HERMES: a molecular-formula-oriented method to target the metabolome.

Comprehensive metabolome analyses are essential for biomedical, environmental, and biotechnological research. However, current MS1- and MS2-based acquisition and data analysis strategies in untargeted metabolomics result in low identification rates of metabolites. Here we present HERMES, a molecular-formula-oriented and peak-detection-free method that uses raw LC/MS1 information to optimize MS2 acquisition. Investigating environmental water, Escherichia coli, and human plasma extracts with HERMES, we achieved an increased biological specificity of MS2 scans, leading to improved mass spectral similarity scoring and identification rates when compared with a state-of-the-art data-dependent acquisition (DDA) approach. Thus, HERMES improves sensitivity, selectivity, and annotation of metabolites. HERMES is available as an R package with a user-friendly graphical interface for data analysis and visualization.

Temporary immobilization methods for closed low-energy ankle fracture-dislocations: comparative analysis of a retrospective cohort.

PURPOSE: Ankle fracture-dislocations (AFD) often necessitate staged management involving temporary external fixation (EF) due to mechanical instability or blistering. However, limited literature exists on the optimal temporary immobilization method for low-energy closed AFD. This study compared baseline patient and fracture characteristics, along with clinical and radiological outcomes between AFD initially immobilized with EF versus splinting. METHODS: A retrospective cohort study was conducted involving patients with AFD temporarily immobilized using EF or splinting, followed by definitive open reduction and internal fixation. Quality of reduction (QOR) was assessed for each patient post-initial immobilization and after the definitive surgery. RESULTS: The study encompassed 194 patients: 138 treated with a splint (71.1%) and 56 (28.9%) with EF. Secondary loss of reduction had occurred in three patients who were splinted (2.2%). The mean ages in the EF and splint groups were 63.2 and 56.1 years, respectively (p = 0.01). Posterior malleolus fracture (PMF) and blisters were more prevalent in EF patients (69.6% vs. 43.5% for PMF and 76.8% vs. 20.3% for blisters, respectively; p = 0.05 and p < 0.01). Postoperative complication rates were 8.9% for EF versus 10.9% for splinting (p = 0.69). Satisfactory final QOR was attained in 79.8% of patients treated with a splint versus 64.3% with EF (p = 0.02). CONCLUSION: Patients immobilized by EF presented with poorer baseline characteristics and had more unstable injuries. Nevertheless, postoperative complication rates were comparable. Thus, EF appears to be a valuable tool for standardizing outcomes in AFD patients with a less favorable prognosis.

Multiligament knee injuries. Ten years' experience at a public university, level I Trauma Center.

PURPOSE: To describe our institutional experience and results in the surgical management of multiligament knee injuries (MLKI). MATERIALS AND METHODS: Retrospective series of MLKI consecutively operated on at a single, level I Trauma Center. Data on patients' baseline characteristics, injuries, treatments, and outcomes were recorded up to one-year follow-up. Recorded outcomes included the Tegner-Lysholm Knee Scoring Scale (TLKSS), return to work, and patient satisfaction. RESULTS: MLKI incidence was 0.03% among 9897 orthopedic trauma admissions. Twenty-four patients of mean age 43.6 years were included in analysis. The mean Injury Severity Score was 12.6. Five patients presented with knee dislocations and six had fracture-dislocations, two of them open fractures. There was one popliteal artery injury requiring a bypass and four common peroneal nerve palsies. Staged ligamental reconstruction was performed in all cases. There were seven postoperative complications. The median TLKSS was 80 and, though patient satisfaction was high, and dissatisfaction was largely restricted to recreational activities (only 58.3% satisfied). Seventeen patients returned to their previous employment. CONCLUSIONS: We found a high aggregation of fracture-dislocations secondary to road traffic accidents. One in four patients experienced complications, particularly stiffness. Complications were more common in cases involving knee dislocation. Most patients had good functional results, but 25% were unable to return to their previous work, which demonstrates the long-lasting sequelae of this injury.

