Nuclear magnetic resonance based profiling of biofluids reveals metabolic dysregulation in HIV-infected persons and those on anti-retroviral therapy

Cardiometabolic Differences in People Living with HIV Receiving Integrase Strand Transfer Inhibitors Compared to Non-nucleoside Reverse Transcriptase Inhibitors: Implications for Current ART Strategies

In people living with HIV (PLHIV), integrase strand transfer inhibitors (INSTIs) are part of the first-line combination antiretroviral therapy (cART), while non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens are alternatives. Distinct cART regimens may variably influence the risk for non-AIDS comorbidities. We aimed to compare the metabolome and lipidome of INSTI and NNRTI-based regimens. The 2000HIV study includes asymptomatic PLHIV (n = 1646) on long-term cART, separated into a discovery cohort with 730 INSTI and 617 NNRTI users, and a validation cohort encompassing 209 INSTI and 90 NNRTI users. Baseline plasma samples from INSTI and NNRTI users were compared using mass spectrometry-based untargeted metabolomic (n = 500) analysis. Perturbed metabolic pathways were identified using MetaboAnalyst software. Subsequently, nuclear magnetic resonance spectroscopy was used for targeted lipoprotein and lipid (n = 141) analysis. Metabolome homogeneity was observed between the different types of INSTI and NNRTI. In contrast, higher and lower levels of 59 and 45 metabolites, respectively, were found in the INSTI group compared to NNRTI users, of which 77.9% (81/104) had consistent directionality in the validation cohort. Annotated metabolites belonged mainly to 'lipid and lipid-like molecules', 'organic acids and derivatives' and 'organoheterocyclic compounds'. In pathway analysis, perturbed 'vitamin B1 (thiamin) metabolism', 'de novo fatty acid biosynthesis', 'bile acid biosynthesis' and 'pentose phosphate pathway' were detected, among others. Lipoprotein and lipid levels in NNRTIs were heterogeneous and could not be compared as a group. INSTIs compared to individual NNRTI types showed that HDL cholesterol was lower in INSTIs compared to nevirapine but higher in INSTIs compared to doravirine. In addition, LDL size was lower in INSTIs and nevirapine compared to doravirine. NNRTIs show more heterogeneous cardiometabolic effects than INSTIs, which hampers the comparison between these two classes of drugs. Targeted lipoproteomic and lipid NMR spectroscopy showed that INSTI use was associated with a more unfavorable lipid profile compared to nevirapine, which was shifted to a more favorable profile for INSTI when substituting nevirapine for doravirine, with evidently higher fold changes. The cardiovascular disease risk profile seems more favorable in INSTIs compared to NNRTIs in untargeted metabolomic analysis using mass-spectrometry.

Plasma metabolomic profile is near-normal in people with HIV on long-term suppressive antiretroviral therapy

Background

Combination antiretroviral therapy (ART) has transformed human immunodeficiency virus (HIV) infection in people with HIV (PWH). However, a chronic state of immune activation and inflammation is maintained despite achieving HIV suppression and satisfactory immunological recovery. We aimed to determine whether the plasma metabolomic profile of PWH on long-term suppressive ART and immunologically recovered approximates the normality by comparison with healthy controls with similar age and gender.

Methods

We carried out a cross-sectional study in 17 PWH on long-term ART (HIV-RNA <50 copies/mL, CD4+ ≥500 cells/mm3, and CD4+/CD8+ ≥1) and 19 healthy controls with similar age and gender. Metabolomics analysis was performed by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). The statistical association analysis was performed by principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and Generalized Linear Models (GLM) with a gamma distribution (log-link). Significance levels (p-value) were corrected for multiple testing (q-value).

Results

PCA and PLS-DA analyses found no relevant differences between groups. Adjusted GLM showed 14 significant features (q-value<0.20), of which only three could be identified: lysophosphatidylcholine (LysoPC) (22:6) (q-value=0.148), lysophosphatidylethanolamine (LysoPE) (22:6) (q-value=0.050) and hydroperoxy-octadecatrienoic acid (HpOTrE)/dihydroperoxy-octadecatrienoic acid (DiHOTrE)/epoxy-octadecadienoic acid (EpODE) (q-value=0.136). These significant identified metabolites were directly correlated to plasma inflammatory biomarkers in PWH and negatively correlated in healthy controls.

Conclusion

PWH on long-term ART have a metabolomic profile that is almost normal compared to healthy controls. Nevertheless, residual metabolic alterations linked to inflammatory biomarkers persist, which could favor the development of age-related comorbidities among this population.

Metabolic Alterations in Mothers Living with HIV and Their HIV-Exposed, Uninfected Infants

HIV-exposed, uninfected (HEU) children present with suboptimal growth and a greater susceptibility to infection in early life when compared to HIV-unexposed, uninfected (HUU) children. The reasons for these findings are poorly understood. We used a metabolomics approach to investigate the metabolic differences between pregnant women living with HIV (PWLWH) and their HEU infants compared to the uninfected and unexposed controls. Untargeted metabolomic profiling was performed using 1H-NMR spectroscopy on maternal plasma at 28 weeks' gestation and infant plasma at birth, 6/10 weeks, and 6 months. PWLWH were older but, apart from a larger 28 week mid-upper-arm circumference, anthropometrically similar to the controls. At all the time points, HEU infants had a significantly reduced growth compared to HUU infants. PWLWH had lower plasma 3-hydroxybutyric acid, acetoacetic acid, and acetic acid levels. In infants at birth, threonine and myo-inositol levels were lower in the HEU group while formic acid levels were higher. At 6/10 weeks, betaine and tyrosine levels were lower in the HEU group. Finally, at six months, 3-hydroxyisobutyric acid levels were lower while glycine levels were higher in the HEU infants. The NMR analysis has provided preliminary information indicating differences between HEU and HUU infants' plasma metabolites involved in energy utilization, growth, and protection from infection.

