def geomModel(sim,
cellCenter=lm.point(*micron(2.0, 2.0, 2.0)),
nucleusRadius=micron(0.4),
cellRadius=micron(2.0)):
# Add locations
cytoplasm = lm.Sphere(cellCenter, cellRadius,
sim.siteTypes["Cytoplasm"])
nucleus = lm.Sphere(cellCenter, nucleusRadius,
sim.siteTypes["Nucleus"])
sim.addShape(cytoplasm)
sim.addShape(nucleus)
def geometryModel(sim,
cellCenter=lm.point(*micron(9, 9, 9)),
cellRadius=micron(8.9),
membraneThickness=micron(0.128),
nuclSize=micron(4.15),
speckleRadius=micron(0.35),
cajalRadius=micron(0.5),
poreRadius=micron(0.083),
n_cajals=4,
n_speckles=20,
n_NPCs=1515,
n_mito=2000,
n_ribo=750,
fb=0.9,
fd=0.8,
steps=11,
lsize=288,
buildER=True,
limits=[lambda x: x <= 65.0**2, lambda x: x > 139.0**2]):
# Create cell components
CellWall = lm.Sphere(cellCenter, cellRadius, sim.siteTypes['CellWall'])
Cytoplasm = lm.Sphere(cellCenter, cellRadius - membraneThickness,
sim.siteTypes['Cytoplasm'])
NucEnv = lm.Sphere(cellCenter, nuclSize, sim.siteTypes['NucEnv'])
Nucleus = lm.Sphere(cellCenter, nuclSize - membraneThickness,
sim.siteTypes['Nucleus'])
CellWall.thisown = 0
Cytoplasm.thisown = 0
NucEnv.thisown = 0
Nucleus.thisown = 0
###### Cajal body: "n_cajal" with radius "cajalRadius" #############################
dist = []
listdist = []
Cajalpre = []
accepted = []
np_accepted = []
cc = 1
point = 0
while cc < n_cajals + 1:
x, y, z = np.random.uniform(-0.5, 0.5, 3)
Rp = nuclSize - cajalRadius - micron(0.1)
xpp = x * Rp + cellCenter.x
ypp = y * Rp + cellCenter.y
zpp = z * Rp + cellCenter.z
caj = [xpp, ypp, zpp]
listdist = []
point += 1
if (point == 1):
accepted.append(caj)
np_accepted = np.array(accepted)
for i in range(0, cc):
dist = np.sqrt(np.sum((np.array(caj) - np_accepted[i])**2))
listdist.append(dist)
np_dist = np.array(listdist)
if (np.all(np_dist > 2 * cajalRadius + micron(0.05))):
accepted.append(caj)
np_accepted = np.array(accepted)
listdist = []
cc += 1
NCajal = np.array(accepted)
cc = []
Cajal = lm.UnionSet(sim.siteTypes['Cajal'])
Cajal.thisown = 0
for k in range(0, n_cajals):
w = lm.Sphere(lm.point(NCajal[k][0], NCajal[k][1], NCajal[k][2]),
cajalRadius, sim.siteTypes['Cajal'])
w.thisown = 0
cc.append(w)
Cajal.addShape(w)
print("Cajal done!")
################ Nuclear Speckles: "n_speckles" with radius "speckleRadius" ##########################
counter = 0
taken = 0
listdist = []
np_acceptspeck = []
acceptspeck = []
while counter < n_speckles + 1:
u = np.random.uniform(-1, 1)
thet = np.random.uniform(0, 2.0 * math.pi)
rad = np.random.uniform(speckleRadius * 1e6,
nuclSize * 1e6 - (speckleRadius * 1e6 + 0.1))
xm = micron(rad * math.sqrt(1 - u**2) * np.cos(thet)) + cellCenter.x
ym = micron(rad * math.sqrt(1 - u**2) * np.sin(thet)) + cellCenter.y
zm = micron(rad * u) + cellCenter.z
point = [xm, ym, zm]
listdist = []
dist = 0
np_dist = []
taken += 1
if (taken == 1):
acceptspeck.append(point)
np_acceptspeck = np.array(acceptspeck)
for i in range(0, counter):
dist = np.sqrt(np.sum((point - np_acceptspeck[i])**2))
listdist.append(dist)
np_dist = np.array(listdist)
tt = 0
if (np.all(np_dist > 2 * speckleRadius + micron(0.1))):
for k in range(0, n_cajals):
if (np.sqrt(np.sum((np.array(point) - NCajal[k])**2)) >
speckleRadius + cajalRadius + micron(0.1)):
tt += 1
if (tt == 4):
acceptspeck.append(point)
np_acceptspeck = np.array(acceptspeck)
counter += 1
listdist = []
NSpeck = np.array(acceptspeck)
collection = []
j = 0
Speckle = lm.UnionSet(sim.siteTypes['Speckle'])
Speckle.thisown = 0
for k in range(0, n_speckles):
q = lm.Sphere(
lm.point(NSpeck[k][j], NSpeck[k][j + 1], NSpeck[k][j + 2]),
speckleRadius, sim.siteTypes['Speckle'])
q.thisown = 0
collection.append(q)
Speckle.addShape(q)
print("Speckles done!")
