Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping

Respiratory tract infections: an update on the complexity of bacterial diversity, therapeutic interventions and breakthroughs

Respiratory tract infections (RTIs) have a significant impact on global health, especially among children and the elderly. The key bacterial pathogens Streptococcus pneumoniae, Haemophilus influenzae, Klebsiella pneumoniae, Staphylococcus aureus and non-fermenting Gram Negative bacteria such as Acinetobacter baumannii and Pseudomonas aeruginosa are most commonly associated with RTIs. These bacterial pathogens have evolved a diverse array of resistance mechanisms through horizontal gene transfer, often mediated by mobile genetic elements and environmental acquisition. Treatment failures are primarily due to antimicrobial resistance and inadequate bacterial engagement, which necessitates the development of alternative treatment strategies. To overcome this, our review mainly focuses on different virulence mechanisms and their resulting pathogenicity, highlighting different therapeutic interventions to combat resistance. To prevent the antimicrobial resistance crisis, we also focused on leveraging the application of artificial intelligence and machine learning to manage RTIs. Integrative approaches combining mechanistic insights are crucial for addressing the global challenge of antimicrobial resistance in respiratory infections.

Proteomic assay for rapid characterisation of Staphylococcus aureus antimicrobial resistance mechanisms directly from blood cultures

PURPOSE

Staphylococcus aureus is one of the most common pathogens causing bloodstream infection. A rapid characterisation of resistance to methicillin and, occasionally, to aminoglycosides for particular indications, is therefore crucial to quickly adapt the treatment and improve the clinical outcomes of septic patients. Among analytical technologies, targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as a promising tool to detect resistance mechanisms in clinical samples.

METHODS

A rapid proteomic method was developed to detect and quantify the most clinically relevant antimicrobial resistance effectors in S. aureus in the context of sepsis: PBP2a, PBP2c, APH(3')-III, ANT(4')-I, and AAC(6')-APH(2''), directly from positive blood cultures and in less than 70 min including a 30-min cefoxitin-induction step. The method was tested on spiked blood culture bottles inoculated with 124 S.aureus, accounting for the known genomic diversity of SCCmec types and the genetic background of the strains.

RESULTS

This method provided 99% agreement for PBP2a (n = 98/99 strains) detection. Agreement was 100% for PBP2c (n = 5/5), APH(3')-III (n = 16/16), and ANT(4')-I (n = 20/20), and 94% for AAC(6')-APH(2'') (n = 16/17). Across the entire strain collection, 100% negative agreement was reported for each of the 5 resistance proteins. Additionally, relative quantification of ANT(4')-I expression allowed to discriminate kanamycin-susceptible and -resistant strains, in all strains harbouring the ant(4')-Ia gene.

CONCLUSION

The LC-MS/MS method presented herein demonstrates its ability to provide a reliable determination of S. aureus resistance mechanisms, directly from positive blood cultures and in a short turnaround time, as required in clinical laboratories.

Discovery of Species-Specific Proteotypic Peptides To Establish a Spectral Library Platform for Identification of Nontuberculosis Mycobacteria from Mass Spectrometry-Based Proteomics

Nontuberculous mycobacteria are opportunistic bacteria pulmonary and extra-pulmonary infections in humans that closely resemble Mycobacterium tuberculosis. Although genome sequencing strategies helped determine NTMs, a common assay for the detection of coinfection by multiple NTMs with M. tuberculosis in the primary attempt of diagnosis is still elusive. Such a lack of efficiency leads to delayed therapy, an inappropriate choice of drugs, drug resistance, disease complications, morbidity, and mortality. Although a high-resolution LC-MS/MS-based multiprotein panel assay can be developed due to its specificity and sensitivity, it needs a library of species-specific peptides as a platform. Toward this, we performed an analysis of proteomes of 9 NTM species with more than 20 million peptide spectrum matches gathered from 26 proteome data sets. Our metaproteomic analyses determined 48,172 species-specific proteotypic peptides across 9 NTMs. Notably, M. smegmatis (26,008), M. abscessus (12,442), M. vaccae (6487), M. fortuitum (1623), M. avium subsp. paratuberculosis (844), M. avium subsp. hominissuis (580), and M. marinum (112) displayed >100 species-specific proteotypic peptides. Finally, these peptides and corresponding spectra have been compiled into a spectral library, FASTA, and JSON formats for future reference and validation in clinical cohorts by the biomedical community for further translation.

