ICP-MS/MS-Based Ionomics: A Validated Methodology to Investigate the Biological Variability of the Human Ionome

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

Metallomic Signatures of Lung Cancer and Chronic Obstructive Pulmonary Disease

Lung cancer (LC) is the leading cause of cancer deaths, and chronic obstructive pulmonary disease (COPD) can increase LC risk. Metallomics may provide insights into both of these tobacco-related diseases and their shared etiology. We conducted an observational study of 191 human serum samples, including those of healthy controls, LC patients, COPD patients, and patients with both COPD and LC. We found 18 elements (V, Al, As, Mn, Co, Cu, Zn, Cd, Se, W, Mo, Sb, Pb, Tl, Cr, Mg, Ni, and U) in these samples. In addition, we evaluated the elemental profiles of COPD cases of varying severity. The ratios and associations between the elements were also studied as possible signatures of the diseases. COPD severity and LC have a significant impact on the elemental composition of human serum. The severity of COPD was found to reduce the serum concentrations of As, Cd, and Tl and increased the serum concentrations of Mn and Sb compared with healthy control samples, while LC was found to increase Al, As, Mn, and Pb concentrations. This study provides new insights into the effects of LC and COPD on the human serum elemental profile that will pave the way for the potential use of elements as biomarkers for diagnosis and prognosis. It also sheds light on the potential link between the two diseases, i.e., the evolution of COPD to LC.

Plasma metallomics reveals potential biomarkers and insights into the ambivalent associations of elements with acute myocardial infarction

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Using a validated and efficient ICP-MS/MS-based workflow, a total of 30 metallomic features were profiled in a study comprising 101 AMI patients and 66 age-matched healthy controls. The metallomic features include 12 essential elements (Ca, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, Zn), 8 non-essential/toxic elements (Al, As, Ba, Cd, Cr, Ni, Rb, Sr, U, V), and 10 clinically relevant element-pair product/ratios (Ca/Mg, Ca×P, Cu/Se, Cu/Zn, Fe/Cu, P/Mg, Na/K, Zn/Se). Preliminary linear regression with feature selection confirmed smoking status as a predominant determinant for the non-essential/toxic elements, and revealed potential routes of action. Univariate assessments with adjustments for covariates revealed insights into the ambivalent relationships of Cu, Fe, and P with AMI, while also confirming cardioprotective associations of Se. Also, beyond their roles as risk factors, Cu and Se may be involved in the response mechanism in AMI onset/intervention, as demonstrated via longitudinal data analysis with 2 additional time-points (1-/6-month follow-up). Finally, based on both univariate tests and multivariate classification modelling, potentially more sensitive markers measured as element-pair ratios were identified (e.g., Cu/Se, Fe/Cu). Overall, metallomics-based biomarkers may have utility for AMI prediction.

A simple, rapid method for simultaneous determination of multiple elements in serum by using an ICP-MS equipped with collision cell

We developed an inductively coupled plasma mass spectrometry method for testing 23 elements, namely, Mg, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Mo, Cd, Sn, Sb, Ba, W, Tl, Pb, and U, in human serum. The serum samples were analyzed after diluting 1/25 with 0.5% nitric acid, 0.02% Triton-X-100, and 2% methanol. Sc, In, Y, Tb, and Bi were assigned internal standards to correct the baseline drift and matrix interference. The kinetic energy discrimination mode of the instrument with helium gas as the collision gas eliminated polyatomic interference. All 23 elements exhibited excellent linearity in their testing range, with a coefficient of determination ≥ 0.9996. The limits of detection of the 23 elements were within the range of 0.0004-0.2232 µg/L. The intra- and inter-day precision (relative standard deviation) were < 12.19%. The recoveries of the spiked standard for all elements were 88.98-109.86%. Among the 23 elements of the serum reference materials, the measured results of Mg, Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, and Se were within the specified range of the certificate, and the results of the other elements were also satisfactory. The developed method was simple, rapid, and effective, and only 60 μL sample was consumed. A total of 1000 serum samples from healthy individuals were randomly selected from the Henan Rural Cohort, which reflects the status of serum elements in rural adults from the Northern Henan province of central China.

