Evaluating line-broadening factors on a reference spectrum as a bucketing method for NMR based metabolomics

The development of machine learning approaches in two-dimensional NMR data interpretation for metabolomics applications

Metabolomics has been widely applied in human diseases and environmental science to study the systematic changes of metabolites over diverse types of stimuli. NMR-based metabolomics has been widely used, but the peak overlap problems in the one-dimensional (1D) NMR spectrum could limit the accuracy of quantitative analysis for metabolomics applications. Two-dimensional (2D) NMR has been applied to solve the 1D NMR overlap problem, but the data processing is still challenging. In this study, we built an automatic approach to process the 2D NMR data for quantitative applications using machine learning approaches. Partial least square discriminant analysis (PLS-DA), artificial neural network classification (ANN-DA), gradient boosted trees classification (XGBoost-DA), and artificial deep learning neural network classification (ANNDL-DA) were applied in combination with an automatic peak selection approach. Standard mixtures, sea anemone extracts, and mouse fecal samples were tested to demonstrate the approach. Our results showed that ANN-DA and ANNDL-DA have high accuracy in selecting 2D NMR peaks (around 90 %), which have a high potential application in 2D NMR-based metabolomics quantitively study, while PLS-DA and XGBoost-DA showed limitations in either data variation or overfitting. Our study built an automatic approach to applying 2D NMR data to routine quantitative analysis in metabolomics.

Persistence and Sexual Dimorphism of Gut Dysbiosis and Pathobiome after Sepsis and Trauma

OBJECTIVE

To evaluate the persistence of intestinal microbiome dysbiosis and gut-plasma metabolomic perturbations following severe trauma or sepsis weeks after admission in patients experiencing chronic critical illness (CCI).

SUMMARY

Trauma and sepsis can lead to gut dysbiosis and alterations in the plasma and fecal metabolome. However, the impact of these perturbations and correlations between gut dysbiosis and the plasma metabolome in chronic critical illness have not been studied.

METHODS

A prospective observational cohort study was performed with healthy subjects, severe trauma patients, and patients with sepsis residing in an intensive care unit for 2 to 3 weeks. A high-throughput multi-omics approach was utilized to evaluate the gut microbial and gut-plasma metabolite responses in critically ill trauma and sepsis patients 14 to 21 days after intensive care unit admission.

RESULTS

Patients in the sepsis and trauma cohorts demonstrated strikingly depleted gut microbiome diversity, with significant alterations and specific pathobiome patterns in the microbiota composition compared to healthy subjects. Further subgroup analyses based on sex revealed resistance to changes in microbiome diversity among female trauma patients compared to healthy counterparts. Sex--specific changes in fecal metabolites were also observed after trauma and sepsis, while plasma metabolite changes were similar in both males and females.

CONCLUSIONS

Dysbiosis induced by trauma and sepsis persists up to 14 to 21 days after onset and is sex-specific, underscoring the implication of pathobiome and entero-septic microbial-metabolite perturbations in post-sepsis and posttrauma chronic critical illness. This indicates resilience to infection or injury in females' microbiome and should inform and facilitate future precision/personalized medicine strategies in the intensive care unit.

A modified Mediterranean-style diet enhances brain function via specific gut-microbiome-brain mechanisms

Alzheimer's disease (AD) is a debilitating brain disorder with rapidly mounting prevalence worldwide, yet no proven AD cure has been discovered. Using a multi-omics approach in a transgenic AD mouse model, the current study demonstrated the efficacy of a modified Mediterranean-ketogenic diet (MkD) on AD-related neurocognitive pathophysiology and underlying mechanisms related to the gut-microbiome-brain axis. The findings revealed that MkD induces profound shifts in the gut microbiome community and microbial metabolites. Most notably, MkD promoted growth of the Lactobacillus population, resulting in increased bacteria-derived lactate production. We discovered elevated levels of microbiome- and diet-derived metabolites in the serum as well, signaling their influence on the brain. Importantly, these changes in serum metabolites upregulated specific receptors that have neuroprotective effects and induced alternations in neuroinflammatory-associated pathway profiles in hippocampus. Additionally, these metabolites displayed strong favorable co-regulation relationship with gut-brain integrity and inflammatory markers, as well as neurobehavioral outcomes. The findings underscore the ameliorative effects of MkD on AD-related neurological function and the underlying gut-brain communication via modulation of the gut microbiome-metabolome arrays.