Allografts and lateral extra-articular tenodesis for revision anterior cruciate ligament reconstruction: enhanced rotational stability and improved functional outcomes.

PURPOSE: Multiple studies have shown higher failure rate and patient-reported outcomes to be significantly worse following revision anterior cruciate ligament reconstructive (ACLR) surgery, especially using allografts. One of the reasons being rotational instability. Because of this, augmentation with lateral extra-articular tenodesis (LET) is often considered. Good short-term results in regards to functional and perceived scores and low complication rate can be expected in revision ACLR using allografts in combination with LET. METHODS: Between 2014 and 2021, 46 patients were registered for revision ACLR using allografts and extra-articular augmentation (modified Lemaire) and included in this prospective study. Patients' demographic and clinical data were collected preoperatively, postoperatively, and during the follow-up period of 12 months. RESULTS: Patient-reported functional outcomes were statistically significant for IKDC, Lysholm, and SF-12 physical scale (p < 0.05). Tegner score showed a decreased number of patients who were able to return to sport at their previous level (p = 0.001). Stability examination tests (Lachman and pivot-shift) showed significant improvements. Concomitant lesions were present in 76.1% of patients. Ten patients (21.7%) presented major complications, including six cases of anteroposterior instability, three cases of knee pain and one graft re-rupture. CONCLUSION: Revision procedures are inherently challenging with a high number of associated chondral and meniscus lesions. However, good short-term functional outcomes and enhanced rotational stability with an acceptable complication rate can be expected in most cases where revision ACLR using allografts is augmented with LET. STUDY DESIGN: Prospective; Case series; Level of evidence IV.

Good rates of return-to-sport in athletes after revision anterior cruciate ligament reconstruction using autologous patellar tendon and lateral extra-articular tenodesis: a 2-year follow-up prospective study.

BACKGROUND: Most athletes who undergo revision of the anterior cruciate ligament reconstruction (ACLR) aim to return to their preinjury sport at a similar level of performance while minimizing the risk for reinjury. Additional lateral extra-articular tenodesis (LET) has recently been correlated with improved outcomes and low complication rate. Yet, there are few series evaluating return-to-sport (RTS) and clinical outcomes after revision ACLR using bone-patellar tendon-bone (BPTB) and LET in athletes. METHODS: The study cohort consisted of 19 eligible athletes who had undergone their first revision ACLR using BPTB and LET (modified Lemaire) between January 2019 and 2020. Patients were prospectively followed and interviewed in a sports activity survey during a 2-year follow-up. RESULTS: Despite all patients returning to sports after revision ACLR surgery, 52.6% resumed playing at their preinjury level. Furthermore, patient-reported functional outcomes improved significantly following revision surgery, as evidenced by improvements in IKDC [64.4 (± 12) to 87.8 (± 6)], Lysholm [71.27 (± 12) to 84.2 (± 9.7)], and SF-12 scales [Physical: 53.3 (± 3) 57 (± 1.2); Mental: 50.2 (± 3.3) to 52.7 (± 2.4)]. One case (5.3%) experienced persistent pain and underwent reoperation for a partial meniscectomy. CONCLUSION: After revision ACLR using autologous BPTB and LET, all active individuals are expected to RTS, similar to primary ACLR. The difference comes down to returning to the preinjury level, where the levels are lower depending on the sport and initial level of play. Good mid-term functional outcomes with a low complication rate can be expected in most cases. STUDY DESIGN: Case series; Level of evidence IV. ETHICAL COMMITTEE APPROVAL NUMBER: PR(ATR)79/2021 and HCB/2023/0173.

Muscular carnosine is a marker for cardiorespiratory fitness and cardiometabolic risk factors in men with type 1 diabetes.

