Detection of exogenous VOCs as a novel in vitro diagnostic technique for the detection of pathogenic bacteria

A matrix-centered view of mass spectrometry platform innovation for volatilome research

Volatile organic compounds (VOCs) are carbon-containing molecules with high vapor pressure and low water solubility that are released from biotic and abiotic matrices. Because they are in the gaseous phase, these compounds tend to remain undetected when using conventional metabolomic profiling methods. Despite this omission, efforts to profile VOCs can provide useful information related to metabolic status and identify potential signaling pathways or toxicological impacts in natural or engineered environments. Over the past several decades mass spectrometry (MS) platform innovation has instigated new opportunities for VOC detection from previously intractable matrices. In parallel, volatilome research linking VOC profiles to other forms of multi-omic information (DNA, RNA, protein, and other metabolites) has gained prominence in resolving genotype/phenotype relationships at different levels of biological organization. This review explores both on-line and off-line methods used in VOC profiling with MS from different matrices. On-line methods involve direct sample injection into the MS platform without any prior compound separation, while off-line methods involve chromatographic separation prior to sample injection and analyte detection. Attention is given to the technical evolution of platforms needed for increasingly resolved VOC profiles, tracing technical progress over time with particular emphasis on emerging microbiome and diagnostic applications.

Surveillance of pathogenic bacteria on a food matrix using machine-learning-enabled paper chromogenic arrays

Global food systems can benefit significantly from continuous monitoring of microbial food safety, a task for which tedious operations, destructive sampling, and the inability to monitor multiple pathogens remain challenging. This study reports significant improvements to a paper chromogenic array sensor - machine learning (PCA-ML) methodology sensing concentrations of volatile organic compounds (VOCs) emitted on a species-specific basis by pathogens by streamlining dye selection, sensor fabrication, database construction, and machine learning and validation. This approach enables noncontact, time-dependent, simultaneous monitoring of multiple pathogens (Listeria monocytogenes, Salmonella, and E. coli O157:H7) at levels as low as 1 log CFU/g with over 90% accuracy. The report provides theoretical and practical frameworks demonstrating that chromogenic response, including limits of detection, depends on time integrals of VOC concentrations. The paper also discusses the potential for implementing PCA-ML in the food supply chain for different food matrices and pathogens, with species- and strain-specific identification.

Dogs can detect an odor profile associated with Staphylococcus aureus biofilms in cultures and biological samples

Introduction

The study investigated the utilization of odor detection dogs to identify the odor profile of Staphylococcus aureus (S. aureus) biofilms in pure in vitro samples and in in vivo biosamples from animals and humans with S. aureus periprosthetic joint infection (PJI). Biofilms form when bacterial communities aggregate on orthopedic implants leading to recalcitrant infections that are difficult to treat. Identifying PJI biofilm infections is challenging, and traditional microbiological cultures may yield negative results even in the presence of clinical signs.

Methods

Dogs were trained on pure in vitro S. aureus biofilms and tested on lacrimal fluid samples from an in vivo animal model (rabbits) and human patients with confirmed S. aureus PJI.

Results

The results demonstrated that dogs achieved a high degree of sensitivity and specificity in detecting the odor profile associated with S. aureus biofilms in rabbit samples. Preliminary results suggest that dogs can recognize S. aureus volatile organic compounds (VOCs) in human lacrimal fluid samples.

Discussion

Training odor detection dogs on in vitro S. aureus, may provide an alternative to obtaining clinical samples for training and mitigates biosecurity hazards. The findings hold promise for culture-independent diagnostics, enabling early disease detection, and improved antimicrobial stewardship. In conclusion, this research demonstrates that dogs trained on in vitro S. aureus samples can identify the consistent VOC profile of PJI S. aureus biofilm infections. The study opens avenues for further investigations into a retained VOC profile of S. aureus biofilm infection. These advancements could revolutionize infectious disease diagnosis and treatment, leading to better patient outcomes and addressing the global challenge of antimicrobial resistance.

