# SSTDhunter: a curated gene database for investigating androgen producing potential in microbiota species

## TL;DR

This paper introduces SSTDhunter, a specialized gene database to study androgen production potential in gut microbiota, aiding in prostate cancer research.

## Contribution

The novel contribution is the creation of a curated database, SSTDhunter, for efficient identification of androgen-producing genes in microbiota.

## Key findings

- SSTDhunter was built using genomic analysis and homologous gene comparisons to identify SSTD-coding genes.
- The database includes homologous tktA genes to reduce false positives in metagenomic analyses.
- SSTDhunter is freely accessible and designed for rapid gene detection in large datasets.

## Abstract

Androgens are critical for the growth of prostate cells, as well as prostate tumor cells. For prostate cancer patients under Androgen Deprivation Therapy (ADT) such as castration treatment, investigating the potential for androgen production by gut microbes is crucial. In microbe species, the side chain cleavage activity of steroid-17, 20-desmolase (SSTD) is responsible for 11-oxy-androgens production by biotransformation from cortisol, as well as from other endogenous steroids and pharmaceutical glucocorticoids. The side-chain cleavage product of prednisone could significantly promote the proliferation of prostate cancer cells. The SSTD is a complex formed by N-terminal and C-terminal transketolases encoded by desA and desB genes, whose activity has been well-characterized in Clostridium scindens ATCC 35704. While a void still existed in evaluating the androgen producing potential by gut microbiota owing to relatively low abundance of SSTD-carrying species and the lack of professional gene database. Meanwhile, mining SSTD encoding genes in explosion sequencing data has become computationally expensive and time-consuming using comprehensive database. Here, a professional database consisted of SSTD-coding genes, named SSTDhunter, was constructed using a large-scale genomic analysis along with homologous genes as background. These SSTD-coding genes were reconstruction through comprehensive characteristics consisted of operon structures, sequence identities, phylogenetic topologies and comparative analysis. To reduce false positives, protein sequences of homologous genes tktA, which encode component of sugar transketolase, were also included in SSTDhunter database as background noise. SSTDhunter is for rapid investigation of SSTD-coding genes in massive metagenomic data, which is freely available at http://www.orgene.net/SSTDhunter/.