Simultaneous quantification of 70 elements in biofluids within 5 min using inductively coupled plasma mass spectrometry to reveal elementomic phenotypes of healthy Chinese adults

High-throughput quantification of the composition of all chemical elements (elementome) in biological samples is essential for understanding their diverse functions in large cohort studies. We, here, established an ICP-MS method to simultaneously quantify 70 elements in 50 μL biofluids within 5 min. This validated method had excellent quantification linearity (R² > 0.998), sensitivity (with LOD as low as 1.0 ng/L), precision (CV<15%), accuracy (|RE|<20% except Hg), recovery (80-120%), throughput and coverage with minute samples. The method also showed good applicability to multiple biofluids including human serum, plasma, urine and goat serum samples. By using this method, we furture measured 70 elements in blood plasma samples from 758 Chinese adult participants and established the first reference intervals for the concentration of these elements from 127 healthy adults in this population. This offers a high-throughput quantitative elementomics method to define population elementomic phenotypes and for investigating the diverse biological functions of many elements in multiple biological matrices.

Targeted and untargeted metabolomic analysis of Procambarus clarkii exposed to a "chemical cocktail" of heavy metals and diclofenac

Water pollution poses an important problem, but limited information is available about the joined effects of xenobiotics of different chemical groups to evaluate the real biological response. Procambarus clarkii (P. clarkii) has been demonstrated to be a good bioindicator for assessing the quality of aquatic ecosystems. In this work, we studied the bioaccumulation of cadmium (Cd), arsenic (As) and diclofenac (DCF) in different tissues of P. clarkii during 21 days after the exposure to a "chemical cocktail" of As, Cd and DCF, and until 28 days considering a depuration period. In addition, a combined untargeted and targeted metabolomic analysis was carried out to delve the metabolic impairments caused as well as the metabolization of DCF. Our results indicate that As and Cd were mainly accumulated in the hepatopancreas followed by gills and finally abdominal muscle. As and Cd show a general trend to increase the concentration throughout the exposure experience, while a decrease in the concentration of these elements is observed after 7 days of the depuration process. This is also the case in the abdominal muscle for Cd, but not for As and DCF, which increased the concentration in this tissue in the depuration phase. The hepatopancreas showed the greatest number of metabolic pathways affected. Thus, we observed a crucial bioaccumulation of xenobiotics and impairments of metabolites in different tissues. This is the first study combining the exposure to metals and pharmaceutically active compounds in P. clarkii by untargeted metabolomics including the biotransformation of DCF.

Artificial Intelligence in Functional Food Ingredient Discovery and Characterisation: A Focus on Bioactive Plant and Food Peptides

Scientific research consistently demonstrates that diseases may be delayed, treated, or even prevented and, thereby, health may be maintained with health-promoting functional food ingredients (FFIs). Consumers are increasingly demanding sound information about food, nutrition, nutrients, and their associated health benefits. Consequently, a nutrition industry is being formed around natural foods and FFIs, the economic growth of which is increasingly driven by consumer decisions. Information technology, in particular artificial intelligence (AI), is primed to vastly expand the pool of characterised and annotated FFIs available to consumers, by systematically discovering and characterising natural, efficacious, and safe bioactive ingredients (bioactives) that address specific health needs. However, FFI-producing companies are lagging in adopting AI technology for their ingredient development pipelines for several reasons, resulting in a lack of efficient means for large-scale and high-throughput molecular and functional ingredient characterisation. The arrival of the AI-led technological revolution allows for the comprehensive characterisation and understanding of the universe of FFI molecules, enabling the mining of the food and natural product space in an unprecedented manner. In turn, this expansion of bioactives dramatically increases the repertoire of FFIs available to the consumer, ultimately resulting in bioactives being specifically developed to target unmet health needs.

IonFlow: a galaxy tool for the analysis of ionomics data sets

INTRODUCTION

Inductively coupled plasma mass spectrometry (ICP-MS) experiments generate complex multi-dimensional data sets that require specialist data analysis tools.

OBJECTIVE

Here we describe tools to facilitate analysis of the ionome composed of high-throughput elemental profiling data.

METHODS

IonFlow is a Galaxy tool written in R for ionomics data analysis and is freely accessible at https://github.com/wanchanglin/ionflow . It is designed as a pipeline that can process raw data to enable exploration and interpretation using multivariate statistical techniques and network-based algorithms, including principal components analysis, hierarchical clustering, relevance network extraction and analysis, and gene set enrichment analysis.