Electropolymerized polypyrrole-MOF composite as a coating material for SPME fiber for extraction VOCs liberated by bacteria

The synthesis of efficient and low-cost coatings for solid-phase microextraction attracted much attention. Conductive polymers are excellent candidates for this purpose due to the possibility of electropolymerization, which results in the reproducible synthesis of films. A plethora of studies reported in the literature concluded that modification of conductive polymers with innovative materials could lead to an increase in sensitivity toward specific analytes. In this work, the metal-organic framework-polypyrrole composite was electrodeposited in one step directly onto a stainless-steel substrate. The effect of synthesis parameters on extraction efficiency was investigated. The obtained PPy@ZIF-8 coating was subjected to physical-chemical characterization using electron microscopy and Fourier-transform IR spectroscopy. The main finding of the study was that the values of the limit of detection and intra- and inter-day reproducibility for analytes with different chemical structures were found to be lower as compared to pure polypyrrole coating. Furthermore, the obtained polypyrrole-MOF coating was applied for the collection of profiles of volatile organic compounds liberated by bacteria. Hence, the polypyrrole@ZIF-8 coating synthesized using a low-cost and facile approach presented in this study can be useful for the profiling of VOCs liberated by bacteria.

Environmental and human health impacts of volatile organic compounds: A perspective review

Volatile organic compounds (VOCs) are synthetic chemicals that are broadly used in the production of numerous day-to-day products for residential and commercial-based applications. VOCs are naturally occurring in the environment; however, average annual emissions of man-made volatile organic compounds may have increased dramatically in recent decades. Although many factors were attributed to influencing volatile compounds' emission, only mankind's activities are mainly proclaimed. Since vehicle and industrial pollution are mounting for years and years, urban areas are highly prone to the impacts of VOCs. Generally, volatile compounds are highly spontaneous and readily react with the particles of ambiance and produce a polluted atmosphere through several physical and chemical reactions. Though the volatile compounds play an indispensable role in the manufacture and maintaining the stability of many products, the health impacts associated with their prolonged exposure are gaining attention as recent research reports underline the influence of a wide range of diseases and disorders. Likewise, since the modern way of life applies a lot of day-to-day chemicals, it is imperative to spread a wide knowledge and safety aspects about these chemicals so that people of a wide category can implement preventive measures according to their exposure and living style. In this context, the review article attempts to shed light on past and current updates concerning the relationship between VOCs exposure and environmental and human health impacts.

Methods and Advances in the Design, Testing and Development of In Vitro Diagnostic Instruments

With the continuous improvement of medical testing and instrumentation engineering technologies, the design, testing and development methods of in vitro diagnostic instruments are developing rapidly. In vitro diagnostic instruments are also gradually developing into a class of typical high-end medical equipment. The design of in vitro diagnostic instruments involves a variety of medical diagnostic methods and biochemical, physical and other related technologies, and its development process involves complex system engineering. This paper systematically organizes and summarizes the design, testing and development methods of in vitro diagnostic instruments and their development in recent years, focusing on summarizing the related technologies and core aspects of the R&D process, and analyzes the development trend of the in vitro diagnostic instrument market.

Profiling of exhaled volatile organics in the screening scenario of a COVID-19 test center

Breath volatile organics (VOCs) may provide immediate information on infection mechanisms and host response. We conducted real-time mass spectrometry-based breath profiling in 708 non-preselected consecutive subjects in the screening scenario of a COVID-19 test center. Recruited subjects were grouped based on PCR-confirmed infection status and presence or absence of flu-like symptoms. Exhaled VOC profiles of SARS-CoV-2-positive cases (n = 36) differed from healthy (n = 256) and those with other respiratory infections (n = 416). Concentrations of most VOCs were suppressed in COVID-19. VOC concentrations also differed between symptomatic and asymptomatic cases. Breath markers mirror effects of infections onto host's cellular metabolism and microbiome. Downregulation of specific VOCs was attributed to suppressive effects of SARS-CoV-2 onto gut or pulmonary microbial metabolism. Breath analysis holds potential for monitoring SARS-CoV-2 infections rather than for primary diagnosis. Breath profiling offers unconventional insight into host-virus cross-talk and infection microbiology and enables non-invasive assessment of disease manifestation.

