The study, published in the journal Ecology and Evolution, is notable for its approach. Rather than relying on fecal samples, which mainly reflect the distal gut and can mask variation between regions, the researchers sampled the gastrointestinal contents directly from three anatomical segments in each of three wild-caught snakes. Because the species is difficult to find in the field, the sample size was small, and the authors are careful to frame the work as an initial exploration rather than a definitive survey. Even so, the resulting dataset offers a rare window into the gut microecology of an understudied reptile lineage, and it adds to a very short list of wild snakes whose gastrointestinal microbiomes have been profiled at this level of detail.

From June to July 2022, the team captured three individuals in Motuo County, a region that receives more than 200 days of precipitation each year, with summer rainfall accounting for over half of the annual total. The snakes were fasted before sampling, and abdominal palpation confirmed that no undigested prey remained in the gut. Contents from the stomach, small intestine, and large intestine were collected into sterile tubes, flash-frozen in liquid nitrogen, and stored at minus 80 degrees Celsius, yielding nine samples in total. This direct sampling strategy matters because each gastrointestinal compartment presents distinct physicochemical conditions, from the acidic, oxygen-exposed stomach to the largely anaerobic large intestine, and those gradients can shape region-specific microbial communities.

On the sequencing side, the team extracted total DNA and performed metagenomic shotgun sequencing, generating roughly 6.58 gigabases of raw data per sample on average. After quality control, more than 97 percent of bases scored at or above Q20, and GC content averaged about 42 percent. Because no reference genome exists for R. himalayanus, reads were filtered against the genome of its close relative Rhabdophis nuchalis to remove host contamination. The clean reads were then assembled, genes were predicted and clustered into a non-redundant catalog, and the resulting unigenes were annotated against microbial databases to build taxonomic and functional profiles. Good’s coverage exceeded 99.9 percent in the alpha diversity analysis, indicating that sequencing depth was sufficient to capture the microbial diversity present.

The taxonomic results were striking in their consistency. Across all nine samples, the researchers identified 1,462 microbial species belonging to 66 phyla and 774 genera, spanning bacteria, archaea, eukaryotes, and viruses. Bacteria dominated, and the five most abundant phyla were Pseudomonadota, Actinomycetota, Bacillota, Campylobacterota, and Bacteroidota. At the genus level, Escherichia, Mycobacteroides, Campylobacter, Nocardia, and Thalassococcus led the rankings, while at the species level Escherichia coli, Mycobacteroides chelonae, Campylobacter sp. CS_ED1, Thalassococcus profundi, and Klebsiella pneumoniae were the top five. In other words, the stomach, small intestine, and large intestine shared several dominant taxa, a pattern that echoes findings from other Rhabdophis species, where Pseudomonadota has also been reported as the dominant phylum.

Yet the shared core did not mean the three segments were microbial clones of one another. Alpha diversity indices did not differ significantly among segments, and neither NMDS ordination nor Adonis testing detected statistically significant clustering between groups. But finer-grained analyses told a subtler story. A heatmap of the 35 most abundant genera showed that 19 genera, including Pseudomonas, Streptomyces, Escherichia, Klebsiella, and Bacteroides, were more abundant in the small intestine than in the stomach, while 14 genera, including Aeromonas, Bacillus, Campylobacter, and Vibrio, were more abundant in the large intestine than in the small intestine. The stomach stood out for elevated levels of Batrachochytrium and Mycobacterium. LEfSe analysis identified ten biomarkers enriched in the small intestine compared with only three in the stomach, and principal component analysis of differential species showed a separation trend between segments.

Some of the species-level differences were particularly intriguing. Multiple Bacteroides species, including B. thetaiotaomicron, B. fragilis, B. ovatus, and B. xylanisolvens, along with Phocaeicola vulgatus and Fusobacterium varium, were significantly more abundant in the small intestine than in the large intestine, while Xanthomonas citri and Pseudomonas monteilii showed the reverse pattern. The presence of genera such as Nocardia and Thalassococcus, which are often associated with external environments, tentatively suggests that the snake’s gastrointestinal microbiota may be influenced by exogenous sources, perhaps reflecting its diet of frogs and toads or its humid mountain habitat. Low-abundance taxa, the authors note, can still play outsized functional roles, modulating immune responses and helping to stabilize the community.