PURPOSE: Muscle is an essential organ for glucose metabolism and can be influenced by metabolic disorders and physical activity. Elevated muscle carnosine levels have been associated with insulin resistance and cardiometabolic risk factors. Little is known about muscle carnosine in type 1 diabetes (T1D) and how it is influenced by physical activity. The aim of this study was to characterize muscle carnosine in vivo by proton magnetic resonance spectroscopy (1H MRS) and evaluate the relationship with physical activity, clinical characteristics and lipoprotein subfractions. METHODS: 16 men with T1D (10 athletes/6 sedentary) and 14 controls without diabetes (9/5) were included. Body composition by DXA, cardiorespiratory capacity (VO2peak) and serum lipoprotein profile by proton nuclear magnetic resonance (1H NMR) were obtained. Muscle carnosine scaled to water (carnosineW) and to creatine (carnosineCR), creatine and intramyocellular lipids (IMCL) were quantified in vivo using 1H MRS in a 3T MR scanner in soleus muscle. RESULTS: Subjects with T1D presented higher carnosine CR levels compared to controls. T1D patients with a lower VO2peak presented higher carnosineCR levels compared to sedentary controls, but both T1D and control groups presented similar levels of carnosineCR at high VO2peak levels. CarnosineW followed the same trend. Integrated correlation networks in T1D demonstrated that carnosineW and carnosineCR were associated with cardiometabolic risk factors including total and abdominal fat, pro-atherogenic lipoproteins (very low-density lipoprotein subfractions), low VO2peak, and IMCL. CONCLUSIONS: Elevated muscle carnosine levels in persons with T1D and their effect on atherogenic lipoproteins can be modulated by physical activity.

Untargeted lipidomics uncovers lipid signatures that distinguish severe from moderate forms of acutely decompensated cirrhosis.

BACKGROUND & AIMS: Acute decompensation (AD) of cirrhosis is a heterogeneous clinical entity associated with moderate mortality. In some patients, this condition develops quickly into the more deadly acute-on-chronic liver failure (ACLF), in which other organs such as the kidneys or brain fail. The aim of this study was to characterize the blood lipidome in a large series of patients with cirrhosis and identify specific signatures associated with AD and ACLF development. METHODS: Serum untargeted lipidomics was performed in 561 patients with AD (518 without and 43 with ACLF) (discovery cohort) and in 265 patients with AD (128 without and 137 with ACLF) in whom serum samples were available to perform repeated measurements during the 28-day follow-up (validation cohort). Analyses were also performed in 78 patients with AD included in a therapeutic albumin trial (43 patients with compensated cirrhosis and 29 healthy individuals). RESULTS: The circulating lipid landscape associated with cirrhosis was characterized by a generalized suppression, which was more manifest during AD and in non-surviving patients. By computing discriminating accuracy and the variable importance projection score for each of the 223 annotated lipids, we identified a sphingomyelin fingerprint specific for AD of cirrhosis and a distinct cholesteryl ester and lysophosphatidylcholine fingerprint for ACLF. Liver dysfunction and infections were the principal net contributors to these fingerprints, which were dynamic and interchangeable between patients with AD whose condition worsened to ACLF and those who improved. Notably, blood lysophosphatidylcholine levels increased in these patients after albumin therapy. CONCLUSIONS: Our findings provide insights into the lipid landscape associated with decompensation of cirrhosis and ACLF progression and identify unique non-invasive diagnostic biomarkers of advanced cirrhosis. LAY SUMMARY: Analysis of lipids in blood from patients with advanced cirrhosis reveals a general suppression of their levels in the circulation of these patients. A specific group of lipids known as sphingomyelins are useful to distinguish between patients with compensated and decompensated cirrhosis. Another group of lipids designated cholesteryl esters further distinguishes patients with decompensated cirrhosis who are at risk of developing organ failures.

Exploring the Use of Gas Chromatography Coupled to Chemical Ionization Mass Spectrometry (GC-CI-MS) for Stable Isotope Labeling in Metabolomics.

