Early Time-Restricted Feeding Amends Circadian Clock Function and Improves Metabolic Health in Male and Female Nile Grass Rats

Explainable AI to Facilitate Understanding of Neural Network-Based Metabolite Profiling Using NMR Spectroscopy

Neural networks (NNs) are emerging as a rapid and scalable method for quantifying metabolites directly from nuclear magnetic resonance (NMR) spectra, but the nonlinear nature of NNs precludes understanding of how a model makes predictions. This study implements an explainable artificial intelligence algorithm called integrated gradients (IG) to elucidate which regions of input spectra are the most important for the quantification of specific analytes. The approach is first validated in simulated mixture spectra of eight aqueous metabolites and then investigated in experimentally acquired lipid spectra of a reference standard mixture and a murine hepatic extract. The IG method revealed that, like a human spectroscopist, NNs recognize and quantify analytes based on an analyte's respective resonance line-shapes, amplitudes, and frequencies. NNs can compensate for peak overlap and prioritize specific resonances most important for concentration determination. Further, we show how modifying a NN training dataset can affect how a model makes decisions, and we provide examples of how this approach can be used to de-bug issues with model performance. Overall, results show that the IG technique facilitates a visual and quantitative understanding of how model inputs relate to model outputs, potentially making NNs a more attractive option for targeted and automated NMR-based metabolomics.

Chrononutrition in the context of Ramadan: Potential implications

Every year, healthy adult Muslims practice dawn to sunset fasting for a whole lunar month. No food or fluid is allowed for the fasting time window. After sunset, eating is allowed. The dramatic change in the timing of meals is accompanied by changes in sleeping hours and thus alterations in circadian rhythms. Hormonal mechanisms mainly determined by the latter also change. These include shifts in cortisol and melatonin. Food-dependent hormones such as Ghrelin and leptin also show changes. A well-established principle of chrononutrition is that the timing of eating may be as or more important than the content of food. Ramadan fasting (RF) is distinct from other forms of intermittent fasting, although there are also some similarities with time restricted eating (TRE). Both have been shown to have health benefits. Here, we examine existing literature to understand and learn from this very commonly practiced form of fasting and its relationships to circadian rhythms and homoeostatic mechanisms.

SAD rats: Effects of short photoperiod and carbohydrate consumption on sleep, liver steatosis, and the gut microbiome in diurnal grass rats

Seasonal affective disorder (SAD) is a recurrent depression triggered by exposure to short photoperiods, with a subset of patients reporting hypersomnia, increased appetite, and carbohydrate craving. Dysfunction of the microbiota - gut - brain axis is frequently associated with depressive disorders, but its role in SAD is unknown. Nile grass rats (Arvicanthis niloticus) are potentially useful for exploring the pathophysiology of SAD, as they are diurnal and have been found to exhibit anhedonia and affective-like behavior in response to short photoperiods. Further, given grass rats have been found to spontaneously develop metabolic syndrome, they may be particularly susceptible to environmental triggers of metabolic dysbiosis. We conducted a 2 × 2 factorial design experiment to test the effects of short photoperiod (4 h:20 h Light:Dark (LD) vs. neutral 12:12 LD), access to a high concentration (8%) sucrose solution, and the interaction between the two, on activity, sleep, liver steatosis, and the gut microbiome of grass rats. We found that animals on short photoperiods maintained robust diel rhythms and similar subjective day lengths as controls in neutral photoperiods but showed disrupted activity and sleep patterns (i.e. a return to sleep after an initial bout of activity that occurs ~ 13 h before lights off). We found no evidence that photoperiod influenced sucrose consumption. By the end of the experiment, some grass rats were overweight and exhibited signs of non-alcoholic fatty liver disease (NAFLD) with micro- and macro-steatosis. However, neither photoperiod nor access to sucrose solution significantly affected the degree of liver steatosis. The gut microbiome of grass rats varied substantially among individuals, but most variation was attributable to parental effects and the microbiome was unaffected by photoperiod or access to sucrose. Our study indicates short photoperiod leads to disrupted activity and sleep in grass rats but does not impact sucrose consumption or exacerbate metabolic dysbiosis and NAFLD.

Rapid and automated lipid profiling by nuclear magnetic resonance spectroscopy using neural networks

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for quantitative metabolomics; however, quantification of metabolites from NMR data is often a slow and tedious process requiring user input and expertise. In this study, we propose a neural network approach for rapid, automated lipid identification and quantification from NMR data. Multilayered perceptron (MLP) networks were developed with NMR spectra as the input and lipid concentrations as output. Three large synthetic datasets were generated, each with 55,000 spectra from an original 30 scans of reference standards, by using linear combinations of standards and simulating experimental-like modifications (line broadening, noise, peak shifts, baseline shifts) and common interference signals (water, tetramethylsilane, extraction solvent), and were used to train MLPs for robust prediction of lipid concentrations. The performances of MLPS were first validated on various synthetic datasets to assess the effect of incorporating different modifications on their accuracy. The MLPs were then evaluated on experimentally acquired data from complex lipid mixtures. The MLP-derived lipid concentrations showed high correlations and slopes close to unity for most of the quantified lipid metabolites in experimental mixtures compared with ground-truth concentrations. The most accurate, robust MLP was used to profile lipids in lipophilic hepatic extracts from a rat metabolomics study. The MLP lipid results analyzed by two-way ANOVA for dietary and sex differences were similar to those obtained with a conventional NMR quantification method. In conclusion, this study demonstrates the potential and feasibility of a neural network approach for improving speed and automation in NMR lipid profiling and this approach can be easily tailored to other quantitative, targeted spectroscopic analyses in academia or industry.

Multi-Tissue Time-Domain NMR Metabolomics Investigation of Time-Restricted Feeding in Male and Female Nile Grass Rats

Metabolic disease resulting from overnutrition is prevalent and rapidly increasing in incidence in modern society. Time restricted feeding (TRF) dietary regimens have recently shown promise in attenuating some of the negative metabolic effects associated with chronic nutrient stress. The purpose of this study is to utilize a multi-tissue metabolomics approach using nuclear magnetic resonance (NMR) spectroscopy to investigate TRF and sex-specific effects of high-fat diet in a diurnal Nile grass rat model. Animals followed a six-week dietary protocol on one of four diets: chow ad libitum, high-fat ad libitum (HF-AD), high-fat early TRF (HF-AM), or high-fat late TRF (HF-PM), and their liver, heart, and white adipose tissues were harvested at the end of the study and were analyzed by NMR. Time-domain complete reduction to amplitude–frequency table (CRAFT) was used to semi-automate and systematically quantify metabolites in liver, heart, and adipose tissues while minimizing operator bias. Metabolite profiling and statistical analysis revealed lipid remodeling in all three tissues and ectopic accumulation of cardiac and hepatic lipids for HF-AD feeding compared to a standard chow diet. Animals on TRF high-fat diet had lower lipid levels in the heart and liver compared to the ad libitum group; however, no significant differences were noted for adipose tissue. Regardless of diet, females exhibited greater amounts of hepatic lipids compared to males, while no consistent differences were shown in adipose and heart. In conclusion, this study demonstrates the feasibility of performing systematic and time-efficient multi-tissue NMR metabolomics to elucidate metabolites involved in the crosstalk between different metabolic tissues and provides a more holistic approach to better understand the etiology of metabolic disease and the effects of TRF on metabolic profiles.