################# NPC #########################
NPCpre = []
taken = 0
ldist = []
npcdist = 0
np_npcdist = []
acceptnpc = []
npc = 0
while npc < n_NPCs + 1:
x, y, z = np.random.uniform(-0.5, 0.5, 3)
r = math.sqrt(x**2 + y**2 + z**2)
Rp = (nuclSize - sim.latticeSpacing) / r
xpp = x * Rp + cellCenter.x
ypp = y * Rp + cellCenter.y
zpp = z * Rp + cellCenter.z
pores = [xpp, ypp, zpp]
NPCpre.append(pores)
ldist = []
np_npcdist = []
taken += 1
if (taken == 1):
acceptnpc.append(pores)
np_acceptnpc = np.array(acceptnpc)
for i in range(0, npc):
npcdist = np.sqrt(np.sum((np.array(pores) - np_acceptnpc[i])**2))
ldist.append(npcdist)
np_npcdist = np.array(ldist)
if (np.all(np_npcdist > 0.2e-6)):
acceptnpc.append(pores)
np_acceptnpc = np.array(acceptnpc)
ldist = []
npc += 1
NP = np.array(NPCpre)
collect = []
j = 0
NPC = lm.UnionSet(sim.siteTypes['NPC'])
NPC.thisown = 0
for k in range(0, n_NPCs):
s = lm.Sphere(lm.point(NP[k][j], NP[k][j + 1], NP[k][j + 2]),
poreRadius, sim.siteTypes['NPC'])
s.thisown = 0
collect.append(s)
NPC.addShape(s)
print("NPCs done!")
####################### Golgi Apparatus #################################################
m1 = lm.Sphere(lm.point(*micron(15, 15, 15)), micron(3.5),
sim.siteTypes['Golgi'])
m11 = lm.Sphere(lm.point(*micron(15, 15, 15)), micron(3.308),
sim.siteTypes['Golgi'])
m12 = lm.Sphere(lm.point(*micron(15, 15, 15)), micron(3.116),
sim.siteTypes['Golgi'])
m13 = lm.Sphere(lm.point(*micron(15, 15, 15)), micron(2.924),
sim.siteTypes['Golgi'])
m14 = lm.Sphere(lm.point(*micron(15, 15, 15)), micron(2.732),
sim.siteTypes['Golgi'])
m2 = lm.Cone(cellCenter, micron(2), micron(6.5), sim.siteTypes['Golgi'],
lm.vector(1.0, 1.0, 1.0))
m22 = lm.Cone(cellCenter, micron(2.5), micron(8), sim.siteTypes['Golgi'],
lm.vector(1.0, 1.0, 1.0))
m23 = lm.Cone(cellCenter, micron(3), micron(9.5), sim.siteTypes['Golgi'],
lm.vector(1.0, 1.0, 1.0))
m24 = lm.Cone(cellCenter, micron(3.5), micron(10.5),
sim.siteTypes['Golgi'], lm.vector(1.0, 1.0, 1.0))
Gol1 = lm.Difference(m1, m11, sim.siteTypes['Golgi'])
Gol2 = lm.Difference(m11, m12, sim.siteTypes['Golgi'])
Gol3 = lm.Difference(m12, m13, sim.siteTypes['Golgi'])
Gol4 = lm.Difference(m13, m14, sim.siteTypes['Golgi'])
G1 = lm.Intersection(Gol1, m2, sim.siteTypes['Golgi'])
G2 = lm.Intersection(Gol2, m22, sim.siteTypes['Golgi'])
G3 = lm.Intersection(Gol3, m23, sim.siteTypes['Golgi'])
G4 = lm.Intersection(Gol4, m24, sim.siteTypes['Golgi'])
G11 = lm.Union(G1, G2, sim.siteTypes['Golgi'])
G22 = lm.Union(G3, G4, sim.siteTypes['Golgi'])
Golgi = lm.Union(G11, G22, sim.siteTypes['Golgi'])
Golgi.thisown = 0
print("Golgi done!")