Isotopic-labeling experiments have been valuable to monitor the flux of metabolic reactions in biological systems, which is crucial to understand homeostatic alterations with disease. Experimental determination of metabolic fluxes can be inferred from a characteristic rearrangement of stable isotope tracers (e.g., 13C or 15N) that can be detected by mass spectrometry (MS). Metabolites measured are generally members of well-known metabolic pathways, and most of them can be detected using both gas chromatography (GC)-MS and liquid chromatography (LC)-MS. In here, we show that GC methods coupled to chemical ionization (CI) MS have a clear advantage over alternative methodologies due to GC's superior chromatography separation efficiency and the fact that CI is a soft ionization technique that yields identifiable protonated molecular ion peaks. We tested diverse GC-CI-MS setups, including methane and isobutane reagent gases, triple quadrupole (QqQ) MS in SIM mode, or selected ion clusters using optimized narrow windows (∼10 Da) in scan mode, and standard full scan methods using high resolution GC-(q)TOF and GC-Orbitrap systems. Isobutane as a reagent gas in combination with both low-resolution (LR) and high-resolution (HR) MS showed the best performance, enabling precise detection of isotopologues in most metabolic intermediates of central carbon metabolism. Finally, with the aim of overcoming manual operations, we developed an R-based tool called isoSCAN that automatically quantifies all isotopologues of intermediate metabolites of glycolysis, TCA cycle, amino acids, pentose phosphate pathway, and urea cycle, from LRMS and HRMS data.

Integrated Probabilistic Annotation: A Bayesian-Based Annotation Method for Metabolomic Profiles Integrating Biochemical Connections, Isotope Patterns, and Adduct Relationships.

In a typical untargeted metabolomics experiment, the huge amount of complex data generated by mass spectrometry necessitates automated tools for the extraction of useful biological information. Each metabolite generates numerous mass spectrometry features. The association of these experimental features to the underlying metabolites still represents one of the major bottlenecks in metabolomics data processing. While certain identification (e.g., by comparison to authentic standards) is always desirable, it is usually achievable only for a limited number of compounds, and scientists often deal with a significant amount of putatively annotated metabolites. The confidence in a specific annotation is usually assessed by considering different sources of information (e.g., isotope patterns, adduct formation, chromatographic retention times, and fragmentation patterns). IPA (integrated probabilistic annotation) offers a rigorous and reproducible method to automatically annotate metabolite profiles and evaluate the resulting confidence of the putative annotations. It is able to provide a rigorous measure of our confidence in any putative annotation and is also able to update and refine our beliefs (i.e., background prior knowledge) by incorporating different sources of information in the annotation process, such as isotope patterns, adduct formation and biochemical relations. The IPA package is freely available on GitHub ( https://github.com/francescodc87/IPA ), together with the related extensive documentation.

FELLA: an R package to enrich metabolomics data.

BACKGROUND: Pathway enrichment techniques are useful for understanding experimental metabolomics data. Their purpose is to give context to the affected metabolites in terms of the prior knowledge contained in metabolic pathways. However, the interpretation of a prioritized pathway list is still challenging, as pathways show overlap and cross talk effects. RESULTS: We introduce FELLA, an R package to perform a network-based enrichment of a list of affected metabolites. FELLA builds a hierarchical representation of an organism biochemistry from the Kyoto Encyclopedia of Genes and Genomes (KEGG), containing pathways, modules, enzymes, reactions and metabolites. In addition to providing a list of pathways, FELLA reports intermediate entities (modules, enzymes, reactions) that link the input metabolites to them. This sheds light on pathway cross talk and potential enzymes or metabolites as targets for the condition under study. FELLA has been applied to six public datasets -three from Homo sapiens, two from Danio rerio and one from Mus musculus- and has reproduced findings from the original studies and from independent literature. CONCLUSIONS: The R package FELLA offers an innovative enrichment concept starting from a list of metabolites, based on a knowledge graph representation of the KEGG database that focuses on interpretability. Besides reporting a list of pathways, FELLA suggests intermediate entities that are of interest per se. Its usefulness has been shown at several molecular levels on six public datasets, including human and animal models. The user can run the enrichment analysis through a simple interactive graphical interface or programmatically. FELLA is publicly available in Bioconductor under the GPL-3 license.

Glucose metabolism during fasting is altered in experimental porphobilinogen deaminase deficiency.

