Validation of key sponge symbiont pathways using genome-centric metatranscriptomics.
Paul A O'BrienShangjin TanPedro R FradeSteven J RobbinsJ Pamela EngelbertsSara C BellInka VanwonterghemDavid J MillerNicole Suzanne WebsterGuo-Jie ZhangDavid G BournePublished in: Environmental microbiology (2023)
The sponge microbiome underpins host function through provision and recycling of essential nutrients in a nutrient poor environment. Genomic data suggest that carbohydrate degradation, carbon fixation, nitrogen metabolism, sulphur metabolism and supplementation of B-vitamins are central microbial functions. However, validation beyond the genomic potential of sponge symbiont pathways is rarely explored. To evaluate metagenomic predictions, we sequenced the metagenomes and metatranscriptomes of three common coral reef sponges: Ircinia ramosa, Ircinia microconulosa and Phyllospongia foliascens. Multiple carbohydrate active enzymes were expressed by Poribacteria, Bacteroidota and Cyanobacteria symbionts, suggesting these lineages have a central role in assimilating dissolved organic matter. Expression of entire pathways for carbon fixation and multiple sulphur compound transformations were observed in all sponges. Gene expression for anaerobic nitrogen metabolism (denitrification and nitrate reduction) were more common than aerobic metabolism (nitrification), where only the I. ramosa microbiome expressed the nitrification pathway. Finally, while expression of the biosynthetic pathways for B-vitamins was common, the expression of additional transporter genes was far more limited. Overall, we highlight consistencies and disparities between metagenomic and metatranscriptomic results when inferring microbial activity, while uncovering new microbial taxa that contribute to the health of their sponge host via nutrient exchange.
Keyphrases
- microbial community
- poor prognosis
- gene expression
- antibiotic resistance genes
- wastewater treatment
- minimally invasive
- healthcare
- genome wide
- dna methylation
- public health
- nitric oxide
- copy number
- long non coding rna
- mental health
- heavy metals
- risk assessment
- transcription factor
- health information
- high intensity
- machine learning
- human health
- deep learning
- genome wide identification