Serum Metabolic Alterations upon Zika Infection

Infection by zika virus increase angiotensin I-converting enzyme activity in mouse brain

Congenital zika virus syndrome (CZS) has become a significant worldwide concern since the sudden rise of microcephaly related to zika virus (ZIKV) in Brazil. Primarily transmitted by Aedes mosquitoes, ZIKV shares serologic similarities with dengue virus (DENV), complicating the diagnosis and/or clinical management. The Angiotensin I-Converting Enzyme (ACE) was associated with either neuroprotective or anti-inflammatory properties in the central nervous system (CNS). The possible role(s) of ACE in these two flaviviruses infection remain largely unexplored. In this study, we evaluate ACE activity in the brain of ZIKV- or DENV-infected mice, both compared to MOCK, showing about 30 % increased ACE activity only in ZIKV-infected mice (p = 0.024), while no change was noticed in brain from DENV-infected animals (p = 0.888). In addition, the treatment with interferon beta (IFNβ), under conditions previously demonstrated to rescue the normal size of microcephalic brains determined by ZIKV infection, also restored ACE activity in ZIKV-infected animals to levels close to that of the MOCK control group. Although inflammatory responses expected for either ZIKV or DENV infections, only ZIKV was associated with microcephaly, as well as with increased ACE activity and reversion by treatment with IFNβ. Furthermore, this increase in ACE activity was observed only after intracerebroventricular (ICV) injection (F (2, 16) = 7.907, p = 0.004), but not for intraperitoneal (IP) administration of ZIKV (F (2, 26) = 1.996, p = 0.156), suggesting that the observed central ACE activity modulation may be associated with the presence of this specific flavivirus in the brain.

Effects of Pera Orange Juice and Moro Orange Juice in Healthy Rats: A Metabolomic Approach

Cardiovascular disease is a leading cause of death worldwide. Heart failure is a cardiovascular disease with high prevalence, morbidity, and mortality. Several natural compounds have been studied for attenuating pathological cardiac remodeling. Orange juice has been associated with cardiovascular disease prevention by attenuating oxidative stress. However, most studies have evaluated isolated phytochemicals rather than whole orange juice and usually under pathological conditions. In this study, we evaluated plasma metabolomics in healthy rats receiving Pera or Moro orange juice to identify possible metabolic pathways and their effects on the heart.

METHODS

Sixty male Wistar rats were allocated into 3 groups: control (C), Pera orange juice (PO), and Moro orange juice (MO). PO and MO groups received Pera orange juice or Moro orange juice, respectively, and C received water with maltodextrin (100 g/L). Echocardiogram and euthanasia were performed after 4 weeks. Plasma metabolomic analysis was performed by high-resolution mass spectrometry. Type I collagen was evaluated in picrosirius red-stained slides and matrix metalloproteinase (MMP)-2 activity by zymography. MMP-9, tissue inhibitor of metalloproteinase (TIMP)-2, TIMP-4, type I collagen, and TNF-α protein expression were evaluated by Western blotting.

RESULTS

We differentially identified three metabolites in PO (N-docosahexaenoyl-phenylalanine, diglyceride, and phosphatidylethanolamine) and six in MO (N-formylmaleamic acid, N2-acetyl-L-ornithine, casegravol isovalerate, abscisic alcohol 11-glucoside, cyclic phosphatidic acid, and torvoside C), compared to controls, which are recognized for their possible roles in cardiac remodeling, such as extracellular matrix regulation, inflammation, oxidative stress, and membrane integrity. Cardiac function, collagen level, MMP-2 activity, and MMP-9, TIMP-2, TIMP-4, type I collagen, and TNF-α protein expression did not differ between groups.

CONCLUSION

Ingestion of Pera and Moro orange juice induces changes in plasma metabolites related to the regulation of extracellular matrix, inflammation, oxidative stress, and membrane integrity in healthy rats. Moro orange juice induces a larger number of differentially expressed metabolites than Pera orange juice. Alterations in plasma metabolomics induced by both orange juice are not associated with modifications in cardiac extracellular matrix components. Our results allow us to postulate that orange juice may have beneficial effects on pathological cardiac remodeling.