Porphobilinogen deaminase (PBGD) haploinsufficiency (acute intermittent porphyria, AIP) is characterized by neurovisceral attacks when hepatic heme synthesis is activated by endogenous or environmental factors including fasting. While the molecular mechanisms underlying the nutritional regulation of hepatic heme synthesis have been described, glucose homeostasis during fasting is poorly understood in porphyria. Our study aimed to analyse glucose homeostasis and hepatic carbohydrate metabolism during fasting in PBGD-deficient mice. To determine the contribution of hepatic PBGD deficiency to carbohydrate metabolism, AIP mice injected with a PBGD-liver gene delivery vector were included. After a 14 h fasting period, serum and liver metabolomics analyses showed that wild-type mice stimulated hepatic glycogen degradation to maintain glucose homeostasis while AIP livers activated gluconeogenesis and ketogenesis due to their inability to use stored glycogen. The serum of fasted AIP mice showed increased concentrations of insulin and reduced glucagon levels. Specific over-expression of the PBGD protein in the liver tended to normalize circulating insulin and glucagon levels, stimulated hepatic glycogen catabolism and blocked ketone body production. Reduced glucose uptake was observed in the primary somatosensorial brain cortex of fasted AIP mice, which could be reversed by PBGD-liver gene delivery. In conclusion, AIP mice showed a different response to fasting as measured by altered carbohydrate metabolism in the liver and modified glucose consumption in the brain cortex. Glucose homeostasis in fasted AIP mice was efficiently normalized after restoration of PBGD gene expression in the liver.

LipSpin: A New Bioinformatics Tool for Quantitative 1H NMR Lipid Profiling.

The structural similarity among lipid species and the low sensitivity and spectral resolution of nuclear magnetic resonance (NMR) have traditionally hampered the routine use of 1H NMR lipid profiling of complex biological samples in metabolomics, which remains mostly manual and lacks freely available bioinformatics tools. However, 1H NMR lipid profiling provides fast quantitative screening of major lipid classes (fatty acids, glycerolipids, phospholipids, and sterols) and some individual species and has been used in several clinical and nutritional studies, leading to improved risk prediction models. In this Article, we present LipSpin, a free and open-source bioinformatics tool for quantitative 1H NMR lipid profiling. LipSpin implements a constrained line shape fitting algorithm based on voigt profiles and spectral templates from spectra of lipid standards, which automates the analysis of severely overlapped spectral regions and lipid signals with complex coupling patterns. LipSpin provides the most detailed quantification of fatty acid families and choline phospholipids in serum lipid samples by 1H NMR to date. Moreover, analytical and clinical results using LipSpin quantifications conform with other techniques commonly used for lipid analysis.

Positional Enrichment by Proton Analysis (PEPA): A One-Dimensional 1 H-NMR Approach for 13 C Stable Isotope Tracer Studies in Metabolomics.

A novel metabolomics approach for NMR-based stable isotope tracer studies called PEPA is presented, and its performance validated using human cancer cells. PEPA detects the position of carbon label in isotopically enriched metabolites and quantifies fractional enrichment by indirect determination of 13 C-satellite peaks using 1D-1 H-NMR spectra. In comparison with 13 C-NMR, TOCSY and HSQC, PEPA improves sensitivity, accelerates the elucidation of 13 C positions in labeled metabolites and the quantification of the percentage of stable isotope enrichment. Altogether, PEPA provides a novel framework for extending the high-throughput of 1 H-NMR metabolic profiling to stable isotope tracing in metabolomics, facilitating and complementing the information derived from 2D-NMR experiments and expanding the range of isotopically enriched metabolites detected in cellular extracts.

geoRge: A Computational Tool To Detect the Presence of Stable Isotope Labeling in LC/MS-Based Untargeted Metabolomics.

