Neuronal Cell-Type Classification and Connectivity

Question 1

What did reticularists believe?

Answer 1

NS consists of tissue network - reticulum - formed by fused processes of nerve cells

Question 2

What did neuronists believe?

Answer 2

NS consists of distinct elements - cells

Question 3

What does a microtome do?

Answer 3

Evenly slices brain tissue

Question 4

What is the law of dynamic polarisation of neurons?

Answer 4

Info flows from dendrites to cell body to axon

Question 5

What is the best definition of neuronal type?

Answer 5

Population of neurons with properties that are homogeneous within population - but differ from those of other neurons

Question 6

What are the 4 types of neuronal properties?

Answer 6

Morphology
Physiology
Molecular
Connectivity

Question 7

How can the protein composition of a neuron be assessed?

Answer 7

Immunohistochemistry

Question 8

How can the mRNA composition of a neuron be assessed?

Answer 8

ISH

RNA sequencing

Question 9

What causes heterogeneity in some properties within a neuronal type?

Answer 9

Development - genetic diversification due to stochastic and environmental differences
Continuous genetically-encoded sources of variation - e.g. topographic gradients
Ongoing change in adult environment - neural activity, hormonal fluctuations, circadian rhythms

Question 10

What is the advantage of single cell genome/RNA sequencing?

Answer 10

Reveal diversity masked by averaging across populations - higher sensitivity

Question 11

What are the steps of RNA-seq?

Answer 11

Separate cells of solid tissue
Isolate RNA
Reverse transcription - amplify - form cDNA library
Sequence library
Form expression profile for cell - compare with others - identify cell types

Question 12

What was the old method of classifying DRG neurons?

Answer 12

Small dark - dense, many vesicles

Large light - less dense

Question 13

What are the steps of DropSeq analysis?

Answer 13

Make single-cell suspension from tissue
Co-encapsulate each cell with uniquely-barcoded bead - in nanolitre-scale droplet
Capture cell mRNA on bead - forms STAMPs
Reverse transcription, amplification, sequencing of 1000s of STAMPs - in one reaction
Use STAMP barcodes to infer transcript’s cell of origin

Question 14

What is the advantage of DropSeq analysis over single- cell RNA-Seq?

Answer 14

Do not run each reaction in separate wells - saves costs and labour

Question 15

What are the steps of PatchSeq analysis?

Answer 15

Record cells in slice - electophysiological data
Extract mRNA from cells
Conduct RNA-Seq
Enables direct correlation of molecular and physiological properties

Question 16

What is the disadvantage of PatchSeq?

Answer 16

Low throughput

Question 17

Name 3 advantages of nuclear RNA-Seq

Answer 17

Observe actively-transcribed genes in each cell - within certain tissue - at specific time
-Each cell has own housekeeping gene - acts as barcode - can identify cell type each nucleus dataset from
Nuclei can be isolated from frozen/fixed/dead tissue

Question 18

What is the purpose of RiboSeq?

Answer 18

Determines which mRNAs actively translated in cell - at specific time (translatome)

Question 19

What is macroconnectomics?

Answer 19

MRI to map long-distance tracts in whole brain
Relate to functionally-defined regions in fMRI
Millimetre scale

Question 20

What is mesoconnectomics?

Answer 20

Map local and inter-area connectivity

Micrometre scale

Question 21

What is microconnectomics?

Answer 21

Map individual cells and synapses - using electron microscopy of slices

Question 22

What are the steps of high throughput optical imaging?

Answer 22

Combined 2-photon microscope and robotic microtome - automatic
Cuts sections and scans
Computer stitches images - 3D structure reconstruction

Question 23

What is CLARITY and how is it used?

Answer 23

Removes all lipids in brain - normally scatter light - makes brain transparent
Use antibody label - with high resolution fluorescence signals
Use microscope to scan through brain - visualisation of labelled long-range projections
Early stages of combining with molecular characterisation over large volumes