A workflow for data integration, analysis, and metabolite annotation for untargeted metabolomics

Metabolomics is the youngest of the \u201comics\u201d disciplines and it is regarded as a promising approach to understand the metabolic changes that can occur in particular conditions and to identify new biomarkers. We present here a workflow for data integration, analysis, and metabolite annotation to be applied to untargeted metabolomic experiments. Data acquired with LC-MS/MS, operating in data dependent mode, are processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The data-table obtained is elaborated and submitted to statistical analysis using the on-line software MetaboAnalyst. Multivariate analysis, in particular principal component and partial least squares discriminant analysis are performed for data visualization. Univariate analysis, in particular T-test for pairwise and ANOVA for multi-groups comparison, are performed to detect significant features among groups. The software BEAMS, developed by the University of Birmingham, is then implemented for grouping adducts and isotopes, and to perform a first annotation. Metabolite annotation is finally completed by comparing the fragmentation pattern obtained from each parent ion corresponding to a significant feature with data stored in on-line databases as Metlin, and with the help of the software MS-FINDER, which performs in-silico fragmentation. We applied this workflow to an untargeted metabolomic experiment performed on 67 urine samples obtained from adult subjects with different smoking habits: non-smokers, electronic cigarette smokers, and traditional tobacco smokers. 117 features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites. We were able to putatively annotate compound classes of most of the significant metabolites (level 3 according to the \u201cProposed minimum reporting standards\u201d; Sumner et al., 2007) and to putatively annotate some of them (level 2). Among them, the glucuronide conjugated of 3-hydroxycotinine supports the validity of the proposed approach

Untargeted metabolomics in urine to investigate smoking exposure

Background: Although thousands of different chemicals have been identified in cigarette smoke, the characterization of urinary metabolites derived from those compounds is still not completely achieved. The aim of this work was to perform an untargeted metabolomic experiment on a pilot cross-sectional study conducted on subjects with different smoking habits. Methods: Urine samples were collected from 67 adults; including 38 non-smokers, 7 electronic cigarette smokers, and 22 traditional tobacco smokers. Samples were analyzed by liquid chromatography/time-of flight mass spectrometer operating in data dependent mode. Data were processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The ANOVA test was used to detect significant features among groups. The software BEAMS (University of Birmingham) was implemented for grouping adducts and isotopes, and to perform a first annotation. Annotation was completed by comparing fragmentation patterns with on-line databases as Metlin, and using the software MS-FINDER. Results: One hundred and seventeen features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites, of which we were able to putatively annotate about half. The identification of the mercapturic acids of acrolein, 1,3-butadiene, and crotonaldeide, chemicals known to be present in tobacco smoke, supports the validity of the proposed approach. With a lower level of confidence, we annotated the glucuronide conjugated of 3-hydroxycotinine and the sulfate conjugate of methoxyphenol; finally, with the lowest degree of confidence, several other sulfate conjugates of small molecules were annotated. Short discussion/conclusions: The proposed approach seems to be useful for the investigation of exposure to toxicants in humans

Investigation of urine metabolites related to tobacco smoke chemicals using an untargeted metabolomic approach

Although thousands of different chemicals have been identified in cigarette smoke, the characterization of urinary metabolites derived from those compounds is still not completely achieved. The aim of this work was to perform an untargeted metabolomic experiment on a pilot cross-sectional study conducted on subjects with different smoking habits. Urine samples were collected from 67 adults; including 38 non-smokers, 7 electronic cigarette smokers, and 22 traditional tobacco smokers. Samples were analyzed by liquid chromatography/time-of flight mass spectrometer operating in data dependent mode. Data were processed using the R-packages IPO and XCMS to perform feature detection, retention time correction and alignment. The ANOVA test was used to detect significant features among groups. The software BEAMS (University of Birmingham) was implemented for grouping adducts and isotopes, and to perform a first annotation. Annotation was completed by comparing fragmentation patterns with on-line databases as Metlin, and using the software MS-FINDER. One hundred and seventeen features, out of 3613, were statistically different among groups. We estimated that they correspond to about 80 metabolites, for which we were able to putatively annotate about half. Among these, the identification of the glucuronide conjugated of 3-hydroxycotinine supports the validity of the proposed approach. Furthermore, several metabolites, mostly as sulfate conjugates, derived from chemicals known to be present in tobacco smoke, were annotated, among which the metabolite of methoxyphenol, acrolein, 1,3-butadiene, and crotonaldeide

