Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
Browse
48 results
Search Results
Item Mathematical models of the colonic microbiota: an evaluation of accuracy using in vitro fecal fermentation data(Frontiers Media S A, 2025-09-25) Geniselli da Silva V; Smith NW; Mullaney JA; Roy NC; Wall C; McNabb WC; Huang HTraditional approaches for studying diet-colonic microbiota interactions are time-consuming, resource-intensive, and often hindered by technical and ethical concerns. Metagenome-scale community metabolic models show promise as complementary tools to overcome these limitations. However, their experimental validation is challenging, and their accuracy in predicting colonic microbial function under realistic dietary conditions remains unclear. This study assessed the accuracy of the Microbial Community model (MICOM) in predicting major short-chain fatty acid (SCFA) production by the colonic microbiota of weaning infants, using fecal samples as a proxy. Model predictions were compared with experimental SCFA production using in vitro fecal fermentation data at the genus level. The model exhibited overall poor accuracy, with only a weak, significant correlation between measured and predicted acetate production (r = 0.17, p = 0.03). However, agreement between predicted and measured SCFA production improved for samples primarily composed of plant-based foods: acetate exhibited a moderate positive correlation (r = 0.31, p = 0.005), and butyrate a trend toward a weak positive correlation (r = 0.21, p = 0.06). These findings suggest that the model is better suited for predicting the influence of complex carbohydrates on the colonic microbiota than for other dietary compounds. Our study demonstrates that, given current limitations, modeling approaches for diet-colonic microbiota interactions should complement rather than replace traditional experimental methods. Further refinement of computational models for microbial communities is essential to advance research on dietary compound-colonic microbiota interactions in weaning infants.Item Sensitivity analysis of global food and nutrition modelling(Springer Nature B V on behalf of the International Society for Plant Pathology, 2025-10-18) Shippey D; Vignes M; McNabb WC; Smith NWComputational models are often used to explore the future of the global food system, including the implications for human nutrition, an essential aspect of sustainability. However, the confidence that can be placed in the outputs of these models is often poorly quantified. Here, a sensitivity analysis of the DELTA Model® - a linear mass balance model calculating global nutrient supply using global and regional food balance sheet, processing, waste, inedible portion, composition, and bioavailability datasets - is conducted. First, a one-at-a-time analysis, varying 4019 underpinning datapoints from the above datasets individually by ± 50% was conducted to identify those with the greatest impact on calculated global nutrient supply. The most influential values from this initial analysis were then carried forward into a multiple value sensitivity analysis, where all possible combinations of ± 50% variations were simulated. Values related to cereals supply, waste, and nutritional value were the most influential on model output, with selenium, cystine, and carbohydrate supply the most sensitive nutrients. When compared to global nutrient requirements, variations in the calculated supply of some nutrients led to qualitative changes from a sufficient global supply to an insufficient supply. These results, while indicative rather than precise estimates of uncertainty, emphasise the critical importance of accurate cereals data in food system models, provide insight on the degree of sensitivity of similar linear models, and should encourage broader application of sensitivity analysis in the field.Item Integrated multi-omic and symptom clustering reveals lower-gastrointestinal disorders of gut-brain interaction heterogeneity(Taylor and Francis Group, 2026-12-31) Dowrick JM; Roy NC; Carco C; James SC; Heenan PE; Frampton CMA; Fraser K; Young W; Cooney J; Trower T; Keenan JI; McNabb WC; Mullaney JA; Bayer SB; Talley NJ; Gearry RB; Angeli-Gordon TRRome IV disorders of gut-brain interaction (DGBI) subtypes are known to be unstable and demonstrate high rates of non-treatment response, likely indicating patient heterogeneity. Cluster analysis, a type of unsupervised machine learning, can identify homogeneous sub-populations. Independent cluster analyses of symptom and biological data have highlighted its value in predicting patient outcomes. Integrated clustering of symptom and biological data may provide a unique multimodal perspective that better captures the complexity of DGBI. Here, integrated symptom and multi-omic cluster analysis was performed on a cohort of healthy controls and patients with lower-gastrointestinal tract DGBI. Cluster stability was assessed by considering how frequently pairs of participants appeared in the same cluster between different bootstrapped datasets. Functional enrichment analysis was performed on the biological signatures of stable DGBI-predominant clusters, implicating disrupted ammonia handling and metabolism as possible pathophysiologies present in a subset of patients with DGBI. Integrated clustering revealed subtypes that were not apparent using a singular modality, suggesting a symptom-only classification is prone to capturing heterogeneous sub-populations.Item Nutrient-adequate diets with the lowest greenhouse gas emissions or price are the least acceptable—insights from dietary optimisation modelling using the iOTA model®(Frontiers Media S.A., 