It is said in Spanish, "si no existe, créalo" or "if it does not exist, create it." This is exactly what sometimes occurs at the Fred Hutch. When we do not have the tools to test a hypothesis, we must be creative! A great example is a collaboration between Dr. Susan Bullman, an Assistant professor of Human Biology, and Dr. Christopher Johnston, an assistant professor of Vaccine and Infectious Disease, that resulted in a recent Nature Protocols publication. The research teams developed a method called INVADEseq (invasion-adhesion-directed expression sequencing) for identifying bacterial transcripts in cancer cells.
A growing number of human cancer types are characterized by the presence and composition of a tumor microbiome, a collection of cancer-associated bacterial species that add yet another layer of complexity to this disease and can influence prognosis or treatment response. Until recently, researchers studying tumor samples have primarily relied on next-generation sequencing-based methods, such as single-cell RNA sequencing (scRNAseq) to study the host cells' transcriptional profiles. However, scRNAseq generally fails to detect bacteria within tumor samples, since this method relies on the poly(A) tail at the 3' end of the transcripts that are present only in eukaryotic mRNAs. As bacterial RNAs generally lack the poly(A) tail, scRNAseq cannot identify bacteria within or those associated with a cancer cell.
So, how can we identify bacterial transcripts within a tumor sample? To answer this question, Dr. Jorge Galeano Niño, a postdoctoral research fellow in the Bullman lab and leading author of the study, took advantage of the fact that ~90% of the bacterial transcriptome is either 16S or 23S ribosomal RNA (rRNA). Since the 16S gene has universally conserved regions across microbial communities, the team developed a new method, the INVADEseq protocol, which introduces a primer that targets the bacterial 16S rRNA gene.
INVADEseq was developed using the 10X Genomics Chrominum 5' scRNA assay, which utilizes the SMART technology (Switching Mechanism at the 5′ end of RNA Template) to construct the cDNA libraries. This technology relies on the template switching activity of Moloney murine leukemia virus reverse transcriptase (MMLV RT) to synthesize and anchor the first-strand cDNA to the gel beads-in-emulsions (GEMs). By using the MMLV RT, the mRNA is first transcribed into cDNA using a primer that binds to the eukaryotic poly(A) mRNA. Additionally, this MMLV RT adds three non-template nucleotides to the 5' end of the newly synthesized first-strand cDNA, which binds to complementary nucleotides from a template switching oligo (TSO) that also contains a 10x barcode sequence and a unique molecular identifier (UMI) that can be used to scale down for the amplification steps thus providing the original transcriptional load. Using this method, the template strands can be switched from cellular RNA to TSO, which serve as primer-binding sites for the subsequent amplification steps. Since bacterial RNA transcripts usually lack poly(A) tails, this approach is not sufficient to detect bacterial transcripts. Here is the trick! The team used the same SMART technology that was implemented to capture poly(A) transcripts to capture bacterial transcripts contained in the GEMs by priming the conserved regions of the bacterial 16S rRNA gene. The subsequent reverse transcription of the variable regions of the 16S rRNA gene allowed the team to taxonomically resolved the bacterial communities that were associated with a single eukaryotic cell.
To test their technology, the team identified cell-associated bacteria in oral squamous cell carcinoma (OSCC) tumor tissue, which is thought to be influenced by the microbiome. By using INVADEseq, the researchers demonstrated that cell-associated bacteria were largely present inside a subset of epithelial and macrophage single cells. Moreover, the team found that Fusobacterium and Treponema species were the predominant bacteria associated with OSCC tumors. The INVADEseq approach has been shown to be an effective method for identifying and analyzing bacterial transcriptomics from tissue samples at a single cell level. More broadly, this tool will enable researchers to investigate the host gene signatures associated to certain bacteria species at the single cell level to further our understanding of how these relationships influence cancer initiation and progression.
The spotlighted research was supported by grants from the Genomics and Bioinformatics Shared Resource of the Fred Hutch/University of Washington Cancer Consortium and the Scientific Computing Infrastructure at Fred Hutch, Interdisciplinary Training Grant in Cancer, the Cancer Research Institute Irvington Postdoctoral Fellowship, the National Institutes of Health the National Institute of Dental and Craniofacial Research, the National Cancer Institute,
Fred Hutch/UW Cancer Consortium members Dr. Susan Bullman and Dr. Christopher Johnston contributed to this work.
Galeano Niño JL, Wu H, LaCourse KD, Srinivasan H, Fitzgibbon M, Minot SS, Sather C, Johnston CD, Bullman S. INVADEseq to identify cell-adherent or invasive bacteria and the associated host transcriptome at single-cell-level resolution. Nat Protoc. 2023 Nov;18(11):3355-3389. doi: 10.1038/s41596-023-00888-7.