Abstract
Since the time when detection of gene expression in single cells by microarrays to the Next Generation Sequencing (NGS) enabled Single Cell Genomics (SCG), it has played a pivotal role to understand and elucidate the functional role of cellular heterogeneity. Along this journey to becoming a key player in the capture of the individuality of cells, SCG overcame many milestones, including scale, speed, sensitivity and sample costs (4S). There have been many important experimental and computational innovations in the efficient analysis and interpretation of SCG data. The increasing role of AI in SCG data analysis has further enhanced its applicability in building models for clinical intervention. Furthermore, SCG has been instrumental in the delineation of the role of cellular heterogeneity in specific diseases, including cancer and infectious diseases. The understanding of the role of differential immune responses in driving coronavirus disease-2019 (COVID-19) disease severity and clinical outcomes has been greatly aided by SCG. With many variants of concern (VOC) in sight, it would be of great importance to further understand the immune response specificity vis-a-vis the immune cell repertoire, the identification of novel cell types, and antibody response. Given the potential of SCG to play an integral part in the multi-omics approach to the study of the host–pathogen interaction and its outcomes, our review attempts to highlight its strengths, its implications for infectious disease biology, and its current limitations. We conclude that the application of SCG would be a critical step towards future pandemic preparedness.
Highlights
The remarkable complexity of the biological processes involved in development, physiological homeostasis, disease, and infection outcomes is governed by the heterogeneity of cell states, cell fates, and cell types
To create sequencing-ready libraries, poly(A) tailed mRNA transcripts are captured using poly(T) oligonucleotides with Unique Molecular Identifier (UMI) sequences and single-cell-specific barcodes, which are converted to cDNA through a reverse transcription step
Single-cell V(D)J sequencing was enabled by scRNA-Seq, revealing the B cell receptors (BCR) and T cell receptors (TCR) sequences; this accelerated the identification of neutralising antibodies against invading pathogens
Summary
The remarkable complexity of the biological processes involved in development, physiological homeostasis, disease, and infection outcomes is governed by the heterogeneity of cell states, cell fates, and cell types. An unravelling of these dynamics was brought about by the development of technological toolkits that allowed the detection and quantification of differential gene expression. Single-cell technologies have profoundly enhanced our comprehension of cellular plasticity, transcriptional dynamics, and gene regulatory relationships [7,8]. The design of experiments is gradually moving towards an unbiased, hypothesis-free approach, and towards the analysis of tissues and organs in their entirety, rather than focusing on specific cell types ScRNA-Seq has found extensive application in both basic and translational research
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