Plant secondary metabolites and primate food choices: A meta-analysis and future directions

A simple assay for measuring tannin-protein precipitation capacity offers insights into the diet and food choice of black howler monkeys (Alouatta pigra)

Phenolics, like tannins, are plant-specialized metabolites that play a protective role against herbivory. Tannins can reduce palatability and bind with proteins to reduce digestibility, acting as deterrents to feeding and impacting nutrient extraction by herbivores. Some assays measure tannin and total phenolics content in plants but lack determination of their biological effects, hindering the interpretation of tannin function in herbivory and its impacts on animal behavior and ecology. In this study, we successfully applied the radial diffusion assay to assess tannin protein precipitation (PP) capacity and evaluate the anti-nutritional effects of tannins in food plants (n = 24) consumed by free-ranging black howler monkeys (Alouatta pigra) in Tabasco, Mexico. We found PP rings in five plant species consumed by the monkeys. The mature fruit of Inga edulis was the most consumed food plant, despite having a high tannin PP capacity (56.66 mg tannic acid equivalent/g dry matter). These findings highlight the presence of tannins in the black howler diet and provide insight into the primates' resilience and potential strategies for coping with anti-nutritional aspects of the diet.

Food preferences and nutrient composition in captive Southern brown howler monkeys, Alouatta guariba clamitans

Studies of food preferences in captive primates have so far mainly been restricted to frugivorous species. It was therefore the aim of the present study to assess the occurrence of spontaneous food preferences in a mainly folivorous primate, the captive Southern brown howler monkey, and to analyze whether these preferences correlate with nutrient composition. Using a two-alternative choice test, we presented ten male and five female adult Alouatta guariba clamitans with all possible binary combinations of ten types of food that are part of their diet in captivity and recorded their choice behavior. We found the howler monkeys to display the following rank order of preference: banana > mango > watermelon > papaya > beetroot > apple > pear > orange > cucumber > tomato. This preference ranking significantly and positively correlated with the total carbohydrate content and with the sucrose content of the food items. We also found significant positive correlations between the food preference ranking and the content of the minerals copper and magnesium. Male and female howler monkeys did not differ significantly in their food preference rankings. These results suggest this howler monkeys under human care are not opportunistic, but selective feeders with regard to maximizing their net gain of energy as only the content of carbohydrates, but not the contents of total energy, proteins, or lipids significantly correlated with the displayed food preferences. Thus, the food preferences of this primate are similar to those reported in several species of frugivorous primates tested with cultivated fruits and vegetables.

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.

Favorite Parts of a Single Leaf for Giant Flying Squirrels to Eat in Three Species of Food Trees

To examine the effect of leaf chemical composition on selective herbivory by the Japanese giant flying squirrels (Petaurista leucogenys), we measured and compared the total phenolic, glucose, and water contents of leaves among their main food tree species, deciduous Quercus acutissima, and evergreen Q. sessilifolia and Phonitia serratifolia. Leaves of these three tree species were available in the warm season (April to October), but the flying squirrels mostly preferred the leaves of Q. acutissima, having higher glucose and water contents than those of the other two tree species. In the cold season (November to the next March), the two evergreen tree species were available, and the flying squirrels used both leaves without any apparent influence of the chemical compositions. On the other hand, the favorite parts of a single leaf differed among the three tree species. Flying squirrels dropped the individual leaves after partial consumption. Their feeding marks on the dropped leaves were distinguished into four types: apical, basal, central, and marginal parts of consumption. The basal parts of consumption were most frequent in Q. acutissima leaves in which more water was contained at the basal part, and the central part consumption followed, which may be related to a lower phenolic content and more glucose and water at the leaf center than its margin. In contrast, the apically consumed leaves dominated in Q. sessilifolia, with relatively homogeneous leaf chemical distribution except for more water at the center. In P. serratifolia, leaves consumed at the center were frequent, but those with marginal consumption were also observed, which may be related to its specific chemical distribution with less phenolics and more glucose at the leaf margin. Thus, the chemical distributions within the single leaf differ among tree species, and the flying squirrel's selectivity of the tree species and the part of each leaf depends partly on the relative compositions of preferable glucose and water and unpreferable phenolics.