Characterization of natural peptides in Pheretima by integrating proteogenomics and label-free peptidomics

Pheretima, also called "earthworms", is a well-known animal-derived traditional Chinese medicine that is extensively used in over 50 Chinese patent medicines (CPMs) in Chinese Pharmacopoeia (2020 edition). However, its zoological origin is unclear, both in the herbal market and CPMs. In this study, a strategy for integrating in-house annotated protein databases constructed from close evolutionary relationship-sourced RNA sequencing data from public archival resources and various sequencing algorithms (restricted search, open search, and de novo) was developed to characterize the phenotype of natural peptides of three major commercial species of Pheretima, including Pheretima aspergillum (PA), Pheretima vulgaris (PV), and Metaphire magna (MM). We identified 10,477 natural peptides in the PA, 7,451 in PV, and 5,896 in MM samples. Five specific signature peptides were screened and then validated using synthetic peptides; these demonstrated robust specificity for the authentication of PA, PV, and MM. Finally, all marker peptides were successfully applied to identify the zoological origins of Brain Heart capsules and Xiaohuoluo pills, revealing the inconsistent Pheretima species used in these CPMs. In conclusion, our integrated strategy could be used for the in-depth characterization of natural peptides of other animal-derived traditional Chinese medicines, especially non-model species with poorly annotated protein databases.

Flow Cytometry: The Next Revolution

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

Unique Peptides of Cathelicidin-1 in the Early Detection of Mastitis-In Silico Analysis

Based on the results of previously performed clinical studies, cathelicidin-1 has been proposed as a potential biomarker for the early diagnosis of mastitis in ewes. It has been hypothesized that the detection of unique peptides (defined as a peptide, irrespective of its length, that exists in only one protein of a proteome of interest) and core unique peptides (CUPs) (representing the shortest peptide that is unique) of cathelicidin-1 may potentially improve its identification and consequently the diagnosis of sheep mastitis. Peptides of sizes larger than those of the size of CUPs, which include consecutive or over-lapping CUPs, have been defined as 'composite core unique peptides' (CCUPs). The primary objective of the present study was the investigation of the sequence of cathelicidin-1 detected in ewes' milk in order to identify its unique peptides and core unique peptides, which would reveal potential targets for accurate detection of the protein. An additional objective was the detection of unique sequences among the tryptic digest peptides of cathelicidin-1, which would improve accuracy of identification of the protein when performing targeted MS-based proteomics. The potential uniqueness of each peptide of cathelicidin-1 was investigated using a bioinformatics tool built on a big data algorithm. A set of CUPs was created and CCUPs were also searched. Further, the unique sequences in the tryptic digest peptides of cathelicidin-1 were also detected. Finally, the 3D structure of the protein was analyzed from predicted models of proteins. In total, 59 CUPs and four CCUPs were detected in cathelicidin-1 of sheep origin. Among tryptic digest peptides, there were six peptides that were unique in that protein. After 3D structure analysis of the protein, 35 CUPs were found on the core of cathelicidin-1 of sheep origin and among them, 29 were located on amino acids in regions of the protein with 'very high' or 'confident' estimates of confidence of the structure. Ultimately, the following six CUPs: QLNEQ, NEQS, EQSSE, QSSEP, EDPD, DPDS, are proposed as potential antigenic targets for cathelicidin-1 of sheep. Moreover, another six unique peptides were detected in tryptic digests and offer novel mass tags to facilitate the detection of cathelicidin-1 during MS-based diagnostics.

Direct Identification of Urinary Tract Pathogens by MALDI-TOF/TOF Analysis and De Novo Peptide Sequencing

For mass spectrometry-based diagnostics of microorganisms, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently routinely used to identify urinary tract pathogens. However, it requires a lengthy culture step for accurate pathogen identification, and is limited by a relatively small number of available species in peptide spectral libraries (≤3329). Here, we propose a method for pathogen identification that overcomes the above limitations, and utilizes the MALDI-TOF/TOF MS instrument. Tandem mass spectra of the analyzed peptides were obtained by chemically activated fragmentation, which allowed mass spectrometry analysis in negative and positive ion modes. Peptide sequences were elucidated de novo, and aligned with the non-redundant National Center for Biotechnology Information Reference Sequence Database (NCBInr). For data analysis, we developed a custom program package that predicted peptide sequences from the negative and positive MS/MS spectra. The main advantage of this method over a conventional MALDI-TOF MS peptide analysis is identification in less than 24 h without a cultivation step. Compared to the limited identification with peptide spectra libraries, the NCBI database derived from genome sequencing currently contains 20,917 bacterial species, and is constantly expanding. This paper presents an accurate method that is used to identify pathogens grown on agar plates, and those isolated directly from urine samples, with high accuracy.

