Bio Flashcards
Defining the nervous system
The nervous system is made up of a network cells specialized to sense information (inputs)
from the “outside” world (light, chemicals, temperature, gravity, touch) senory neurons
from the “inside” world (internal states, signals from other cells)
These cells (neurons) can propagate information, along axons and dendrites, in the form of electrical impulses
Graded potentials
Action potentials
Neurons convey information to each other via chemical and electrical synapses
The nervous system generates outputs that integrate sensory information to elicit behavioral and/or physiological responses
e.g., muscle contraction and movement
e.g., heart rate, digestion, temperature
e.g., feeding, courtship, locomotion
Information flow in the nervous system
Let’s use visual processing in the retina to review how information
flows through neural circuits:
Receptor cells in the retina have special proteins (photoreceptors) that detect light to trigger a change in voltage across the cell membrane
Here, light is converted into an electrical signal in the receptor cells
Electrical signals travels to synapses, where they trigger the release of chemicals (neurotransmitters) that bind neurotransmitter receptors on post-synaptic Bipolar cells
chemical synapses convert electrical signals into chemical signals
The neurotransmitter receptors on Bipolar cells produce graded electrical responses
Stronger light → more NT secretion by receptor cell
More NT → stronger change in membrane voltage
(depolarization) of the Bipolar cell we are back to an
electrical signal Graded responses reach Bipolar cell nerve terminals which synapse onto Ganglion cells
Neurotransmitters are secreted again
Bind to NT receptors on Ganglion cells to once again trigger graded electrical responses
Graded vs action potential
When graded depolarization is strong enough, excitable neurons (like Ganglion cells) generate action potentials (APs)
All or none electrical responses that travel very fast along nerve fibers (e.g., axons)
Graded potentials “fizzle out” over time
Ions/charges that give rise to graded potentials are quickly depleted
Graded potentials can be excitatory (depolarizing) or inhibitory (hyperpolarizing)
Excitatory Post-Synaptic Potentials = EPSPs
Inhibitory Synaptic Potentials = IPSPs
Action potentials arise when graded potentials activate voltage-gated sodium (NaV) and potassium (KV) channels
Unlike graded potentials, APs don’t dissipate
All-or-none electrical impulses that can travel up to 120 m/s along axons!
NaV channels drive membrane depolarization, while KV channels drive repolarization/hyperpolarization
Some key action potential functions in neurons:
Transmit signals along axons
Trigger pre-synaptic Ca2+ influx at nerve terminals, through voltage-gated calcium channels, causing the regulated release of neurotransmitters (exocytosis)
Graded vs. action potentials in other cells
Key function in muscle:
Driving contraction
Key function in endocrine cells:
Driving secretion of hormones (exocytosis)
Challenges associated with understanding the nervous system
As biologists, we often think of biological systems in genetic and chemical terms:
i.e., reactions and interactions involving DNA, RNA, proteins, membrane lipids, etc.
However, the movement of electrical signals through neural structures requires
understanding some core principles in physics:
i.e., current, voltage, resistance/conductance, capacitance, etc.
In this course we aim to integrate these two ways of thinking about biological systems, to better understand how our own nervous system operates
And by extension, how disease states emerge at the intersect between molecular biology and electrophysiology
Early inroads into understanding the nervous system
We didn’t always know that neurons are cells…
The cell theory (1838):
Made possible by technological advances in microscopy- used light microscope
Based on combined observations by numerous scientists
All living organisms are composed of cells
The cell is the basic unit of structure and organization in organisms
All cells come from pre-existing cells
Didn’t see discrete cells in neuronal structure- challenge had to be overcome to see that neurons are made of cells
The reticular theory of the nervous system
The reticular theory of the nervous system ignored the cell theory (1861):
i.e., The nervous system is made up of a single contiguous network (not separate cells!)