Prediction of Bloodstream Infection in Pediatric Acute Leukemia by Microbiota and Volatile Organic Compounds Analysis

INTRODUCTION

Bloodstream infections (BSIs) cause treatment-related mortality in pediatric acute leukemia. We explored the potential of intestinal microbiota and fecal volatile organic compounds (VOCs) analyses to predict BSI.

METHODS

In this case-control study, fecal samples of pediatric acute leukemia patients were collected. Microbiota composition and fecal VOC profiles of BSI cases and matched non-BSI controls were compared.

RESULTS

In total, 6 patients were included, of which 1 developed BSI and 1 neutropenic fever. Both showed reduced microbial diversity and stability of Bacteroidetes. In the BSI case, Pantoea was identified 15 days before BSI. Significant differences in fecal VOC profiles were measured between the case and controls.

CONCLUSION

Microbiota and fecal VOC could serve as biomarkers to predict BSI in pediatric leukemia.

Disposable Paper-Based Biosensors for the Point-of-Care Detection of Hazardous Contaminations-A Review

The fast detection of trace amounts of hazardous contaminations can prevent serious damage to the environment. Paper-based sensors offer a new perspective on the world of analytical methods, overcoming previous limitations by fabricating a simple device with valuable benefits such as flexibility, biocompatibility, disposability, biodegradability, easy operation, large surface-to-volume ratio, and cost-effectiveness. Depending on the performance type, the device can be used to analyze the analyte in the liquid or vapor phase. For liquid samples, various structures (including a dipstick, as well as microfluidic and lateral flow) have been constructed. Paper-based 3D sensors are prepared by gluing and folding different layers of a piece of paper, being more user-friendly, due to the combination of several preparation methods, the integration of different sensor elements, and the connection between two methods of detection in a small set. Paper sensors can be used in chromatographic, electrochemical, and colorimetric processes, depending on the type of transducer. Additionally, in recent years, the applicability of these sensors has been investigated in various applications, such as food and water quality, environmental monitoring, disease diagnosis, and medical sciences. Here, we review the development (from 2010 to 2021) of paper methods in the field of the detection and determination of toxic substances.

Nondestructive multiplex detection of foodborne pathogens with background microflora and symbiosis using a paper chromogenic array and advanced neural network

We have developed an inexpensive, standardized paper chromogenic array (PCA) integrated with a machine learning approach to accurately identify single pathogens (Listeria monocytogenes, Salmonella Enteritidis, or Escherichia coli O157:H7) or multiple pathogens (either in multiple monocultures, or in a single cocktail culture), in the presence of background microflora on food. Cantaloupe, a commodity with significant volatile organic compound (VOC) emission and large diverse populations of background microflora, was used as the model food. The PCA was fabricated from a paper microarray via photolithography and paper microfluidics, into which 22 chromogenic dye spots were infused and to which three red/green/blue color-standard dots were taped. When exposed to VOCs emitted by pathogens of interest, dye spots exhibited distinguishable color changes and pattern shifts, which were automatically segmented and digitized into a ΔR/ΔG/ΔB database. We developed an advanced deep feedforward neural network with a learning rate scheduler, L₂ regularization, and shortcut connections. After training on the ΔR/ΔG/ΔB database, the network demonstrated excellent performance in identifying pathogens in single monocultures, multiple monocultures, and in cocktail culture, and in distinguishing them from the background signal on cantaloupe, providing accuracy of up to 93% and 91% under ambient and refrigerated conditions, respectively. With its combination of speed, reliability, portability, and low cost, this nondestructive approach holds great potential to significantly advance culture-free pathogen detection and identification on food, and is readily extendable to other food commodities with complex microflora.