Evaluation of synchronization protocols and methods of early pregnancy diagnosis in dairy cattle

The studies aimed to evaluate the pregnancy rate (PR) for timed artificial insemination (TAI) after G7G-Ovsynch, modified G7G-Ovsynch (MG7G-Ovsynch) and Ovsynch protocols and to assess the accuracy of using pregnancy-associated glycoproteins (PAGs) and plasma progesterone (P4) in pregnancy diagnosis compared with ultrasonography (US). In study 1, Holstein cows (n = 37) were bred by TAI following the G7G-Ovsynch protocol (n = 19) or MG7G-Ovsynch (n = 18). Pregnancy was evaluated by US at days 31, 59, and 87 after breeding. The PR was not different for the G7G-Ovsynch and MG7G-Ovsynch. Blood and milk samples were collected on day 3 after insemination and then weekly through day 59 post TAI in cows diagnosed as not pregnant on day 31 and through day 87 in pregnant cows. PAGs were measured using ELISA and P4 by radioimmunoassay (RIA). In the second study, Holstein cows (n = 212) were bred by TAI following G7G-Ovsynch protocol (n = 110) or standard Ovsynch (n = 102). Cows were subjected to pregnancy diagnosis on days 30, 60, and 90. A subset (n = 15 in each group) was subjected to blood and milk samples on days 30, 45, 60, 75, and 90 to measure PAGs and P4. In study 2, PR was not significantly different between synchronization protocols on days 30, 60, and 90. Pregnancy loss averaged 15% between day 30 and day 90. The use of PAGs and P4 proved equally effective in diagnosis of pregnancy. Thus, G7G-Ovsynch was deemed the protocol of choice in postpartum cows, and PAGs assayed in milk or plasma could be used to diagnose pregnancy

Airway macrophages display decreased expression of receptors mediating and regulating scavenging in early cystic fibrosis lung disease

Background: Cystic fibrosis (CF) airway disease is characterized by chronic inflammation, featuring neutrophil influx to the lumen. Airway macrophages (AMs) can promote both inflammation and resolution, and are thus critical to maintaining and restoring homeostasis. CF AM functions, specifically scavenging activity and resolution of inflammation, have been shown to be impaired, yet underlying processes remain unknown. We hypothesized that impaired CF AM function results from an altered expression of receptors that mediate or regulate scavenging, and set out to investigate changes in expression of these markers during the early stages of CF lung disease. Methods: Bronchoalveolar lavage fluid (BALF) was collected from 50 children with CF aged 1, 3 or 5 years. BALF cells were analyzed using flow cytometry. Expression levels of surface markers on AMs were expressed as median fluorescence intensities (MFI) or percentage of AMs positive for these markers. The effect of age and neutrophilic inflammation, among other variables, on marker expression was assessed with a multivariate linear regression model.Results: AM expression of scavenger receptor CD163 decreased with age (p = 0.016) and was negatively correlated with BALF %neutrophils (r = -0.34, p = 0.016). AM expression of immune checkpoint molecule SIRPα also decreased with age (p = 0.0006), but did not correlate with BALF %neutrophils. Percentage of AMs expressing lipid scavenger CD36 was low overall (mean 20.1% ± 16.5) and did not correlate with other factors. Conversely, expression of immune checkpoint PD-1 was observed on the majority of AMs (mean PD-1pos 72.9% ± 11.8), but it, too, was not affected by age or BALF %neutrophils. Compared to matched blood monocytes, AMs had a higher expression of CD16, CD91, and PD-1, and a lower expression of CD163, SIRPα and CD36. Conclusion: In BALF of preschool children with CF, higher age and/or increased neutrophilic inflammation coincided with decreased expression of scavenger receptors on AMs. Expression of scavenging receptors and regulators showed a distinctly different pattern in AMs compared to blood monocytes. These findings suggest AM capacity to counter inflammation and promote homeostasis reduces during initiation of CF airway disease and highlight new avenues of investigation into impaired CF AM function.</p