######################## Mitochondria ###############################3
mit = []
pp1 = []
pp2 = []
Mito = lm.UnionSet(sim.siteTypes['Mito'])
Mito.thisown = 0
for i in range(1, n_mito + 1):
u = np.random.uniform(-1, 1)
thet = np.random.uniform(0, 2.0 * math.pi)
rad = np.random.uniform(4.706, 8.5)
xm = micron(rad * math.sqrt(1 - u**2) * np.cos(thet)) + micron(9)
ym = micron(rad * math.sqrt(1 - u**2) * np.sin(thet)) + micron(9)
zm = micron(rad * u) + micron(9)
centers = [xm, ym, zm]
if i < 666:
point1 = [xm - micron(0.125), ym - micron(0.125), zm]
point2 = [xm + micron(0.125), ym + micron(0.125), zm]
elif i >= 666 and i < 1332:
point1 = [xm, ym - micron(0.125), zm - micron(0.125)]
point2 = [xm, ym + micron(0.125), zm + micron(0.125)]
elif i >= 1332:
point1 = [xm - micron(0.125), ym, zm - micron(0.125)]
point2 = [xm + micron(0.125), ym, zm + micron(0.125)]
pp1.append(point1)
pp2.append(point2)
mp1 = np.array(pp1)
mp2 = np.array(pp2)
for h in range(0, n_mito):
m = lm.Capsule(lm.point(mp1[h][0], mp1[h][1], mp1[h][2]),
lm.point(mp2[h][0], mp2[h][1], mp2[h][2]),
micron(0.249), sim.siteTypes['Mito'])
m.thisown = 0
mit.append(m)
Mito.addShape(m)
print("Mito done!")
# Add all geometries to the simulation
sim.lm_builder.addRegion(CellWall)
sim.lm_builder.addRegion(Cytoplasm)
sim.lm_builder.addRegion(NucEnv)
sim.lm_builder.addRegion(Nucleus)
sim.lm_builder.addRegion(NPC)
sim.lm_builder.addRegion(Cajal)
sim.lm_builder.addRegion(Speckle)
sim.lm_builder.addRegion(Mito)
sim.lm_builder.addRegion(Golgi)
######################### ER #########################################
print("Building ER")
if buildER:
deathLimitFxn = lambda s: int(fd * 27 *
(steps - 0.25 * s)**2 / steps**2)
birthNumberFxn = lambda s: int(fb * 27)
im = createERCellularAutomaton(lsize,
dimensions=3,
survivalRate=0.85,
deathLimitFxn=deathLimitFxn,
birthNumberFxn=birthNumberFxn,
steps=steps,
limits=limits)
# Save the grid to a 3D lattice as a numpy array; this can be loaded with np.load()
np.save("ER.npy", np.array(im, dtype="float"))
print("Done building ER")
print("Loading ER")
ER = np.load("ER.npy")
print("Discretizing")
lattice = sim.getLattice()
print("Setting ER")
for x in range(ER.shape[0]):
for y in range(ER.shape[1]):
for z in range(ER.shape[2]):
idx = (x, y, z)
if ER[x, y, z]:
sim.setLatticeSite(idx, "ER")
print("ER Done")
######################### Ribosomes #########################################
# Add 750 ribosomes to the cell's cytoplasm randomly
if n_ribo > 0:
added = 0
for x, y, z in np.random(5 * n_ribo * 3).reshape(
(5 * n_ribo, 3)) * cellRadius:
if Cytoplasm.intersects(lm.Sphere(lm.Point(x, y, z)), nm(32),
sim.siteTypes['Cytoplasm']):
sim.setLatticeSite((x, y, z), 'Ribosome')
added += 1
if added >= n_ribo:
break
def geometryModel(sim,
cellCenter = lm.point(*micron(2.755,2.755,2.755)),
cellRadius1 = micron(2.625), # Long dimension of ellipsoid for cell
cellRadius2 = micron(1.75), # Short dimension of ellipsoid for cell
membraneThickness= nm(28.7), # As determined from the Earnest et al. manuscript
nuclSize1 = micron(1.09), # Long dimension of ellipsoid for nucleus
nuclSize2 = micron(0.911), # Short dimension of ellipsoid for nucleus
speckleRadius=micron(0.05), # Size reduced for smaller nuclear volume
cajalRadius=micron(0.07), # Size reduced for smaller nuclear volume
poreRadius=micron(0.040), # As determined in Earnest et al.
