PMID- 31589599
OWN - NLM
STAT- MEDLINE
DCOM- 20200203
LR  - 20200602
IS  - 1553-7358 (Electronic)
IS  - 1553-734X (Print)
IS  - 1553-734X (Linking)
VI  - 15
IP  - 10
DP  - 2019 Oct
TI  - A simulation of the random and directed motion of dendritic cells in chemokine 
      fields.
PG  - e1007295
LID - 10.1371/journal.pcbi.1007295 [doi]
LID - e1007295
AB  - Dendritic cells (DCs) are the most effective professional antigen-presenting 
      cell. They ferry antigen from the extremities to T cells and are essential for 
      the initiation of an adaptive immune response. Despite interest in how DCs 
      respond to chemical stimuli, there have been few attempts to model DC migration. 
      In this paper, we simulate the motility of DCs by modeling the generation of 
      forces by filopodia and a force balance on the cell. The direction of fliopodial 
      extension is coupled to differential occupancy of cognate chemokine receptors 
      across the cell. Our model simulates chemokinesis and chemotaxis in a variety of 
      chemical and mechanical environments. Simulated DCs undergoing chemokinesis were 
      measured to have a speed of 5.1 +/- 0.07 mum.min-1 and a persistence time of 3.2 +/- 
      0.46 min, consistent with experiment. Cells undergoing chemotaxis exhibited a 
      stronger chemotactic response when exposed to lower average chemokine 
      concentrations, also consistent with experiment. We predicted that when placed in 
      two opposing gradients, cells will cluster in a line, which we call the "line of 
      equistimulation;" this clustering has also been observed. We calculated the 
      effect of varying gradient steepness on the line of equistimulation, with steeper 
      gradients resulting in tighter clustering. Moreover, gradients are found to be 
      most potent when cells are in a gradient of chemokine whose mean concentration is 
      close to the binding of the Kd to the receptor, and least potent when the mean 
      concentration is 0.1Kd. Comparing our simulations to experiment, we can give a 
      quantitative measure of the strength of certain chemokines relative to others. 
      Assigning the signal of CCL19 binding CCR7 a baseline strength of 1, we found 
      CCL21 binding CCR7 had a strength of 0.28, and CXCL12 binding CXCR4 had a 
      strength of 0.30. These differences emerge despite both chemokines having 
      virtually the same Kd, suggesting a mechanism of signal amplification in DCs 
      requiring further study.
FAU - Parr, Avery
AU  - Parr A
AUID- ORCID: 0000-0003-1036-8362
AD  - Harriton High School, Rosemont, Pennsylvania, United States of America.
AD  - Department of Chemical and Biological Engineering, University of Pennsylvania, 
      Philadelphia, Pennsylvania, United States of America.
FAU - Anderson, Nicholas R
AU  - Anderson NR
AUID- ORCID: 0000-0001-6027-9101
AD  - Department of Chemical and Biological Engineering, University of Pennsylvania, 
      Philadelphia, Pennsylvania, United States of America.
FAU - Hammer, Daniel A
AU  - Hammer DA
AUID- ORCID: 0000-0002-3522-3154
AD  - Department of Chemical and Biological Engineering, University of Pennsylvania, 
      Philadelphia, Pennsylvania, United States of America.
AD  - Department of Bioengineering, University of Pennsylvania, Philadelphia, 
      Pennsylvania, United States of America.
LA  - eng
GR  - R01 GM123019/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20191007
PL  - United States
TA  - PLoS Comput Biol
JT  - PLoS computational biology
JID - 101238922
RN  - 0 (Chemokines)
SB  - IM
MH  - Adaptive Immunity
MH  - Animals
MH  - Cell Movement
MH  - Chemokines/*physiology
MH  - Chemotaxis/physiology
MH  - Computer Simulation
MH  - Dendritic Cells/*physiology
MH  - Humans
MH  - Models, Theoretical
MH  - Motion
MH  - Signal Transduction/immunology
PMC - PMC6797211
COIS- The authors have declared that no competing interests exist.
EDAT- 2019/10/08 06:00
MHDA- 2020/02/06 06:00
PMCR- 2019/10/07
CRDT- 2019/10/08 06:00
PHST- 2019/01/31 00:00 [received]
PHST- 2019/07/30 00:00 [accepted]
PHST- 2019/10/17 00:00 [revised]
PHST- 2019/10/08 06:00 [pubmed]
PHST- 2020/02/06 06:00 [medline]
PHST- 2019/10/08 06:00 [entrez]
PHST- 2019/10/07 00:00 [pmc-release]
AID - PCOMPBIOL-D-18-01787 [pii]
AID - 10.1371/journal.pcbi.1007295 [doi]
PST - epublish
SO  - PLoS Comput Biol. 2019 Oct 7;15(10):e1007295. doi: 10.1371/journal.pcbi.1007295. 
      eCollection 2019 Oct.