Tailoring metal-organic frameworks-based nanozymes for bacterial theranostics

Nanozymes are next-generation artificial enzymes having distinguished features such as cost-effective, enhanced surface area, and high stability. However, limited selectivity and moderate activity of nanozymes in the biochemical environment hindered their usage and encouraged researchers to seek alternative catalytic materials. Recently, metal-organic frameworks (MOFs) characterized by distinct crystalline porous structures with large surface area, tunable pores, and uniformly dispersed active sites emerged, that filled the gap between natural enzymes and nanozymes. Moreover, by selecting suitable metal ions and organic linkers, MOFs can be designed for effective bacterial theranostics. In this review, we briefly presented the design and fabrication of MOFs. Then, we demonstrated the applications of MOFs in bacterial theranostics and their safety considerations. Finally, we proposed the major obstacles and opportunities for further development in research on the interface of nanozymes and MOFs. We expect that MOFs based nanozymes with unique physicochemical and intrinsic enzyme-mimicking properties will gain broad interest in both fundamental research and biomedical applications.

Detection of Bacterial Metabolic Volatile Indole Using a Graphene-Based Field-Effect Transistor Biosensor

The existence of bacteria is a great threat to food safety. Volatile compounds secreted by bacteria during their metabolic process can be dissected to evaluate bacterial contamination. Indole, as a major volatile molecule released by Escherichia coli (E. coli), was chosen to examine the presence of E. coli in this research. In this work, a graphene field-effect transistor (G-FET) was employed to detect the volatile molecule-indole based on a π-π stacking interaction between the indole and the graphene. The exposure of G-FET devices to the indole provokes a change in electrical signal, which is ascribed to the adsorption of the indole molecule onto the graphene surface via π-π stacking. The adsorption of the indole causes a charge rearrangement of the graphene-indole complex, which leads to changes in the electrical signal of G-FET biosensors with a different indole concentration. Currently, the indole biosensor can detect indole from 10 ppb to 250 ppb and reach a limit of detection of 10 ppb for indole solution detection. We believe that our detection strategy for detecting bacterial metabolic gas molecules will pave a way to developing an effective platform for bacteria detection in food safety monitoring.

Recognition of pathogens in food matrixes based on the untargeted in vivo microbial metabolite profiling via a novel SPME/GC × GC-QTOFMS approach

Foodborne diseases incurred by pathogenic bacteria are one of the major threats in food safety, and thus it is important to develop facile and effective recognition methodology of pathogens in food. Herein, a new automatic approach for detection of in vivo volatile metabolites emitted from foodborne pathogens was proposed by coupling solid phase microextraction (SPME) technique with a comprehensive two-dimensional gas chromatography quadrupole time-of-flight mass spectrometry (GC × GC-QTOFMS). A novel polymer composite based SPME probe which possessed high-coverage of microbial metabolites was utilized in this contribution to realize the sensitive extraction of untargeted metabolites. As a result, a total of 126 in vivo metabolites generated by the investigated pathogens were detected and identified, with 33, 29, 25, 21 and 18 volatile metabolites belonging to Shigella sonnei, Escherichia coli, Salmonella typhimurium, Vibrio parahaemolyticus and Staphylococcus aureus, respectively. Multivariate statistical analyses were applied for further analysis of metabolic data and separation of responsive metabolic features among different microbial systems were found, which were also successfully verified in foodstuffs contaminated by microorganisms. The growth trend of the potential volatile markers of each pathogen in food samples kept consistent with that of the pure strain incubated in medium during the whole incubation time. This study promotes the application of SPME technology in microbial volatile metabolomics and contributes to the development of new approaches for foodborne pathogens recognition.

Characterization of Volatile Organic Compounds Emitted from Endophytic Burkholderia cenocepacia ETR-B22 by SPME-GC-MS and Their Inhibitory Activity against Various Plant Fungal Pathogens

The use of antagonistic microorganisms and their volatile organic compounds (VOCs) to control plant fungal pathogens is an eco-friendly and promising substitute for chemical fungicides. In this work, endophytic bacterium ETR-B22, isolated from the root of Sophora tonkinensis Gagnep., was found to exhibit strong antagonistic activity against 12 fungal pathogens found in agriculture. Strain ETR-B22 was identified as Burkholderia cenocepacia based on 16S rRNA and recA sequences. We evaluated the antifungal activity of VOCs emitted by ETR-B22. The VOCs from strain ETR-B22 also showed broad-spectrum antifungal activity against 12 fungal pathogens. The composition of the volatile profiles was analyzed based on headspace solid phase microextraction (HS-SPME) gas chromatography coupled to mass spectrometry (GC-MS). Different extraction strategies for the SPME process significantly affected the extraction efficiency of the VOCs. Thirty-two different VOCs were identified. Among the VOC of ETR-B22, dimethyl trisulfide, indole, methyl anthranilate, methyl salicylate, methyl benzoate, benzyl propionate, benzyl acetate, 3,5-di-tert-butylphenol, allyl benzyl ether and nonanoic acid showed broad-spectrum antifungal activity, and are key inhibitory compounds produced by strain ETR-B22 against various fungal pathogens. Our results suggest that the endophytic strain ETR-B22 and its VOCs have high potential for use as biological controls of plant fungal pathogens.