Integrated NMR and MS Analysis of the Plasma Metabolome Reveals Major Changes in One-Carbon, Lipid, and Amino Acid Metabolism in Severe and Fatal Cases of COVID-19

Brazil has the second-highest COVID-19 death rate worldwide, and Rio de Janeiro is among the states with the highest rate in the country. Although vaccine coverage has been achieved, it is anticipated that COVID-19 will transition into an endemic disease. It is concerning that the molecular mechanisms underlying clinical evolution from mild to severe disease, as well as the mechanisms leading to long COVID-19, are not yet fully understood. NMR and MS-based metabolomics were used to identify metabolites associated with COVID-19 pathophysiology and disease outcome. Severe COVID-19 cases (n = 35) were enrolled in two reference centers in Rio de Janeiro within 72 h of ICU admission, alongside 12 non-infected control subjects. COVID-19 patients were grouped into survivors (n = 18) and non-survivors (n = 17). Choline-related metabolites, serine, glycine, and betaine, were reduced in severe COVID-19, indicating dysregulation in methyl donors. Non-survivors had higher levels of creatine/creatinine, 4-hydroxyproline, gluconic acid, and N-acetylserine, indicating liver and kidney dysfunction. Several changes were greater in women; thus, patients' sex should be considered in pandemic surveillance to achieve better disease stratification and improve outcomes. These metabolic alterations may be useful to monitor organ (dys) function and to understand the pathophysiology of acute and possibly post-acute COVID-19 syndromes.

Metabolomics Profiles Reveal New Insights of Herpes Simplex Virus Type 1 Infection

Herpes simplex virus type 1 (HSV-1) is a ubiquitous human pathogen that can cause significant morbidity, primarily facial cold sores and herpes simplex encephalitis. Previous studies have shown that a variety of viruses can reprogram the metabolic profiles of host cells to facilitate self-replication. In order to further elucidate the metabolic interactions between the host cell and HSV-1, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze the metabolic profiles in human lung fibroblasts KMB17 infected with HSV-1. The results showed that 654 and 474 differential metabolites were identified in positive and negative ion modes, respectively, and 169 and 114 metabolic pathways that might be altered were screened. These altered metabolites are mainly involved in central carbon metabolism, choline metabolism, amino acid metabolism, purine and pyrimidine metabolism, cholesterol metabolism, bile secretion, and prolactin signaling pathway. Further, we confirmed that the addition of tryptophan metabolite kynurenine promotes HSV-1 replication, and the addition of 25-Hydroxycholesterol inhibits viral replication. Significantly, HSV-1 replication was obviously enhanced in the ChOKα (a choline metabolic rate-limiting enzyme) deficient mouse macrophages. These results indicated that HSV-1 induces the metabolic reprogramming of host cells to promote or resist viral replication. Taken together, these observations highlighted the significance of host cell metabolism in HSV-1 replication, which would help to clarify the pathogenesis of HSV-1 and identify new anti-HSV-1 therapeutic targets.

Differential Plasma Metabolites between High- and Low-Grade Meningioma Cases

Meningiomas (MGMs) are currently classified into grades I, II, and III. High-grade tumors are correlated with decreased survival rates and increased recurrence rates. The current grading classification is based on histological criteria and determined only after surgical tumor sampling. This study aimed to identify plasma metabolic alterations in meningiomas of different grades, which would aid surgeons in predefining the ideal surgical strategy. Plasma samples were collected from 51 patients with meningioma and classified into low-grade (LG) (grade I; n = 43), and high-grade (HG) samples (grade II, n = 5; grade III, n = 3). An untargeted metabolomic approach was used to analyze plasma metabolites. Statistical analyses were performed to select differential biomarkers among HG and LG groups. Metabolites were identified using tandem mass spectrometry along with database verification. Five and four differential biomarkers were identified for HG and LG meningiomas, respectively. To evaluate the potential of HG MGM metabolites to differentiate between HG and LG tumors, a receiving operating characteristic curve was constructed, which revealed an area under the curve of 95.7%. This indicates that the five HG MGM metabolites represent metabolic alterations that can differentiate between LG and HG meningiomas. These metabolites may indicate tumor grade even before the appearance of histological features.

