Sepsis: Current Challenges and Emerging Diagnostics and Therapies

Infections are one of the most significant complications of neonates, especially those born preterm, with sepsis as one of the principal causes of mortality. Coagulase-negative staphylococci (CoNS), a group of staphylococcal species that naturally inhabit healthy human skin and mucosa, are the most common cause of late-onset sepsis, especially in preterms. One of the risk factors for the development of CoNS infections is the presence of implanted biomedical devices, which are frequently used for medications and/or nutrient delivery, as they serve as a scaffold for biofilm formation. The major concerns related to CoNS infections have to do with the increasing resistance to multiple antibiotics observed among this bacterial group and biofilm cells’ increased tolerance to antibiotics. As such, the treatment of CoNS biofilm-associated infections with antibiotics is increasingly challenging and considering that antibiotics remain the primary form of treatment, this issue will likely persist in upcoming years. For that reason, the development of innovative and efficient therapeutic measures is of utmost importance. This narrative review assesses the current challenges and emerging diagnostic tools and therapies for the treatment of CoNS biofilm-associated infections, with a special focus on late-onset sepsis.

Group B Streptococcus Early-Onset Disease: New Preventive and Diagnostic Tools to Decrease the Burden of Antibiotic Use

The difficulty in recognizing early-onset neonatal sepsis (EONS) in a timely manner due to non-specific symptoms and the limitations of diagnostic tests, combined with the risk of serious consequences if EONS is not treated in a timely manner, has resulted in a low threshold for starting empirical antibiotic treatment. New guideline strategies, such as the neonatal sepsis calculator, have been proven to reduce the antibiotic burden related to EONS, but lack sensitivity for detecting EONS. In this review, the potential of novel, targeted preventive and diagnostic methods for EONS is discussed from three different perspectives: maternal, umbilical cord and newborn perspectives. Promising strategies from the maternal perspective include Group B Streptococcus (GBS) prevention, exploring the virulence factors of GBS, maternal immunization and antepartum biomarkers. The diagnostic methods obtained from the umbilical cord are preliminary but promising. Finally, promising fields from the newborn perspective include biomarkers, new microbiological techniques and clinical prediction and monitoring strategies. Consensus on the definition of EONS and the standardization of research on novel diagnostic biomarkers are crucial for future implementation and to reduce current antibiotic overexposure in newborns.

Test Performance and Potential Clinical Utility of the GenMark Dx ePlex Blood Culture Identification Gram-Negative Panel

The test performance and potential clinical utility of the ePlex blood culture identification Gram-negative (BCID-GN) panel was evaluated relative to matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry on bacterial isolates and conventional antimicrobial susceptibility testing. The majority (106/108, 98.1%) of GN bacteria identified by MALDI were on the BCID-GN panel, and valid tests (107/108, 99.1%) yielded results on average 26.7 h earlier. For all valid tests with on-panel organisms, the positive percent agreement was 102/105 (97.2%) with 3 false negatives and the negative percent agreement was 105/105. Chart review (n = 98) showed that in conjunction with Gram stain results, negative pan-Gram-positive (GP) markers provided the opportunity to discontinue GP antibiotic coverage in 63/98 (64.3%) cases on average 26.2 h earlier. Only 8/12 (66.7%) Enterobacterales isolates with resistance to third-generation cephalosporins harbored the CTX-M gene. In contrast, 8/8 CTX-M⁺ samples yielded a resistant isolate. Detection of 1 Stenotrophomonas maltophilia (18 h), 1 OXA23/48⁺ Acinetobacter baumannii (52.4 h), and 3 CTX-M⁺ Enterobacterales isolates on ineffective treatment (47.1 h) and 1 on suboptimal therapy (72.6 h) would have additionally enabled early antimicrobial optimization in 6/98 (6.1%) patients. IMPORTANCE The GenMark Dx ePlex rapid blood culture diagnostic system enables earlier time to identification of antimicrobial-resistant Gram-negative bacteria causing bloodstream infections. Its ability to rule out Gram-positive bacteria enabled early discontinuation of unnecessary antibiotics in 63/98 (64.3%) cases on average 26.2 h earlier. Detection of bacteria harboring the CTX-M gene as well as early identification of highly resistant bacteria such as Stenotrophomonas maltophilia and Acinetobacter baumannii enabled optimization of ineffective therapy in 6/98 (6.1%) patients. Its implementation in clinical microbiology laboratories optimizes therapy and improves patient care.