Detection of β-alanyl aminopeptidase as a biomarker for Pseudomonas aeruginosa in the sputum of patients with cystic fibrosis using exogenous volatile organic compound evolution

A novel, rapid and sensitive analytical method has been developed and applied to 105 sputum samples from patients with cystic fibrosis, including 5 samples from post-lung transplant patients. This new method is specifically targeted to measure β-alanyl aminopeptidase activity which is characteristic of some important Gram-negative pathogens. Of relevance to this study are Pseudomonas aeruginosa and pathogens of the Burkholderia cepacia complex both of which are commonly associated with respiratory infections as well as increased morbidity and mortality in adult cystic fibrosis patients. The analytical method involves the addition of a novel enzyme substrate (i.e. 3-amino-N-(3-fluorophenyl)propanamide) that interacts with β-alanyl aminopeptidase to generate an exogenous volatile organic compound 3-fluoroaniline (LOD 0.02 μg mL⁻¹; LOQ 0.06 μg mL⁻¹). 3-Fluoroaniline was determined at 20 times above its calculated limit of quantification in the sputum samples by HS-SPME-GC-MS and then the results compared with standard culture methods and bacterial identification using MALDI-TOF-MS. Detection of 3-fluoroaniline was possible after only 8 h incubation of the sputum samples with a 95% success rate; this increased to 100% at 24 h which was well within the typical routine timeframe of 48 h. To our knowledge, this is the first demonstration of detection of P. aeruginosa by use of a custom-designed substrate to liberate a detectable and unique VOC. The very high negative predictive value (100% in this study) means such an assay could be appropriate as a screening technique for patients who are not yet colonized by this pathogen.

A novel, rapid and sensitive analytical method has been developed and applied to 105 sputum samples from patients with cystic fibrosis, including 5 samples from post-lung transplant patients.

Volatile scents of influenza A and S. pyogenes (co-)infected cells

Influenza A is a serious pathogen itself, but often leads to dangerous co-infections in combination with bacterial species such as Streptococcus pyogenes. In comparison to classical biochemical methods, analysis of volatile organic compounds (VOCs) in headspace above cultures can enable destruction free monitoring of metabolic processes in vitro. Thus, volatile biomarkers emitted from biological cell cultures and pathogens could serve for monitoring of infection processes in vitro. In this study we analysed VOCs from headspace above (co)-infected human cells by using a customized sampling system. For investigating the influenza A mono-infection and the viral-bacterial co-infection in vitro, we analysed VOCs from Detroit cells inoculated with influenza A virus and S. pyogenes by means of needle-trap micro-extraction (NTME) and gas chromatography mass spectrometry (GC-MS). Besides the determination of microbiological data such as cell count, cytokines, virus load and bacterial load, emissions from cell medium, uninfected cells and bacteria mono-infected cells were analysed. Significant differences in emitted VOC concentrations were identified between non-infected and infected cells. After inoculation with S. pyogenes, bacterial infection was mirrored by increased emissions of acetaldehyde and propanal. N-propyl acetate was linked to viral infection. Non-destructive monitoring of infections by means of VOC analysis may open a new window for infection research and clinical applications. VOC analysis could enable early recognition of pathogen presence and in-depth understanding of their etiopathology.

