Comparison of Analytical Methods Of Serum Untargeted Metabolomics

Funding Information: IV. ACKNOWLEDGEMENTS This research was funded by Fundação para a Ciência e a Tecnologia (FCT), grant DSAIPA/DS/0117/2020 and RNEM-LISBOA-01-0145-FEDER-022125 (Portuguese Mass Spectrometry Network). Centro de Química Estrutural is a Research Unit funded by FCT through projects UIDB/00100/2020 and UIDP/00100/2020. Institute of Molecular Sciences is an Associate Laboratory funded by FCT through project LA/P/0056/2020. Publisher Copyright: © 2023 IEEE.Metabolomics has emerged as a powerful tool in the discovery of new biomarkers for medical diagnosis and prognosis. However, there are numerous challenges, such as the methods used to characterize the system metabolome. In the present work, the comparison of two analytical platforms to acquire the serum metabolome of critically ill patients was conducted. The untargeted serum metabolome analysis by ultraperformance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) enabled to identify a set of metabolites statistically different between deceased and discharged patients. This set of metabolites also enabled to develop a very good predictive model, based on linear discriminant analysis (LDA) with a sensitivity and specificity of 80% and 100%, respectively. Fourier Transform Infrared (FTIR) spectroscopy was also applied in a high-throughput, simple and rapid mode to analyze the serum metabolome. Despite this technique not enabling the identification of metabolites, it allowed to identify molecular fingerprints associated to each patient group, while leading to a good predictive model, based on principal component analysis-LDA, with a sensitivity and specificity of 100% and 90%, respectively. Therefore, both analytical techniques presented complementary characteristics, that should be further explored for metabolome characterization and application as for biomarkers discovery for medical diagnosis and prognosis.publishersversionpublishe

Infection Biomarkers Based on Metabolomics

Funding Information: Funding: This work was supported by the project grant DSAIPA/DS/0117/2020 supported by Fundação para a Ciência e a Tecnologia, Portugal; and by the project grant NeproMD/ISEL/2020 financed by Instituto Politécnico de Lisboa.Current infection biomarkers are highly limited since they have low capability to predict infection in the presence of confounding processes such as in non-infectious inflammatory processes, low capability to predict disease outcomes and have limited applications to guide and evaluate therapeutic regimes. Therefore, it is critical to discover and develop new and effective clinical infection biomarkers, especially applicable in patients at risk of developing severe illness and critically ill patients. Ideal biomarkers would effectively help physicians with better patient management, leading to a decrease of severe outcomes, personalize therapies, minimize antibiotics overuse and hospitalization time, and significantly improve patient survival. Metabolomics, by providing a direct insight into the functional metabolic outcome of an organism, presents a highly appealing strategy to discover these biomarkers. The present work reviews the desired main characteristics of infection biomarkers, the main metabolomics strategies to discover these biomarkers and the next steps for developing the area towards effective clinical biomarkers.publishersversionpublishe

The Impact of the Serum Extraction Protocol on Metabolomic Profiling Using UPLC-MS/MS and FTIR Spectroscopy

Funding Information: This research was funded by Fundação para a Ciência e a Tecnologia (FCT), Grants DSAIPA/DS/0117/2020 and RNEM-LISBOA-01-0145-FEDER-022125 (Portuguese Mass Spectrometry Network). The Centro de Química Estrutural is a Research Unit funded by FCT through projects UIDB/00100/2020 and UIDP/00100/2020. The Institute of Molecular Sciences is an Associate Laboratory funded by FCT through project LA/P/0056/2020. Publisher Copyright: © 2023 The Authors. Published by American Chemical Society.Biofluid metabolomics is a very appealing tool to increase the knowledge associated with pathophysiological mechanisms leading to better and new therapies and biomarkers for disease diagnosis and prognosis. However, due to the complex process of metabolome analysis, including the metabolome isolation method and the platform used to analyze it, there are diverse factors that affect metabolomics output. In the present work, the impact of two protocols to extract the serum metabolome, one using methanol and another using a mixture of methanol, acetonitrile, and water, was evaluated. The metabolome was analyzed by ultraperformance liquid chromatography associated with tandem mass spectrometry (UPLC-MS/MS), based on reverse-phase and hydrophobic chromatographic separations, and Fourier transform infrared (FTIR) spectroscopy. The two extraction protocols of the metabolome were compared over the analytical platforms (UPLC-MS/MS and FTIR spectroscopy) concerning the number of features, the type of features, common features, and the reproducibility of extraction replicas and analytical replicas. The ability of the extraction protocols to predict the survivability of critically ill patients hospitalized at an intensive care unit was also evaluated. The FTIR spectroscopy platform was compared to the UPLC-MS/MS platform and, despite not identifying metabolites and consequently not contributing as much as UPLC-MS/MS in terms of information concerning metabolic information, it enabled the comparison of the two extraction protocols as well as the development of very good predictive models of patient’s survivability, such as the UPLC-MS/MS platform. Furthermore, FTIR spectroscopy is based on much simpler procedures and is rapid, economic, and applicable in the high-throughput mode, i.e., enabling the simultaneous analysis of hundreds of samples in the microliter range in a couple of hours. Therefore, FTIR spectroscopy represents a very interesting complementary technique not only to optimize processes as the metabolome isolation but also for obtaining biomarkers such as those for disease prognosis.publishersversionpublishe

