Caterpillars lack a resident gut microbiome

Abstract

Many animals are inhabited by microbial symbionts that influence their hosts’ development, physiology, ecological interactions, and evolutionary diversification. However, firm evidence for the existence and functional importance of resident microbiomes in larval Lepidoptera (caterpillars) is lacking, despite the fact that these insects are enormously diverse, major agricultural pests, and dominant herbivores in many ecosystems. Using 16S rRNA gene sequencing and quantitative PCR, we characterized the gut microbiomes of wild leaf-feeding caterpillars in the United States and Costa Rica, representing 124 species from 16 families. Compared with other insects and vertebrates assayed using the same methods, the microbes we detected in caterpillar guts were unusually low-density and highly variable among individuals. Furthermore, the abundance and composition of leaf-associated microbes were reflected in the feces of caterpillars consuming the same plants. Thus, microbes ingested with food are present (though possibly dead or dormant) in the caterpillar gut, but host-specific, resident symbionts are largely absent. To test whether transient microbes might still contribute to feeding and development, we conducted an experiment on field-collected caterpillars of the model species Manduca sexta. Antibiotic suppression of gut bacterial activity did not significantly affect caterpillar weight gain, development, or survival. The high pH, simple gut structure, and fast transit times that typify caterpillar digestive physiology may prevent microbial colonization. Moreover, host-encoded digestive and detoxification mechanisms likely render microbes unnecessary for caterpillar herbivory. Caterpillars illustrate the potential ecological and evolutionary benefits of independence from symbionts, a lifestyle which may be widespread among animals.

Gut microbiota structure differs between honeybees in winter and summer

“…2e). Such quantitative microbiome profiling approaches can reveal important associations between gut bacteria and the host, as previously demonstrated for the human microbiota [29] or the microbiota of caterpillars [47]. We argue that absolute abundances should be routinely assessed when analyzing microbial communities, as changes in absolute abundance-but not necessarily relative abundance -may alter the impact of a given bacterium on its environment.…”

Not all animals need a microbiome

“…Microbiologists and ecologists have long placed an important distinction between these two categories (e.g. Janzen 1977;Harris 1993;Berg 1996;Snell Taylor et al 2018), and an increasing number of animal microbiome studies are making efforts to differentiate resident from transient taxa as well (David et al 2014;Lee et al 2016;Hammer et al 2017;Auchtung et al 2018).…”

“…Likewise, leaves and wood are difficult-todigest, nitrogen-poor diets that may bring to mind symbiontdependent animals, such as leafcutter ants and termites (Aylward, Currie and Suen 2012; Brune and Dietrich 2015). However, a variety of other animals use host-encoded mechanisms to subsist on leaves or wood without direct microbial assistance (German and Bittong 2009;Shelomi, Watanabe and Arakawa 2014;Hammer et al 2017;Besser et al 2018). (These capabilities are sometimes conferred by genes horizontally acquired from microbes, but we do not consider such genes, nor mitochondria, to be part of an animal's microbiome).…”

“…Microbiome-free animals would miss out on the welldocumented benefits that symbionts are capable of providing, and excluding microbes is likely neither cheap nor easyparticularly for species that encounter large numbers of potential colonists in their food or environment. On the other hand, they would avoid paying the widely acknowledged costs of hosting and relying on symbionts (Vorburger and Gouskov 2011;Bennett and Moran 2015;Hammer et al 2017;Rodrigo et al 2017).…”

Distinguishing nutrient‐dependent plant driven bacterial colonization patterns in alfalfa

“…To confirm that our results were unaffected by such bias, we applied a different approach than previous computational prediction tools (Langille et al ., ; Angly et al ., ) by pairing our 16S rRNA amplicon data with viable counts of the total synthetic community inoculum. Correlations between 16S rRNA copy number and viable counts have been previously assessed to establish if organisms were over or underrepresented in 16S rRNA gene amplicon sequencing (Hammer et al ., ). We established a ratio of between the number of reads assigned to each member of our synthetic community from the sequenced total community inoculum sample and the viable counts in the same sequenced inoculum.…”