RESULTS AND CONCLUSION

The pipeline is described and tested on two benchmark data sets of the haploid S. Cerevisiae ionome and of the human HeLa cell ionome.

An Overview of Cell-Based Assay Platforms for the Solute Carrier Family of Transporters

The solute carrier (SLC) superfamily represents the biggest family of transporters with important roles in health and disease. Despite being attractive and druggable targets, the majority of SLCs remains understudied. One major hurdle in research on SLCs is the lack of tools, such as cell-based assays to investigate their biological role and for drug discovery. Another challenge is the disperse and anecdotal information on assay strategies that are suitable for SLCs. This review provides a comprehensive overview of state-of-the-art cellular assay technologies for SLC research and discusses relevant SLC characteristics enabling the choice of an optimal assay technology. The Innovative Medicines Initiative consortium RESOLUTE intends to accelerate research on SLCs by providing the scientific community with high-quality reagents, assay technologies and data sets, and to ultimately unlock SLCs for drug discovery.

1,135 ionomes reveal the global pattern of leaf and seed mineral nutrient and trace element diversity in Arabidopsis thaliana

Soil is a heterogeneous reservoir of essential elements needed for plant growth and development. Plants have evolved mechanisms to balance their nutritional needs based on availability of nutrients. This has led to genetically based variation in the elemental composition, the 'ionome', of plants, both within and between species. We explore this natural variation using a panel of wild-collected, geographically widespread Arabidopsis thaliana accessions from the 1001 Genomes Project including over 1,135 accessions, and the 19 parental accessions of the Multi-parent Advanced Generation Inter-Cross (MAGIC) panel, all with full-genome sequences available. We present an experimental design pipeline for high-throughput ionomic screenings and analyses with improved normalisation procedures to account for errors and variability in conditions often encountered in large-scale, high-throughput data collection. We report quantification of the complete leaf and seed ionome of the entire collection using this pipeline and a digital tool, Ion Explorer, to interact with the dataset. We describe the pattern of natural ionomic variation across the A. thaliana species and identify several accessions with extreme ionomic profiles. It forms a valuable resource for exploratory genetic mapping studies to identify genes underlying natural variation in leaf and seed ionome and genetic adaptation of plants to soil conditions.

Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.

Integrated renal metabolomic and metallomic profiling revealed protective effect and metabolic mechanism of Gushudan on glucocorticoid-induced osteoporotic rat based on GC-MS and ICP-MS

Based on the traditional Chinese medicine theory, kidney is considered to govern the bones and dominate the store of essence ('jing' in Chinese). Gushudan (GSD) is a traditional Chinese medicine prescription for the treatment osteoporosis in the clinic and is beneficial for improving kidney function and strengthening bone in vivo. This study aims to reveal the renal metabolic profiling of glucocorticoid-induced osteoporosis (GIOP) rats and the potential preventive effect of GSD based on an integrative metabolomic and metallomic approach. Gas chromatography-mass spectrometry (GC-MS) and inductively coupled plasma mass spectrometry (ICP-MS) were combined for the investigation of renal metabolomic and metallomic profiling. In the metabolomic analysis, 17 potential biomarkers were found to be related to GIOP, such as glucose, malate, γ-aminobutyric acid and arachidonic acid. And seven metallic elements, including Zn, Mn, Se, Fe, Mo, As and Ba, were identified in rat kidney tissue in the metallomic analysis. The major metabolic pathways included aerobic glycolysis, and neurotransmitter amino acids metabolism. It was worth mentioning that the levels of trace metal elements (Zn, Mn, Se, Fe, As and Ba) significantly reduced in the model group, while the contents of Zn, Mn, Se, Fe and As were elevated after administration of GSD. Finally, a correlation metabolic regulatory network and the metabolic pathways associated with trace metal elements were further investigated to illuminate the role of potential biomarkers and trace metal elements in GIOP rats. These variations of potential biomarkers and trace metal elements suggested the existence of kidney damage and metabolic disorder in GIOP rats, which indicated a close relationship between bone and kidney in vivo. Moreover, the integrated renal metabolomic and metallomic profiling could be as an effective supplementary measure to the plasma and urine metabolomic research, and it was helpful to further understand the holistic formation process of osetoporosis and the potential preventive effects of GSD on GIOP rats.

