Lecture notes. Written from the material of MIT 8.591J 2004, licensed CC BY-NC-SA 4.0. These are notes, not a transcript: the material has been reorganised and rewritten. This adaptation carries the same licence, and the original is linked above.
15. Quorum Sensing and Cell-Cell Communication¶
What this covers¶
This is the transition slide set into the course's last unit: from a single cell treated on its own to a multicellular organism built from cells that talk to one another. The only source for this chapter is a slide deck (converted from a PDF with no text layer, its figures removed for copyright), so the chapter is short and stays close to what those slide headings actually assert. It assumes the earlier framing of the course — single-cell systems biology, both at the level of the whole cell as a reactor and at the level of diffusion and gradients inside it — and does not attempt to reconstruct any mechanism the slides only showed as a picture.
Three levels of systems biology¶
The slides frame the course's material as three nested questions, moving from a single cell in isolation to a population of cells that must coordinate:
- Systems microbiology treats the single cell as a well-stirred bio-reactor.
- Systems cell biology stays with the single cell but now takes diffusion and spatial gradients seriously, since these matter for regulation inside the cell.
- Systems developmental biology asks how a multicellular organism is built from single cells — which requires cell-cell communication.
This chapter's material sits at the start of the third of these: it introduces the experimental system the course uses to study cell-cell communication.
Quorum sensing as the experimental system¶
The slides name bacterial quorum sensing as "a tractable experimental system for cell-cell communication," and identify N-acyl-L-homoserine lactones (AHLs) as the main signalling molecules in that system. Beyond those two facts, the slides carry no reconstructable content here: the explanatory figures for both headings were removed from the converted source for copyright reasons, and there is no accompanying transcript to describe what they showed. So this chapter can record that quorum sensing and AHL signalling are the system chosen for study, but not the mechanism — the threshold behaviour, the diffusion argument, or whatever diagram made the case for "tractable" — since none of that survived the conversion.
An engineered example: programmed population control¶
The slides point to a specific paper as "an example of engineering cell-cell communication":
You, L., R. S. Cox 3rd, R. Weiss, and F. H. Arnold. "Programmed population control by cell-cell communication and regulated killing." Nature 428, no. 6985 (22 April 2004): 868–71.
As with the two headings above, the figure illustrating the circuit was removed from the converted slides, and there is no transcript describing it. The pointer itself — that a synthetic cell-cell-communication circuit can be built to regulate a population's size by coupling communication to killing — is everything this material supports; the circuit's design and how it achieves that regulation are not recoverable from what was supplied and should be read from the paper directly.
Sources¶
- Slides:
lectures/23-notes.md(converted fromlectures/23-notes.pdf, MIT OCW 8.591J, Fall 2004) — the three-level table of systems microbiology / systems cell biology / systems developmental biology; the quorum sensing and AHL headings; the pointer to You et al., Nature 428 (2004): 868–71. - No transcript, written notes, or exercises were supplied for this lecture.
- Not included here: the slide deck's administrative announcements (a problem-set correction to Eq. 3b, the recitation and lecture schedule) and the three figures the deck marked as "removed due to copyright considerations" — the quorum sensing diagram, the AHL structure/pathway figure, and the population-control circuit diagram. None of these is reconstructable from the supplied material.
← 14. Alternative views on gradient sensing · Contents · 16. Drosophila Morphogen Gradients and Robustness →