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Stochastic Optical Reconstruction Microscopy of the Endoplasmic Reticulum

Chung, Manloeng Andrew

[Thesis]. Manchester, UK: The University of Manchester; 2018.

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Abstract

Super-resolution techniques have opened many new possibilities for scientists. With greater resolution, subcellular structures are better defined, which provides more details to probe structure/ functions and relationships between different cell types. With the super-resolution technique, stochastic optical reconstruction microscopy (STORM), super-resolution images were acquired on how the endoplasmic reticulum (ER) interacts with early endosomal vesi cles. The endoplasmic reticulum membrane is the site of production of all transmembrane proteins and the lipids for most of the cell's organelles, including the Golgi apparatus, lysosomes, en dosomes, secretory vesicles and the plasma membrane. But because the ER is such a small organelle (approximately 0.5 um thick) and early endosomes are even smaller, super-resolu tion microscopy is needed to image the subcellular structure of the organelles in greater depth. The ER and early endosomes were stained with Alexa Fluor 647 and Alexa 568 fluor ophores and were excited to fluoresce to produce many localisations per camera frame. The frames were reconstructed into a super-resolution image using ThunderSTORM. The super-resolution images were analysed in FiberApp to extract the coordinates along each branch point of the ER, and the persistence length of the ER was calculated. The persistence length of the ER tubules was lp = 4.17 +/- 0.14 um, the flexural rigidity was EI = 7.63 * 10^-26 Nm^2 +/- 2.27 * 10^-27 Nm^2 and the wall thickness of the ER tubules (3 - 5 nm) is used to give a Young's modulus of E = 21 kPa +/- 0.6 kPa - 34 kPa +/- 1 kPa this suggests the ER is a semi flexible organelle. Comparisons have been made between the early endosome markers, Rab5 and EEA1. The current ex perimental results suggest that the specific proteins to which they are binding are still currently unknown.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Master of Philosophy
Degree programme:
MPhil Physics
Publication date:
Location:
Manchester, UK
Total pages:
100
Abstract:
Super-resolution techniques have opened many new possibilities for scientists. With greater resolution, subcellular structures are better defined, which provides more details to probe structure/ functions and relationships between different cell types. With the super-resolution technique, stochastic optical reconstruction microscopy (STORM), super-resolution images were acquired on how the endoplasmic reticulum (ER) interacts with early endosomal vesi cles. The endoplasmic reticulum membrane is the site of production of all transmembrane proteins and the lipids for most of the cell's organelles, including the Golgi apparatus, lysosomes, en dosomes, secretory vesicles and the plasma membrane. But because the ER is such a small organelle (approximately 0.5 um thick) and early endosomes are even smaller, super-resolu tion microscopy is needed to image the subcellular structure of the organelles in greater depth. The ER and early endosomes were stained with Alexa Fluor 647 and Alexa 568 fluor ophores and were excited to fluoresce to produce many localisations per camera frame. The frames were reconstructed into a super-resolution image using ThunderSTORM. The super-resolution images were analysed in FiberApp to extract the coordinates along each branch point of the ER, and the persistence length of the ER was calculated. The persistence length of the ER tubules was lp = 4.17 +/- 0.14 um, the flexural rigidity was EI = 7.63 * 10^-26 Nm^2 +/- 2.27 * 10^-27 Nm^2 and the wall thickness of the ER tubules (3 - 5 nm) is used to give a Young's modulus of E = 21 kPa +/- 0.6 kPa - 34 kPa +/- 1 kPa this suggests the ER is a semi flexible organelle. Comparisons have been made between the early endosome markers, Rab5 and EEA1. The current ex perimental results suggest that the specific proteins to which they are binding are still currently unknown.
Thesis main supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:314439
Created by:
Chung, Manloeng
Created:
4th May, 2018, 21:20:23
Last modified by:
Chung, Manloeng
Last modified:
8th June, 2018, 12:03:29

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