Multielemental Analysis of Low-Volume Samples Reveals Cancer-Specific Profile in Serum and Sorted Immune Cells

We developed and validated a reliable, robust, and easy-to-implement quantitative method for multielemental analysis of low-volume samples. Our ICP-MS-based method comprises the analysis of 20 elements (Mg, P, S, K, Ca, V, Cr, Mn, Fe, Co, Cu, Zn, Se, Br, Rb, Sr, Mo, I, Cs, and Ba) in 10 μL of serum and 12 elements (Mg, S, Mn, Fe, Co, Cu, Zn Se, Br, Rb, Mo, and Cs) in less than 250 000 cells. As a proof-of-concept, we analyzed the elemental profiles of serum and sorted immune T cells derived from naı̈ve and tumor-bearing mice. The results indicate a tumor systemic effect on the elemental profiles of both serum and T cells. Our approach highlights promising applications of multielemental analysis in precious samples such as rare cell populations or limited volumes of biofluids that could provide a deeper understanding of the essential role of elements as cofactors in biological and pathological processes.

Microelement composition of serum in Dolgans, indigenous inhabitants of the Russian Arctic, in the conditions of industrial development of territories

The geochemical conditions of landscapes are the content in the environment of certain chemical elements and their compounds, the lack or excess of which causes deviations in the state of human health. This problem has arisen in connection with the extraction of alluvial diamonds and the forthcoming development of the Tomtor deposit of rare-earth metals in the territories where the indigenous peoples of the North live. The study included 107 indigenous people of the North, belonging to the ethnic group of Dolgans living in the village of Yuryung-Khaya, Anabar district, Yakutia of Russia. The method of mass spectrometry was used to study the content of 13 trace elements in blood serum (P, Sc, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Rb, Sr, Cs, Pb). The study revealed an increase in the content of the macroelement phosphorus (148 mg/L) and trace elements of chromium (277 μg/L), manganese (133 μg/L), iron (5219 μg/L), nickel (57 μg/L) in serum of Dolgans, which may affect the development of diseases of the cardiovascular system and other diseases among indigenous inhabitants of the Arctic under conditions of industrial development of territories.

Advances in lung cancer biomarkers: The role of (metal-) metabolites and selenoproteins

Lung cancer (LC) is the second most common cause of death in men after prostate cancer, and the third most recurrent type of tumor in women after breast and colon cancers. Unfortunately, when LC symptoms begin to appear, the disease is already in an advanced stage and the survival rate only reaches 2%. Thus, there is an urgent need for early diagnosis of LC using specific biomarkers, as well as effective therapies and strategies against LC. On the other hand, the influence of metals on more than 50% of proteins is responsible for their catalytic properties or structure, and their presence in molecules is determined in many cases by the genome. Research has shown that redox metal dysregulation could be the basis for the onset and progression of LC disease. Moreover, metals can interact between them through antagonistic, synergistic and competitive mechanisms, and for this reason metals ratios and correlations in LC should be explored. One of the most studied antagonists against the toxic action of metals is selenium, which plays key roles in medicine, especially related to selenoproteins. The study of potential biomarkers able to diagnose the disease in early stage is conditioned by the development of new analytical methodologies. In this sense, omic methodologies like metallomics, proteomics and metabolomics can greatly assist in the discovery of biomarkers for LC early diagnosis.

The chemical exposome of type 2 diabetes mellitus: Opportunities and challenges in the omics era

Type 2 diabetes mellitus (T2DM) is a global silent killer, with > 450 million affected adults worldwide. A diverse array of non-modifiable risk factors such as family history, age (> 45 yrs), race/ethnicity, genetics, and history of gestational diabetes and modifiable risk factors such as physical inactivity, high body fat, body weight, high blood pressure, and high cholesterol for progression of prediabetes to T2DM. Given, that the modern world human population is constantly exposed to multiple stressors in the form of physical (i.e., sound, weather etc.) and chemical environment (i.e., diet, pollutants etc.), industrialization, and modernization has led to form a basis for exposomal correlation with T2DM incidence. Over the past decade, there have been emerging reports on association of levels of persistent organic pollutants (POPs), phthalates, antibiotics, drugs, air pollution, pesticides, and heavy metals with T2DM. In this review, we discuss the well known chemical exposome that has been associated with T2DM; the tools and approaches to capture this chemical exposome, and future opportunities and challenges in this exciting area of research. We further provide a window of thoughts, whether omics technologies can help fill in the gaps to help provide high throughput exposomics datasets in an unbiased manner to help understand T2DM pathophysiology in the context of industrialization, drastic lifestyle changes, urbanization, and pollution. We also discuss and provide guidelines/call to action for future exposomics studies investigating the association of T2DM with exposomes in the context of both epidemiological and experimental approaches.