Studying the flow of chemical moieties through the complex set of metabolic reactions that happen in the cell is essential to understanding the alterations in homeostasis that occur in disease. Recently, LC/MS-based untargeted metabolomics and isotopically labeled metabolites have been used to facilitate the unbiased mapping of labeled moieties through metabolic pathways. However, due to the complexity of the resulting experimental data sets few computational tools are available for data analysis. Here we introduce geoRge, a novel computational approach capable of analyzing untargeted LC/MS data from stable isotope-labeling experiments. geoRge is written in the open language R and runs on the output structure of the XCMS package, which is in widespread use. As opposed to the few existing tools, which use labeled samples to track stable isotopes by iterating over all MS signals using the theoretical mass difference between the light and heavy isotopes, geoRge uses unlabeled and labeled biologically equivalent samples to compare isotopic distributions in the mass spectra. Isotopically enriched compounds change their isotopic distribution as compared to unlabeled compounds. This is directly reflected in a number of new m/z peaks and higher intensity peaks in the mass spectra of labeled samples relative to the unlabeled equivalents. The automated untargeted isotope annotation and relative quantification capabilities of geoRge are demonstrated by the analysis of LC/MS data from a human retinal pigment epithelium cell line (ARPE-19) grown on normal and high glucose concentrations mimicking diabetic retinopathy conditions in vitro. In addition, we compared the results of geoRge with the outcome of X(13)CMS, since both approaches rely entirely on XCMS parameters for feature selection, namely m/z and retention time values. To ensure data traceability and reproducibility, and enabling for comparison with other existing and future approaches, raw LC/MS files have been deposited in MetaboLights (MTBLS213) and geoRge is available as an R script at https://github.com/jcapelladesto/geoRge.

eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics.

Gas chromatography coupled to mass spectrometry (GC/MS) has been a long-standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex data sets characterized by coeluting compounds and extensive fragmentation of molecular ions caused by the hard electron ionization. In order to identify and extract quantitative information on metabolites across multiple biological samples, integrated computational workflows for data processing are needed. Here we introduce eRah, a free computational tool written in the open language R composed of five core functions: (i) noise filtering and baseline removal of GC/MS chromatograms, (ii) an innovative compound deconvolution process using multivariate analysis techniques based on compound match by local covariance (CMLC) and orthogonal signal deconvolution (OSD), (iii) alignment of mass spectra across samples, (iv) missing compound recovery, and (v) identification of metabolites by spectral library matching using publicly available mass spectra. eRah outputs a table with compound names, matching scores and the integrated area of compounds for each sample. The automated capabilities of eRah are demonstrated by the analysis of GC-time-of-flight (TOF) MS data from plasma samples of adolescents with hyperinsulinaemic androgen excess and healthy controls. The quantitative results of eRah are compared to centWave, the peak-picking algorithm implemented in the widely used XCMS package, MetAlign, and ChromaTOF software. Significantly dysregulated metabolites are further validated using pure standards and targeted analysis by GC-triple quadrupole (QqQ) MS, LC-QqQ, and NMR. eRah is freely available at http://CRAN.R-project.org/package=erah .

Urine metabolome profiling of immune-mediated inflammatory diseases.

BACKGROUND: Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn's disease, and ulcerative colitis. METHODS: Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls. RESULTS: In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (P FDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (P FDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an over-representation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways. CONCLUSIONS: This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs.

SYNBIOCHEM-a SynBio foundry for the biosynthesis and sustainable production of fine and speciality chemicals.

The Manchester Synthetic Biology Research Centre (SYNBIOCHEM) is a foundry for the biosynthesis and sustainable production of fine and speciality chemicals. The Centre's integrated technology platforms provide a unique capability to facilitate predictable engineering of microbial bio-factories for chemicals production. An overview of these capabilities is described.

Liposcale: a novel advanced lipoprotein test based on 2D diffusion-ordered 1H NMR spectroscopy.