A Combination of MALDI-TOF MS Proteomics and Species-Unique Biomarkers' Discovery for Rapid Screening of Brucellosis

Brucellosis is considered to be a zoonotic infection with a predominant incidence in most parts of Iran that may even simply involve diagnostic laboratory personnel. In the present study, we apply matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for rapid and reliable discrimination of Brucella abortus and Brucella melitensis, based on proteomic mass patterns from chemically treated whole-cell analyses. Biomarkers of the low molecular weight proteome in the MALDI-TOF MS spectra were assigned to conserved ribosomal and structural protein families that were found in genome assemblies of B. abortus and B. melitensis in the NCBI database. Significant protein mass signals successfully mapped to ribosomal proteins and structural proteins, such as integration host factor subunit alpha, cold-shock proteins, HU family DNA-binding protein, ATP synthase subunit C, and GNAT family N-acetyltransferase, with specific biomarker peaks that have been identified for each virulent and vaccine strain. Web-accessible bioinformatics algorithms, with a robust data analysis workflow, followed by ribosomal and structural protein mapping, significantly enhanced the reliable assignment of key proteins and accurate identification of Brucella species. Furthermore, clinical samples were analyzed to confirm the most dominant protein biomarker candidates and their relevance for the identifications of B. melitensis and B. abortus. With proper optimization, we envision that the presented MALDI-TOF MS proteomics analyses, coupled with special usage of bioinformatics, could be used as a cost-efficient strategy for the diagnostics of brucellosis and introduce a reliable identification protocol for species of dangerous bacteria.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach

Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation shows that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in identifying antibiotic resistance proteins. In addition to having high sensitivity and precision, MiCId's workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 min per MS/MS sample using computing resources that are available in most desktop and laptop computers. We have also demonstrated other use of MiCId's workflow. Using MS/MS data sets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions agree with the published study. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases

Rapid and precise diagnostic methods are required to control emerging infectious diseases effectively. Human body fluids are attractive clinical samples for discovering diagnostic targets because they reflect the clinical statuses of patients and most of them can be obtained with minimally invasive sampling processes. Body fluids are good reservoirs for infectious parasites, bacteria, and viruses. Therefore, recent clinical proteomics methods have focused on body fluids when aiming to discover human- or pathogen-originated diagnostic markers. Cutting-edge liquid chromatography-mass spectrometry (LC-MS)-based proteomics has been applied in this regard; it is considered one of the most sensitive and specific proteomics approaches. Here, the clinical characteristics of each body fluid, recent tandem mass spectroscopy (MS/MS) data-acquisition methods, and applications of body fluids for proteomics regarding infectious diseases (including the coronavirus disease of 2019 [COVID-19]), are summarized and discussed.

Mass Spectrometry Proteotyping-Based Detection and Identification of Staphylococcus aureus, Escherichia coli, and Candida albicans in Blood

Bloodstream infections (BSIs), the presence of microorganisms in blood, are potentially serious conditions that can quickly develop into sepsis and life-threatening situations. When assessing proper treatment, rapid diagnosis is the key; besides clinical judgement performed by attending physicians, supporting microbiological tests typically are performed, often requiring microbial isolation and culturing steps, which increases the time required for confirming positive cases of BSI. The additional waiting time forces physicians to prescribe broad-spectrum antibiotics and empirically based treatments, before determining the precise cause of the disease. Thus, alternative and more rapid cultivation-independent methods are needed to improve clinical diagnostics, supporting prompt and accurate treatment and reducing the development of antibiotic resistance. In this study, a culture-independent workflow for pathogen detection and identification in blood samples was developed, using peptide biomarkers and applying bottom-up proteomics analyses, i.e., so-called "proteotyping". To demonstrate the feasibility of detection of blood infectious pathogens, using proteotyping, Escherichia coli and Staphylococcus aureus were included in the study, as the most prominent bacterial causes of bacteremia and sepsis, as well as Candida albicans, one of the most prominent causes of fungemia. Model systems including spiked negative blood samples, as well as positive blood cultures, without further culturing steps, were investigated. Furthermore, an experiment designed to determine the incubation time needed for correct identification of the infectious pathogens in blood cultures was performed. The results for the spiked negative blood samples showed that proteotyping was 100- to 1,000-fold more sensitive, in comparison with the MALDI-TOF MS-based approach. Furthermore, in the analyses of ten positive blood cultures each of E. coli and S. aureus, both the MALDI-TOF MS-based and proteotyping approaches were successful in the identification of E. coli, although only proteotyping could identify S. aureus correctly in all samples. Compared with the MALDI-TOF MS-based approaches, shotgun proteotyping demonstrated higher sensitivity and accuracy, and required significantly shorter incubation time before detection and identification of the correct pathogen could be accomplished.