Traces of dietary patterns in saliva of hominids: Profiling salivary amino acid fingerprints in great apes and humans

Herbivorous animals that regularly consume tannin-rich food are known to secrete certain tannin-binding salivary proteins (TBSPs), especially proline-rich proteins and histidine-rich proteins, as an effective measure to counteract the antinutritive effects of dietary tannins. Due to their high binding capacity, TBSPs complex with tannins in the oral cavity, and thereby protect dietary proteins and digestive enzymes. Although the natural diet of great apes (Hominidae) is biased toward ripe fruits, analyses of food plants revealed that their natural diet contains considerable amounts of tannins, which is raising the question of possible counter-measures to cope with dietary tannins. In our study, we investigated the salivary amino acid profiles of zoo-housed Pan paniscus, Pan troglodytes, Gorilla gorilla, and Pongo abelii, and compared their results with corresponding data from Homo sapiens. Individual saliva samples of 42 apes and 17 humans were collected and quantitated by amino acid analysis, using cation-exchange chromatography with postcolumn derivatization, following acid hydrolysis. We found species-specific differences in the salivary amino acid profiles with average total salivary protein concentration ranging from 308.8 mg/dL in Po. abelii to 1165.6 mg/dL in G. gorilla. Total salivary protein was consistently higher in ape than in human saliva samples (174 mg/dL). All apes had on average also higher relative proline levels than humans did. Histidine levels had the highest concentration in the samples from Po. abelii followed by P. paniscus. In all ape species, the high salivary concentrations of proline and histidine are considered to be indicative of high concentrations of TBSPs in hominids. Given that the species differences in salivary composition obtained in this study correspond with overall patterns of secondary compound content in the diet of wild populations, we assume that salivary composition is resilient to acute and long-lasting changes in diet composition in general and tannin content in particular.

Food preferences in a generalist pollen feeder: A nutritional strategy mainly driven by plant carbohydrates

Introduction

Animal nutritional strategies have been extensively studied in vertebrates, where generalism at the individual scale is the rule. In insect herbivores, the determinants of the nutritional strategy of individual-scale generalists remain poorly studied, and the focus has been placed mainly on the influence of plant defense. Moreover, the integration of a physiological dimension in such studies remains rare. Here, we investigated the determinants of the nutritional strategy of pre-diapausing pollen beetles, Brassicogethes aeneus, with a focus on the influence of macronutrients. Before their diapause, pollen beetles are known to feed from plants belonging to many different families. This raises three questions: (i) Is the generalism of pollen beetles a populational consequence of individuals specialized on different plant families? (ii) Do individuals feed at random on flowers available or do they have a particular nutritional strategy? and (iii) In case of non-random feeding choices, do pollen macronutrients explain this nutritional strategy?

Methods

To answer these questions, we used a series of laboratory experiments including feeding choice tests on flowers and artificial substrates, quantification of pollen nutrient content, quantification of the insect energetic budget, and performance experiments.

Results

We show that pollen beetles are generalist at the individual scale, and that clear and stable food preferences are established over a few hours in a multi-choice context. Pollen beetles prefer to feed on flowers with a carbohydrate-rich pollen, and this preference is adaptive since performance correlates positively with the plant carbohydrate content. This better performance may be explained by the fact that individuals feeding on carbohydrate-rich resources accumulate more glycogen and total energetic reserves.

Discussion

This study represents one of the few evidences of generalism at the individual scale in an herbivorous insect. It provides a better understanding of the nutritional strategy of a non-bee pollen feeder and shows the importance of carbohydrates in this strategy. It highlights the need to combine assessments of the plant macronutrient content and insect energetic budget in an adaptive framework to better understand the nutritional strategies of herbivores.