Metabolomic and Immunologic Discriminators of MIS-C at Emergency Room Presentation.

Multisystem Inflammatory Syndrome in Childhood (MIS-C) follows SARS-CoV-2 infection and frequently leads to intensive care unit admission. The inability to rapidly discriminate MIS-C from similar febrile illnesses delays treatment and leads to misdiagnosis. To identify diagnostic discriminators at the time of emergency department presentation, we enrolled 104 children who met MIS-C screening criteria, 14 of whom were eventually diagnosed with MIS-C. Before treatment, we collected breath samples for volatiles and peripheral blood for measurement of plasma proteins and immune cell features. Clinical and laboratory features were used as inputs for a machine learning model to determine diagnostic importance. MIS-C was associated with significant changes in breath volatile organic compound (VOC) composition as well as increased plasma levels of secretory phospholipase A2 (PLA2G2A) and lipopolysaccharide binding protein (LBP). In an integrated model of all analytes, the proportion of TCRVß21.3+ non-naive CD4 T cells expressing Ki-67 had a high sensitivity and specificity for MIS-C, with diagnostic accuracy further enhanced by low sodium and high PLA2G2A. We anticipate that accurate diagnosis will become increasingly difficult as MIS-C becomes less common. Clinical validation and application of this diagnostic model may improve outcomes in children presenting with multisystem febrile illnesses.

Volatile profiling distinguishes Streptococcus pyogenes from other respiratory streptococcal species.

Sore throat is one of the most common complaints encountered in the ambulatory clinical setting. Rapid, culture-independent diagnostic techniques that do not rely on pharyngeal swabs would be highly valuable as a point-of-care strategy to guide outpatient antibiotic treatment. Despite the promise of this approach, efforts to detect volatiles during oropharyngeal infection have yet been limited. In our research study, we sought to evaluate for specific bacterial volatile organic compounds (VOC) biomarkers in isolated cultures in vitro, in order to establish proof-of-concept prior to initial clinical studies of breath biomarkers. A particular challenge for the diagnosis of pharyngitis due to Streptococcus pyogenes is the likelihood that many metabolites may be shared by S. pyogenes and other related oropharyngeal colonizing bacterial species. Therefore, we evaluated whether sufficient metabolic differences are present, which distinguish the volatile metabolome of Group A streptococci from other streptococcal species that also colonize the respiratory mucosa, such as Streptococcus pneumoniae and Streptococcus intermedius. In this work, we identified 27 discriminatory VOCs (q-values < 0.05), composed of aldehydes, alcohols, nitrogen-containing compounds, hydrocarbons, ketones, aromatic compounds, esters, ethers, and carboxylic acid. From this group of volatiles, we identify candidate biomarkers that distinguish S. pyogenes from other species and establish highly produced VOCs that indicate the presence of S. pyogenes in vitro, supporting future breath-based diagnostic testing for streptococcal pharyngitis. IMPORTANCE Acute pharyngitis accounts for approximately 15 million ambulatory care visits in the United States. The most common and important bacterial cause of pharyngitis is Streptococcus pyogenesis, accounting for 15%-30% of pediatric pharyngitis. Distinguishing between bacterial and viral pharyngitis is key to management in US practice. The culture of a specimen obtained by a throat swab is the standard laboratory procedure for the microbiologic confirmation of pharyngitis; however, this method is time-consuming, which delays appropriate treatment. If left untreated, S. pyogenes pharyngitis may lead to local and distant complications. In this study, we characterized the volatile metabolomes of S. pyogenes and other related oropharyngeal colonizing bacterial species. We identify candidate biomarkers that distinguish S. pyogenes from other species and provide evidence to support future breath-based diagnostic testing for streptococcal pharyngitis.

Breath Metabolites to Diagnose Infection.