Clinical Diagnostic Performance of Droplet Digital PCR for Suspected Bloodstream Infections

Accurate and timely etiological diagnosis is crucial for bloodstream infections (BSIs) due to their high disability and mortality. We conducted a single-center prospective cohort study to compare the digital droplet PCR (ddPCR) assay with traditional blood culture. A total of 169 blood samples from 122 patients with suspected BSIs were collected, mostly from the department of infectious diseases, the emergency department, and the intensive care units, and the clinical data were also recorded. Nucleic acid was extracted from the blood samples, and a 5-fluorescent-channel droplet digital PCR assay was performed and then fed back with the pathogen and its copies. In BSI patients, ddPCR reported an overall 85.71% (12/14) (95% confidence interval [CI], 56.15 to 97.48%) sensitivity, 100% (7/7) (95% CI, 56.09 to 100.00%) and 71.43% (5/7) (95% CI, 30.26 to 94.89%) sensitivity in patients without empirical treatment and in empirically treated patients, respectively. Compared to traditional blood culture, the overall detection rate of ddPCR was significantly higher, 11.27% (16/142) (95% CI, 6.78 to 17.93%) versus 30.28% (43/142) (95% CI, 23.01 to 38.64%), and the extra detection rate of ddPCR was 19.01% (27/142) (95% CI, 13.11 to 26.63%). Of the ddPCR-positive culture-negative cases, 74.19% (23/31) (95% CI, 55.07 to 87.46%) were consistent with the final clinical diagnosis, including 10 bacteria and fungi. The detection rate of ddPCR was significantly higher in patients with white blood cell (WBC) counts of >10 · 109/L, C-reactive protein (CRP) of >70 mg/L, or procalcitonin (PCT) of >0.9 ng/L. Pathogen loads detected by ddPCR are correlated with WBC, CRP, and especially, PCT levels, precisely and rapidly reflecting clinical disease progression. ddPCR has an important guiding value for the clinical use of antibiotics to achieve the best pathogen coverage and the antibacterial effect. Collectively, ddPCR showed a great diagnostic performance in BSIs and had an overall higher detection rate than blood culture. In addition, ddPCR could be used to dynamically monitor the disease progression and provide medication guidance on antibiotic use. IMPORTANCE ddPCR is a promising method to address the current challenges of BSI diagnosis and precise treatment, as it is highly efficient in DNA detection. It shortens the identification of BSI-related pathogens from several days of traditional bacterial culture to 4 to 5 h. It is extremely sensitive and more tolerant to PCR inhibitors, which may facilitate the amplification and enable the detection of a meager amount of DNA fragments in detecting BSI-related pathogens and drug-resistant genes. It can identify almost 20 pathogens in one reaction, which reduces the usage of clinical blood samples to no more than 2 mL. Additionally, dynamic monitoring, assessment of pathogens, and antibiotic resistance genes in patients could be used to guide timely and precise adjustment of antimicrobial prescription. The short turnaround time of ddPCR may have the potential to guide antimicrobial treatment in the very early stage of sepsis and reduce the mortality and disability rate of sepsis.

Use of full blood count parameters and haematology cell ratios in screening for sepsis in South Africa

Background

Sepsis is characterised by multi-organ failure due to an uncontrolled immune response to infection. Sepsis prevalence is increased in developing countries and requires prompt diagnosis and treatment. Reports, although controversial, suggest that full blood count parameters and cell ratios could assist in the early screening for sepsis.

Objective

The study evaluated the use of haematological cell ratios in screening for sepsis in a South African population.

Methods

The study retrospectively analysed the complete blood counts, blood cultures (BC) and biochemical test results of 125 adult patients who presented between January 2021 and July 2021 at a hospital in Cape Town. An ISO15189-accredited laboratory performed all of the tests. We compared and correlated the automated differential counts, neutrophil, monocyte and platelet-to-lymphocyte ratios with procalcitonin levels. A p-value of < 0.05 was considered significant.

Results

Sixty-two sepsis patients (procalcitonin > 2 ng/L and positive BC) were identified and compared to 63 non-sepsis controls. All cell ratios were significantly elevated in sepsis patients (p < 0.001). However, the two groups had no significant difference in absolute monocyte counts (p = 0.377). In addition, no correlation was detected between any cell ratios and procalcitonin.

Conclusion

In combination with complete blood count parameters, haematology cell ratios can be used for early sepsis detection. The full blood count is widely available, inexpensive, and routinely requested by emergency care clinicians. Although procalcitonin and BC remain the gold standard, the calculation of cell ratios could provide a simple screening tool for the early detection of sepsis.

What this study adds

This study adds evidence to the proposal that calculating haematological cell ratios assists in the early screening of sepsis in a South African setting.

Metagenomics by next-generation sequencing (mNGS) in the etiological characterization of neonatal and pediatric sepsis: A systematic review

Introduction

Pediatric and neonatal sepsis is one of the main causes of mortality and morbidity in these age groups. Accurate and early etiological identification is essential for guiding antibiotic treatment, improving survival, and reducing complications and sequelae. Currently, the identification is based on culture-dependent methods, which has many limitations for its use in clinical practice, and obtaining its results is delayed. Next-generation sequencing enables rapid, accurate, and unbiased identification of multiple microorganisms in biological samples at the same time. The objective of this study was to characterize the etiology of neonatal and pediatric sepsis by metagenomic techniques.