2025-08-01) Tavan M; Smith NW; Fletcher AJ; Hill JP; McNabb WC; Das AOver the past decade, there has been an increasing interest in the environmental sustainability of diets because food systems are responsible for a third of the anthropogenic greenhouse gas emissions (GHGE). However, less attention has been paid to the nutrient adequacy, consumer acceptability, and affordability of such diets. Such knowledge is particularly scarce in New Zealand, where approximately 40% of adults and 20% of children may live under severe to moderate food insecurity. The iOTA Model® is a country-specific dietary optimisation tool designed to fill this gap by bringing the various aspects of diet sustainability together and providing evidence-based knowledge on not just the environmental impact of food but also its economic and nutritional sustainability. The iOTA Model® was constructed using mixed integer linear programming by integrating New Zealand-specific dietary data. Features such as digestibility and bioavailability considerations have been incorporated as part of the iOTA Model®, allowing for a more accurate estimation of nutrient supply. The model is available as an open-access tool and allows users to explore various dimensions of a sustainable diet. Eight optimisation scenarios, along with baseline diets, were investigated for adult males and females in New Zealand. Results showed that reducing dietary GHGE or price by approximately 80% was possible while meeting nutrient adequacy requirements. However, such diets deviated substantially from the baseline eating patterns, indicating lower consumer acceptability, and only included a limited variety of foods. On the contrary, diets with minimum deviation from baseline remained realistic while adhering to nutrient targets and reducing GHGE by 10 and 30% in female and male consumers aged 19–30 years, respectively, and weekly price remained below the baseline. Expansion of the model to additional countries and its open-access nature will allow independent dietary sustainability research through optimisation.Item Gaps in environmental and social evidence base are holding back strategic action on our national food system(Taylor and Francis Group on behalf of the Royal Society of New Zealand, 2025-07-03) Smith NW; McDowell RW; Smith C; Foster M; Eason C; Stephens M; McNabb WCWhile there is broad agreement on the challenges facing the Aotearoa New Zealand food system now and in the near future, there is less agreement on the action to be taken. Poor agreement is fuelled by gaps in both our scientific understanding of the food system and data to support our decision making, particularly in the environmental and social spaces. Filling these gaps and being transparent about scientific confidence in future predictions will strengthen the evidence base for action.Item Concentration of milk oxylipins after heat and homogenization treatments(Frontiers Media S A, 2023-05-26) Thum C; Cirelli A; Otoki Y; Ozturk G; Taha AY; McNabb WC; Roy NC; de Moura Bell JMLN; Hebishy EHeat treatment and homogenization of milk are common processing steps intended to reduce microbial load for safe human consumption, and to avoid creaming, respectively. Although the effects of combined pasteurization and homogenization on free fatty acids (FFA) and lipid oxidation markers such as hydroperoxides, and thiobarbituric acid reactive species (TBARS) have been well characterized, their effects on primary oxidized fatty acids known as oxylipins have not yet been determined. This study aimed to determine the effects of two heat treatments: milk pasteurization [high-temperature short time, 72°C for 15 s (HTST)] and sterilization [ultra-high temperature, 135°C for 3 s (UHT)] with or without homogenization (10, 17 or 24 MPa) on FFA (%), primary (hydroperoxides and oxylipins) and secondary oxidation compounds (TBARS). Heat treatments alone significantly reduced most oxylipins compared with raw milk, but did not alter % FFA, hydroperoxide, and TBARS levels. The combination of UHT and homogenization at 24 MPa increased % FFA, hydroperoxide value, and some oxylipins, compared to raw milk and other treatments. Overall, the combination of heat treatment and homogenization significantly increased oxylipin formation compared with heat treatment alone.Item Dietary patterns influencing the human colonic microbiota from infancy to centenarian age: a narrative review(Frontiers Media S A, 2025-06-04) Geniselli da Silva V; Roy NC; Smith NW; Wall C; Mullaney JA; McNabb WC; Benítez-Páez AOur dietary choices not only affect our body but also shape the microbial community inhabiting our large intestine. The colonic microbiota strongly influences our physiology, playing a crucial role in both disease prevention and development. Hence, dietary strategies to modulate colonic microbes have gained notable attention. However, most diet-colonic microbiota research has focused on adults, often neglecting other key life stages, such as infancy and older adulthood. In this narrative review, we explore the impact of various dietary patterns on the colonic microbiota from early infancy to centenarian age, aiming to identify age-specific diets promoting health and well-being by nourishing the microbiota. Diversified diets rich in fruits, vegetables, and whole grains, along with daily consumption of fermented foods, and moderate amounts of fish and lean meats (two to four times a week), increase colonic microbial diversity, the abundance of saccharolytic taxa, and the production of beneficial microbial metabolites. Most of the current knowledge of diet-microbiota interactions is limited to studies using fecal samples as a