BACKGROUND: Starkly highlighted by the current COVID-19 pandemic, infectious diseases continue to have an outsized impact on human health worldwide. Diagnostic testing for infection can be challenging due to resource limitations, time constraints, or shortcomings in the accuracy of existing diagnostics. Rapid, simple diagnostics are highly desirable. There is increasing interest in the development of diagnostics that use exhaled breath analysis as a convenient and safe diagnostic method, as breath sampling is noninvasive, secure, and easy to perform. Volatile organic compounds (VOCs) present in exhaled breath reflect the fingerprint of the underlying metabolic and biophysical processes during disease. CONTENT: In this review, we overview the major biomarkers present in exhaled breath in infectious diseases. We outline the promising recent advances in breath-based diagnosis of respiratory infections, including those caused by influenza virus, SARS-CoV-2, Mycobacterium tuberculosis, Pseudomonas aeruginosa, and Aspergillus fumigatus. In addition, we review the current landscape of diagnosis of 2 other globally important infections: Helicobacter pylori gastrointestinal infection and malaria. SUMMARY: Characteristic and reproducible breath VOCs are associated with several infectious diseases, suggesting breath analysis as a promising strategy for diagnostic development. Ongoing challenges include poor standardization of breath collection and analysis and lack of validation studies. Further research is required to expand the applicability of breath analysis to clinical settings.

Reproducible Breath Metabolite Changes in Children with SARS-CoV-2 Infection.

SARS-CoV-2 infection is diagnosed through detection of specific viral nucleic acid or antigens from respiratory samples. These techniques are relatively expensive, slow, and susceptible to false-negative results. A rapid noninvasive method to detect infection would be highly advantageous. Compelling evidence from canine biosensors and studies of adults with COVID-19 suggests that infection reproducibly alters human volatile organic compound (VOC) profiles. To determine whether pediatric infection is associated with VOC changes, we enrolled SARS-CoV-2 infected and uninfected children admitted to a major pediatric academic medical center. Breath samples were collected from children and analyzed through state-of-the-art GCxGC-ToFMS. Isolated features included 84 targeted VOCs. Candidate biomarkers that were correlated with infection status were subsequently validated in a second, independent cohort of children. We thus find that six volatile organic compounds are significantly and reproducibly increased in the breath of SARS-CoV-2 infected children. Three aldehydes (octanal, nonanal, and heptanal) drew special attention, as aldehydes are also elevated in the breath of adults with COVID-19. Together, these biomarkers demonstrate high accuracy for distinguishing pediatric SARS-CoV-2 infection and support the ongoing development of novel breath-based diagnostics.

Discrimination of SARS-CoV-2 infected patient samples by detection dogs: A proof of concept study.

While the world awaits a widely available COVID-19 vaccine, availability of testing is limited in many regions and can be further compounded by shortages of reagents, prolonged processing time and delayed results. One approach to rapid testing is to leverage the volatile organic compound (VOC) signature of SARS-CoV-2 infection. Detection dogs, a biological sensor of VOCs, were utilized to investigate whether SARS-CoV-2 positive urine and saliva patient samples had a unique odor signature. The virus was inactivated in all training samples with either detergent or heat treatment. Using detergent-inactivated urine samples, dogs were initially trained to find samples collected from hospitalized patients confirmed with SARS-CoV-2 infection, while ignoring samples collected from controls. Dogs were then tested on their ability to spontaneously recognize heat-treated urine samples as well as heat-treated saliva from hospitalized SARS-CoV-2 positive patients. Dogs successfully discriminated between infected and uninfected urine samples, regardless of the inactivation protocol, as well as heat-treated saliva samples. Generalization to novel samples was limited, particularly after intensive training with a restricted sample set. A unique odor associated with SARS-CoV-2 infection present in human urine as well as saliva, provides impetus for the development of odor-based screening, either by electronic, chemical, or biological sensing methods. The use of dogs for screening in an operational setting will require training with a large number of novel SARS-CoV-2 positive and confirmed negative samples.

Reproducible breath metabolite changes in children with SARS-CoV-2 infection.

SARS-CoV-2 infection is diagnosed through detection of specific viral nucleic acid or antigens from respiratory samples. These techniques are relatively expensive, slow, and susceptible to false-negative results. A rapid non-invasive method to detect infection would be highly advantageous. Compelling evidence from canine biosensors and studies of adults with COVID-19 suggests that infection reproducibly alters human volatile organic compounds (VOCs) profiles. To determine whether pediatric infection is associated with VOC changes, we enrolled SARS-CoV-2-infected and -uninfected children admitted to a major pediatric academic medical center. Breath samples were collected from children and analyzed through state-of-the-art GCxGC-ToFMS. Isolated features included 84 targeted VOCs. Candidate biomarkers that were correlated with infection status were subsequently validated in a second, independent cohort of children. We thus find that six volatile organic compounds are significantly and reproducibly increased in the breath of SARS-CoV-2-infected children. Three aldehydes (octanal, nonanal, and heptanal) drew special attention, as aldehydes are also elevated in the breath of adults with COVID-19. Together, these biomarkers demonstrate high accuracy for distinguishing pediatric SARS-CoV-2 infection and support the ongoing development of novel breath-based diagnostics.