SREBP2-dependent lipid gene transcription enhances the infection of human dendritic cells by Zika virus

The emergence of Zika virus (ZIKV) as a global health threat has highlighted the unmet need for ZIKV-specific vaccines and antiviral treatments. ZIKV infects dendritic cells (DC), which have pivotal functions in activating innate and adaptive antiviral responses; however, the mechanisms by which DC function is subverted to establish ZIKV infection are unclear. Here we develop a genomics profiling method that enables discrete analysis of ZIKV-infected versus neighboring, uninfected primary human DCs to increase the sensitivity and specificity with which ZIKV-modulated pathways can be identified. The results show that ZIKV infection specifically increases the expression of genes enriched for lipid metabolism-related functions. ZIKV infection also increases the recruitment of sterol regulatory element-binding protein (SREBP) transcription factors to lipid gene promoters, while pharmacologic inhibition or genetic silencing of SREBP2 suppresses ZIKV infection of DCs. Our data thus identify SREBP2-activated transcription as a mechanism for promoting ZIKV infection amenable to therapeutic targeting.

Reprogramming of red blood cell metabolism in Zika virus–infected donors

BACKGROUND

Diseases caused by arthropod-borne viruses remain a burden to global health; in particular, Zika virus (ZIKV) has been reported in 87 countries and territories. In healthy blood donors, ZIKV RNA can be detected in red blood cells (RBCs) months after infection, clearance of detectable nucleic acid in plasma, and seroconversion. However, little information is available on the impact of ZIKV infection to metabolism.

STUDY DESIGN AND METHODS

We applied mass spectrometry-based metabolomics and lipidomics approaches to investigate the impact of ZIKV infection on RBCs over the course of infection. ZIKV-infected blood donors (n = 25) were identified through molecular and serologic methods, which included nucleic acid amplification testing and real-time polymerase chain reaction (PCR) for detection of ZIKV RNA and enzyme-linked immunosorbent assay (ELISA) for detection of flavivirus-specific IgM and IgG.

RESULTS

In ZIKV RNA-positive donors, we observed lower glucose and lactate levels, and higher levels of ribose phosphate, suggestive of the activation of the pentose phosphate pathway. The top pathways altered in RBCs from ZIKV-IgM-positive donors include amino acid metabolism and biosynthesis, fatty acid metabolism and biosynthesis, linoleic acid and arachidonate metabolism and glutathione metabolism. RBCs from ZIKV-infected donors had increased levels of early glycolytic metabolites, and higher levels of metabolites of the pentose phosphate pathway. Alterations in acyl-carnitine and fatty acid metabolism are consistent with impaired membrane lipid homeostasis in RBCs from ZIKV IgM positive donors.

CONCLUSION

RBC from healthy blood donors who had been infected by ZIKV are characterized by long-lasting metabolic alterations even months after infection has resolved.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Untargeted Metabolomics Insights into Newborns with Congenital Zika Infection

Zika virus (ZIKV), an emerging virus belonging to the Flaviviridae family, causes severe neurological clinical complications and has been associated with Guillain-Barré syndrome, fetal abnormalities known collectively as congenital Zika syndrome, and microcephaly. Studies have shown that ZIKV infection can alter cellular metabolism, directly affecting neural development. Brain growth requires controlled cellular metabolism, which is essential for cell proliferation and maturation. However, little is known regarding the metabolic profile of ZIKV-infected newborns and possible associations related to microcephaly. Furthering the understanding surrounding underlying mechanisms is essential to developing personalized treatments for affected individuals. Thus, metabolomics, the study of the metabolites produced by or modified in an organism, constitutes a valuable approach in the study of complex diseases. Here, 26 serum samples from ZIKV-positive newborns with or without microcephaly, as well as controls, were analyzed using an untargeted metabolomics approach involving gas chromatography-mass spectrometry (GC-MS). Significant alterations in essential and non-essential amino acids, as well as carbohydrates (including aldohexoses, such as glucose or mannose) and their derivatives (urea and pyruvic acid), were observed in the metabolic profiles analyzed. Our results provide insight into relevant metabolic processes in patients with ZIKV and microcephaly.