Systems Biology of Selenium and Complex Disease

Selenium is an essential trace element for maintenance of overall health, whose deficiency and dyshomeostasis have been linked to a variety of diseases and disorders. The majority of previous researches focused on characterization of genes encoding selenoproteins or proteins involved in selenium metabolism as well as their functions. Many studies in humans also investigated the relationship between selenium and complex diseases, but their results have been inconsistent. In recent years, systems biology and "-omics" approaches have been widely used to study complex and global variations of selenium metabolism and function in physiological and different pathological conditions. The present paper reviews recent progress in large-scale and systematic analyses of the relationship between selenium status or selenoproteins and several complex diseases, mainly including population-based cohort studies and meta-analyses, genetic association studies, and some other omics-based studies. Advances in ionomics and its application in studying the interaction between selenium and other trace elements in human health and diseases are also discussed.

Essential Mineral Intake During Pregnancy and Its Association With Maternal Health and Birth Outcomes in South East Queensland, Australia

Micronutrient supplements are often recommended during pregnancy, yet their role and necessity remain poorly understood in the Australian population. This study aimed to determine the essential mineral intake of a population of pregnant women in South East Queensland and investigate the effects of supplements on their micronutrient status and birth outcomes. Women completing the Oral Glucose Tolerance Test at two South East Queensland hospitals between 180 and 210 days gestation provided fasting blood samples and dietary data using the Maternal Outcomes and Nutrition Tool (n = 127). Birth outcomes were sourced from medical records. Serum elemental profiles were determined by inductively coupled plasma mass spectrometry (ICP-MS) analysis. Intake of 8 essential minerals was compared with Australian dietary recommendations; matched serum mineral levels were compared with the current Queensland pregnancy reference ranges. Data were examined using cross-sectional cohort design and independent sample t-tests. Supplement use had no significant influence on serum values of trace elements or the incidence of hypertensive disorders, gestational diabetes, preterm birth or infant birthweight. Dietary selenium, zinc and iodine were significantly higher in women birthing beyond 41 completed weeks; selenium (P = .026) and zinc (P = .034) both made unique contributions to the regression models when controlling for confounders. Women exhibited adequate to excessive serum micronutrient levels compared with pregnancy reference ranges, a finding consistent with dietary intake calculations. Data suggest that excessive essential mineral intake contributed to prolonged pregnancy in this cohort, supporting previous studies in this population. Further research is required to determine individual needs and eliminate the potential for harm before recommending pregnancy supplements.

A quick and simple method for the determination of six trace elements in mammalian serum samples using ICP-MS/MS

In order to assess the individual trace element status of humans for either medical or scientific purposes, amongst others, blood serum levels are determined. Furthermore, animal models are used to study interactions of trace elements. Most published methods require larger amounts (500-1000 μL) of serum to achieve a reliable determination of multiple trace elements. However, oftentimes, these amounts of serum cannot be dedicated to a single analysis and the amount available for TE-determination is much lower. Therefore, a published ICP-MS/MS method for trace element determination in serum was miniaturized, optimized and validated for the measurement of Mn, Fe, Cu Zn, I and Se in as little as 50 μL of human and murine serum and is presented in this work. For validation, recoveries of multiple LOTs and levels from commercially available human reference serum samples were determined, intra- and inter-day variations were assessed and limits of detection and quantification determined. It is shown, that the method is capable of giving accurate and reproducible results for all six elements within the relevant concentration ranges for samples from humans living in central Europe as well as from laboratory mice. As a highlight, the achieved limits of detection and quantification for Mn were found to be at 0.02 μg/L serum and 0.05 μg/L serum, respectively, while using an alkaline diluent for the parallel determination of iodine.