The metabolic consequences of HIV/TB co-infection

BACKGROUND

The synergy between the human immunodeficiency virus (HIV) and Mycobacterium tuberculosis during co-infection of a host is well known. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms that contribute to the associated disease burden experienced during HIV/tuberculosis (TB) co-infection remain poorly understood. Furthermore, while anti-HIV treatments suppress viral replication, these therapeutics give rise to host metabolic disruption and adaptations beyond that induced by only infection or disease.

METHODS

In this study, the serum metabolic profiles of healthy controls, untreated HIV-negative TB-positive patients, untreated HIV/TB co-infected patients, and HIV/TB co-infected patients on antiretroviral therapy (ART), were measured using two-dimensional gas chromatography time-of-flight mass spectrometry. Since no global metabolic profile for HIV/TB co-infection and the effect of ART has been published to date, this pilot study aimed to elucidate the general areas of metabolism affected during such conditions.

RESULTS

HIV/TB co-infection induced significant changes to the host's lipid and protein metabolism, with additional microbial product translocation from the gut to the blood. The results suggest that HIV augments TB synergistically, at least in part, contributing to increased inflammation, oxidative stress, ART-induced mitochondrial damage, and its detrimental effects on gut health, which in turn, affects energy availability. ART reverses these trends to some extent in HIV/TB co-infected patients but not to that of healthy controls.

CONCLUSION

This study generated several new hypotheses that could direct future metabolic studies, which could be combined with other research techniques or methodologies to further elucidate the underlying mechanisms of these changes.

Metabolite variations in the sera of HIV+ patients after an oral administration of effervescent glutamine and in comparison to non-HIV individuals by NMR

It was demonstrated that effervescent glutamine supplementation in HIV+ individuals treated with antiretroviral therapy (ART) increased CD4+ T lymphocytes, decreased inflammation biomarkers, and brought health benefits. This pilot study aimed to explore serum metabolite variations in the HIV+ group under ART after 30 days of supplementation with glutamine, and in comparison to the matched HIV- group. The group of HIV+ showed lower levels of choline, creatine, pyruvate, glutamate, lysine, and tyrosine when compared to the HIV- group. Glucose, lipids, lactate, glutamine, phenylalanine, threonine, and phenylalanine/tyrosine were higher in HIV+ patients under long ART. Serum metabolome variations were shown to be consistent with the health improvements observed in the HIV+ group after effervescent glutamine supplementation, which might aid in ART in HIV+ individuals.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part III: Implementations for the Diagnosis of Non-Cancerous Disorders, Both Oral and Systemic

This communication represents Part III of our series of reports based on the applications of human saliva as a useful and conveniently collectable medium for the discovery, identification and monitoring of biomarkers, which are of some merit for the diagnosis of human diseases. Such biomarkers, or others reflecting the dysfunction of specific disease-associated metabolic pathways, may also be employed for the prognostic pathological tracking of these diseases. Part I of this series set the experimental and logistical groundwork for this report, and the preceding paper, Part II, featured the applications of newly developed metabolomics technologies to the diagnosis and severity grading of human cancer conditions, both oral and systemic. Clearly, there are many benefits, both scientific and economic, associated with the donation of human saliva samples (usually as whole mouth saliva) from humans consenting to and participating in investigations focused on the discovery of biomolecular markers of diseases. These include usually non-invasive collection protocols, relatively low cost when compared against blood sample collection, and no requirement for clinical supervision during collection episodes. This paper is centred on the employment and value of 'state-of-the-art' metabolomics technologies to the diagnosis and prognosis of a wide range of non-cancerous human diseases. Firstly, these include common oral diseases such as periodontal diseases (from type 1 (gingivitis) to type 4 (advanced periodontitis)), and dental caries. Secondly, a wide range of extra-oral (systemic) conditions are covered, most notably diabetes types 1 and 2, cardiovascular and neurological diseases, and Sjögren's syndrome, along with a series of viral infections, e.g., pharyngitis, influenza, HIV and COVID-19. Since the authors' major research interests lie in the area of the principles and applications of NMR-linked metabolomics techniques, many, but not all, of the studies reviewed were conducted using these technologies, with special attention being given to recommended protocols for their operation and management, for example, satisfactory experimental model designs; sample collection and laboratory processing techniques; the selection of sample-specific NMR pulse sequences for saliva analysis; and strategies available for the confirmation of resonance assignments for both endogenous and exogenous molecules in this biofluid. This article also features an original case study, which is focussed on the use of NMR-based salivary metabolomics techniques to provide some key biomarkers for the diagnosis of pharyngitis, and an example of how to 'police' such studies and to recognise participants who perceive that they actually have this disorder but do not from their metabolic profiles and multivariate analysis pattern-based clusterings. The biochemical and clinical significance of these multidimensional metabolomics investigations are discussed in detail.