Determination of lipoprotein particle size and number using advanced lipoprotein tests (ALTs) is of particular importance to improve cardiovascular risk prediction. Here we present the Liposcale test, a novel ALT based on 2D diffusion-ordered (1)H NMR spectroscopy. Our method uses diffusion coefficients to provide a direct measure of the mean particle sizes and numbers. Using 177 plasma samples from healthy individuals and the concentration of ApoB and ApoA from isolated lipoprotein fractions, our test showed a stronger correlation between the NMR-derived lipoprotein particle numbers and apolipoprotein concentrations than the LipoProfile(®) test commercialized by Liposcience. We also converted LDL particle numbers to ApoB equivalents (milligrams per deciliter) and our test yielded similar values of LDL-ApoB to the LipoProfile(®) test (absolute mean bias of 8.5 and 7.4 mg/dl, respectively). In addition, our HDL particle number values were more concordant with the calibrated values determined recently using ion mobility. Finally, principal component analysis distinguished type 2 diabetic patients with and without atherogenic dyslipidemia (AD) on a second cohort of 307 subjects characterized using the Liposcale test (area under the curve = 0.88) and showed concordant relationships between variables explaining AD. Altogether, our method provides reproducible and reliable characterization of lipoprotein particles and it is applicable to pathological states such as AD.

Integrative analysis reveals novel pathways mediating the interaction between adipose tissue and pancreatic islets in obesity in rats.

AIMS/HYPOTHESIS: Comprehensive characterisation of the interrelation between the peripancreatic adipose tissue and the pancreatic islets promises novel insights into the mechanisms that regulate beta cell adaptation to obesity. Here, we sought to determine the main pathways and key molecules mediating the crosstalk between these two tissues during adaptation to obesity by the way of an integrated inter-tissue, multi-platform analysis. METHODS: Wistar rats were fed a standard or cafeteria diet for 30 days. Transcriptomic variations by diet in islets and peripancreatic adipose tissue were examined through microarray analysis. The secretome from peripancreatic adipose tissue was subjected to a non-targeted metabolomic and proteomic analysis. Gene expression variations in islets were integrated with changes in peripancreatic adipose tissue gene expression and protein and metabolite secretion using an integrated inter-tissue pathway and network analysis. RESULTS: The highest level of data integration, linking genes differentially expressed in both tissues with secretome variations, allowed the identification of significantly enriched canonical pathways, such as the activation of liver/retinoid X receptors, triacylglycerol degradation, and regulation of inflammatory and immune responses, and underscored interaction network hubs, such as cholesterol and the fatty acid binding protein 4, which were unpredicted through single-tissue analysis and have not been previously implicated in the peripancreatic adipose tissue crosstalk with beta cells. CONCLUSIONS/INTERPRETATION: The integrated analysis reported here allowed the identification of novel mechanisms and key molecules involved in peripancreatic adipose tissue interrelation with beta cells during the development of obesity; this might help the development of novel strategies to prevent type 2 diabetes.

Focus: a robust workflow for one-dimensional NMR spectral analysis.

One-dimensional (1)H NMR represents one of the most commonly used analytical techniques in metabolomic studies. The increase in the number of samples analyzed as well as the technical improvements involving instrumentation and spectral acquisition demand increasingly accurate and efficient high-throughput data processing workflows. We present FOCUS, an integrated and innovative methodology that provides a complete data analysis workflow for one-dimensional NMR-based metabolomics. This tool will allow users to easily obtain a NMR peak feature matrix ready for chemometric analysis as well as metabolite identification scores for each peak that greatly simplify the biological interpretation of the results. The algorithm development has been focused on solving the critical difficulties that appear at each data processing step and that can dramatically affect the quality of the results. As well as method integration, simplicity has been one of the main objectives in FOCUS development, requiring very little user input to perform accurate peak alignment, peak picking, and metabolite identification. The new spectral alignment algorithm, RUNAS, allows peak alignment with no need of a reference spectrum, and therefore, it reduces the bias introduced by other alignment approaches. Spectral alignment has been tested against previous methodologies obtaining substantial improvements in the case of moderate or highly unaligned spectra. Metabolite identification has also been significantly improved, using the positional and correlation peak patterns in contrast to a reference metabolite panel. Furthermore, the complete workflow has been tested using NMR data sets from 60 human urine samples and 120 aqueous liver extracts, reaching a successful identification of 42 metabolites from the two data sets. The open-source software implementation of this methodology is available at http://www.urr.cat/FOCUS.