Metagenomics reveals functional profiling of microbial communities in OCP contaminated sites with rapeseed oil and tartaric acid biostimulation

Organochlorine pesticides (OCPs) contaminated sites pose great threats to both human health and environmental safety. Targeted bioremediation in these regions largely depends on microbial diversity and activity. This study applied metagenomics to characterize the microbial communities and functional groups composition features during independent or simultaneous rapeseed oil and tartaric acid applications, as well as the degradation kinetics of OCPs. Results showed that: the degradation rates of α-chlordane, β-chlordane and mirex were better when (0.50% w/w) rapeseed oil and (0.05 mol L^-1) tartaric acid were applied simultaneously than singular use, yielding removal rates of 56.4%, 53.9%, and 49.4%, respectively. Meanwhile, bio-stimulation facilitated microbial enzyme (catalase/superoxide dismutase/peroxidase) activity in soils significantly, promoting the growth of dominant bacterial communities. Classification at phylum level showed that the relative abundance of Proteobacteria was significantly increased (p < 0.05). Network analysis showed that bio-stimulation substantially increased the dominant bacterial community's proportion, especially Proteobacteria. The functional gene results illustrated that bio-stimulation facilitated total relative abundance of degradation genes, phosphorus, carbon, nitrogen, sulfur metabolic genes, and iron transporting genes (p < 0.05). In metabolic pathways, functional genes related to methanogenesis and ammonia generation were markedly upregulated, indicating that bio-stimulation promoted the transformation of metabolic genes, such as carbon and nitrogen. This research is conducive to exploring the microbiological response mechanisms of bio-stimulation in indigenous flora, which may provide technical support for assessing the microbial ecological remediation outcomes of bio-stimulation in OCP contaminated sites.

Learning from -omics strategies applied to uncover Haemophilus influenzae host-pathogen interactions: Current status and perspectives

Haemophilus influenzae has contributed to key bacterial genome sequencing hallmarks, as being not only the first bacterium to be genome-sequenced, but also starring the first genome-wide analysis of chromosomes directly transformed with DNA from a divergent genotype, and pioneering Tn-seq methodologies. Over the years, the phenomenal and constantly evolving development of -omic technologies applied to a whole range of biological questions of clinical relevance in the H. influenzae-host interplay, has greatly moved forward our understanding of this human-adapted pathogen, responsible for multiple acute and chronic infections of the respiratory tract. In this way, essential genes, virulence factors, pathoadaptive traits, and multi-layer gene expression regulatory networks with both genomic and epigenomic complexity levels are being elucidated. Likewise, the unstoppable increasing whole genome sequencing information underpinning H. influenzae great genomic plasticity, mainly when referring to non-capsulated strains, poses major challenges to understand the genomic basis of clinically relevant phenotypes and even more, to clearly highlight potential targets of clinical interest for diagnostic, therapeutic or vaccine development. We review here how genomic, transcriptomic, proteomic and metabolomic-based approaches are great contributors to our current understanding of the interactions between H. influenzae and the human airways, and point possible strategies to maximize their usefulness in the context of biomedical research and clinical needs on this human-adapted bacterial pathogen.

Early and specific targeted mass spectrometry-based identification of bacteria in endotracheal aspirates of patients suspected with ventilator-associated pneumonia

Rapid and reliable pathogen identification is compulsory to confirm ventilator-associated pneumonia (VAP) in order to initiate appropriate antibiotic treatment. In the present proof of concept, the effectiveness of rapid microorganism identification with a targeted bottom-up proteomics approach was investigated in endotracheal aspirate (ETA) samples of VAP patients. To do so, a prototype selected-reaction monitoring (SRM)-based assay was developed on a triple quadrupole mass spectrometer tracking proteotypic peptide surrogates of bacterial proteomes. Through the concurrent monitoring of 97 species-specific peptides, this preliminary assay was dimensioned to characterize the occurrence of six most frequent bacterial species responsible for over more than 65% of VAP. Assay performance was subsequently evaluated by analyzing early and regular 37 ETA samples collected from 15 patients. Twenty-five samples were above the significant threshold of 10⁵ CFU/mL and five samples showed mixed infections (both pathogens ≥ 10⁵ CFU/mL). The targeted proteomics assay showed 100% specificity for Acinetobacter baumannii, Escherichia coli, Haemophilus influenzae, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae. No false bacterial identification was reported and no interference was detected arising from the commensal flora. The overall species identification sensitivity was 19/25 (76%) and was higher at the patient level (84.6%). This successful proof of concept provides a rational to broaden the panel of bacteria for further clinical evaluation.