n_cajals=4,
n_speckles=20,
n_NPCs=139, # As determined in Earnest et al.
n_mito=95, # Scaled by ratio of yeast:HeLa cell volume
):
##########################
# Create cell components #
##########################
# Create an ellipsoid aligned along the X-axis with an
# aspect ratio of 1.5 as determined in the Earnest et al. manuscript
CellWall = lm.Ellipse(cellCenter, cellRadius1, cellRadius2, cellRadius2, sim.siteTypes['CellWall'])
Cytoplasm = lm.Ellipse(cellCenter, cellRadius1-membraneThickness, cellRadius2-membraneThickness, cellRadius2-membraneThickness, sim.siteTypes['Cytoplasm'])
# Create an ellipsoid aligned along the X-axis with an
# aspect ratio of 1.2 as determined in the Earnest et al. manuscript
NucEnv = lm.Ellipsoid(cellCenter, nuclSize1, nuclSize2, nuclSize2 sim.siteTypes['NucEnv'])
Nucleus = lm.Ellipsoide(cellCenter, nuclSize1-membraneThickness, nuclSize2-membraneThickness, nuclSize2-membraneThickness, sim.siteTypes['Nucleus'])
# The following code snippets are required to prevent python from
# garbage collecting the objects when the function exits, allowing
# lattice microbes to refer to them later when building the cell
CellWall.thisown = 0
Cytoplasm.thisown = 0
NucEnv.thisown = 0
Nucleus.thisown = 0
###### Cajal body: "n_cajal" with radius "cajalRadius" #############################
dist = [] ; listdist = []
Cajalpre = []
accepted = []
np_accepted = []
cc = 1 ; point = 0
while cc < n_cajals + 1:
x,y,z = np.random.uniform(-0.5,0.5,3)
Rp = nuclSize2 - cajalRadius - micron(0.1)
# Account for elliposoidal nature of nucleus in X-axis
xpp = 1.2*x*Rp + cellCenter.x
ypp = y*Rp + cellCenter.y
zpp = z*Rp + cellCenter.z
caj = [xpp,ypp,zpp]
listdist = []
point += 1
if (point == 1 ):
accepted.append(caj)
np_accepted = np.array(accepted)
for i in range (0, cc):
dist = np.sqrt(np.sum((np.array(caj)-np_accepted[i])**2))
listdist.append(dist)
np_dist = np.array(listdist)
if(np.all(np_dist > 2*cajalRadius + micron(0.05))):
accepted.append(caj)
np_accepted = np.array(accepted)
listdist = []
cc += 1
NCajal = np.array(accepted)
cc = []
Cajal = lm.UnionSet(sim.siteTypes['Cajal'])
Cajal.thisown = 0
for k in range(0, n_cajals):
w = lm.Sphere(lm.point(NCajal[k][0],
NCajal[k][1],
NCajal[k][2]),
cajalRadius,
sim.siteTypes['Cajal'])
w.thisown=0
cc.append(w)
Cajal.addShape(w)
print("Cajal done!")
################ Nuclear Speckles: "n_speckles" with radius "speckleRadius" ##########################
counter = 0
taken = 0
listdist = [] ; np_acceptspeck = [] ; acceptspeck = []
while counter < n_speckles + 1:
u = np.random.uniform(-1, 1)
thet = np.random.uniform(0, 2.0*math.pi)
rad = np.random.uniform(speckleRadius*1e6 , nuclSize2*1e6 - (speckleRadius*1e6 + 0.1))
# Account for elliposoidal nature of nucleus
xm = 1.2*micron(rad*math.sqrt(1-u**2)*np.cos(thet)) + cellCenter.x
ym = micron(rad*math.sqrt(1-u**2)*np.sin(thet)) + cellCenter.y
zm = micron(rad*u) + cellCenter.z
point = [xm, ym, zm]
listdist = [] ; dist = 0 ; np_dist = []
taken += 1
if ( taken == 1 ):
acceptspeck.append(point)
np_acceptspeck = np.array(acceptspeck)
for i in range (0, counter):
dist = np.sqrt(np.sum((point-np_acceptspeck[i])**2))
listdist.append(dist)
np_dist = np.array(listdist)
tt = 0
if(np.all(np_dist > 2*speckleRadius + micron(0.1))):
for k in range (0, n_cajals):
if (np.sqrt(np.sum((np.array(point)-NCajal[k])**2)) > speckleRadius + cajalRadius + micron(0.1)):
tt += 1
if (tt == 4):
acceptspeck.append(point)
np_acceptspeck = np.array(acceptspeck)
counter += 1
listdist = []
NSpeck = np.array(acceptspeck)
collection = []
j = 0
Speckle = lm.UnionSet(sim.siteTypes['Speckle'])
Speckle.thisown = 0
for k in range(0, n_speckles):
q = lm.Sphere(lm.point(NSpeck[k][j],
NSpeck[k][j+1],
NSpeck[k][j+2]),
speckleRadius,
sim.siteTypes['Speckle'])
q.thisown=0
collection.append(q)
Speckle.addShape(q)
print("Speckles done!")