Altered lipid metabolites accelerate early dysfunction of T cells in HIV-infected rapid progressors by impairing mitochondrial function

The complex mechanism of immune-system damage in HIV infection is incompletely understood. HIV-infected "rapid progressors" (RPs) have severe damage to the immune system early in HIV infection, which provides a "magnified" opportunity to study the interaction between HIV and the immune system. In this study, forty-four early HIV-infected patients (documented HIV acquisition within the previous 6 months) were enrolled. By study the plasma of 23 RPs (CD4⁺ T-cell count < 350 cells/µl within 1 year of infection) and 21 "normal progressors" (NPs; CD4⁺ T-cell count > 500 cells/μl after 1 year of infection), eleven lipid metabolites were identified that could distinguish most of the RPs from NPs using an unsupervised clustering method. Among them, the long chain fatty acid eicosenoate significantly inhibited the proliferation and secretion of cytokines and induced TIM-3 expression in CD4⁺ and CD8⁺ T cells. Eicosenoate also increased levels of reactive oxygen species (ROS) and decreased oxygen consumption rate (OCR) and mitochondrial mass in T cells, indicating impairment in mitochondrial function. In addition, we found that eicosenoate induced p53 expression in T cells, and inhibition of p53 effectively decreased mitochondrial ROS in T cells. More importantly, treatment of T cells with the mitochondrial-targeting antioxidant mito-TEMPO restored eicosenoate-induced T-cell functional impairment. These data suggest that the lipid metabolite eicosenoate inhibits immune T-cell function by increasing mitochondrial ROS by inducing p53 transcription. Our results provide a new mechanism of metabolite regulation of effector T-cell function and provides a potential therapeutic target for restoring T-cell function during HIV infection.

Trans cohort metabolic reprogramming towards glutaminolysis in long-term successfully treated HIV-infection

Despite successful combination antiretroviral therapy (cART), persistent low-grade immune activation together with inflammation and toxic antiretroviral drugs can lead to long-lasting metabolic flexibility and adaptation in people living with HIV (PLWH). Our study investigated alterations in the plasma metabolic profiles by comparing PLWH on long-term cART(>5 years) and matched HIV-negative controls (HC) in two cohorts from low- and middle-income countries (LMIC), Cameroon, and India, respectively, to understand the system-level dysregulation in HIV-infection. Using untargeted and targeted LC-MS/MS-based metabolic profiling and applying advanced system biology methods, an altered amino acid metabolism, more specifically to glutaminolysis in PLWH than HC were reported. A significantly lower level of neurosteroids was observed in both cohorts and could potentiate neurological impairments in PLWH. Further, modulation of cellular glutaminolysis promoted increased cell death and latency reversal in pre-monocytic HIV-1 latent cell model U1, which may be essential for the clearance of the inducible reservoir in HIV-integrated cells.

Development of a method for dansylation of metabolites using organic solvent-compatible buffer systems for amine/phenol submetabolome analysis

Metabolomics, which serves as a readout of biological processes and diseases monitoring, is an informative research area for disease biomarker discovery and systems biology studies. In particular, reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) has become a powerful and popular tool for metabolomics analysis, enabling the detection of most metabolites. Very polar and ionic metabolites, however, are less easily detected because of their poor retention in RP columns. Dansylation of metabolites simplifies the sub-metabolome analysis by reducing its complexity and increasing both hydrophobicity and ionization ability. However, the various metabolite concentrations in clinical samples have a wide dynamic range with highly individual variation in total metabolite amount, such as in saliva. The bicarbonate buffer typically used in dansylation labeling reactions induces solvent stratification, resulting in poor reproducibility, selective sample loss and an increase in false-determined metabolite peaks. In this study, we optimized the dansylation protocol for samples with wide concentration range of metabolites, utilizing diisopropylethylamine (DIPEA) or tri-ethylamine (TEA) in place of bicarbonate buffer, and presented the results of a systemic investigation of the influences of individual processes involved on the overall performance of the protocol. In addition to achieving high reproducibility, substitution of DIPEA or TEA buffer resulted in similar labeling efficiency of most metabolites and more efficient labeling of some metabolites with a higher pK_a. With this improvement, compounds that are only present in samples in trace amounts can be detected, and more comprehensive metabolomics profiles can be acquired for biomarker discovery or pathway analysis, making it possible to analyze clinical samples with limited amounts of metabolites.

Metabolomics as a Tool to Investigate HIV/TB Co-Infection

The HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) and tuberculosis (TB) pandemics are perpetuated by a significant global burden of HIV/TB co-infection. The synergy between HIV and Mycobacterium tuberculosis (Mtb) during co-infection of a host is well established. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms thereof remain poorly understood. Metabolomics has been applied to study various aspects of HIV and Mtb infection separately, yielding insights into infection- and treatment-induced metabolic adaptations experienced by the host. Despite the contributions that metabolomics has made to the field, this approach has not yet been systematically applied to characterize the HIV/TB co-infected state. Considering that limited HIV/TB co-infection metabolomics studies have been published to date, this review briefly summarizes what is known regarding the HIV/TB co-infection synergism from a conventional and metabolomics perspective. It then explores metabolomics as a tool for the improved characterization of HIV/TB co-infection in the context of previously published human-related HIV infection and TB investigations, respectively as well as for addressing the gaps in existing knowledge based on the similarities and deviating trends reported in these HIV infection and TB studies.

Raman-based metabonomics unravels metabolic changes related to a first-line tenofovir-based treatment in a small cohort of South African HIV-infected patients