High fat diet reveals sex-specific fecal and liver metabolic alterations in C57BL/6J obese mice

Obesity is a major health concern that poses significant risks for many other diseases, including diabetes, cardiovascular disease, and cancer. Prevalence of these diseases varies by biological sex. This study utilizes a mouse (C57BL/6J) model of obesity to analyze liver and fecal metabolic profiles at various time points of dietary exposure: 5, 9, and 12 months in control or high fat diet (HFD)-exposed mice. Our study discovered that the female HFD group has a more discernable perturbation and set of significant changes in metabolic profiles than the male HFD group. In the female mice, HFD fecal metabolites including pyruvate, aspartate, and glutamate were lower than control diet-exposed mice after both 9th and 12th month exposure time points, while lactate and alanine were significantly downregulated only at the 12th month. Perturbations of liver metabolic profiles were observed in both male and female HFD groups, compared to controls at the 12th month. Overall, the female HFD group showed higher lactate and glutathione levels compared to controls, while the male HFD group showed higher levels of glutamine and taurine compared to controls. These metabolite-based findings in both fecal and liver samples for a diet-induced effect of obesity may help guide future pioneering discoveries relating to the analysis and prevention of obesity in people, especially for females.

Resistant starches from dietary pulses modulate the gut metabolome in association with microbiome in a humanized murine model of ageing

Emerging evidence suggests that plant-based fiber-rich diets improve ageing-associated health by fostering a healthier gut microbiome and microbial metabolites. However, such effects and mechanisms of resistant starches from dietary pulses remain underexplored. Herein, we examine the prebiotic effects of dietary pulses-derived resistant starch (RS) on gut metabolome in older (60-week old) mice carrying a human microbiome. Gut metabolome and its association with microbiome are examined after 20-weeks feeding of a western-style diet (control; CTL) fortified (5% w/w) with RS from pinto beans (PTB), black-eyed-peas (BEP), lentils (LEN), chickpeas (CKP), or inulin (INU; reference control). NMR spectroscopy-based untargeted metabolomic analysis yield differential abundance linking phenotypic differences in specific metabolites among different RS groups. LEN and CKP increase butyrate, while INU promotes propionate. Conversely, bile acids and cholesterol are reduced in prebiotic groups along with suppressed choline-to-trimethylamine conversion by LEN and CKP, whereas amino acid metabolism is positively altered. Multi-omics microbiome-metabolome interactions reveal an association of beneficial metabolites with the Lactobacilli group, Bacteroides, Dubosiella, Parasutterella, and Parabacteroides, while harmful metabolites correlate with Butyricimonas, Faecalibaculum, Colidextribacter, Enterococcus, Akkermansia, Odoribacter, and Bilophila. These findings demonstrate the functional effects of pulses-derived RS on gut microbial metabolism and their beneficial physiologic responses in an aged host.

Dietary fiber modulates gut microbiome and metabolome in a host sex-specific manner in a murine model of aging

Emerging evidence reveals the fundamental role of the gut microbiome in human health. Among various factors regulating our gut microbiome, diet is one of the most indispensable and prominent one. Inulin is one of the most widely-studied dietary fiber for its beneficial prebiotic effects by positively modulating the gut microbiome and microbial metabolites. Recent research underscores sexual dimorphism and sex-specific disparities in microbiome and also diet-microbiome interactions. However, whether and how the prebiotic effects of dietary fiber differ among sexes remain underexplored. To this end, we herein examine sex-specific differences in the prebiotic effects of inulin on gut microbiome and metabolome in a humanized murine model of aging i.e., aged mice carrying human fecal microbiota. The findings demonstrate that inulin exerts prebiotic effects, but in a sex-dependent manner. Overall, inulin increases the proportion of Bacteroides, Blautia, and glycine, while decreasing Eggerthella, Lactococcus, Streptococcus, trimethylamine, 3-hydroxyisobutyrate, leucine and methionine in both sexes. However, we note sex-specific effects of inulin including suppression of f_Enteroccaceae:_, Odoribacter, bile acids, malonate, thymine, valine, acetoin, and ethanol while promotion of Dubosiella, pyruvate, and glycine in males. Whereas, suppression of Faecalibaculum, Lachnoclostridium, Schaedlerella, phenylalanine and enhancement of Parasutterella, Phocaeicola, f_Lachnospiraceae;_, Barnesiella, Butyricimonas, glycine, propionate, acetate and glutamate are observed in females. Altogether, the study reveals that prebiotic mechanisms of dietary fiber vary in a sex-dependent manner, underscoring the importance of including both sexes in preclinical/clinical studies to comprehend the mechanisms and functional aspects of dietary interventions for effective extrapolation and translation in precision nutrition milieus.