Determination of Zn, Cu and Fe in human patients' serum using micro-sampling ICP-MS and sample dilution

A high-throughput, sensitive and rapid method was developed for the determination of Zn, Cu and Fe in small volumes (30 μL) of human serum using inductively coupled plasma mass spectrometry (ICP-MS). The sample preparation procedure employed simple 100-fold dilution of the serum samples with 1.0% butanol, 0.5% v/v ammonia, 0.02% v/v Triton X-100 and 0.01% v/v HNO₃. The reliability of the method was evaluated using serum UTAK certified reference material, and the results matched well with the certified values. The method was applied to determine Zn, Cu and Fe in 81 human serum samples from participants in Alzheimer disease (AD) and age-related macular degeneration (AMD) studies. No significant differences were found in Zn and Cu levels between age matched controls, AD and AMD patients. Whilst iron levels appeared marginally higher in the AMD group, compared with the AD group, iron showed larger overall variability than the other two elements.

Integrated metallomic and metabolomic profiling of plasma and tissues provides deep insights into the protective effect of raw and salt-processed Achyranthes bidentata Blume extract in ovariectomia rats

ETHNOPHARMACOLOGICAL RELEVANCE

Achyranthes bidentata Blume (AB) is a well-known traditional Chinese medicine for treating osteoporosis and bone fracture. In the current, researches on pharmacological mechanism of AB mostly focused on molecular pathways, knowledge about its metabolic signatures is largely unclear. This study aims to develop an integrative metabolomics and metallomic approach for deciphering the biochemical basis of anti-osteoporosis effects of raw and salt-processed AB.

METHOD

Gas chromatography-mass spectrometry (GC-MS) and inductively coupled plasma mass spectrometry (ICP-MS) were combined for metabolomic and metallomic profiling of rats serum, liver and kidney derived from the sham group, model group, E2, raw and salt-processed AB treated groups. Meanwhile, micro-CT and biomechanical analysis were carried out to ensure the success of the osteoporosis model and to validate the anti-osteoporosis effect of raw and salt-processed AB. Partial least squares discriminant analysis (PLS-DA) was employed to screen potential biomarkers and the MetaboAnalyst and KEGG PATHWAY Database were used to investigate the metabolic pathway.

RESULTS

Raw and salt-processed AB protected the rats against osteoporosis, as evidenced by the restoration of the alkaline phosphatase activity, osteocalcin concentration, urine calcium/creatinine ratio and urine phosphorus/creatinine ratio. The combination of PCA and PLS-DA revealed deviations in ninety-four differential biomarkers between raw AB treated group and model group. The identified biomarkers were primarily engaged in the metabolic pathways including galactose metabolism, urea cycle, arginine and proline metabolism, alanine metabolism, lactose degradation, ammonia recycling and glycine and serine metabolism. The levels of these biomarkers showed significant alterations and a tendency to be restored to normal values in raw and salt-processed AB treated osteoporosis rats. Of note, the levels of trace elements, such as Zn, Se, Mn, Cu and Fe, were elevated after raw and salt-processed AB treatment. Finally, a correlation network diagram was constructed to show the biomarkers perturbed by raw and salt-processed AB.

CONCLUSION

Our findings indicate that raw and salt-processed AB has positive effects on osteoporosis rats. Meanwhile, metabolomic and metallomic method coupled with metabolites enrichment analysis and pattern recognition serves as a useful tool for revealing the action mechanism of traditional Chinese medicine.

Sex-Specific Associations of Blood-Based Nutrient Profiling With Body Composition in the Elderly

The intake of adequate amounts and types of nutrients is key for sustaining health and a good quality of life, particularly in the elderly population. There is considerable evidence suggesting that physiological changes related to age and sex modify nutritional needs, and this may be related to age-associated changes in body composition (BC), specifically in lean and fat body mass. However, there is a clear lack of understanding about the association of nutrients in blood and BC parameters in the elderly. This study investigated the relationships among blood nutrients (amino acids, fatty acids, major elements, trace-elements, and vitamins), BC and nutrient intake in a population of 176 healthy male and female Italian adults between the ages of 65 and 79 years. 89 blood markers, 77 BC parameters and dietary intake were evaluated. Multivariate data analysis was applied to infer relationships between datasets. As expected, the major variability between BC and the blood nutrient profile (BNP) observed was related to sex. Aside from clear sex-specific differences in BC, female subjects had higher BNP levels of copper, copper-to-zinc ratio, phosphorous and holotranscobalamin II and lower concentrations of branched-chain amino acids (BCAAs) and proline. Fat mass, percentage of fat mass, percentage of lean mass and the skeletal muscle index (SMI) correlated the most with BNP in both sexes. Our data showed positive correlations in male subjects among ethanolamine, glycine, albumin, and sulfur with SMI, while palmitoleic acid and oleic acid exhibited negative correlations. This differed in female subjects, where SMI was positively associated with albumin, folic acid and sulfur, while CRP, proline and cis-8,11,14-eicosatrienoic acid were negatively correlated. We investigated the influence of diet on the observed BNP and BC correlations. Intriguingly, most of the components of the BNP, except for folate, did not exhibit a correlation with nutrient intake data. An understanding of the physiological and biochemical processes underpinning the observed sex-specific correlations between BNP and BC could help in identifying nutritional strategies to manage BC-changes in aging. This would contribute to a deeper understanding of aging-associated nutritional needs with the aim of helping the elderly population to maintain metabolic health.