Breath Collection from Children for Disease Biomarker Discovery.

Breath collection and analysis can be used to discover volatile biomarkers in a number of infectious and non-infectious diseases, such as malaria, tuberculosis, lung cancer, and liver disease. This protocol describes a reproducible method for sampling breath in children and then stabilizing breath samples for further analysis with gas chromatography-mass spectrometry (GC-MS). The goal of this method is to establish a standardized protocol for the acquisition of breath samples for further chemical analysis, from children aged 4-15 years. First, breath is sampled using a cardboard mouthpiece attached to a 2-way valve, which is connected to a 3 L bag. Breath analytes are then transferred to a thermal desorption tube and stored at 4-5 °C until analysis. This technique has been previously used to capture breath of children with malaria for successful breath biomarker identification. Subsequently, we have successfully applied this technique to additional pediatric cohorts. The advantage of this method is that it requires minimal cooperation on part of the patient (of particular value in pediatric populations), has a short collection period, does not require trained staff, and can be performed with portable equipment in resource-limited field settings.

Comparison of breath sampling methods: a post hoc analysis from observational cohort studies.

In this report, we present a post hoc analysis from two observational cohorts, comparing the global breath volatile profile captured when using polymer sampling bags (mixed breath) versus Bio-VOC™ (alveolar breath). The cohorts were originally designed to characterize the breath volatile profiles of Malawian children with and without uncomplicated falciparum malaria. Children aged 3-15 years were recruited from ambulatory pediatric centers in Lilongwe, Malawi. Breath sampling was carried out two months apart (one study using a Bio-VOC™ and the second using sampling bags), and all samples were analyzed by gas chromatography/mass spectrometry. The efficacy of breath collection was assessed by quantifying levels of two high prevalence breath compounds, acetone and isoprene, as well as determining the overall number of breath compounds collected and their abundance. We found that the mean number of volatiles detected using sampling bags was substantially higher than when using the Bio-VOC™ (137 vs. 47). Breath collection by Bio-VOC™ also yielded reduced levels of endogenous breath volatiles, isoprene and acetone, even after breath volume correction. This suggests that the Bio-VOC™ dilutes the volatiles and introduces dead air or ambient air. Our results suggest that sampling bags are better suited for biomarker discovery and untargeted search of volatiles in pediatric populations, as evidenced by superior breath volatile detection.

Stability control for breath analysis using GC-MS.

Gas chromatography mass spectrometry (GC-MS) instruments provide researchers and clinicians with a vast amount of information on sample composition, thus these instruments are seen as gold standard in breath analysis research. However, there are many factors that can confound the data measured by GC-MS instruments. These factors will make interpretation of GC-MS data unreliable for breath analysis research. We present in this paper detailed studies of two of these factors: instrument variation over time and chemical degradation of known biomarkers during storage in sorbent tubes. We found that a single quadrupole MS showed larger variability in measurements than a quadrupole time-of-flight MS when the same mixture of chemical standards was analysed for a period of up to 8 weeks. We recommend procedures of normalising the data. Moreover, the stability studies of breath biomarkers like thioethers, previously found indicative of malaria, showed that there is a need to store the samples in sorbent tubes at low temperature, 6 °C, for no more than 20 days to avoid the total decay of the chemicals.

Diurnal variation in expired breath volatiles in malaria-infected and healthy volunteers.