Camillo Golgi and J. von Gerlach
Ironically, Golgi invented “la reazione nera”:
i.e., “the black reaction”
a.k.a. the Golgi stain
Apply potassium dichromate and silver nitrate to fixed neurons
Randomly labels a subset of neurons in their entirety, permitting single cell tracing
Ignores cell theory- nervous system made of single network
Golgi stain- applies chemicals to fixed(dead) neurons- a small subset of neurons turn black- can trace the stucture
Hard to distinguish distinct neurons, they are overlapping, do it enough can depict specific shapes
Golgi technique shows how neurons are made of single cells
Santiago Ramón y Cajal…
Visionary histologist who studied a broad range of nervous system tissues
One of the first to see the great potential of the Golgi stain
Did seminal work that disproved the reticular theory in favour of the neuron theory (along with others)
i.e., The nervous system is made up of separate cells
Used golgi stain to find neurological structure of neurons
provided evidence that neurons are made of single cells
neuron theory/doctrine
The “” is a broad synthesis of principles about nerneuron theory/doctrinevous system organization, put forth by Heinrich Waldeyer
However, it was Ramón y Cajal and his colleagues who generated the data that was used for formulating the neuron doctrine…
the neuron doctrine:
Neurons (cells) are the functional units of the nervous system
Tenets of the neuron doctrine:
Neurons (cells) are the functional units of the nervous system
Nerve fibers project from the soma of single neurons
The nucleus is the nutritive center of the neuron
Have varying structures
All have dendrites, axonal projection
Tenets of the neuron doctrine
Law of dynamic polarization
Nerve cells have a single axon that serves
as an effector
Dendrites and cell body serve as receptor surfaces of the neuron
Directionallity to nerve propogation, passes information in one way
Dendrites= receiver
Information travels from dendrites to
axons
Tenets of the neuron doctrine
Neurons communicate via regions of cell-cell contact (synapses).
Neurons communicate via regions of cell-cell contact (synapses).
Charles Scott Sherrington later put forward the concept of synaptic transmission.
Dale’s law: single neurons utilize a single type of neurotransmitter (e.g., glutamate, glycine, GABA, etc.).
Came from discovery of electrical synapses
issues with the neuron doctrine:
Extensive gap junctions (electrical synapses) in the CNS encroach upon the reticular theory.
Axons can act as dendrites, while dendrites can act as axons (reciprocal synapses).
Signals can travel against “polarity” (e.g., from soma/axon to dendrites).
Some neurons can secrete more than one neurotransmitter type.
Can have so many gap junctions that the cytoplasm of the cells interact and affect one another= matches reticular theory
Can have back propogation
understanding how the nervous system operates
Thing to note: our first major inroads towards understanding how the nervous system operates came from detailed studies of neuron morphology, projection, and (synaptic) connectivity.
Also, technological advances paved the way for these important discoveries (i.e., microscopy and staining techniques).
Ramón y Cajal’s influence:
Understanding nervous system structure & connectivity =
understanding information flow in the nervous system. If you can map synaptic transmissions, should understand how this is done
This paradigm in thinking remains prominent….
Many researchers have devoted their careers towards establishing new or improved neural imaging and tracing techniques.
This work has been extremely fruitful towards understanding
nervous system function.
However, there is an increasing appreciation that neural “connectomics” is not enough.
analogy: if you map the entire system of roadways in a city, would that be enough to understand all the traffic patterns that flow through it at different times of the day?
Advances in neural imaging: Florescent dyes
Fluorescent dyes have electrons that absorb light and emit fluorescence as they drop back down to lower energy orbitals
Unlike the Golgi stain, dyes can be used to label live neurons
Inject into neuron → diffuses or is transported throughout
Some dyes can travel through gap junctions- to track synaptic transmission
Flourescent dyes- absorb light and emit different colours of light
Can inject this into living neuron and label neuron
Some dyes can label sub-cellular structures
MitoTracker (mitochondria)
LysoTracker (lysosomes)
Hoechst and DAPI (nucleus)
You can conjugate some dyes to other molecules
e.g., toxins such as phallacidin – binds to actin and prevents it from depolymerising (labels F-actin), causing cell to die
Bovine pulmonary endothelial cells: DAPI (blue), MitoTracker (red), and BODIPY FL Phallacidin (green)
Advances in neural imaging: Protein and mRNA localization
Genes can be used to label and identify neurons
“Marker” genes are only expressed in cells of interest
Detecting mRNAs in cells/tissues = in situ hybridization
Labeled antisense RNA that complements a target mRNA is used as a probe