An Optimistic Vision of Future: Diagnosis of Bacterial Infections by Sensing Their Associated Volatile Organic Compounds

Simple tests using sniff analysis that have the ability of diagnosing and rapidly distinguishing between infections due to different bacteria are urgently required by medical community worldwide. Professionals interested in this topic wish for these tests to be simultaneously cheap, fast, easily applicable, non-invasive, robust, reliable, and sensitive. Current analytical instrumentation has already the ability for performing real time (minutes or a few dozens of minutes) analysis of volatile bacterial biomarkers (the VOCs emitted by bacteria). Although many articles are available, a review displaying an objective evaluation of the current status in the field is still needed. This review tries to present an overview regarding the bacterial biomarkers released from in vitro cultivation of various bacterial strains and also from different biological matrices investigated, over the last 10 years. We have described results of relevant studies, which used modern analytical techniques to evaluate specific biomarker profiles associated with bacterial infections. Our purpose was to present a comprehensive view of available possibilities for detection of emitted bacterial VOCs from different matrices. We intend that this review to be of general interest for both medical doctors and for all researchers preoccupied with bacterial infectious diseases and their rapid diagnosis using analytical instrumentation.

GC-MS application in determination of volatile profiles emitted by infected and uninfected human tissue

Volatile organic compounds (VOCs) released into the headspace air over human tissues infected with different bacteria were investigated in this work. The above-mentioned VOCs result both from bacterial metabolic processes (pathogen-specific signals) and from the matrix (tissue samples themselves). The objective of this study was to investigate whether one could reliably identify various microorganism strains that exist inside infected tissue samples by direct monitoring of the headspace atmosphere above their cultures. Headspace samples were directly interrogated using a GC-MS system, which produced distinct profiles for samples contaminated with single bacterial strains or with multiple strains (mixed infections). Principal component analysis (PCA) and predictive analysis based on receiver operating characteristics curves (ROC) were the statistical procedures utilized for differentiating between infected and uninfected samples, while network analysis and heat-mapping were used to highlight the connections between emitted volatiles and infectious pathogens. By using ROC curves, obtained results demonstrated that the area under the ROC (95% probability interval) was 0.86 in case of infected samples and 0.48 for uninfected samples. On the other hand, PCA highlighted separation between components coming from infected and uninfected patients, where 67% of variance was described from the first 2 principal components. The biomarker chemicals documented from this work, as well as the developed methodology may ultimately be applied to identify bacterial infections by analyzing exhaled breath.

Biogenic Volatile Compounds for Plant Disease Diagnosis and Health Improvement

Plants and microorganisms (microbes) use information from chemicals such as volatile compounds to understand their environments. Proficiency in sensing and responding to these infochemicals increases an organism's ecological competence and ability to survive in competitive environments, particularly with regard to plant-pathogen interactions. Plants and microbes acquired the ability to sense and respond to biogenic volatiles during their evolutionary history. However, these signals can only be interpreted by humans through the use of state-of the-art technologies. Newly-developed tools allow microbe-induced plant volatiles to be detected in a rapid, precise, and non-invasive manner to diagnose plant diseases. Beside disease diagnosis, volatile compounds may also be valuable in improving crop productivity in sustainable agriculture. Bacterial volatile compounds (BVCs) have potential for use as a novel plant growth stimulant or as improver of fertilizer efficiency. BVCs can also elicit plant innate immunity against insect pests and microbial pathogens. Research is needed to expand our knowledge of BVCs and to produce BVC-based formulations that can be used practically in the field. Formulation possibilities include encapsulation and sol-gel matrices, which can be used in attract and kill formulations, chemigation, and seed priming. Exploitation of biogenic volatiles will facilitate the development of smart integrated plant management systems for disease control and productivity improvement.

Fecal Volatile Organic Compounds in Preterm Infants Are Influenced by Enteral Feeding Composition

