Low-Input and Single-Cell Transcriptomic Technologies and Their Application to Disease Studies

With the rapid progress of next-generation sequencing (NGS) technologies, new tools and methods have emerged to investigate the transcriptomics of various organisms. RNA sequencing (RNA-seq) employs NGS to evaluate the presence and abundance of RNA transcripts in biological samples. This technique offers a comprehensive snapshot of the RNA dynamics within cells. With the ability to profile the entire transcriptome of organisms rapidly and accurately, RNA-seq has become the state-of-the-art method for transcriptome profiling, surpassing the traditional microarray approach. Single-cell RNA sequencing (scRNA-seq) was introduced in 2009 to profile the single-cell gene expression in highly heterogeneous samples such as brain tissue and tumors. The advancement of scRNA-seq technologies enables the in-depth transcriptomic study in each cell subtype. When selecting an scRNA-seq method, researchers must weigh the trade-off between profiling more single cells versus obtaining more comprehensive transcripts per cell, while considering the overall costs. The throughput of full-length scRNA-seq methods is usually lower, as each single cell needs to be processed separately to produce scRNA-seq libraries. However, full-length methods enable the researchers to investigate the splicing variants and allele-specific expression. Non-full-length methods only capture the 3' or 5' ends of transcripts, which limits their application in isoform detection, but as cells are pooled after barcoding for cDNA synthesis, the throughput is 2–3 orders of magnitude higher than full-length methods. We developed a droplet-based platform for full-length single-cell RNA-seq, which enabled the efficient recovery of full-length mRNA from individual cells in a high-throughput manner. The developed platform can process ~8,000 single cells within 2 days and detect ~20% more genes compared to Drop-seq. Besides scRNA-seq technology development, we also applied a low-input RNA-seq method to study the transcriptomics in different biological samples. When handling precious biological samples, a low-input method is necessary to profile the transcriptome of homogeneous cell populations. We first studied the epigenomic and transcriptomic regulations in colorectal cancer (CRC) using MOWChIP-seq, a low-input high-throughput method, in conjunction with our low-input RNA-seq approach. Fusobacterium nucleatum (Fnn) is closely related to the progression of cancers like CRC and pancreatic cancer. However, the molecular mechanisms of how Fnn adjusts the tumor microenvironment (TME) and leads to poor clinical outcomes are still unclear. In this in-vitro study, we characterized how hypoxia, an important TME ignored by previous research, facilitates Fnn infection of CRC and corresponding alterations of global epigenome and transcriptome. We infer that hypoxia has similar effects as Fnn infection alone on the CRC cells. The Fnn infection under hypoxia further boosts the proliferation and progression of CRC.
We then applied our low-input RNA-seq method to study brain neuroscience and immunology. Psychedelics like DOI show promising clinical efficacy in patients with psychiatric conditions. Although psychedelics exhibit rapid antidepression action and long-lasting effectiveness compared to conventional treatment, their acute psychotic symptoms and potential for drug abuse discourage their application in clinical practice. In this case, it is important to comprehend the molecular mechanisms responsible for psychedelics' clinical efficacy. This understanding can pave the way for the development of improved treatments that do not rely on psychedelics. After profiling the transcriptome of mouse brain samples exposed to psychedelics with different post-exposure times, we concluded that the psychedelic-induced transcriptomic variations are more transient than epigenomic changes. In the second brain neuroscience project, we first applied 3-color FACS sorting to differentiate four neuron and non-neuron subtypes in human postmortem prefrontal cortex tissues. Then we profiled the gene expression of the four subtypes and validated the FACS sorting by examining the expression of marker genes. Differentially expressed genes between each subtype and the others were extracted and proceeded to gene ontology analysis. We identified unique altered biological pathways related to each subtype.
The immunology research focuses on revealing the difference between low-grade inflammation and monocyte exhaustion, as well as the unique biological pathways they regulate. Therefore, we profiled the transcriptome of bone marrow-derived monocytes stimulated by PBS control, a low- or high-dose LPS. In addition to wild-type mice, we also included TRAM-deficient and IRAK-M-deficient mice. We concluded that low-dose LPS specifically regulates the TRAM-dependent pathway of TLR4 signaling, and high-dose LPS exclusively upregulates exhaustion markers by impacting metabolic and proliferative pathways.