Saliva NMR-Based Metabolomics in the War Against COVID-19

COVID-19 is an emergent, worldwide public health concern. Joint efforts have been made by scientific communities of various fields to better understand the mechanisms of action of SARS-CoV-2. The need to understand the pathophysiological fingerprint and pathways of this disease make metabolomics-related approaches an indispensable tool for properly answering concerns relating to disease course. Determination of the metabolomic profile may help to explain the heterogeneous spectra of COVID-19 clinical phenotypes and be useful in monitoring disease progression as well as therapeutic treatments. In this sense, saliva has proven to be a strategic biofluid, owing not only to its appeal as a noninvasive sampling method but also due to the capacity of the virus to invade epithelial cells of the oral mucosa and salivary gland ducts via ACE2 receptors. Accordingly, important changes in metabolism have been described relating to COVID-19, indicating that metabolomics may open new avenues for understanding the pathophysiology of this disease, especially via longitudinal study designs. Thus, we discuss the importance of comprehending the SARS-CoV-2 salivary metabolomic fingerprint and also highlight the situation of Brazil on the frontlines of the war against COVID-19.

Metabolomics applied in the study of emerging arboviruses caused by Aedes aegypti mosquitoes: A review

Arboviruses, such as chikungunya, dengue, yellow fever, and zika, caused by the bite of the Aedes aegypti mosquito, have been a frequent public health problem, with a high incidence of outbreaks in tropical and subtropical countries. These diseases are easily confused with a flu-like illness and present very similar symptoms, difficult to distinguish, and treat appropriately. The effects that these infections cause in the organism are fundamentally derived from complex metabolic processes. A prominent area of science that investigates the changes in the metabolism of complex organisms is the metabolomics. Metabolomics measures the metabolites produced or altered in biological organisms, through the use of robust analytical platforms, such as separation techniques hyphenated with mass spectrometry, combined with bioinformatics. This review article presents an overview of the basic concepts of metabolomics workflow and advances in this field, and compiles research articles that use this omic approach to study these arboviruses. In this context, the metabolomics is applied to search new therapies, understand the viral replication mechanisms, and access the host-virus interactions.

The role of brain innate immune response in lysosomal storage disorders: fundamental process or evolutionary side effect?

Sphingolipidoses are diseases caused by mutations in genes responsible for sphingolipid degradation and thereby lead to sphingolipid accumulation. Most sphingolipidoses have a neurodegenerative manifestation characterized by innate immune activation in the brain. However, the role of the immune response in disease progression is ill-understood. In contrast to infectious diseases, immune activation is unable to eliminate the offending agent in sphingolipidoses resulting in ineffective, chronic inflammation. This paradox begs two fundamental questions: Why has this immune response evolved in sphingolipidoses? What role does it play in disease progression? Here, starting from the observation that sphingolipids (SLs) are elevated also in infectious diseases, I discuss the possibility that the activation of the brain immune response by SLs has evolved as a part of the immune response against pathogens and plays no major role in sphingolipidoses.

Lipid hijacking: a unifying theme in vector-borne diseases

Vector-borne illnesses comprise a significant portion of human maladies, representing 17% of global infections. Transmission of vector-borne pathogens to mammals primarily occurs by hematophagous arthropods. It is speculated that blood may provide a unique environment that aids in the replication and pathogenesis of these microbes. Lipids and their derivatives are one component enriched in blood and are essential for microbial survival. For instance, the malarial parasite Plasmodium falciparum and the Lyme disease spirochete Borrelia burgdorferi, among others, have been shown to scavenge and manipulate host lipids for structural support, metabolism, replication, immune evasion, and disease severity. In this Review, we will explore the importance of lipid hijacking for the growth and persistence of these microbes in both mammalian hosts and arthropod vectors.

