The first lecture in a series for the module Cells and Immunity. This lecture covers the basics of the module from understanding systems biology to geography of the cell, cell biology and more. A great way to start your understanding of the module or to miss a lecture or two.
Lecture:
Systems biology
o Reductionist approach can be used to analyses how things work in a cell
Doesn’t work – no interactions/context
o Computation applied to systems bio to analyze data (modelling – eg genes)
o Now systems bio is useds
Integrative approach combines components (in situ) and use modelling
o Cellular systems (controlled by transcription and translation): energy, info, cell fate
processes
Not all systems work in the same way in all cells
o Human genome = 1010
o Information (I) = log2(# of possible combinations)
o Relevance to genome size and complexity of organism
Non-coding = regulation and spacing of genome (allows regulation)
Size of genome /= # of proteins produced
Bacteria = tightly packed genes
Eukaryotes = ↑ variable genome size and structure
o Compare physiological components (mass spec)
o Build component information → model (experimental vs actual result)
Models show what cannot be seen in wet lab results (∆ too fast)
What is missing in the genome sequence to match experimental and actual?
Cell mapping – shows abundance of proteins where cell is putting its energy
Cytoskeletal systems present in complex multicellular
o HeLa cells = cancer cell line
Comparison of proteins expressed in cells = distinct cell lines & variation
within cell sequence
Cancer cells have such variation to human = different species
o Network map
Subsystem blocks but all systems link (cross regulation)
o Personalized medicine (computational)
Analyze and make sense of genome to determine what will work
How does software come to conclusions? (combination drugs)
o Work out lower and upper bound of an estimate
Works out order of magnitude eg within a factor of 10
Geography of the cell
o Golgi reorganizes to the direction the cell is moving in
o Cell census – relative number of the components in the cell
Variation in cell size/number of proteins in pop
Average cell isn’t a real cell (data lost)
Highly organized to reduce transport or size to fit through caps (cell
architecture)
Cell biology by the numbers
o Number of cells in the human body (10 27-1028)
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