Fate Mapping Escherichia Coli Tissue Development!Atri Choksi!

Department of Bioengineering, Stanford University

I. Motivation II. Processing Pipeline

III. Algorithm Evaluation IV. Geometric Characterization Cell Density Across Algorithms

Cel

l Den

sity

[c

ells

/Are

a]

Time

Roundness of Tissues

Rou

ndne

ss

[4π

*Are

a/P

erim

eter

2 ]

Time

Cell Density of Organs

Cel

l Den

sity

[c

ells

/Are

a]

Time

Fractal Dimension

Dim

ensi

on

Time

The best tissue abstraction algorithm produces tissues that (A) do not extend beyond outer cell boundaries, (B) do not overlap with other tissues, and (C) do not have holes. In other words, tissue abstraction algorithms should minimize cell density. From this study, FILLING is the best algorithm because small region removal produces holes and morphological closing does not maximize cell density. Time 8 10 12 14 16 18 20 22

A single cell gives rise to tissues, organs, and eventually, an organism through cell divisions. One important tool in studying how tissues shape over time is tracing cell lineage. An extension of cell lineage tracing now presents itself as a challenge to biologists: tissue fate mapping. A tissue fate mapping algorithm would allow researchers to observe the structure of tissue in terms of cell lineage automatically.

Simula'ons  

Preprocessing   Detect  Tissues  

Recreate  Organ  

Abstract Tissue

Geometric Characteri-

zation

Closing  

Small  Region  Removal  

Filling  

Roundness  

Cell  Density  

Fractal  Dimension  

FOR

all

tissu

es

In this project, I abstract the cell lineage map into a “tissue” lineage map and measure several geometric properties of the map.

Cell Density?

Roundness?

Fractal Dimension? Cel

l Lin

eage

M

ap