Combination of peak-picking and binning for NMR-based untargeted metabonomics study

In NMR-based untargeted metabolomic studies, ¹H NMR spectra are usually divided into equal bins/buckets to diminish the effects of peak shift caused by sample status or instrument instability, and to reduce the number of variables used as input for the multivariate statistical analysis. It was noticed that the peaks near bin boundaries may cause significant changes in integral values of adjacent bins, and the weaker peak may be obscured if it is allocated in the same bin with intense peaks. Several efforts have been taken to improve the performance of binning. Here we propose an alternative method, named P-Bin, based on the combination of the classic peak-picking and binning procedures. The location of each peak defined by peak-picking is used as the center of the individual bin. P-Bin is expected to keep all spectral information associated with the peaks and significantly reduce the data size as the spectral regions without peaks are not considered. In addition, both peak-picking and binning are routine procedures, making P-Bin easy to be implemented. To verify the performance, two sets of experimental data from human plasma and Ganoderma lucidum (G. lucidum) extracts were processed using the conventional binning method and the proposed method, before the principal component analysis (PCA) and the orthogonal projection to latent structures discriminant analysis (OPLS-DA). The results indicate that the proposed method has improved both the clustering performance of PCA score plots and the interpretability of OPLS-DA loading plots, and P-Bin could be an improved version of data preparation for metabonomic study.

Metabolomic analysis of honey bee (Apis mellifera L.) response to glyphosate exposure

Glyphosate is among the world's most commonly used herbicides in agriculture and weed control. The use of this agrochemical has unintended consequences on non-target organisms, such as honey bees (Apis mellifera L.), the Earth's most prominent insect pollinator. However, detailed understanding of the biological effects in bees in response to sub-lethal glyphosate exposure is still limited. In this study, 1H NMR-based metabolomics was performed to investigate whether oral exposure to an environmentally realistic concentration (7.12 mg L-1) of glyphosate affects the regulation of honey bee metabolites in 2, 5, and 10 days. On Day 2 of glyphosate exposure, the honey bees showed significant downregulation of several essential amino acids, including leucine, lysine, valine, and isoleucine. This phenomenon indicates that glyphosate causes an obvious metabolic perturbation when the honey bees are subjected to the initial caging process. The mid-term (Day 5) results showed negligible metabolite-level perturbation, which indicated the low glyphosate impact on active honeybees. However, the long-term (Day 10) data showed evident separation between the control and experimental groups in the principal component analysis (PCA). This separation is the result of the combinatorial changes of essential amino acids such as threonine, histidine, and methionine, while the non-essential amino acids glutamine and proline as well as the carbohydrate sucrose were all downregulated. In summary, our study demonstrates that although no significant behavioral differences were observed in honey bees under sub-lethal doses of glyphosate, metabolomic level perturbation can be observed under short-term exposure when met with other environmental stressors or long-term exposure.

An NMR-based metabolomics study on sea anemones Exaiptasia diaphana (Rapp, 1829) with atrazine exposure

Sea anemones have been recommended as critical bioindicators for marine environmental stressors; however, the understanding of the biological effects in response to sublethal pollutant exposure is still limited. In this study, NMR-based metabolomics was performed to investigate the effects of atrazine on Exaiptasia diaphana with concentrations ranging from 3 to 90 ppb. As a result, the metabolic profiling of E. diaphana was significantly affected after 70 ppb treatment while a partial perturbation was observed as early as 3 ppb treatment. Glutamate was significantly changed at low atrazine concentrations with increased upregulation in concentrated atrazine experiments which is a potential biomarker for E. diaphana exposed to atrazine stressors. The TCA intermediates succinate and malate as well as the TCA cycle-related metabolites such as alanine, glycine, and taurine downregulated after atrazine treatment which also indicated the lower energy supply of E. diaphana. In summary, our study demonstrated that significant metabolic level perturbation could be detected at low atrazine concentrations before a physical change could be observed, and glutamate or the nitrogen metabolism may be the initial target for sea anemones by atrazine. The study may provide pioneering results for using E. diaphana to predict the impacts of exposure to atrazine toxin in marine systems.