In addition to immunological disorders, human immunodeficiency virus (HIV) also causes metabolic abnormalities. Though successful in viral suppression and immune restoration, continued use of antiretroviral therapy (ART) has also been linked to the development of several metabolic ailments. Currently, the only clinical markers used to manage and monitor the development of HIV-induced metabolic disorders, disease progression as well as observing individual's response to antiviral treatment are CD4 count, viral loads and several other single variable colometric assays. Despite the common use of these clinical markers, these markers remain unreliable and limited in the ability to monitor the development of metabolic disorders as well as monitor treatment response. Given these limitations, it is imperative to discover and develop reliable biological markers for overall HIV disease management. Here, Raman spectroscopy was used to profile metabolic changes in the plasma of 22 HIV⁺ receiving a first-line tenofovir-based combination antiretroviral therapy compared to their 8 HIV⁺ ART^- and 10 HIV^- counterparts. Multivariate statistical analysis was performed in order to classify the samples into their respective groups and to identify significantly altered metabolites between the control and experimental groups. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) discriminant analysis identified significant differences (p < 0.05) in 9 different metabolites. Alterations were identified in spectral regions associated with glucose (1124 cm^-1), lipids/phospholipids (1116 cm^-1, 1098 cm^-1, 1077 cm^-1), proteins (1120 cm^-1), nucleic acids (1081 cm^-1) and phenylalanine (1103 cm^-1). Pathway analysis also revealed 3 significantly altered pathways. This study presented the reproducible nature of Raman spectroscopy in distinguishing between HIV-infected (treated and untreated) and uninfected blood plasma and allowed for the detection and identification of treatment induced metabolite changes. The results obtained in the study may, therefore, give insights into understanding the metabolic effect of HIV therapy.

Nephropathogenic Infectious Bronchitis Virus Infection Altered the Metabolome Profile and Immune Function of the Bursa of Fabricius in Chicken

Infectious bronchitis is a highly contagious, acute viral respiratory disease of chickens, regardless of the strain, and its infection may lead to considerable economic losses to the poultry industry. New nephropathogenic infectious bronchitis virus (NIBV) strains have increasingly emerged in recent years; hence, evaluating their infection-influenced immune function changes and the alteration of metabolite profiling is important. Initially, chickens were randomly distributed into two groups: the control group (Con) and the disease group (Dis). Here, the partial cytokines were examined, and the metabolome alterations of the bursa of Fabricius (BF) in NIBV infections in chickens were profiled by gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS). The results revealed that the NIBV infection promotes the mRNA expression of inflammatory cytokines. Metabolic profile analysis indicated that clustering differed between the two groups and there were 75 significantly different metabolites detected between the two groups, suggesting that the host metabolism was significantly changed by NIBV infection. Notably, the following 12 metabolites were identified as the potential biomarkers: 3-phenyllactic acid, 2-deoxytetronic acid, aminomalonic acid, malonamide 5, uric acid, arachidonic acid, 2-methylglutaric acid, linoleic acid, ethanolamine, stearic acid, N-alpha-acetyl-l-ornithine, and O-acetylserine. Furthermore, the results of the correlation analysis showed that a strong correlation existed between metabolic biomarkers and inflammatory cytokines. Our results describe an immune and metabolic profile for the BF of chickens when infected with NIBV and provide new biomarkers of NIBV infection as potential targets and indicators of indicating therapeutic efficacy.

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.

H, Bhavesh NS, Tandon R. Plasma metabolomic study in perinatally HIV-infected children using 1H NMR spectroscopy reveals perturbed metabolites that sustain during therapy

BACKGROUND

Perinatally HIV-infected children on anti-retroviral treatment (ART) are reported to have metabolic abnormalities such as dyslipidemia, lipodystrophy, and insulin resistance which potentially increase the risk of diabetes, kidney, liver and cardiovascular disease.

OBJECTIVE

To elucidate HIV-mediated metabolic complications that sustain even during ART in perinatally HIV-infected children.

METHOD

We have carried out metabolic profiling of the plasma of treatment-naïve and ART-suppressed perinatally HIV-infected children and uninfected controls using 1H nuclear magnetic resonance (NMR) spectroscopy followed by statistical analysis and annotation.

RESULT

Validated multivariate analysis showed clear distinction among our study groups. Our results showed elevated levels of lactate, glucose, phosphoenolpyruvic acid, propionic acid, 2-ketobutyric acid and tricarboxylic acid (TCA) cycle metabolites in untreated HIV-infected children compared to uninfected controls. ART normalized the levels of several metabolites, however the level of lactate, phosphoenolpyruvic acid, oxoglutaric acid, oxaloacetic acid, myoinositol and glutamine remained upregulated despite ART in HIV-infected children. Pathway analysis revealed perturbed propanoate metabolism, amino acid metabolism, glycolysis and TCA cycle in untreated and ART-suppressed HIV-infected children.

CONCLUSION

Developing therapeutic strategies targeting metabolic abnormalities may be beneficial for preventing diabetes, cardiovascular disease or other associated complications in perinatally HIV-infected children.

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.

Salivary Metabolomics: From Diagnostic Biomarker Discovery to Investigating Biological Function

Metabolomic profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, metabolomic analysis of saliva, the most readily-available human biofluid, has lagged. This review explores the history of saliva-based metabolomics and summarizes current knowledge of salivary metabolomics. Current applications of salivary metabolomics have largely focused on diagnostic biomarker discovery and the diagnostic value of the current literature base is explored. There is also a small, albeit promising, literature base concerning the use of salivary metabolomics in monitoring athletic performance. Functional roles of salivary metabolites remain largely unexplored. Areas of emerging knowledge include the role of oral host-microbiome interactions in shaping the salivary metabolite profile and the potential roles of salivary metabolites in oral physiology, e.g., in taste perception. Discussion of future research directions describes the need to begin acquiring a greater knowledge of the function of salivary metabolites, a current research direction in the field of the gut metabolome. The role of saliva as an easily obtainable, information-rich fluid that could complement other gastrointestinal fluids in the exploration of the gut metabolome is emphasized.

Application of NMR metabolomics to search for human disease biomarkers in blood

Recently, nuclear magnetic resonance spectroscopy (NMR)-based metabolomics analysis and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The purpose of these efforts is to identify unique metabolite biomarkers in a specific human disease so as to (1) accurately predict and diagnose diseases, including separating distinct disease stages; (2) provide insights into underlying pathways in the pathogenesis and progression of the malady and (3) aid in disease treatment and evaluate the efficacy of drugs. In this review we discuss recent developments in the application of NMR-based metabolomics in searching disease biomarkers in human blood samples in the last 5 years.