High-Throughput Metabolomics by 1D NMR

Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one of the -omic sciences, it relates to biology, physiology, pathology and medicine; but metabolites are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification and quantitation in complex biological matrices requires a solid chemical ground. With respect to for example, DNA, metabolites are much more prone to oxidation or enzymatic degradation: we can reconstruct large parts of a mammoth's genome from a small specimen, but we are unable to do the same with its metabolome, which was probably largely degraded a few hours after the animal's death. Thus, we need standard operating procedures, good chemical skills in sample preparation for storage and subsequent analysis, accurate analytical procedures, a broad knowledge of chemometrics and advanced statistical tools, and a good knowledge of at least one of the two metabolomic techniques, MS or NMR. All these skills are traditionally cultivated by chemists. Here we focus on metabolomics from the chemical standpoint and restrict ourselves to NMR. From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population-wide health screening technique.

Nutrient pattern analysis in critically ill patients using Omics technology (NAChO) - Study protocol for a prospective observational study

INTRODUCTION

Intensive care unit-acquired weakness (ICU-AW) is often observed in critically ill patients with prolonged intensive care unit (ICU) stay. We hypothesized that evolving metabolic abnormalities during prolonged ICU stay are reflected by changing nutrient patterns in blood, urine and skeletal muscle, and that these patterns differ in patients with/without ICU-AW and between patients with/without sepsis.

METHODS

In a prospective single-center observational trial, we aim to recruit 100 critically ill patients (ICU length of stay ≥ 5 days) with severe sepsis/septic shock ("sepsis group", n = 50) or severe head trauma/intracerebral hemorrhage ("CNS group", n = 50). Patients will be sub-grouped for presence or absence of ICU-AW as determined by the Medical Research Council sum score. Blood and urine samples will be collected and subjected to comprehensive nutrient analysis at different time points by targeted quantitative mass spectrometric methods. In addition, changes in muscular tissue (biopsy, when available), muscular architecture (ultrasound), electrophysiology, body composition analyses (bioimpedance, cerebral magnetic resonance imaging), along with clinical status will be assessed. Patients will be followed-up for 180 and 360 days including assessment of quality of life.

DISCUSSION

Key objective of this trial is to assess changes in nutrient pattern in blood and urine over time in critically ill patients with/without ICU-AW by using quantitative nutrient analysis techniques. Peer-reviewed published NAChO data will allow for a better understanding of metabolic changes in critically ill patients on standard liquid enteral nutrition and will likely open up new avenues for future therapeutic and nutritional interventions.

The guard cell ionome: Understanding the role of ions in guard cell functions

The ionome is critical for plant growth, productivity, defense, and it eventually affects human food quantity and quality. Located on the leaf surface, stomatal guard cells are critical gatekeepers for water, gas, and pathogens. Insights form ionomics (metallomics) is imperative as we enter an omics-driven systems biology era where an understanding of guard cell function and physiology is advanced through efforts in genomics, transcriptomics, proteomics, and metabolomics. While the roles of major cations (K, Ca) and anions (Cl) are well known in guard cell function, the related physiology, movement and regulation of trace elements, metal ions, and heavy metals are poorly understood. The majority of the information on the role of trace elements in guard cells emanates from classical feeding experiments, field or in vitro fortification, micropropagation, and microscopy studies, while novel insights are available from limited metal ion transporter and ion channel studies. Given the rejuvenated and recent interest in the constantly changing ionome in plant mineral balance and eventually in human nutrition and health, we looked into the far from established guard cell ionome in lieu of the modern omics era of high throughput research endeavors. Newer technologies and tools i.e., high resolution mass spectrometry, advanced imaging, and phenomics are now available to delve into the guard cell ionomes. In this review, research efforts on guard cell ionomes were collated and categorized, and we highlight the underlying role of the largely unknown ionome in guard cell function towards a systems physiology understanding of plant health and productivity.