SARS-CoV-2 perturbs the renin-angiotensin system and energy metabolism

The COVID-19 pandemic, caused by the novel coronavirus, SARS-CoV-2, is threating our health systems and daily lives and is responsible for causing substantial morbidity and mortality. In particular, aged individuals and individuals with comorbidities, including obesity, diabetes mellitus, and hypertension, have significantly higher risks of hospitalization and death than normal individuals. The renin-angiotensin system (RAS) plays a pivotal role in the pathogenesis of diabetes mellitus, obesity, and hypertension. Angiotensin-converting enzyme 2 (ACE2), belonging to the RAS family, has received much attention during this COVID-19 pandemic, owing to the fact that SARS-CoV-2 uses ACE2 as a receptor for cellular entry. Additionally, the RAS greatly affects energy metabolism in certain pathological conditions, including cardiac failure, diabetes mellitus, and viral infections. This article discusses the potential mechanisms by which SARS-CoV-2 modulates the RAS and energy metabolism in individuals with obesity and diabetes mellitus. The article aims to highlight the appropriate strategies for combating the COVID-19 pandemic in the clinical setting and emphasize on the areas that require further investigation in relation to COVID-19 infections in patients with obesity and diabetes mellitus from the viewpoint of endocrinology and metabolism.

Metabolomics and Machine Learning Approaches Combined in Pursuit for More Accurate Paracoccidioidomycosis Diagnoses

Brazil and many other Latin American countries are areas of endemicity for different neglected diseases, and the fungal infection paracoccidioidomycosis (PCM) is one of them. Among the clinical manifestations, pneumopathy associated with skin and mucosal lesions is the most frequent. PCM definitive diagnosis depends on yeast microscopic visualization and immunological tests, but both present ambiguous results and difficulty in differentiating PCM from other fungal infections. This research has employed metabolomics analysis through high-resolution mass spectrometry to identify PCM biomarkers in serum samples in order to improve diagnosis for this debilitating disease. To upgrade the biomarker selection, machine learning approaches, using Random Forest classifiers, were combined with metabolomics data analysis. The proposed combination of these two analytical methods resulted in the identification of a set of 19 PCM biomarkers that show accuracy of 97.1%, specificity of 100%, and sensitivity of 94.1%. The obtained results are promising and present great potential to improve PCM definitive diagnosis and adequate pharmacological treatment, reducing the incidence of PCM sequelae and resulting in a better quality of life.IMPORTANCE Paracoccidioidomycosis (PCM) is a fungal infection typically found in Latin American countries, especially in Brazil. The identification of this disease is based on techniques that may fail sometimes. Intending to improve PCM detection in patient samples, this study used the combination of two of the newest technologies, artificial intelligence and metabolomics. This combination allowed PCM detection, independently of disease form, through identification of a set of molecules present in patients' blood. The great difference in this research was the ability to detect disease with better confidence than the routine methods employed today. Another important point is that among the molecules, it was possible to identify some indicators of contamination and other infection that might worsen patients' condition. Thus, the present work shows a great potential to improve PCM diagnosis and even disease management, considering the possibility to identify concomitant harmful factors.

Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases

Viral emergence is an unpredictable but obvious event, particularly in the era of climate change and globalization. Efficient management of viral outbreaks depends on pre-existing knowledge and alertness. The potential hotspots of viral emergence often remain neglected and the information related to them is insufficient, particularly for emerging viruses. Viral replication and transmission rely upon usurping the host metabolic machineries. So altered host metabolic pathways can be exploited for containment of these viruses. Metabolomics provides the insight for tracing out such checkpoints. Consequently introspection of metabolic alteration at virus-host interface has evolved as prime area in current virology research. Chromatographic separation followed by mass spectrometry has been used as the predominant analytical platform in bulk of the analyses followed by nuclear magnetic resonance (NMR) and fluorescence based techniques. Although valuable information regarding viral replication and modulation of host metabolic pathways have been extracted but ambiguity often superseded the real events due to population effect over the infected cells. Exploration of cellular heterogeneity and differentiation of infected cells from the nearby healthy ones has become essential. Single cell metabolomics (SCM) emerges as necessity to explore such minute details. Mass spectrometry imaging (MSI) coupled with several soft ionization techniques such as electrospray ionization (ESI), laser ablation electrospray ionization (LAESI), matrix assisted laser desorption/ionization (MALDI), matrix-free laser desorption ionization (LDI) have evolved as the best suited platforms for SCM analyses. The potential of SCM has already been exploited to resolve several biological conundrums. Thus SCM is knocking at the door of virus-host interface.

Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers

Weight gain is a metabolic disorder that often culminates in the development of obesity and other comorbidities such as diabetes. Obesity is characterized by the development of a chronic, subclinical systemic inflammation, and is regarded as a remarkably important factor that contributes to the development of such comorbidities. Therefore, laboratory methods that allow the identification of subjects at higher risk for severe weight-associated morbidity are of utter importance, considering the health, and safety of populations. This contribution analyzed the plasma of 180 Brazilian individuals, equally divided into a eutrophic control group and case group, to assess the presence of biomarkers related to weight gain, aiming at characterizing the phenotype of this population. Samples were analyzed by mass spectrometry and most discriminant features were determined by a machine learning approach using Random Forest algorithm. Five biomarkers related to the pathogenesis and chronicity of inflammation in weight gain were identified. Two metabolites of arachidonic acid were upregulated in the case group, indicating the presence of inflammation, as well as two other molecules related to dysfunctions in the cycle of nitric oxide (NO) and increase in superoxide production. Finally, a fifth case group marker observed in this study may indicate the trigger for diabetes in overweight and obesity individuals. The use of mass spectrometry combined with machine learning analyses to prospect and characterize biomarkers associated with weight gain will pave the way for elucidating potential therapeutic and prognostic targets.

Molecular signatures associated with prostate cancer cell line (PC-3) exposure to inactivated Zika virus

The recent outbreak of Zika virus (ZIKV) infection associated with microcephaly cases has elicited much research on the mechanisms involved in ZIKV-host cell interactions. It has been described that Zika virus impairs cell growth, raising a hypothesis about its oncolytic potential against cancer cells. ZIKV tumor cell growth inhibition was later confirmed for glioblastoma. It was also demonstrated that an inactivated ZIKV prototype (ZVp) based on bacterial outer membrane vesicles has antiproliferative activity upon other cancer cell lines, such as PC-3 prostate cancer cell. This study aims at understanding the pathways that might be involved with the antiproliferative effect of Zika virus against prostate cancer cells. A metabolomic approach based on high-resolution mass spectrometry analysis led to the identification of 21 statistically relevant markers of PC-3 cells treated with ZVp. The markers were associated with metabolic alterations that trigger lipid remodeling, endoplasmic reticulum stress, inflammatory mediators, as well as disrupted porphyrin and folate metabolism. These findings highlight molecular signatures of ZVp-induced response that may be involved on cellular pathways triggered by its antiproliferative effect. To our knowledge, this is the first reported metabolomic assessment of ZIKV effect on prostate cancer cells, a promising topic for further research.

Inflammation markers in the saliva of infants born from Zika-infected mothers: exploring potential mechanisms of microcephaly during fetal development

Zika virus (ZIKV) has emerged as one of the most medically relevant viral infections of the past decades; the devastating effects of this virus over the developing brain are a major matter of concern during pregnancy. Although the connection with congenital malformations are well documented, the mechanisms by which ZIKV reach the central nervous system (CNS) and the causes of impaired cortical growth in affected fetuses need to be better addressed. We performed a non-invasive, metabolomics-based screening of saliva from infants with congenital Zika syndrome (CZS), born from mothers that were infected with ZIKV during pregnancy. We were able to identify three biomarkers that suggest that this population suffered from an important inflammatory process; with the detection of mediators associated with glial activation, we propose that microcephaly is a product of immune response to the virus, as well as excitotoxicity mechanisms, which remain ongoing even after birth.