proxy. Future directions in colonic microbiota research include personalized in silico simulations to predict the impact of diets on colonic microbes. Complementary to traditional methodologies, modeling has the potential to reduce the costs of colonic microbiota investigations, accelerate our understanding of diet-microbiota interactions, and contribute to the advancement of personalized nutrition across various life stages.Item Protein Intake and Protein Quality Patterns in New Zealand Vegan Diets: An Observational Analysis Using Dynamic Time Warping(MDPI (Basel, Switzerland), 2025-05-26) Soh BXP; Vignes M; Smith NW; Von Hurst PR; McNabb WC; Hayes M; Naik ASBackground/Objectives: Inadequate intake of indispensable amino acids (IAAs) is a significant challenge in vegan diets. Since IAAs are not produced or stored over long durations in the human body, regular and balanced dietary protein consumption throughout the day is essential for metabolic function. The objective of this study is to investigate the variation in protein and IAA intake across 24 h among New Zealand vegans with time-series clustering, using Dynamic Time Warping (DTW). Methods: This data-driven approach objectively categorised vegan dietary data into distinct clusters for protein intake and protein quality analysis. Results: Total protein consumed per eating occasion (EO) was 11.1 g, with 93.5% of the cohort falling below the minimal threshold of 20 g of protein per EO. The mean protein intake for each EO in cluster 1 was 6.5 g, cluster 2 was 11.4 g and only cluster 3 was near the threshold at 19.0 g. IAA intake was highest in cluster 3, with lysine and leucine being 3× higher in cluster 3 than cluster 1. All EOs in cluster 1 were below the reference protein intake relative to body weight, closely followed by cluster 2 (91.5%), while cluster 3 comparatively had the lowest EOs under this reference (31.9%). Conclusions: DTW produced three distinct dietary patterns in the vegan cohort. Further exploration of plant protein combinations could inform recommendations to optimise protein quality in vegan diets.Item Gastric protein digestion of cow, goat, and sheep milk is not reflected in the amino acid appearance in the blood of suckling piglets(Elsevier Inc on behalf of the American Dairy Science Association, 2025-06) Roy D; Montoya CA; Stroebinger N; Hodgkinson SM; Ye A; McNabb WC; Moughan PJ; Singh HStructural changes in milk during gastric digestion are a key driving factor for the rate of digestion of nutrients in the gastrointestinal tract. Thus, the influence of gastric coagulation behavior on the kinetics of protein digestion of raw cow, goat, and sheep whole milk in the stomach was investigated using the 3-wk-old suckled male piglet as an animal model for human infants. Piglets received a single meal of fresh raw milk normalized for protein content, and were slaughtered at 0, 30, 90, 150, or 210 min postprandially. Gastric chyme and cardiac blood samples were collected. Gastric pepsin activity, rate of protein hydrolysis, and gastric emptying of AA were determined along with how these changes influence the appearance of AA in the plasma. The disappearance rates of individual proteins (especially β-LG and αS-CN), total digested proteins entering the small intestine, as well as the gastric emptying of some AA (proline, leucine) were (or tended to be) greater for goat and sheep milk than for cow milk. Differences in plasma concentrations for some AA (e.g., leucine) were observed across milk types, but they did not directly reflect changes in gastric protein digestion and the gastric emptying of AA. In conclusion, a combination of protein (and AA) composition, susceptibility of specific proteins to hydrolysis, and the nature of the curd structure formed influenced the digestion behavior of milk proteins in the stomach and their subsequent release into the small intestine.Item Complementary foods in infants: an in vitro study of the faecal microbial composition and organic acid production(Royal Society of Chemistry, 2025-05-07) Geniselli da Silva V; Mullaney JA; Roy NC; Smith NW; Wall C; Tatton CJ; McNabb WCThe transition from breastmilk to complementary foods is critical for maturing the colonic microbiota of infants. Dietary choices at weaning can lead to long-lasting microbial changes, potentially influencing health later in life. However, the weaning phase remains underexplored in colonic microbiome research, and the current understanding of how complementary foods impact the infant's colonic microbiota is limited. To address this knowledge gap, this study assessed the influence of 13 food ingredients on the in vitro microbial composition and production of organic acids by the faecal microbiota in New Zealand infants aged 5 to 11 months. To better represent real feeding practices, ingredients were combined with infant formula, other complementary foods, or both infant formula and other foods. Among the individual food ingredients, fermentation with peeled kūmara (sweet potato) increased the production of lactate and the relative abundance of the genus Enterococcus. Fermentation with blackcurrants, strawberries, or raspberries enhanced acetate and propionate production. Additionally, fermentation with blackcurrants increased the relative abundance of the genus Parabacteroides, while raspberry fermentation increased the relative abundance of the genera Parabacteroides and Eubacterium. When combined with infant formula or with blackcurrants, fermenting black beans increased butyrate production and stimulated the relative abundance of Clostridium sensu stricto 1. These foods are promising candidates for future clinical trials.