Sulfur speciation by HPLC-ICPQQQMS in complex human biological samples: taurine and sulfate in human serum and urine

The advent of the triple quadrupole technology to the inductively coupled plasma mass spectrometry (ICPMS) technique has allowed a strong improvement in the accuracy and detection limits of ICPMS for non-metal elements such as sulfur by removing major polyatomic interferences. Up to now, there has been no report utilizing this development for sulfur speciation in complex human biological matrices. In the present report, we show the success of HPLC-ICPQQQMS for the simultaneous determination of two major sulfur metabolites, taurine and sulfate, in human urine and serum, by direct injection without the need for sample clean-up. The optimized chromatographic method was validated, tested for robustness, and applied for investigating the intra-individual variability in taurine urinary excretion in eight healthy volunteers over a period of 8 weeks. The limit of detection and limit of quantification for taurine determination was found to be 0.2 and 0.7 pmol, respectively. The concentrations found in the analyzed group of urine samples (n = 64) had a range, mean, and SD of 0.6-99, 20.4, and 23.2 μg mL-1 for taurine, and 115-1373, 616, and 259 μg mL-1 for sulfate. Taurine was found to exhibit a much higher intra-individual variability than sulfate. The developed method can be applied in large-scale epidemiological studies and clinical studies in order to establish the potential cardioprotective effects of taurine. Graphical abstract ᅟ.

Development, validation and application of an ICP-MS/MS method to quantify minerals and (ultra-)trace elements in human serum

Multi-element determination in human samples is very challenging. Especially in human intervention studies sample volumes are often limited to a few microliters and due to the high number of samples a high-throughput is indispensable. Here, we present a state-of-the-art ICP-MS/MS-based method for the analysis of essential (trace) elements, namely Mg, Ca, Fe, Cu, Zn, Mo, Se and I, as well as food-relevant toxic elements such as As and Cd. The developed method was validated regarding linearity of the calibration curves, method LODs and LOQs, selectivity and trueness as well as precision. The established reliable method was applied to quantify the element serum concentrations of participants of a human intervention study (LeguAN). The participants received isocaloric diets, either rich in plant protein or in animal protein. While the serum concentrations of Mg and Mo increased in participants receiving the plant protein-based diet (above all legumes), the Se concentration in serum decreased. In contrast, the animal protein-based diet, rich in meat and dairy products, resulted in an increased Se concentration in serum.

Use of Metabolomics in Improving Assessment of Dietary Intake

BACKGROUND

Nutritional metabolomics is rapidly evolving to integrate nutrition with complex metabolomics data to discover new biomarkers of nutritional exposure and status.

CONTENT

The purpose of this review is to provide a broad overview of the measurement techniques, study designs, and statistical approaches used in nutrition metabolomics, as well as to describe the current knowledge from epidemiologic studies identifying metabolite profiles associated with the intake of individual nutrients, foods, and dietary patterns.

SUMMARY

A wide range of technologies, databases, and computational tools are available to integrate nutritional metabolomics with dietary and phenotypic information. Biomarkers identified with the use of high-throughput metabolomics techniques include amino acids, acylcarnitines, carbohydrates, bile acids, purine and pyrimidine metabolites, and lipid classes. The most extensively studied food groups include fruits, vegetables, meat, fish, bread, whole grain cereals, nuts, wine, coffee, tea, cocoa, and chocolate. We identified 16 studies that evaluated metabolite signatures associated with dietary patterns. Dietary patterns examined included vegetarian and lactovegetarian diets, omnivorous diet, Western dietary patterns, prudent dietary patterns, Nordic diet, and Mediterranean diet. Although many metabolite biomarkers of individual foods and dietary patterns have been identified, those biomarkers may not be sensitive or specific to dietary intakes. Some biomarkers represent short-term intakes rather than long-term dietary habits. Nonetheless, nutritional metabolomics holds promise for the development of a robust and unbiased strategy for measuring diet. Still, this technology is intended to be complementary, rather than a replacement, to traditional well-validated dietary assessment methods such as food frequency questionnaires that can measure usual diet, the most relevant exposure in nutritional epidemiologic studies.