Multi-platform metabonomics unravel amino acids as markers of HIV/combination antiretroviral therapy-induced oxidative stress

Infection by the human immunodeficiency virus (HIV) elicits an immune response wherein neutrophils produce reactive oxygen species (ROS) to defend against pathogen invasion. Consequently, disproportionate levels of ROS in relation to antioxidants lead to oxidative stress (OS), which plays a key role in HIV disease progression and pathogenesis. There is a close relationship between oxidative stress status and HIV infection/progression, both separately and in the presence of combination antiretroviral therapy (cART). Biomarkers of oxidative stress present an additional means of monitoring HIV disease progression and/or management. Thus, the objective of this study was to apply untargeted nuclear magnetic resonance (NMR)-based metabonomics followed by targeted quantitative gas chromatography-mass spectrometry (GC/MS) analyses to identify predictors of oxidative stress in HIV infected individuals, with or without cART. Untargeted NMR-based metabonomics allowed a global profiling of metabolic perturbations in HIV-infected sera. The cohort consisted of 21 HIV-negative control subjects (HIV^-) and 113 HIV-infected individuals, of which 100 were on cART. Significant differences in metabolic features corresponding to changes in glucose, lipids, phenylalanine, glutamic acid, aspartic acid and branched amino acids were observed, which point to oxidative stress and insulin resistance. To further confirm oxidative stress, targeted GC/MS-based metabonomics, performed in succession, allowed for a quantitative description of a total of 9 oxidative stress-related metabolites. Significant up-regulation of aspartic acid, phenylalanine and glutamic acid were observed in the HIV-infected cohorts as compared to controls. Tryptophan and tyrosine were down-regulated whereas cystine levels were increased in HIV-infected and untreated individuals as compared to both HIV treated and negative control subjects. Pathway analysis also revealed 11 metabolic pathways to be significantly altered by infection and/or treatment. These pathways included aminoacyl-tRNA biosynthesis, nitrogen metabolism and phenylalanine, tyrosine and tryptophan biosynthesis. This pilot study demonstrated the use of multiplatform metabonomic strategies to elucidate metabolic markers that would be essential in predicting HIV/cART-induced oxidative stress. This could aid and contribute in HIV treatment and management programmes.

A Rapid Method for the Detection of Sarcosine Using SPIONs/Au/CS/SOX/NPs for Prostate Cancer Sensing

BACKGROUND

Sarcosine is an amino acid that is formed by methylation of glycine and is present in trace amounts in the body. Increased sarcosine concentrations in blood plasma and urine are manifested in sarcosinemia and in some other diseases such as prostate cancer. For this purpose, sarcosine detection using the nanomedicine approach was proposed. In this study, we have prepared superparamagnetic iron oxide nanoparticles (SPIONs) with different modified surface area. Nanoparticles (NPs) were modified by chitosan (CS), and sarcosine oxidase (SOX). SPIONs without any modification were taken as controls. Methods and Results: The obtained NPs were characterized by physicochemical methods. The size of the NPs determined by the dynamic light scattering method was as follows: SPIONs/Au/NPs (100⁻300 nm), SPIONs/Au/CS/NPs (300⁻700 nm), and SPIONs/Au/CS/SOX/NPs (600⁻1500 nm). The amount of CS deposited on the NP surface was found to be 48 mg/mL for SPIONs/Au/CS/NPs and 39 mg/mL for SPIONs/Au/CS/SOX/NPs, and repeatability varied around 10%. Pseudo-peroxidase activity of NPs was verified using sarcosine, horseradish peroxidase (HRP) and 3,3',5,5'-tetramethylbenzidine (TMB) as a substrate. For TMB, all NPs tested evinced substantial pseudo-peroxidase activity at 650 nm. The concentration of SPIONs/Au/CS/SOX/NPs in the reaction mixture was optimized to 0⁻40 mg/mL. Trinder reaction for sarcosine detection was set up at 510 nm at an optimal reaction temperature of 37 °C and pH 8.0. The course of the reaction was linear for 150 min. The smallest amount of NPs that was able to detect sarcosine was 0.2 mg/well (200 µL of total volume) with the linear dependence y = 0.0011x - 0.0001 and the correlation coefficient r = 0.9992, relative standard deviation (RSD) 6.35%, limit of detection (LOD) 5 µM. The suggested method was further validated for artificial urine analysis (r = 0.99, RSD 21.35%, LOD 18 µM). The calculation between the detected and applied concentrations showed a high correlation coefficient (r = 0.99). NPs were tested for toxicity and no significant growth inhibition was observed in any model system (S. cerevisiae, S. aureus, E. coli). The hemolytic activity of the prepared NPs was similar to that of the phosphate buffered saline (PBS) control. The reaction system was further tested on real urine specimens. Conclusion: The proposed detection system allows the analysis of sarcosine at micromolar concentrations and to monitor changes in its levels as a potential prostate cancer marker. The whole system is suitable for low-cost miniaturization and point-of-care testing technology and diagnostic systems. This system is simple, inexpensive, and convenient for screening tests and telemedicine applications.

