We are delighted to announce a new thematic collection in Lab on a Chip, focusing on multimodal single cell analysis, with Professors Daniel T. Chiu and Pratip K. Chattopadhyay as thought leaders.
Professors Chiu and Chattopadhyay describe the current challenges in the field in their recent editorial in Lab on a Chip on “The Next Frontier in Single Cell Analysis: MultiModal Studies and Clinical Translation”:
“Biological processes are inherently complex. Stochasticity, redundancy, plasticity, and noise are built into fundamental cellular activities from gene transcription to protein expression. A major challenge in biomedical research is to untangle this complexity. Microarray technology influenced biological research because it demonstrated clearly the wide selection of cellular molecules available for measurement and provided an efficient means to query them. However, microarrays require a large amount of material and assay large numbers of cells together in bulk.
Single cell analysis overcomes the problems of bulk measurements, but for many years the only available technology—flow cytometry—was incapable of highly multiplexed measurements. The current movement in single cell analysis is multimodal characterization. These approaches, which are rapidly replacing one-dimensional single cell analysis in biomedical research, simultaneously combine measurements of transcription with post-transcriptional regulation, epigenetic modifications, and surface protein expression. It is possible that lipid and metabolite composition, and/or cellular morphology may also be analyzed with the transcriptome or proteome.
We now have a dizzying array of tools that provide us with the potential to comprehensively and accurately characterize the cells involved in a biological process. We are a step away from using these tools widely and efficiently to impact clinical care, but there are large obstacles we must break down first. With a better understanding of the complexity ingrained in cellular systems, how do we smartly choose subsets of markers and cell types to survey, remembering that samples from patients are often limited as are research budgets? Once we know what to measure, there is the critical question of how to measure it, since there are a myriad of technical platforms and data analysis tools from which to choose. As we make measurements, how do we ensure that they are robust—are there general validation and quality control principles we can establish, or are such measures wholly platform-specific? Finally, are highly multiplexed, single cell technologies valuable only as a screening tool to identify simple biomarkers, or can these highly complex technologies (and their associated data analysis algorithms) be used directly for clinical diagnostics?”
We invite review and research manuscripts that suggest answers to these questions and related issues for inclusion in a thematic collection focused on multimodal single cell analysis. If you are interested in submitting to the collection please contact the Editorial Office.
This collection open for submissions now, and into 2020.
If you’re interested in this topic, you can read our previous thematic collection on droplet-based single-cell sequencing here. The articles are free to read until November 15th 2019.