Fecal volatile organic compound (VOC) analysis has shown great potential as a noninvasive diagnostic biomarker for a variety of diseases. Before clinical implementation, the factors influencing the outcome of VOC analysis need to be assessed. Recent studies found that the sampling conditions can influence the outcome of VOC analysis. However, the dietary influences remains unknown, especially in (preterm) infants. Therefore, we assessed the effects of feeding composition on fecal VOC patterns of preterm infants (born at <30 weeks gestation). Two subgroups were defined: (1) daily intake >75% breastmilk (BM) feeding and (2) daily intake >75% formula milk (FM) feeding. Fecal samples, which were collected at 7, 14 and 21 days postnatally, were analyzed by an electronic nose device (Cyranose 320^®). In total, 30 preterm infants were included (15 FM, 15 BM). No differences in the fecal VOC patterns were observed at the three predefined time-points. Combining the fecal VOC profiles of these time-points resulted in a statistically significant difference between the two subgroups although this discriminative accuracy was only modest (AUC [95% CI]; p-value; sensitivity; and specificity of 0.64 [0.51–0.77]; 0.04; 68%; and 51%, respectively). Our results suggest that the influence of enteral feeding on the outcome of fecal VOC analysis cannot be ignored in this population. Furthermore, in both subgroups, the fecal VOC patterns showed a stable longitudinal course within the first month of life.

Functionalized gold and persistent luminescence nanoparticle-based ratiometric absorption and TR-FRET nanoplatform for high-throughput sequential detection of l-cysteine and insulin

In vitro diagnostic is a crucial component of healthcare systems for early diagnosis of diseases and follow-up therapy, which generally makes clinical diagnosis faster, easier, and painless for patients. Herein, we report a dual-signaling nanoplatform for ratiometric absorption and time-resolved fluorescence resonance energy transfer based on l-cysteine-mediated aggregated gold nanoparticles and long afterglow nature of persistent luminescence nanoparticles. With this nanoplatform, we have achieved high-throughput sequential detection of l-cysteine and insulin in human serum without matrix interference. The proposed nanoplatform shows excellent linearity and precision for the determination of l-cysteine in the range of 10 nM to 5.5 μM with the limit of detection (LOD) of 2.2 nM and for the detection of insulin in the range of 12 pM to 3.44 nM with LOD of 2.06 pM. The developed dual-signaling nanoplatform has been successfully applied for the sequential determination of l-cysteine and insulin in human serum.

Application of Fecal Volatile Organic Compound Analysis in Clinical Practice: Current State and Future Perspectives

Increasing interest is noticed in the potential of volatile organic compound (VOC) analysis as non-invasive diagnostic biomarker in clinical medical practice. The spectrum of VOCs, originating from (patho)physiological metabolic processes in the human body and detectable in bodily excrements, such as exhaled breath, urine and feces, harbors a magnificent source of information. Thus far, the majority of studies have focused on VOC analysis in exhaled breath, aiming at identification of disease-specific VOC profiles. Recently, an increasing number of studies have evaluated the usability of VOC present in the headspace of feces in the diagnostic work-up of a wide range of gastrointestinal diseases. Promising results have been demonstrated particularly in those diseases in which microbiota alterations are considered to play a significant etiological role, such as colorectal carcinoma, inflammatory bowel disease, irritable bowel syndrome, celiac disease and infectious bowel diseases. In addition, fecal VOC analysis seems to have potential as a diagnostic biomarker for extra-intestinal diseases, including bronchopulmonary dysplasia and sepsis. Different methods for VOC analysis have been used in medical studies, such as gas-chromatography mass spectrometry, selected-ion flow tube-mass spectrometry, ion-mobility spectrometry, and electronic nose devices. In this review, the available literature on the potential of fecal VOCs as diagnostic biomarker, including an overview of relevant VOC detection techniques, is discussed. In addition, future hurdles, which need to be taken prior to implementation of VOC analysis in daily clinical practice, are outlined.

Mass spectrometric techniques for the analysis of volatile organic compounds emitted from bacteria

Bacteria are the main cause of many human diseases. Typical bacterial identification methods, for example culture-based, serological and genetic methods, are time-consuming, delaying the potential for an early and accurate diagnosis and the appropriate subsequent treatment. Nevertheless, there is a stringent need for in situ tests that are rapid, noninvasive and sensitive, which will greatly facilitate timely treatment of the patients. This review article presents volatile organic metabolites emitted from various micro-organism strains responsible for common bacterial infections in humans. Additionally, the manuscript shows the application of different analytical techniques for fast bacterial identification. Details of these techniques are given, which focuses on their advantages and drawbacks in using for volatile organic components analysis.