Persistent metabolic changes in HIV-infected patients during the first year of combination antiretroviral therapy

The HIV-human metabolic relationship is a complex interaction convoluted even more by antiretroviral therapy (cART) and comorbidities. The ability of cART to undo the HIV induced metabolic dysregulation is unclear and under-investigated. Using targeted metabolomics and multiplex immune biomarker analysis, we characterized plasma samples obtained from 18 untreated HIV-1-infected adult patients and compared these to a non-HIV infected (n = 23) control population. The biogenic amine perturbations during an untreated HIV infection implicated altered tryptophan- nitrogen- and muscle metabolism. Furthermore, the lipid profiles of untreated patients were also significantly altered compared to controls. In untreated HIV infection, the sphingomyelins and phospholipids correlated negatively to markers of infection IP-10 and sIL-2R whereas a strong association was found between triglycerides and MCP-1. In a second cohort, we characterized plasma samples obtained from 28 HIV-1-infected adult patients before and 12 months after the start of cART, to investigate the immune-metabolic changes associated with cART. The identified altered immune-metabolic pathways of an untreated HIV infection showed minimal change after 12 months of cART. In conclusion, 12 months of cART impacts only mildly on the metabolic dysregulation underlying an untreated HIV infection and provide insights into the comorbidities present in virally suppressed HIV patients.

Metabolic characterization of plasma samples in HIV-1-infected individuals

AIM

To identify potential biomarkers for the diagnosis and monitoring of HIV-1 progression.

METHODS

19 subjects, diagnosed with HIV-1 infection in the follow-up, prospective, clinical cohort more than 6000 subjects from 2006, were incorporated into our study. The subjects included ten non-progressors and nine rapid progressors. The plasmas of subjects before HIV-1 seroconversion and after seroconversion were collected and analyzed with nontargeted metabolomics.

RESULTS

20:0-Glc-Campesterol and A-norgorgostanol could significantly distinguished after HIV-1 seroconversion from before HIV-1 seroconversion. PG(O-18:0/18:0) could totally distinguish the plasma of rapid progressor before seroconversion from that of nonprogressor before seroconversion.

CONCLUSION

20:0-Glc-Campesterol, A-norgorgostanol and  PG(O-18:0/18:0) could be potential biomarkers for the diagnosis and monitoring of HIV-1 progression.

HIV/HAART-associated oxidative stress is detectable by metabonomics

Chronic human immunodeficiency virus (HIV) infection, separately and in combination with highly active antiretroviral therapy (HAART) is closely associated with oxidative stress (OS). Most studies demonstrating redox imbalances in HIV-infected individuals have done so using conventional biochemical methodologies. The limited simultaneous detection of multiple OS markers within one sample is a major drawback of these methodologies and can be addressed through the use of metabonomics. HIV-metabonomic studies utilizing biofluids from HAART cohorts as the investigative source, are on the increase. Data from many of these studies identified metabolic markers indicative of HIV-induced OS, usually as an outcome of an untargeted metabonomics study. Untargeted studies cast a wide net for any and all detectable metabolites in complex mixtures. Given the prevalence of OS during HIV infection and antiviral treatment, it is perhaps not surprising that indicators of this malady would become evident during metabolite identification. At times, targeted studies for specific (non-OS) metabolites would also yield OS markers as an outcome. This review examines the findings of these studies by first providing the necessary background information on OS and the main ways in which free radicals/reactive oxygen species (ROS) produced during OS, cause biomolecular damage. This is followed by information on the biomarkers which come about as a result of free radical damage and the techniques used for assaying these stress indicators. The established links between elevated ROS and lowered antioxidants during HIV infection and the subsequent use of HAART is then presented followed by a review of the OS markers detected in HIV metabonomic studies to date. We identify gaps in HIV/HAART-associated OS research and finally suggest how these research gaps can be addressed through metabonomic analysis, specifically targeting the multiple markers of HIV-induced OS.

Metabolomics in Immunology Research

There is a growing appreciation that metabolic processes and individual metabolites can shape the function of immune cells and thereby play important roles in the outcome of immune responses. In this respect, the use of MS- and NMR spectroscopy-based platforms to characterize and quantify metabolites in biological samples has recently yielded important novel insights into how our immune system functions and has contributed to the identification of biomarkers for immune-mediated diseases. Here, these recent immunological studies in which metabolomics has been used and made significant contributions to these fields will be discussed. In particular the role of metabolomics to the rapidly advancing field of cellular immunometabolism will be highlighted as well as the future prospects of such metabolomic tools in immunology.

Phenotype-driven identification of modules in a hierarchical map of multifluid metabolic correlations

The identification of phenotype-driven network modules in complex, multifluid metabolomics data poses a considerable challenge for statistical analysis and result interpretation. This is the case for phenotypes with only few associations ('sparse' effects), but, in particular, for phenotypes with a large number of metabolite associations ('dense' effects). Herein, we postulate that examining the data at different layers of resolution, from metabolites to pathways, will facilitate the interpretation of modules for both the sparse and the dense cases. We propose an approach for the phenotype-driven identification of modules on multifluid networks based on untargeted metabolomics data of plasma, urine, and saliva samples from the German Study of Health in Pomerania (SHIP-TREND) study. We generated a hierarchical, multifluid map of metabolism covering both metabolite and pathway associations using Gaussian graphical models. First, this map facilitates a fundamental understanding of metabolism within and across fluids for our study, and can serve as a valuable and downloadable resource. Second, based on this map, we then present an algorithm to identify regulated modules that associate with factors such as gender and insulin-like growth factor I (IGF-I) as examples of traits with dense and sparse associations, respectively. We found IGF-I to associate at the rather fine-grained metabolite level, while gender shows well-interpretable associations at pathway level. Our results confirm that a holistic and interpretable view of metabolic changes associated with a phenotype can only be obtained if different layers of metabolic resolution from multiple body fluids are considered.

