Unravelling the metabolic alterations of liver damage induced by thirdhand smoke

Interplay of Oxidative Stress, Gut Microbiota, and Nicotine in Metabolic-Associated Steatotic Liver Disease (MASLD)

Oxidative stress has been described as one of the main drivers of intracellular damage and metabolic disorders leading to metabolic syndrome, a major health problem worldwide. In particular, free radicals alter lipid metabolism and promote lipid accumulation in the liver, existing in the hepatic facet of metabolic syndrome, the metabolic dysfunction-associated steatotic liver disease (MASLD). Recent literature has highlighted how nicotine, especially if associated with a high-fat diet, exerts a negative effect on the induction and progression of MASLD by upregulating inflammation and increasing oxidative stress, abdominal fat lipolysis, and hepatic lipogenesis. Moreover, considerable evidence shows the central role of intestinal dysbiosis in the pathogenesis of MASLD and the impact of nicotine-induced oxidative stress on the gut microbiome. This results in an intricate network in which oxidative stress stands at the intersection point between gut microbiome, nicotine, and MASLD. The aim of this review is to delve into the molecular mechanisms linking tobacco smoking and MASLD, focusing on nicotine-induced microbiota modifications and their impact on MASLD development.

Spatial metabolomics and its application in the liver

Hepatocytes work in highly structured, repetitive hepatic lobules. Blood flow across the radial axis of the lobule generates oxygen, nutrient, and hormone gradients, which result in zoned spatial variability and functional diversity. This large heterogeneity suggests that hepatocytes in different lobule zones may have distinct gene expression profiles, metabolic features, regenerative capacity, and susceptibility to damage. Here, we describe the principles of liver zonation, introduce metabolomic approaches to study the spatial heterogeneity of the liver, and highlight the possibility of exploring the spatial metabolic profile, leading to a deeper understanding of the tissue metabolic organization. Spatial metabolomics can also reveal intercellular heterogeneity and its contribution to liver disease. These approaches facilitate the global characterization of liver metabolic function with high spatial resolution along physiological and pathological time scales. This review summarizes the state of the art for spatially resolved metabolomic analysis and the challenges that hinder the achievement of metabolome coverage at the single-cell level. We also discuss several major contributions to the understanding of liver spatial metabolism and conclude with our opinion on the future developments and applications of these exciting new technologies.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Examination of human osteoarchaeological remains as a feasible source of polar and apolar metabolites to study past conditions

Metabolomics is a modern tool that aids in our understanding of the molecular changes in organisms. Archaeological science is a branch of archaeology that explores different archaeological materials using modern analytical tools. Human osteoarchaeological material are a frequent finding in archaeological contexts and have the potential to offer information about previous human populations, which can be illuminating about our current condition. Using a set of samples comprising different skeletal elements and bone structures, here we explore for the first time the possibility of extracting metabolites from osteoarchaeological material. Here, a protocol for extraction and measurement of extracted polar and less-polar/apolar metabolites by ultra-high performance liquid chromatography hyphenated to high resolution mass spectrometry is presented to measure the molecules separated after a reversed phase and hydrophilic interaction liquid chromatography column. Molecular information was obtained, showing that osteoarchaeological material is a viable source of molecular information for metabolomic studies.

Handwashing Results in Incomplete Nicotine Removal from Fingers of Individuals who Smoke: A Randomized Controlled Experiment

OBJECTIVE

Tobacco residue, also known as third-hand smoke (THS), contains toxicants and lingers in dust and on surfaces and clothes. THS also remains on hands of individuals who smoke, with potential transfer to infants during visitation while infants are hospitalized in neonatal intensive care units (NICUs), raising concerns (e.g., hindered respiratory development) for vulnerable infants. Previously unexplored, this study tested handwashing (HW) and sanitization efficacy for finger-nicotine removal in a sample of adults who smoked and were visiting infants in an NICU.

STUDY DESIGN

A cross-sectional sample was recruited to complete an interview, carbon monoxide breath samples, and three nicotine wipes of separate fingers (thumb, index, and middle). Eligible participants (n = 14) reported current smoking (verified with breath samples) and were randomly assigned to 30 seconds of HW (n = 7) or alcohol-based sanitization (n = 7), with the order of finger wipes both counterbalanced and randomly assigned. After randomization, the first finger was wiped for nicotine. Participants then washed or sanitized their hands and finger two was wiped 5 minutes later. An interview assessing tobacco/nicotine use and exposure was then administered, followed by a second breath sample and the final finger wipe (40-60 minutes after washing/sanitizing).

RESULTS

Generalized linear mixed models found that HW was more effective than sanitizer for nicotine removal but failed to completely remove nicotine.

CONCLUSIONS

Without proper protections (e.g., wearing gloves and gowns), NICU visitors who smoke may inadvertently expose infants to THS. Research on cleaning protocols are needed to protect vulnerable medical populations from THS and associated risks.

KEY POINTS

· NICU infants may be exposed to THS via visitors.. · THS is not eliminated by HW or sanitizing.. · THS removal protections for NICU infants are needed..