Un approccio metabolomico non mirato per indagare l&apos;esposizione a sostanze tossiche nel fumo di sigaretta

Introduzione: Nel fumo di sigaretta siano state identificate migliaia di diverse sostanze chimiche pericolose; ci\uf2 nonostante la caratterizzazione dei metaboliti urinari di queste sostanze a seguito di esposizione nell'uomo \ue8 stata effettuata sono parzialmente. Obiettivo: Lo studio si propone di applicare un approccio metabolomico non mirato all'analisi di campioni di urina di soggetti con diversa abitudine al fumo, allo scopo di identificare i metaboliti derivanti da sostanze tossiche associati. Metodi: Sono stati raccolti campioni estemporanei di urina da 67 soggetti suddivisi in tre gruppi sulla base della loro abitudine al fumo: 38 soggetti erano non fumatori, 7 erano fumatori di sigaretta elettronica e 22 erano fumatori di tabacco. I campioni sono stati analizzati utilizzando la cromatografia liquida accoppiata ad uno spettrometro di massa con tempo di volo, raccogliendo i segnali degli ioni negativi. I dati sono stati processati utilizzando i pacchetti R IPA e MXCMS per correggere i tempi di ritenzione ed effettuare l'allineamento tra i cromatogrammi. Il test ANOVA \ue8 stato utilizzato per identificare gli elementi caratteristici che distinguono tra loro i gruppi. Il software BEAMS, sviluppato dall'universit\ue0 di Birmingham, \ue8 stato applicato per raggruppare gli addotti e gli isotopi riferiti ad una stessa sostanza ed effettuare una prima annotazione dei picchi. L'annotazione \ue8 stata completata confrontando gli spettri di frammentazione ottenuti da standard puri e con il database Metlin, usando il software MS-FINDER Risultati: Nei cromatogrammi ottenuti sono stati identificati complessivamente 3613 segnali, di cui 117 sono risultati diversi nei gruppi studiati. Questi segnali sono stati attribuiti a circa 80 diversi metaboliti, dei quali siamo riusciti ad annotarne putativamente circa la met\ue0. L\u2019identificazione, con un grado di confidenza pari a 1, degli acidi mercapturici dell\u2019acroleina, del 1,3-butadiene, e della crotonaldeide, sostanze risaputamene presenti nel fumo di tabacco, supportano la validit\ue0 dell\u2019approccio adottato (il grado di confidenza 1 si attribuisce alle molecole identificate con certezza per confronto con lo standard puro). Con un grado di confidenza minore (pari a 2) sono state identificati: il coniugato glucuronide della 3-idrossicotinina e il coniugato solfato del metossifenolo. Infine, con un grado di confidenza 3, sono state identificate numerose altre piccole molecole, escrete come coniugati solfati. Conclusione: L\u2019approccio proposto sembra utile per indagare l\u2019esposizione a miscele di sostanze tossiche nell\u2019uomo. Dato che l\u2019esposizione a miscele di sostanze chimiche, piuttosto che a singoli composti, \ue8 una caratteristica peculiare di molti ambienti di lavoro, si reputa che questo approccio apra interessanti prospettive per la medicina del lavoro

Pharmacokinetic-pharmacodynamic correlation of imipenem in pediatric burn patients using a bioanalytical liquid chromatographic method