################# NPC #########################
NPCpre = []
taken = 0
ldist = [] ; npcdist = 0 ; np_npcdist = []
acceptnpc = []
npc = 0
while npc < n_NPCs + 1:
x,y,z = np.random.uniform(-0.5,0.5,3)
r = math.sqrt(x**2 + y**2 + z**2)
# Account for elliposoidal nature of nucleus
Rp = (nuclSize2 - sim.latticeSpacing)/r
xpp = 1.2*x*Rp + cellCenter.x
ypp = y*Rp + cellCenter.y
zpp = z*Rp + cellCenter.z
pores = [xpp,ypp,zpp]
NPCpre.append(pores)
ldist = [] ; np_npcdist = []
taken += 1
if (taken == 1 ):
acceptnpc.append(pores)
np_acceptnpc = np.array(acceptnpc)
for i in range (0, npc):
npcdist = np.sqrt(np.sum((np.array(pores)-np_acceptnpc[i])**2))
ldist.append(npcdist)
np_npcdist = np.array(ldist)
if(np.all(np_npcdist > 0.2e-6)):
acceptnpc.append(pores)
np_acceptnpc = np.array(acceptnpc)
ldist = []
npc += 1
NP = np.array(NPCpre)
collect = []
j = 0
NPC = lm.UnionSet(sim.siteTypes['NPC'])
NPC.thisown = 0
for k in range(0, n_NPCs):
s = lm.Sphere(lm.point(NP[k][j],
NP[k][j+1],
NP[k][j+2]),
poreRadius,
sim.siteTypes['NPC'])
s.thisown=0
collect.append(s)
NPC.addShape(s)
print("NPCs done!")
####################### Golgi Apparatus #################################################
# Skip golgi apparatus as done in Earnest et al.
######################## Mitochondria ###############################3
mit = []
pp1 = []
pp2 = []
Mito = lm.UnionSet(sim.siteTypes['Mito'])
Mito.thisown=0
for i in range(1, n_mito+1):
u = np.random.uniform(-1, 1)
thet = np.random.uniform(0, 2.0*math.pi)
rad = np.random.uniform(0.5, 2.5) # Modified for smaller cell
xm = 1.5*micron(rad*math.sqrt(1-u**2)*np.cos(thet)) + micron(9)
ym = micron(rad*math.sqrt(1-u**2)*np.sin(thet)) + micron(9)
zm = micron(rad*u) + micron(9)
centers = [xm, ym, zm]
if i < 666 :
point1 = [xm - micron(0.125), ym-micron(0.125) , zm]
point2 = [xm + micron(0.125), ym+micron(0.125) , zm]
elif i >= 666 and i < 1332 :
point1 = [xm, ym - micron(0.125), zm- micron(0.125)]
point2 = [xm, ym + micron(0.125), zm+ micron(0.125)]
elif i >= 1332 :
point1 = [xm - micron(0.125), ym , zm - micron(0.125)]
point2 = [xm + micron(0.125), ym , zm + micron(0.125)]
pp1.append(point1)
pp2.append(point2)
mp1 = np.array(pp1)
mp2 = np.array(pp2)
for h in range(0, n_mito):
m = lm.Capsule(lm.point(mp1[h][0], mp1[h][1], mp1[h][2]),
lm.point(mp2[h][0], mp2[h][1], mp2[h][2]),
micron(0.249),
sim.siteTypes['Mito'])
m.thisown = 0
mit.append(m)
Mito.addShape(m)
print("Mito done!")
# Add all geometries to the simulation
sim.lm_builder.addRegion(CellWall)
sim.lm_builder.addRegion(Cytoplasm)
sim.lm_builder.addRegion(NucEnv)
sim.lm_builder.addRegion(Nucleus)
sim.lm_builder.addRegion(NPC)
sim.lm_builder.addRegion(Cajal)
#sim.lm_builder.addRegion(Cajal) # Removed
sim.lm_builder.addRegion(Speckle)
sim.lm_builder.addRegion(Mito)