Dermal thirdhand smoke exposure induces oxidative damage, initiates skin inflammatory markers, and adversely alters the human plasma proteome

BACKGROUND

Thirdhand smoke (THS) exposure correlated with significant metabolism of carcinogenic chemicals and the potential to cause detrimental health effects. Human harm research of THS exposure is limited to one other study and overall, there is a general lack of knowledge of the human health responses to THS exposure.

METHODS

This was a clinical investigation to evaluate the health effects of 3-h dermal THS exposure from urine and plasma. 10 healthy, non-smoking subjects were recruited for dermal exposure for 3 h exposed to clothing impregnated with filtered clean air or THS. Exposures to clean air or THS occurred 20-30 days apart.

FINDINGS

In THS-exposed group, there was a significant elevation of urinary 8-OHdG, 8-isoprostane, protein carbonyls. The THS 3-h exposure identified proteomics pathways of inflammatory response (p=2.18 × 10-8), adhesion of blood cells (p=2.23 × 10-8), atherosclerosis (p=2.78 × 10-9), and lichen planus (p=1.77 × 10-8). Nine canonical pathways were significantly activated including leukocyte extravasation signaling (z-score=3.0), and production of nitric oxide and reactive oxygen in macrophages (z-score=2.1). The THS 22-h proteomics pathways revealed inflammation of organ (p=3.09 × 10-8), keratinization of the epidermis (p=4.0 × 10-7), plaque psoriasis (p=5.31 × 10-7), and dermatitis (p=6.0 × 10-7). Two activated canonical pathways were production of nitric oxide and reactive oxygen in macrophages (z-score=2.646), and IL-8 signaling (z-score=2.0).

INTERPRETATION

This is a clinical study demonstrating that acute dermal exposure to THS mimics the harmful effects of cigarette smoking, alters the human plasma proteome, initiates mechanisms of skin inflammatory disease, and elevates urinary biomarkers of oxidative harm.

FUNDING

Funding was provided by the Tobacco Related Disease Research Program (TRDRP) 24RT-0037 TRDRP, 24RT-0039 TRDRP, and 28PT-0081 TRDRP.

Toxicity of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in early development: A wide-scope metabolomics assay in zebrafish embryos

The tobacco-specific nitrosamine 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is a carcinogenic and ubiquitous environmental pollutant for which toxic activity has been thoroughly investigated in murine models and human tissues. However, its potential deleterious effects on vertebrate early development are yet poorly understood. In this work, we characterized the impact of NNK exposure during early developmental stages of zebrafish embryos, a known alternative model for mammalian toxicity studies. Embryos exposed to different NNK concentrations were monitored for lethality and for the appearance of malformations during the first five days after fertilization. LC-MS based untargeted metabolomics was subsequently performed for a wide-scope assay of NNK-related metabolic alterations. Our results revealed the presence of not only the parental compound, but also of two known NNK metabolites, 4-Hydroxy-4-(3-pyridyl)-butyric acid (HPBA) and 4-(Methylnitrosamino)-1-(3-pyridyl-N-oxide)-1-butanol (NNAL-N-oxide) in exposed embryos likely resulting from active CYP450-mediated α-hydroxylation and NNK detoxification pathways, respectively. This was paralleled by a disruption in purine and pyrimidine metabolisms and the activation of the base excision repair pathway. Our results confirm NNK as a harmful embryonic agent and demonstrate zebrafish embryos to be a suitable early development model to monitor NNK toxicity.

Impacts of Cigarette Smoking Status on Metabolomic and Gut Microbiota Profile in Male Patients With Coronary Artery Disease: A Multi-Omics Study

Background: Cigarette smoking has been considered a modifiable risk factor for coronary artery disease (CAD). Changes in gut microbiota and microbe-derived metabolites have been shown to influence atherosclerotic pathogenesis. However, the effect of cigarette smoking on the gut microbiome and serum metabolites in CAD remains unclear. Method: We profiled the gut microbiota and serum metabolites of 113 male participants with diagnosed CAD including 46 current smokers, 34 former smokers, and 33 never smokers by 16S ribosomal RNA (rRNA) gene sequencing and untargeted metabolomics study. A follow-up study was conducted. PICRUSt2 was used for metagenomic functional prediction of important bacterial taxa. Results: In the analysis of the microbial composition, the current smokers were characterized with depleted Bifidobacterium catenulatum, Akkermansia muciniphila, and enriched Enterococcus faecium, Haemophilus parainfluenzae compared with the former and never smokers. In the untargeted serum metabolomic study, we observed and annotated 304 discriminant metabolites, uniquely including ceramides, acyl carnitines, and glycerophospholipids. Pathway analysis revealed a significantly changed sphingolipids metabolism related to cigarette smoking. However, the change of the majority of the discriminant metabolites is possibly reversible after smoking cessation. While performing PICRUSt2 metagenomic prediction, several key enzymes (wbpA, nadM) were identified to possibly explain the cross talk between gut microbiota and metabolomic changes associated with smoking. Moreover, the multi-omics analysis revealed that specific changes in bacterial taxa were associated with disease severity or outcomes by mediating metabolites such as glycerophospholipids. Conclusions: Our results indicated that both the gut microbiota composition and metabolomic profile of current smokers are different from that of never smokers. The present study may provide new insights into understanding the heterogenic influences of cigarette smoking on atherosclerotic pathogenesis by modulating gut microbiota as well as circulating metabolites.