Methods

A systematic review of the literature was carried out using the PRISMA-2020 guide. Observational, descriptive, and case report studies on pediatric patients were included, with a diagnostic evaluation by clinical criteria of sepsis based on the systemic inflammatory response, in sterile and non-sterile biofluid samples. The risk of bias assessment of the observational studies was carried out with the STROBE-metagenomics instrument and the CARE checklist for case reports.

Results and Discussion

Five studies with a total of 462 patients were included. Due to the data obtained from the studies, it was not possible to perform a quantitative synthesis (meta-analysis). Based on the data from the included studies, the result identified that mNGS improves the etiological identification in neonatal and pediatric sepsis, especially in the context of negative cultures and in the identification of unusual microorganisms (bacteria that are difficult to grow in culture, viruses, fungi, and parasites). The number of investigations is currently limited, and the studies are at high risk of bias. Further research using this technology would have the potential to improve the rational use of antibiotics.

FCGR2C: An emerging immune gene for predicting sepsis outcome

Background

Sepsis is a life-threatening disease associated with immunosuppression. Immunosuppression could ultimately increase sepsis mortality. This study aimed to identify the prognostic biomarkers related to immunity in sepsis.

Methods

Public datasets of sepsis downloaded from the Gene Expression Omnibus (GEO) database were divided into the discovery cohort and the first validation cohort. We used R software to screen differentially expressed genes (DEGs) and analyzed DEGs' functional enrichment in the discovery dataset. Immune-related genes (IRGs) were filtered from the GeneCards website. A Lasso regression model was used to screen candidate prognostic genes from the intersection of DEGs and IRGs. Then, the candidate prognostic genes with significant differences were identified as prognostic genes in the first validation cohort. We further validated the expression of the prognostic genes in the second validation cohort of 81 septic patients recruited from our hospital. In addition, we used four immune infiltration methods (MCP-counter, ssGSEA, ImmuCellAI, and CIBERSORT) to analyze immune cell composition in sepsis. We also explored the correlation between the prognostic biomarker and immune cells.

Results

First, 140 genes were identified as prognostic-related immune genes from the intersection of DEGs and IRGs. We screened 18 candidate prognostic genes in the discovery cohort with the lasso regression model. Second, in the first validation cohort, we identified 4 genes (CFHR2, FCGR2C, GFI1, and TICAM1) as prognostic immune genes. Subsequently, we found that FCGR2C was the only gene differentially expressed between survivors and non-survivors in 81 septic patients. In the discovery and first validation cohorts, the AUC values of FCGR2C were 0.73 and 0.67, respectively. FCGR2C (AUC=0.84) had more value than SOFA (AUC=0.80) and APACHE II (AUC=0.69) in evaluating the prognosis of septic patients in our recruitment cohort. Moreover, FCGR2C may be closely related to many immune cells and functions, such as B cells, NK cells, neutrophils, cytolytic activity, and inflammatory promotion. Finally, enrichment analysis showed that FCGR2C was enriched in the phagosome signaling pathway.

Conclusion

FCGR2C could be an immune biomarker associated with prognosis, which may be a new direction of immunotherapy to reduce sepsis mortality.

Time to positivity of blood cultures in neonatal late-onset bacteraemia

OBJECTIVE

To determine the time to positivity (TTP) of blood cultures among infants with late-onset bacteraemia and predictors of TTP >36 hours.

DESIGN

Retrospective cohort study.

SETTING

16 birth centres in two healthcare systems.

PATIENTS

Infants with positive blood cultures obtained >72 hours after birth.

OUTCOME

The main outcome was TTP, defined as the time interval from specimen collection to when a neonatal provider was notified of culture growth. TTP analysis was restricted to the first positive culture per infant. Patient-specific and infection-specific factors were analysed for association with TTP >36 hours.

RESULTS

Of 10 235 blood cultures obtained from 3808 infants, 1082 (10.6%) were positive. Restricting to bacterial pathogens and the first positive culture, the median TTP (25th-75th percentile) for 428 cultures was 23.5 hours (18.4-29.9); 364 (85.0%) resulted in 36 hours. Excluding coagulase-negative staphylococci (CoNS), 275 of 294 (93.5%) cultures were flagged positive by 36 hours. In a multivariable model, CoNS isolation and antibiotic pretreatment were significantly associated with increased odds of TTP >36 hours. Projecting a 36-hour empiric duration at one site and assuming that all negative evaluations were associated with an empiric course of antibiotics, we estimated that 1164 doses of antibiotics would be avoided in 629 infants over 10 years, while delaying a subsequent antibiotic dose in 13 infants with bacteraemia.

CONCLUSIONS

Empiric antibiotic administration in late-onset infection evaluations (not targeting CoNS) can be stopped at 36 hours. Longer durations (48 hours) should be considered when there is pretreatment or antibiotic therapy is directed at CoNS.