Evaluating the impact of culture conditions on human mesenchymal stem/stromal cell-derived exosomes through FTIR spectroscopy

In the last decade, the therapeutic effects of mesenchymal stem/stromal cells (MSCs) have been attributed to a paracrine activity exerted by extracellular vesicles secreted by MSCs, as exosomes. Their properties as intercellular communication vehicles have led to an increase interest in their use for cell-free therapeutic applications. The present work aimed to evaluate how different culture conditions, as culture medium (xenogeneic -free (XF) vs serum-containing medium), conditioning time (1, 2 and 3 days) and different MSC donors (n=6), affect the chemical characteristics of exosomes. For that, purified MSC-derived exosomes were characterized by Fourier-Transform InfraRed (FTIR) spectroscopy, a highly sensitive, fast and high throughput technique. The principal component analysis (PCA) of pre-processed FTIR spectra of purified exosomes was conducted, enabling the evaluation of the replica variance of the exosomes chemical fingerprint in a reduced dimensionality space. For that, different pre-processing methods were studied as baseline correction, standard normal variation and first and second derivative. It was observed that the chemical fingerprint of exosomes is more dependent of the medium used for MSCs cultivation than the MSC donor and conditioning days. Exosomes secreted by MSCs cultured with serum-containing medium presented a more homogenous chemical fingerprint than exosomes obtained with XF medium. Moreover, for a given medium (XF or serum-containing medium), the exosomes chemical fingerprint depends more of the MSC donor than of the conditioning days. The regression vector of the PCA enabled to identified relevant spectral bands that enabled the separation of samples in the score-plot of the previous analysis. Ratios between these spectral bands were determined, since these attenuate artifacts due to cell quantity and baseline distortions underneath each band. Statistically inference analysis of the ratios of spectral bands were conducted, by comparing the equality of the means of the populations using appropriate hypothesis tests and considering the significance level of 5%. It was possible to define ratios of spectral bands, that can be used as biomarkers, enabling the discrimination of exosomes chemical fingerprint in function of the medium used for MSC grown and the MSC donor. This work is therefore a step forward into understanding how different culture conditions and MSC donors affect MSC exosomes characteristics

Alternative Serum Biomarkers of Bacteraemia for Intensive Care Unit Patients

Funding Information: This work was supported by the project grant DSAIPA/DS/0117/2020 supported by Fundação para a Ciência e a Tecnologia, Portugal and by the project grant NeproMD/ISEL/2020 financed by Instituto Politécnico de Lisboa. Publisher Copyright: © 2023 IEEE.The diagnosis of infections in hospital or clinical settings usually involves a series of time-consuming steps, including biological sample collection, culture growth of the organism isolation and subsequent characterization. For this, there are diverse infection biomarkers based on blood analysis, however, these are of limited use in patients presenting confound processes as inflammatory process as occurring at intensive care units. In this preliminary study, the application of serum analysis by FTIR spectroscopy, to predict bacteraemia in 102 critically ill patients in an ICU was evaluated. It was analysed the effect of spectra pre-processing methods and spectral sub-regions on t-distributed stochastic neighbour embedding. By optimizing Support Vector Machine (SVM) models, based on normalised second derivative spectra of a smaller subregion, it was possible to achieve a good bacteraemia predictive model with a sensitivity and specificity of 76%. Since FTIR spectra of serum is acquired in a simple, economic and rapid mode, the technique presents the potential to be a cost-effective methodology of bacteraemia identification, with special relevance in critically ill patients, where a rapid infection diagnostic will allow to avoid the unnecessary use of antibiotics, which ultimately will ease the load on already fragile patients' metabolism.publishersversionpublishe

Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection

Funding: This research was funded by project grant DSAIPA/DS/0117/2020 supported by Fundação para a Ciência e a Tecnologia, Portugal, and by the project grant NeproMD/ISEL/2020 financed by Instituto Politécnico de Lisboa. The present work was conducted in the Engineering & Health Laboratory, that resulted from a collaboration protocol established between Universidade Católica Portuguesa and Instituto Politécnico de Lisboa.Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine vol-ume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic dam-age and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Prote-omics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manu-script reviews biofluids proteomics toward biomarkers discovery that specifically identify subclin-ical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.publishersversionpublishe