Metabolism consists of complex interactions across various organs and body fluids, which poses a substantial challenge for the analysis of metabolic data. To address this problem, Jan Krumsiek from Helmholtz Zentrum München and colleagues used metabolomics measurements of plasma, urine, and saliva from 1000 people to statistically reconstruct a map of interactions in human metabolism. Based on this map, a novel approach that identifies highly correlated biochemical modules that are associated with a given phenotype, was tested for gender and insulin-like growth factor I (IGF-I). The identified modules provided insights into the interaction between metabolome and phenotype that reach beyond what can be found by commonly used statistical approaches for metabolomics. The approach is generic and can be readily applied to new datasets by other colleagues from the field.

Identification of a discriminative metabolomic fingerprint of potential clinical relevance in saliva of patients with periodontitis using 1H nuclear magnetic resonance (NMR) spectroscopy

Periodontitis is characterized by the loss of the supporting tissues of the teeth in an inflammatory-infectious context. The diagnosis relies on clinical and X-ray examination. Unfortunately, clinical signs of tissue destruction occur late in the disease progression. Therefore, it is mandatory to identify reliable biomarkers to facilitate a better and earlier management of this disease. To this end, saliva represents a promising fluid for identification of biomarkers as metabolomic fingerprints. The present study used high-resolution ¹H-nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to identify the metabolic signature of active periodontitis. The metabolome of stimulated saliva of 26 patients with generalized periodontitis (18 chronic and 8 aggressive) was compared to that of 25 healthy controls. Principal Components Analysis (PCA), performed with clinical variables, indicated that the patient population was homogeneous, demonstrating a strong correlation between the clinical and the radiological variables used to assess the loss of periodontal tissues and criteria of active disease. Orthogonal Projection to Latent Structure (OPLS) analysis showed that patients with periodontitis can be discriminated from controls on the basis of metabolite concentrations in saliva with satisfactory explained variance (R2X = 0.81 and R2Y = 0.61) and predictability (Q2Y = 0.49, CV-AUROC = 0.94). Interestingly, this discrimination was irrespective of the type of generalized periodontitis, i.e. chronic or aggressive. Among the main discriminating metabolites were short chain fatty acids as butyrate, observed in higher concentrations, and lactate, γ-amino-butyrate, methanol, and threonine observed in lower concentrations in periodontitis. The association of lactate, GABA, and butyrate to generate an aggregated variable reached the best positive predictive value for diagnosis of periodontitis. In conclusion, this pilot study showed that 1H-NMR spectroscopy analysis of saliva could differentiate patients with periodontitis from controls. Therefore, this simple, robust, non-invasive method, may offer a significant help for early diagnosis and follow-up of periodontitis.

Metabolomics: Strategies to Define the Role of Metabolism in Virus Infection and Pathogenesis

Metabolomics is an analytical profiling technique for measuring and comparing large numbers of metabolites present in biological samples. Combining high-throughput analytical chemistry and multivariate data analysis, metabolomics offers a window on metabolic mechanisms. Because they intimately utilize and often rewire host metabolism, viruses are an excellent choice to study by metabolomics techniques. Studies of the effects of viruses on metabolism during replication in vitro and infection in animal models or human subjects have provided novel insights into these networks and provided new targets for therapy and biomarker development. Identifying the common metabolic pathways utilized by viruses has the potential to reveal those that can be targeted by broad-spectrum antiviral and vaccine approaches.

Plasma Metabolomics Biosignature According to HIV Stage of Infection, Pace of Disease Progression, Viremia Level and Immunological Response to Treatment

BACKGROUND

We evaluated plasma samples HIV-infected individuals with different phenotypic profile among five HIV-infected elite controllers and five rapid progressors after recent HIV infection and one year later and from 10 individuals subjected to antiretroviral therapy, five of whom were immunological non-responders (INR), before and after one year of antiretroviral treatment compared to 175 samples from HIV-negative patients. A targeted quantitative tandem mass spectrometry metabolomics approach was used in order to determine plasma metabolomics biosignature that may relate to HIV infection, pace of HIV disease progression, and immunological response to treatment.

RESULTS

Twenty-five unique metabolites were identified, including five metabolites that could distinguish rapid progressors and INRs at baseline. Severe deregulation in acylcarnitine and sphingomyelin metabolism compatible with mitochondrial deficiencies was observed. β-oxidation and sphingosine-1-phosphate-phosphatase-1 activity were down-regulated, whereas acyl-alkyl-containing phosphatidylcholines and alkylglyceronephosphate synthase levels were elevated in INRs. Evidence that elite controllers harbor an inborn error of metabolism (late-onset multiple acyl-coenzyme A dehydrogenase deficiency [MADD]) was detected.

CONCLUSIONS

Blood-based markers from metabolomics show a very high accuracy of discriminating HIV infection between varieties of controls and have the ability to predict rapid disease progression or poor antiretroviral immunological response. These metabolites can be used as biomarkers of HIV natural evolution or treatment response and provide insight into the mechanisms of the disease.

Serum metabolomics analysis of patients with chikungunya and dengue mono/co-infections reveals distinct metabolite signatures in the three disease conditions

Chikungunya and dengue are arboviral infections with overlapping clinical symptoms. A subset of chikungunya infection occurs also as co-infections with dengue, resulting in complications during diagnosis and patient management. The present study was undertaken to identify the global metabolome of patient sera infected with chikungunya as mono infections and with dengue as co-infections. Using nuclear magnetic resonance (NMR) spectroscopy, the metabolome of sera of three disease conditions, namely, chikungunya and dengue as mono-infections and when co-infected were ascertained and compared with healthy individuals. Further, the cohorts were analyzed on the basis of age, onset of fever and joint involvement. Here we show that many metabolites in the serum are significantly differentially regulated during chikungunya mono-infection as well as during chikungunya co-infection with dengue. We observed that glycine, serine, threonine, galactose and pyrimidine metabolisms are the most perturbed pathways in both mono and co-infection conditions. The affected pathways in our study correlate well with the clinical manifestation like fever, inflammation, energy deprivation and joint pain during the infections. These results may serve as a starting point for validations and identification of distinct biomolecules that could be exploited as biomarker candidates thereby helping in better patient management.