mRNAs are mostly located in the soma… you don’t get to see
where the translated proteins end up
Detecting proteins in situ = immuno-labelling
Protein “epitopes” are used to generate antibodies
Antibodies bind target proteins and can be detected
Marker genes- genes that the molecule expresses, makes it that specific neuron
Ex glutamate and glu1
Ex gaba and gab1
Make synthetic mrna molecule- make complimentary mrna- will bind specifically to mrna in cell, apply probe and the complimentary cells will bound with the cells ecxpressing that gene and use dye \
Protein in situ- make antibodies, take binding region and replicate it then insert it into another organism, the immune system will make antibodies for this antidote
Conjugate antibodies with a label \
Advances in neural imaging: Fluorescent proteins
Like fluorescent dyes, fluorescent proteins absorb light and emit fluorescence, genetically encoded
Green fluorescent protein (GFP) was cloned from the jellyfish
Aequorea victoria
Can genetically express GFP in specific neurons
Use cell-specific promoters to drive expression in neurons of interest
Labels entire neuron, like fluorescent dyes
Can create fusion proteins
i.e., “stick” the GFP protein to another protein of interest
Visualize where the protein of interest spends its time inside/outside of the cell
Take the gene and use promoter of interest
Gfp doesn’t have preference for cell
If bind it to another protein, will be binded to those proteins
Researchers have since mutated GFP (and monomeric red fluorescent protein/mRFP) to generate many different colors
Brainbow: A “technicolor” Golgi stain
Developed by Jeff Lichtman and his team at Harvard
Each ball is a neuron, express proteins in different wavelengths
central dogma of cell biology
DNA in the eukaryotic cell nucleus contains various genes.
Genes that encode proteins are transcribed by RNA polymerase enzyme to generate messenger RNAs (mRNA).
Need promoters in the DNA sequence that recruit transcription factors and other machinery required for transcription.
Transcribed RNA polymers need to be processed to make mature mRNA.
mRNA is shuttled to the cytoplasm, where ribosomes drive
translation of the RNA sequences into corresponding amino acid
protein sequences.
Proteins are the general machinery of the cell (enzymes, transcription factors, ion channels etc.).
Green fluorescent protein (GFP) and its derivatives (XFPs where X
denotes different colors such as yellow: YFP) are derived from genes in cells via the central dogma.
Brainbow
Brainbow: A “technicolor” Golgi stain
Developed by Jeff Lichtman and his team at Harvard
Each ball is a neuron, express proteins in different wavelengths
Brainbow in vivo:
Approach: randomly integrate XFP genes into the mouse genome, each capable of randomly recombining to express either: CFP, YFP, or RFP
Neurons will randomly express a different combination of fluorescent proteins, producing a unique fluorescence profile
Akin to a technicolor Golgi stain!
In synthetic gene have promoter region, bind promoter to 3 genes
Mouse will make rna to complete gene
Added 2enxymes- to snip stop codon. Bringing the gene beside promoter
Mutually exclusive events- which ever gets to gene first wins, get product one or two not both
Key limitation:
Fluorescent protein
Neuron projections in the CNS are tightly packed… Brainbow tracing is ineffective at high magnification where synaptic connectivity takes place
. Advances in neuronal imaging: Tracing neural circuits
Several tools/technologies have been developed that can be used to label synaptically-connected neurons
Static tracers are transported within the cell in either retrograde or anterograde direction, but are restricted to that cell
e.g., Cholera toxin B (retrograde), Phaseolus vulgaris-leucoagglutinin (anterograde)
e.g., several modified adeno-associated viruses (AAVs) can label single neurons in either
retrograde or anterograde directions (promote expression of a detectable gene product
Retrograde- moves backwards
Anterograde- forward
Monosynaptic tracers can jump across a single synapse
Polysynaptic tracers can jump across a series of synapses
Generally, trans-synaptic tracers are derived from modified viruses
Modified rabies and pseudorabies viruses can label neural circuits in an
retrograde manner
Modified herpes simplex viruses can label neural circuits in an anterograde
manner
Advances in neuronal imaging:
Serial EM reconstruction and connectomics
Serial sections are made from fixed nervous system tissue
Sections are imaged with scanning electron microscopy
Computer algorithms identify separate cells and create a 3D reconstruction
Advances in neuronal imaging:
Serial EM reconstruction and connect
Full neural connectome for C. elegans
Achieved by Nobel laureate Sydney Brenner and his team (1986)
Only 302 neurons… should be simple to understand!!
Useful to guide research, but does not explain nervous system function
Take-home: need to understand the patterns in neuronal signaling (i.e., “the traffic”) that takes place along of the connectivity map
(“the roadways”)