Lipidomic Analysis Reveals Serum Alteration of Plasmalogens in Patients Infected With ZIKA Virus

Zika virus (ZIKV) is an arthropod-borne virus (arbovirus) in the Flavivirus genus of the Flaviviridae family. Since the large outbreaks in French Polynesia in 2013–2014 and in Brazil in 2015, ZIKV has been considered a new public health threat. Similar to other related flavivirus, ZIKV is associated with mild and self-limiting symptoms such as rash, pruritus, prostration, headache, arthralgia, myalgia, conjunctivitis, lower back pain and, when present, a short-term low grade fever. In addition, ZIKV has been implicated in neurological complications such as neonatal microcephaly and Guillain–Barré syndrome in adults. Herein, serum lipidomic analysis was used to identify possible alterations in lipid metabolism triggered by ZIKV infection. Patients who presented virus-like symptoms such as fever, arthralgia, headache, exanthema, myalgia and pruritus were selected as the control group. Our study reveals increased levels of several phosphatidylethanolamine (PE) lipid species in the serum of ZIKV patients, the majority of them plasmenyl-phosphatidylethanolamine (pPE) (or plasmalogens) linked to polyunsaturated fatty acids. Constituting up to 20% of total phospholipids in humans, plasmalogens linked to polyunsaturated fatty acids are particularly enriched in neural membranes of the brain. The biosynthesis of plasmalogens requires functional peroxisomes, which are important sites for viral replication, including ZIKV. Thus, increased levels of plasmalogens in serum of ZIKV infected subjects suggest a link between ZIKV life cycle and peroxisomes. Our data provide important insights into specific host cellular lipids that are likely associated with ZIKV replication and may serve as platform for antiviral strategy against ZIKV.

Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses

The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host⁻virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans.

Zika Virus Infection of Human Mesenchymal Stem Cells Promotes Differential Expression of Proteins Linked to Several Neurological Diseases

The recent microcephaly outbreak in Brazil has been associated with Zika virus (ZIKV) infection. The current understanding of damage caused by ZIKV infection is still unclear, since it has been implicated in other neurodegenerative and developmental complications. Here, the differential proteome analysis of human mesenchymal stem cells (hMSC) infected with a Brazilian strain of ZIKV was identified by shotgun proteomics (MudPIT). Our results indicate that ZIKV induces a potential reprogramming of the metabolic machinery in nucleotide metabolism, changes in the energy production via glycolysis and other metabolic pathways, and potentially inhibits autophagy, neurogenesis, and immune response by downregulation of signaling pathways. In addition, proteins previously described in several brain pathologies, such as Alzheimer's disease, autism spectrum disorder, amyotrophic lateral sclerosis, and Parkinson's disease, were found with altered expression due to ZIKV infection in hMSC. This potential link between ZIKV and several neuropathologies beyond microcephaly is being described here for the first time and can be used to guide specific follow-up studies concerning these specific diseases and ZIKV infection.

Integrated human-virus metabolic stoichiometric modelling predicts host-based antiviral targets against Chikungunya, Dengue and Zika viruses

Current and reoccurring viral epidemic outbreaks such as those caused by the Zika virus illustrate the need for rapid development of antivirals. Such development would be facilitated by computational approaches that can provide experimentally testable predictions for possible antiviral strategies. To this end, we focus here on the fact that viruses are directly dependent on their host metabolism for reproduction. We develop a stoichiometric, genome-scale metabolic model that integrates human macrophage cell metabolism with the biochemical demands arising from virus production and use it to determine the virus impact on host metabolism and vice versa. While this approach applies to any host–virus pair, we first apply it to currently epidemic viruses Chikungunya, Dengue and Zika in this study. We find that each of these viruses causes specific alterations in the host metabolic flux towards fulfilling their biochemical demands as predicted by their genome and capsid structure. Subsequent analysis of this integrated model allows us to predict a set of host reactions, which, when constrained, inhibit virus production. We show that this prediction recovers known targets of existing antiviral drugs, specifically those targeting nucleotide production, while highlighting a set of hitherto unexplored reactions involving both amino acid and nucleotide metabolic pathways, with either broad or virus-specific antiviral potential. Thus, this computational approach allows rapid generation of experimentally testable hypotheses for novel antiviral targets within a host.

