The descriptive discoveries by single-cell omics bring less useful knowledge?

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The other day I was initiating the Charles Darwin’s On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life (物种起源) based on my supervisor Fuchou Tang’s recommendation. A absolute must read although the conclusions from it seems obvious and true in modern knowledge. You will be shocked by the views in the book only base on the large number observations of species, geography oversea. His logic was so clear that he could make absolutely definitive conclusions without any genetic knowledge at that early stages.

It means, a systematic and acurate description absolutely can provide prospective and new knowledge.

During my PhD at Bing Liu’s lab, I focused on the hematopoietic stem cell (HSC) formation during mammalian embryogenesis.

1. We firstly explored a new marker to enrich the so rare functional HSCs (10-20 cells per embryo) by the unique single-cell initiated in vivo transplant system.
2. We combined the single-cell transcriptome profiling to uncover the gene expression patterns. The endothelial-to-HSC transition(EC-HSC transition) enriched multiple signaling pathway.
3. We hypothesis the mTOR could potentially regulate the HSC emergence.
4. We specifically inhibited the mTOR in the endothelial cells before the HSC formation, resulting in a deletion of HSC emergence.

This looped study strongly indicates the single-cell gene expression patterns (so-called descriptive sequencing-based results) largely helped us mine so much critical potential candidate regulators during this EC-HSC transition. This story and my experience told us these resources could powerful to uncover the principles of many biological process if it is based on,

a. Whether we provided a higher-sensitivity/precision or untouched-yield database by a newly-developed wet/dry strategies, compared with the previous studies.
b. Whether we launched inspiring hypothesis based on the data mining (otherwise it maybe just visualize the well-known conclusions in an omics ways).
c. Whether we initiate the study with specific questions.
d. Whether we link the omics-based conclusion with the phenotype by following functional validations.

The single-cell biology indeed presents a unprecedented opportunity to explore the cell heterogeneity (accurate molecular landscape of the specific cell types) from the multidimensional molecular patterns at a so-far limiting resolution. The deep meaning could be that we can harvest a clear molecule activity map with THE TARGET CELL, which will never been read out with the measurement from bulk cells since it always only contains a AVERAGE level within the mixture of target and untarget cells. Taking the HSC emergence for example, we would never know any new clues from a bulk profiling of the whole AGM tissue (the core site of HSC derivation) or even CD31+CD45+/- cells (containing just one functional HSC from the other fifty cells) of the embryo at the very beginning of our study.

Taking the training from both the conventional developmental biology and single-cell biology together: Besides technically, the higher throughout, more accurate, more applicable in other fields (e.g. industry and clinical diagnosis), simultaneously more multi-dimensional omics methods at single-cell level and less costly, I assumed there will be no widespread question that the near future is absolutely the world of data mining and molecular feature-phenotype linking (a must read from J. Gray Camp et al.). I’m recently thinking about this by myself (you probably heard a lot from others),

1. Measure/describe the scientific phenomenon/principle.
2. Explore/understand the deep mechanism behind the principle.
3. Manipulate the principle to promote the public health and nature.

These probably could be the three major steps and outcomes of life science. Are you enjoyable with your current queue?