Functionally, the metagenomic data painted a picture of a microbiome built for a carnivorous, intermittently feeding predator. eggNOG annotation showed that the most represented categories were amino acid transport and metabolism, replication and repair, and carbohydrate transport and metabolism. Within the CAZy database of carbohydrate-active enzymes, glycoside hydrolases formed the largest group, followed by glycosyltransferases and carbohydrate-binding modules. Two families stood out: CBM14, a chitin-binding module, and GH18, a family that includes chitinases. Their high relative abundance suggests the gut microbes of R. himalayanus may be equipped to bind and degrade chitin, a plausible adaptation given that the snake’s anuran prey contains chitinous material from ingested arthropods. The small intestine carried twelve enzyme families at higher abundance than the other segments, while the large intestine showed elevations in three families, and twelve CAZy families differed significantly between the small and large intestines.

The metabolomics layer added a biochemical dimension. Using ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry, the team profiled gastrointestinal contents in both positive and negative ionization modes. Principal component analysis showed the first two components explaining 26.49 and 19.55 percent of variance, with quality control samples clustering tightly, though overall metabolite profiles did not separate significantly among segments. Pairwise comparisons, however, revealed dozens of differentially abundant metabolites. In positive ion mode, 33 metabolites differed between stomach and small intestine, and 27 between stomach and large intestine. KEGG pathway enrichment pointed to amino acid metabolism, nucleotide metabolism, lipid metabolism, and cofactor-related pathways, including tryptophan, histidine, phenylalanine, and beta-alanine metabolism. Tryptophan metabolism is especially interesting because microbially derived tryptophan metabolites can modulate gut homeostasis and inflammation through the aryl hydrocarbon receptor signaling pathway, hinting at a potential microbiota-host crosstalk axis in these snakes.

The regional metabolite patterns also make physiological sense. The large intestine is a classic anaerobic fermentation chamber where dense microbial populations drive high metabolic activity, while the stomach, despite its acidity, hosts microbes capable of adaptive responses to low pH and oxidative stress. The small intestine, by contrast, presents a harsher environment for microbes: contents flow quickly, making stable colonization difficult, and its higher oxygen content limits anaerobic fermentation. That structural specificity, the authors argue, may constrain microbial complexity in the small intestine relative to the other two segments. The enrichment of amino acid and carbohydrate metabolic pathways across the gut aligns with the snake’s high-protein, low-carbohydrate diet and its remarkable digestive plasticity, the ability to rapidly restore gastrointestinal function after prolonged fasting, a trait that may itself be supported by microbiota-mediated metabolic flexibility.

The authors are candid about the study’s limits. Three individuals cannot capture the full variability of a wild population, and the statistical power to detect differences among segments was constrained. Sampling cryptic reptiles in remote Himalayan terrain poses formidable logistical and ethical challenges, which is precisely why so few snake species have been characterized this way. Still, the work establishes a baseline: a shared dominant core of Pseudomonadota and other taxa across gut regions, segment-specific differences in low-abundance taxa and carbohydrate enzymes, and a metabolite landscape centered on amino acid and lipid metabolism. Future studies with larger samples, long-term monitoring, and populations from different geographic regions will be needed to test how stable these patterns are and what ecological forces drive them. For now, the orange-collared keelback has moved from genomic anonymity to a species whose inner microbial world is, at last, on the map, and it offers conservation-relevant insight at a time when gut microbiomes are increasingly recognized as tools for managing vulnerable wildlife.

Subject of Research: Gastrointestinal microbiome and metabolite profiles across digestive tract segments of the orange-collared keelback snake

Article Title: Characteristics of Microbiota in Different Segments of the Digestive Tract of Orange‐Collared Keelback (Rhabdophis himalayanus)

Article References: Chen, J., Jiang, J., Zhou, X., Fan, L., Wu, F., Liang, P., Song, H., Wang, J., Luo, J., & Zhu, G. (2026). Characteristics of Microbiota in Different Segments of the Digestive Tract of Orange‐Collared Keelback ( Rhabdophis himalayanus ). Ecology and Evolution, 16(10), Article e74508. https://doi.org/10.1002/ece3.74508

Image Credits: AI Generated

DOI: 10.1002/ece3.74508

Keywords: snake microbiome, Rhabdophis himalayanus, metagenomics, metabolomics, gastrointestinal tract, Pseudomonadota, chitin degradation, CAZy enzymes, tryptophan metabolism, Himalayas, herpetology, gut microecology