The role of lipids in the inception, maintenance and complications of dengue virus infection

Dengue fever is a viral condition that has become a recurrent issue for public health in tropical countries, common endemic areas. Although viral structure and composition have been widely studied, the infection phenotype in terms of small molecules remains poorly established. This contribution providing a comprehensive overview of the metabolic implications of the virus-host interaction using a lipidomic-based approach through direct-infusion high-resolution mass spectrometry. Our results provide further evidence that lipids are part of both the immune response upon Dengue virus infection and viral infection maintenance mechanism in the organism. Furthermore, the species described herein provide evidence that such lipids may be part of the mechanism that leads to blood-related complications such as hemorrhagic fever, the severe form of the disease.

A Machine Learning Application Based in Random Forest for Integrating Mass Spectrometry-Based Metabolomic Data: A Simple Screening Method for Patients With Zika Virus

Recent Zika outbreaks in South America, accompanied by unexpectedly severe clinical complications have brought much interest in fast and reliable screening methods for ZIKV (Zika virus) identification. Reverse-transcriptase polymerase chain reaction (RT-PCR) is currently the method of choice to detect ZIKV in biological samples. This approach, nonetheless, demands a considerable amount of time and resources such as kits and reagents that, in endemic areas, may result in a substantial financial burden over affected individuals and health services veering away from RT-PCR analysis. This study presents a powerful combination of high-resolution mass spectrometry and a machine-learning prediction model for data analysis to assess the existence of ZIKV infection across a series of patients that bear similar symptomatic conditions, but not necessarily are infected with the disease. By using mass spectrometric data that are inputted with the developed decision-making algorithm, we were able to provide a set of features that work as a "fingerprint" for this specific pathophysiological condition, even after the acute phase of infection. Since both mass spectrometry and machine learning approaches are well-established and have largely utilized tools within their respective fields, this combination of methods emerges as a distinct alternative for clinical applications, providing a diagnostic screening-faster and more accurate-with improved cost-effectiveness when compared to existing technologies.

Evaluating the effects of the adulterants in milk using direct-infusion high-resolution mass spectrometry

Milk is an extremely complex food, capable of providing essential nutrients as well as being an important source of energy, and high-quality proteins and fats. Due to advances in technology, and to meet the increasing demand, production costs have increased, turning milk into a target of adulterations. Routine methods usually applied to certify the quality of the milk are restricted to microbiological tests, and assays that attest the nutritional composition within the expected values. However, potentially harmful byproducts generated by adulterating substances in general are not detected through these methodologies. In this contribution, we simulated the adulteration of freshly produced milk samples with four adulterants whose use already had reported for extended shelf life: formaldehyde, hydrogen peroxide, sodium hydroxide, and sodium hypochlorite. These samples were submitted to direct-infusion high-resolution mass spectrometry analysis and multivariate statistical analysis. This approach allows the characterization of a series of molecules modified by the adulterants, what demonstrates how these species affect the nutritious characteristics of this product.

A Metabolomic Overview of Follicular Fluid in Cows

Follicular fluid (FF) protects the oocyte against proteolysis and extrusion during ovulation, providing an appropriate microenvironment that favors proper embryonic development; thereby, FF plays a key role in embryo quality. Being directly related to cattle breeding, studying FF is extremely important in livestock science to measure cattle fertility. This may eventually help to assess the quality of both meat and milk, products widely consumed worldwide. There is an important commercial interest in the evaluation and characterization of compounds present in the FF of livestock that present greater likelihood of pregnancy. Mass spectrometry is a great ally for this type of analysis and can provide quick and efficient screening for molecular markers in biological samples. The present study demonstrated the potential of high-resolution mass spectrometry in analyzing FF samples from two distinct groups of Nellore cows (Bos indicus): high and low fertility, as determined by the number of oocytes produced. We were able to delineate markers of interest for each group, which may ultimately be related to biochemical pathways that lead to higher or lower reproductive performance.