Part A: Open-ended questions

1. How would you use SynBio to non-invasively measure levels of many RNAs from many cells at once?

I started compiling the list below before I found this Wikipedia article which already summarizes a lot of the commonly used methods in (spatial) transcriptomics.

Method Description
RNA sequencing (RNA-seq) RNA is extracted from the cells and read either directly (modern methods) or first reverse transcribed into double-stranded cDNA and then read by high-throughput short-read sequencing methods. Provides quantitative change in gene expression over the whole transcriptome, but lacks spatial context.
Fluorescent in situ hybridization Single-molecule fluorescence in situ hybridization (smFISH): Detect mRNA or longer RNA molecules in tissue samples. Fluorescently labeled oligonucleotides bind to the RNA and can be imaged by fluorescent microscopy. Spatial information is retained but it's limited to a small number of RNAs.
There are a lot of other *FISH approaches like osmFISH, MERFISH, seqFISH, seqFISH+ which produce similar output data but address a lot of the limitations of smFISH.
in situ sequencing Fluorescent in situ sequencing (FISSEQ): Combines the spatial context of RNA-FISH and the global transcriptome profiling of RNA-seq. Within the tissue, each DNA/RNA molecule is first amplified in-situ via rolling-circle amplification to create localized rolling circle colonies (copies of the parent molecule). After a series of biochemical steps, in the kth cycle, a fluorescent tag is introduced. Its color corresponds to the kth nucleotide in the parent DNA strand. The system is then imaged. Each colony appears across a series of fluorescent images as a spot with the sequence of colors corresponding to the nucleotide sequence of the parent molecule.
Other methods include Barista-seq and STARmap.

2. What aspects of electronic circuits (e.g. sensors, analyses, actuators, etc.) are most obviously missing from synbio and how would you extend SynBio to handle these?

This paper outlines an interesting four-pronged approach to merge biology and electronics:

  1. The mapping of biological circuits to electronic circuits via quantitatively exact schematics
  2. The use of existing electronic circuit software for hierarchical modeling, design, and analysis with such schematics
  3. The use of cytomorphic electronic hardware for rapid stochastic simulation of circuit schematics and associated parameter discovery to fit measured biological data
  4. The use of bio-electronic reporting circuits rather than bio-optical circuits for measurement

3. Scenarios in which public use of synbio might be ethically acceptable, economically desirable, and even mandatory?