Metabolomics technology and their application to the study of the viral infection

OBJECTIVE

In the present review article we have summarized the use of the metabolomics approach to study the metabolic modifications occurring in several bio-fluids due to viral infections. The aim is to highlight the ability of metabolomics to find early fingerprints, which are related to the infections.

METHODS

The (1)H-NMR, UHPLC/MS/MS(2), UPLC/ESI-SYNAPT-HDMS, UPLC-Q-TOF-HDMS analyses were used for the determination of several metabolites representative of the viral infections. The data were analyzed by Principal Component Analysis (PCA), Partial Least Square Discriminant Analysis (PLS-DA) and by regression techniques.

RESULTS

The major changes were related to nucleotide, carbohydrates, lipids and amino acid metabolisms.

CONCLUSIONS

The metabolomics approach could be considered a viable option for characterization of the viral infection and for detecting on going differences in the bio-fluids composition.

A combined chemometric and quantitative NMR analysis of HIV/AIDS serum discloses metabolic alterations associated with disease status

Individuals infected with the human immunodeficiency virus (HIV) often suffer from concomitant metabolic complications. Treatment with antiretroviral therapy has also been shown to alter the metabolism of patients. Although chemometric analysis of nuclear magnetic resonance (NMR) spectra of human sera can distinguish normal sera (HIVneg) from HIV-infected sera (HIVpos) and sera from HIV-infected patients on antiretroviral therapy (ART), quantitative analysis of the discriminating metabolites and their relationship to disease status has yet to be determined. The objectives of the study were to analyze NMR spectra of HIVneg, HIVpos, and ART serum samples with a combination of chemometric and quantitative methods and to compare the NMR data with disease status as measured by viral load and CD4 count. High-resolution magic angle spinning (HRMAS) NMR spectroscopy was performed on HIVneg (N = 10), HIVpos (N = 10), and ART (N = 10) serum samples. Chemometric linear discriminant analysis classified the three groups of spectra with 100% accuracy. Concentrations of 12 metabolites were determined with a semi-parametric metabolite quantification method named high-resolution quantum estimation (HR-QUEST). CD4 count was directly associated with alanine (p = 0.008), and inversely correlated with both glutamine (p = 0.017) and glucose (p = 0.022) concentrations. A multivariate linear model using alanine, glutamine and glucose as covariates demonstrated an association with CD4 count (p = 0.038). The combined chemometric and quantitative analysis of the data disclosed previously unknown associations between specific metabolites and disease status. The observed associations with CD4 count are consistent with metabolic disorders that are commonly seen in HIV-infected patients.

Network-based approach for analyzing intra- and interfluid metabolite associations in human blood, urine, and saliva

Most studies investigating human metabolomics measurements are limited to a single biofluid, most often blood or urine. An organism's biochemical pool, however, comprises complex transboundary relationships, which can only be understood by investigating metabolic interactions and physiological processes spanning multiple parts of the human body. Therefore, we here propose a data-driven network-based approach to generate an integrated picture of metabolomics associations over multiple fluids. We performed an analysis of 2251 metabolites measured in plasma, urine, and saliva, from 374 participants of the Qatar Metabolomics Study on Diabetes (QMDiab). Gaussian graphical models (GGMs) were used to estimate metabolite-metabolite interactions on different subsets of the data set. First, we compared similarities and differences of the metabolome and the association networks between the three fluids. Second, we investigated the cross-talk between the fluids by analyzing correlations occurring between them. Third, we propose a framework for the analysis of medically relevant phenotypes by integrating type 2 diabetes, sex, age, and body mass index into our networks. In conclusion, we present a generic, data-driven network-based approach for structuring and visualizing metabolite correlations within and between multiple body fluids, enabling unbiased interpretation of metabolomics multifluid data.

Mid-ATR-FTIR spectroscopic profiling of HIV/AIDS sera for novel systems diagnostics in global health

Global health, whether in developed or developing countries, is in need of robust systems diagnostics for major diseases, such as HIV/AIDS, impacting the world populations. Fourier transform Infrared (FTIR) spectroscopy of serum is a quick and reagent-free methodology with which to analyze metabolic alterations such as those caused by disease or treatment. In this study, Attenuated Total Reflectance Fourier-Transform (ATR-FTIR) Spectroscopy was investigated as a means of distinguishing HIV-infected treatment-experienced (HIV(pos) ART(pos), n=39) and HIV-infected-treatment-naïve (HIV(pos) ART(neg), n=16) subjects from uninfected control subjects (n=30). Multivariate pattern recognition techniques, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), successfully distinguished sample classes, while univariate approaches identified significant differences (p<0.05) after Benjamini-Hochberg corrections. OPLS-DA discriminated between all groups with sensitivity, specificity, and accuracy of >90%. Compared to uninfected controls, HIV(pos) ART(pos) and HIV(pos) ART(neg) subjects displayed significant differences in spectral regions linked to lipids/fatty acids (3010 cm(-1)), carbohydrates (1299 cm(-1); 1498 cm(-1)), glucose (1035 cm(-1)), and proteins (1600 cm(-1); 1652 cm(-1)). These are all molecules shown by conventional biochemical analysis to be affected by HIV/ART interference. The biofluid metabolomics approach applied here successfully differentiated global metabolic profiles of HIV-infected patients and uninfected controls and detected potential biomarkers for development into indicators of host response to treatment and/or disease progression. Our findings therefore contribute to ongoing efforts for capacity-building in global health for robust omics science and systems diagnostics towards major diseases impacting population health.