We previously showed that thioether levels in the exhaled breath volatiles of volunteers undergoing controlled human malaria infection (CHMI) with P. falciparum increase as infection progresses. In this study, we show that thioethers have diurnal cyclical increasing patterns and their levels are significantly higher in P. falciparum CHMI volunteers compared to those of healthy volunteers. The synchronized cycle and elevation of thioethers were not present in P. vivax-infection, therefore it is likely that the thioethers are associated with unique factors in the pathology of P. falciparum. Moreover, we found that time-of-day of breath collection is important to accurately predict (98%) P. falciparum-infection. Critically, this was achieved when the disease was asymptomatic and parasitemia was below the level detectable by microscopy. Although these findings are encouraging, they show limitations because of the limited and logistically difficult diagnostic window and its utility to P. falciparum malaria only. We looked for new biomarkers in the breath of P. vivax CHMI volunteers and found that a set of terpenes increase significantly over the course of the malaria infection. The accuracy of predicting P. vivax using breath terpenes was up to 91%. Moreover, some of the terpenes were also found in the breath of P. falciparum CHMI volunteers (accuracy up to 93.5%). The results suggest that terpenes might represent better biomarkers than thioethers to predict malaria as they were not subject to malaria pathogens diurnal changes.

Analysis of Breath Specimens for Biomarkers of Plasmodium falciparum Infection.

Currently, the majority of diagnoses of malaria rely on a combination of the patient's clinical presentation and the visualization of parasites on a stained blood film. Breath offers an attractive alternative to blood as the basis for simple, noninvasive diagnosis of infectious diseases. In this study, breath samples were collected from individuals during controlled malaria to determine whether specific malaria-associated volatiles could be detected in breath. We identified 9 compounds whose concentrations varied significantly over the course of malaria: carbon dioxide, isoprene, acetone, benzene, cyclohexanone, and 4 thioethers. The latter group, consisting of allyl methyl sulfide, 1-methylthio-propane, (Z)-1-methylthio-1-propene, and (E)-1-methylthio-1-propene, had not previously been associated with any disease or condition. Before the availability of antimalarial drug treatment, there was evidence of concurrent 48-hour cyclical changes in the levels of both thioethers and parasitemia. When thioether concentrations were subjected to a phase shift of 24 hours, a direct correlation between the parasitemia and volatile levels was revealed. Volatile levels declined monotonically approximately 6.5 hours after initial drug treatment, correlating with clearance of parasitemia. No thioethers were detected in in vitro cultures of Plasmodium falciparum. The metabolic origin of the thioethers is not known, but results suggest that interplay between host and parasite metabolic pathways is involved in the production of these thioethers.

Drosophila olfactory receptors as classifiers for volatiles from disparate real world applications.

Olfactory receptors evolved to provide animals with ecologically and behaviourally relevant information. The resulting extreme sensitivity and discrimination has proven useful to humans, who have therefore co-opted some animals' sense of smell. One aim of machine olfaction research is to replace the use of animal noses and one avenue of such research aims to incorporate olfactory receptors into artificial noses. Here, we investigate how well the olfactory receptors of the fruit fly, Drosophila melanogaster, perform in classifying volatile odourants that they would not normally encounter. We collected a large number of in vivo recordings from individual Drosophila olfactory receptor neurons in response to an ecologically relevant set of 36 chemicals related to wine ('wine set') and an ecologically irrelevant set of 35 chemicals related to chemical hazards ('industrial set'), each chemical at a single concentration. Resampled response sets were used to classify the chemicals against all others within each set, using a standard linear support vector machine classifier and a wrapper approach. Drosophila receptors appear highly capable of distinguishing chemicals that they have not evolved to process. In contrast to previous work with metal oxide sensors, Drosophila receptors achieved the best recognition accuracy if the outputs of all 20 receptor types were used.

Feature selection for chemical sensor arrays using mutual information.

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays.

Comparisons of contact chemoreception and food acceptance by larvae of polyphagous Helicoverpa armigera and oligophagous Bombyx mori.

We compared food choice and the initial response to deterrent treated diet between fifth instars of Helicoverpa armigera, a polyphagous generalist pest, and Bombyx mori, an oligophagous specialist beneficial. Bombyx mori was more behaviorally sensitive to salicin than to caffeine. The relative sensitivities were reversed for H. armigera, which was tolerant to the highest levels of salicin found in natural sources but sensitive to caffeine. A single gustatory receptor neuron (GRN) in the medial styloconic sensillum of B. mori was highly sensitive to salicin and caffeine. The styloconic sensilla of H. armigera did not respond consistently to either of the bitter compounds. Phagostimulants also were tested. Myo-inositol and sucrose were detected specifically by two GRNs located in B. mori lateral styloconic sensillum, whereas, in H. armigera, sucrose was sensed by a GRN in the lateral sensillum, and myo-inositol by a GRN in the medial sensillum. Myo-inositol responsiveness in both species occurred at or below 10(-3) mM, which is far below the naturally occurring concentration of 1 mM in plants. Larval responses to specific plant secondary compounds appear to have complex determinants that may include host range, metabolic capacity, and gustatory repertoire.

Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose.

Analysis of 34 Sauvignon Blanc wine samples from three different countries and six regions was performed by gas chromatography-mass spectrometry (GC-MS). Linear discriminant analysis (LDA) showed that there were three distinct clusters or classes of wines with different aroma profiles. Wines from the Loire region in France and Australian wines from Tasmania and Western Australia were found to have similar aroma patterns. New Zealand wines from the Marlborough region as well as the Australian ones from Victoria were grouped together based on the volatile composition. Wines from South Australia region formed one discrete class. Seven analytes, most of them esters, were found to be the relevant chemical compounds that characterized the classes. The grouping information obtained by GC-MS, was used to train metal oxide based electronic (MOS-Enose) and mass spectrometry based electronic (MS-Enose) noses. The combined use of solid phase microextraction (SPME) and ethanol removal prior to MOS-Enose analysis, allowed an average error of prediction of the regional origins of Sauvignon Blanc wines of 6.5% compared to 24% when static headspace (SHS) was employed. For MS-Enose, the misclassification rate was higher probably due to the requirement to delimit the m/z range considered.

Bio-benchmarking of electronic nose sensors.

BACKGROUND: Electronic noses, E-Noses, are instruments designed to reproduce the performance of animal noses or antennae but generally they cannot match the discriminating power of the biological original and have, therefore, been of limited utility. The manner in which odorant space is sampled is a critical factor in the performance of all noses but so far it has been described in detail only for the fly antenna. METHODOLOGY: Here we describe how a set of metal oxide (MOx) E-Nose sensors, which is the most commonly used type, samples odorant space and compare it with what is known about fly odorant receptors (ORs). PRINCIPAL FINDINGS: Compared with a fly's odorant receptors, MOx sensors from an electronic nose are on average more narrowly tuned but much more highly correlated with each other. A set of insect ORs can therefore sample broader regions of odorant space independently and redundantly than an equivalent number of MOx sensors. The comparison also highlights some important questions about the molecular nature of fly ORs. CONCLUSIONS: The comparative approach generates practical learnings that may be taken up by solid-state physicists or engineers in designing new solid-state electronic nose sensors. It also potentially deepens our understanding of the performance of the biological system.

Comparison of metal oxide-based electronic nose and mass spectrometry-based electronic nose for the prediction of red wine spoilage.

Taints caused by Brettanomyces sp. spoilage are of concern to winemakers and consumers. Typically the taints are described as "barnyard", "sweaty saddle", and "Band-aid" when present in red wine at concentrations of several hundred micrograms per liter or more. The two main components of the taint are 4-ethylphenol (4EP) and 4-ethylguaiacol (4EG), which are metabolites produced by Brettanomyces yeasts. There is a need for a rapid instrumental method to quantify these compounds in wines. In this paper are compared two techniques, the metal oxide sensor-based electronic nose (MOS-Enose) and the mass spectrometry-based electronic nose (MS-Enose). Gas chromatography-mass spectrometry (GC-MS) was used for quantification and prediction purposes. Following ethanol removal, the limits of detection of a MOS-Enose were determined as 44 microg L(-1) for 4EP and 91 microg L(-1) for 4EG, using the SY/gCT sensor. These values are significantly lower than the reported human sensory thresholds. Partial least-squares (PLS) regression of electronic nose signals against known levels of 4EP and 4EG in 46 Australian red wines showed that the MOS-Enose was unable to identify "brett" spoilage reliably because of the response of the gas sensors to intersample variation in volatile compounds other than ethylphenols. Conversely, the MS-Enose was capable of reliably estimating concentrations of 4EP higher than 20 microg L(-1). Correlations (r2) of 0.97 and 0.98 were obtained between estimates of 4EP and 4EG concentrations with the concentrations determined by conventional GC-MS. It is concluded that, following ethanol removal, existing metal oxide sensors are sufficiently sensitive to detect brett taints in wine but lack the selectivity needed to perform this task when the aroma volatile background varies.