Establishing a mass spectrometry-based system for rapid detection of SARS-CoV-2 in large clinical sample cohorts

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pressing public health systems around the world, and large population testing is a key step to control this pandemic disease. Here, we develop a high-throughput targeted proteomics assay to detect SARS-CoV-2 nucleoprotein peptides directly from nasopharyngeal and oropharyngeal swabs. A modified magnetic particle-based proteomics approach implemented on a robotic liquid handler enables fully automated preparation of 96 samples within 4 hours. A TFC-MS system allows multiplexed analysis of 4 samples within 10 min, enabling the processing of more than 500 samples per day. We validate this method qualitatively (Tier 3) and quantitatively (Tier 1) using 985 specimens previously analyzed by real-time RT-PCR, and detect up to 84% of the positive cases with up to 97% specificity. The presented strategy has high sample stability and should be considered as an option for SARS-CoV-2 testing in large populations.

Exoproteomics for Better Understanding Pseudomonas aeruginosa Virulence

Pseudomonas aeruginosa is the most common human opportunistic pathogen associated with nosocomial diseases. In 2017, the World Health Organization has classified P. aeruginosa as a critical agent threatening human health, and for which the development of new treatments is urgently necessary. One interesting avenue is to target virulence factors to understand P. aeruginosa pathogenicity. Thus, characterising exoproteins of P. aeruginosa is a hot research topic and proteomics is a powerful approach that provides important information to gain insights on bacterial virulence. The aim of this review is to focus on the contribution of proteomics to the studies of P. aeruginosa exoproteins, highlighting its relevance in the discovery of virulence factors, post-translational modifications on exoproteins and host-pathogen relationships.

Genomic and Proteomic Characterization of the Extended-Spectrum β-Lactamase (ESBL)-Producing Escherichia coli Strain CCUG 73778: A Virulent, Nosocomial Outbreak Strain

Escherichia coli strain CCUG 78773 is a virulent extended-spectrum β-lactamase (ESBL)-producing ST131-O25b type strain isolated during an outbreak at a regional university hospital. The complete and closed genome sequence, comprising one chromosome (5,076,638 bp) and six plasmids (1718–161,372 bp), is presented. Characterization of the genomic features detected the presence of 59 potential antibiotic resistance factors, including three prevalent β-lactamases. Several virulence associated elements were determined, mainly related with adherence, invasion, biofilm formation and antiphagocytosis. Twenty-eight putative type II toxin-antitoxin systems were found. The plasmids were characterized, through in silico analyses, confirming the two β-lactamase-encoding plasmids to be conjugative, while the remaining plasmids were mobilizable. BLAST analysis of the plasmid sequences showed high similarity with plasmids in E. coli from around the world. Expression of many of the described virulence and AMR factors was confirmed by proteomic analyses, using bottom-up, liquid chromatography-tandem mass spectrometry (LC-MS/MS). The detailed characterization of E. coli strain CCUG 78773 provides a reference for the relevance of genetic elements, as well as the characterization of antibiotic resistance and the spread of bacteria harboring ESBL genes in the hospital environment.

The value of biomarker-guided antibiotic therapy

INTRODUCTION

There is an increasing interest to individualize patient management and decisions regarding antibiotic treatment. Biomarkers may provide relevant information for this purpose.

AREAS COVERED

Despite a growing number of clinical trials investigating several biomarkers, there remain open questions regarding the best type of biomarker, timing or frequency of testing, and optimal cutoffs among others. The most promising results in regard to diagnosis of bacterial infection and therapy monitoring are found for procalcitonin (PCT), although some recent trials were not able to validate the promising earlier findings. Furthermore, less specific markers like C-reactive protein (CRP) and new prognostic biomarkers such as proadrenomedullin (MR-proADM) may improve the prognostic assessment of patients and proteomics may help shorten time to microbiological results. The aim of this review is to summarize the current concept of biomarker-guided management and provide an outlook of promising ongoing investigations.

EXPERT OPINION

'Antibiotic stewardship' is complex and needs more than just the measurement of one single biomarker. However, when integrated into the context of a thorough clinical examination, standard blood parameters and a well done risk stratification by clinical scores such as the SOFA-score, biomarkers have great potential to improve the diagnostic and prognostic assessment of patients.