A bioanalytical method was developed and applied to quantify the free imipenem concentrations for pharmacokinetics and PK/PD correlation studies of the dose adjustments required to maintain antimicrobial effectiveness in pediatric burn patients. A reverse-phase Supelcosil LC18 column (250 x 4.6 mm 5 micra), binary mobile phase consisting of 0.01 M, pH 7.0 phosphate buffer and acetonitrile (99:1, v/v), flow rate of 0.8 mL/min, was applied. The method showed good absolute recovery (above 90%), good linearity (0.25-100.0 µg/mL, r2=0.999), good sensitivity (LLOQ: 0.25 µg/mL; LLOD: 0.12 µg/mL) and acceptable stability. Inter/intraday precision values were 7.3/5.9%, and mean accuracy was 92.9%. A bioanalytical method was applied to quantify free drug concentrations in children with burns. Six pediatric burn patients (median 7.0 years old, 27.5 kg), normal renal function, and 33% total burn surface area were prospectively investigated; inhalation injuries were present in 4/6 (67%) of the patients. Plasma monitoring and PK assessments were performed using a serial blood sample collection for each set, totaling 10 sets. The PK/PD target attained (40%T>MIC) for each minimum inhibitory concentration (MIC: 0.5, 1.0, 2.0, 4.0 mg/L) occurred at a percentage higher than 80% of the sets investigated and 100% after dose adjustment. In conclusion, the purification of plasma samples using an ultrafiltration technique followed by quantification of imipenem plasma measurements using the LC method is quite simple, useful, and requires small volumes for blood sampling. In addition, a small amount of plasma (0.25 mL) is needed to guarantee drug effectiveness in pediatric burn patients. There is also a low risk of neurotoxicity, which is important because pharmacokinetics are unpredictable in these critical patients with severe hospital infection. Finally, the PK/PD target was attained for imipenem in the control of sepsis in pediatric patients with burns.</p

FKBP12.6 Deficiency and Defective Calcium Release Channel (Ryanodine Receptor) Function Linked to Exercise-Induced Sudden Cardiac Death

AbstractArrhythmias, a common cause of sudden cardiac death, can occur in structurally normal hearts, although the mechanism is not known. In cardiac muscle, the ryanodine receptor (RyR2) on the sarcoplasmic reticulum releases the calcium required for muscle contraction. The FK506 binding protein (FKBP12.6) stabilizes RyR2, preventing aberrant activation of the channel during the resting phase of the cardiac cycle. We show that during exercise, RyR2 phosphorylation by cAMP-dependent protein kinase A (PKA) partially dissociates FKBP12.6 from the channel, increasing intracellular Ca2+ release and cardiac contractility. FKBP12.6−/− mice consistently exhibited exercise-induced cardiac ventricular arrhythmias that cause sudden cardiac death. Mutations in RyR2 linked to exercise-induced arrhythmias (in patients with catecholaminergic polymorphic ventricular tachycardia [CPVT]) reduced the affinity of FKBP12.6 for RyR2 and increased single-channel activity under conditions that simulate exercise. These data suggest that “leaky” RyR2 channels can trigger fatal cardiac arrhythmias, providing a possible explanation for CPVT

Automatic segmentation of cerebral infarcts in follow-up computed tomography images with convolutional neural networks

Background and purpose: Infarct volume is a valuable outcome measure in treatment trials of acute ischemic stroke and is strongly associated with functional outcome. Its manual volumetric assessment is, however, too demanding to be implemented in clinical practice. Objective: To assess the value of convolutional neural networks (CNNs) in the automatic segmentation of infarct volume in follow-up CT images in a large population of patients with acute ischemic stroke. Materials and methods: We included CT images of 1026 patients from a large pooling of patients with acute ischemic stroke. A reference standard for the infarct segmentation was generated by manual delineation. We introduce three CNN models for the segmentation of subtle, intermediate, and severe hypodense lesions. The fully automated infarct segmentation was defined as the combination of the results of these three CNNs. The results of the three-CNNs approach were compared with the results from a single CNN approach and with the reference standard segmentations. Results: The median infarct volume was 48 mL (IQR 15–125 mL). Comparison between the volumes of the three-CNNs approach and manually delineated infarct volumes showed excellent agreement, with an intraclass correlation coefficient (ICC) of 0.88. Even better agreement was found for severe and intermediate hypodense infarcts, with ICCs of 0.98 and 0.93, respectively. Although the number of patients used for training in the single CNN approach was much larger, the accuracy of the three-CNNs approach strongly outperformed the single CNN approach, which had an ICC of 0.34. Conclusion: Convolutional neural networks are valuable and accurate in the quantitative assessment of infarct volumes, for both subtle and severe hypodense infarcts in follow-up CT images. Our proposed three-CNNs approach strongly outperforms a more straightforward single CNN approach