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BIOMD0000000573 - Aguilera 2014 - HIV latency. Interaction between HIV proteins and immune response

 

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Reference Publication
Publication ID: 24997239
Aguilera LU, Rodríguez-González J.
Studying HIV latency by modeling the interaction between HIV proteins and the innate immune response.
J. Theor. Biol. 2014 Nov; 360: 67-77
Centro de Investigacion y de Estudios Avanzados del IPN, Unidad Monterrey, Vıa del Conocimiento 201, Parque PIIT, CP 66600 Apodaca NL, Mexico; University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany. Electronic address: luis.aguilera@bioquant.uni-heidelberg.de.  [more]
Model
Original Model: BIOMD0000000573.origin
Submitter: Luis Ubaldo Aguilera de Lira
Submission ID: MODEL1503180001
Submission Date: 18 Mar 2015 15:47:58 UTC
Last Modification Date: 08 Apr 2016 18:53:31 UTC
Creation Date: 30 Mar 2015 14:07:36 UTC
Encoders:  Audald Lloret i Villas
   Luis Ubaldo Aguilera de Lira
set #1
bqbiol:hasProperty Human Disease Ontology human immunodeficiency virus infectious disease
set #2
bqbiol:isVersionOf Gene Ontology innate immune response
set #3
bqbiol:hasTaxon Taxonomy Homo sapiens
Notes
Aguilera 2014 - HIV latency. Interaction between HIV proteins and immune response

This model is described in the article:

Aguilera LU, Rodríguez-González J.
J. Theor. Biol. 2014 Nov; 360: 67-77

Abstract:

HIV infection leads to two cell fates, the viral productive state or viral latency (a reversible non-productive state). HIV latency is relevant because infected active CD4+ T-lymphocytes can reach a resting memory state in which the provirus remains silent for long periods of time. Despite experimental and theoretical efforts, the causal molecular mechanisms responsible for HIV latency are only partially understood. Studies have determined that HIV latency is influenced by the innate immune response carried out by cell restriction factors that inhibit the postintegration steps in the virus replication cycle. In this study, we present a mathematical study that combines deterministic and stochastic approaches to analyze the interactions between HIV proteins and the innate immune response. Using wide ranges of parameter values, we observed the following: (1) a phenomenological description of the viral productive and latent cell phenotypes is obtained by bistable and bimodal dynamics, (2) biochemical noise reduces the probability that an infected cell adopts the latent state, (3) the effects of the innate immune response enhance the HIV latency state, (4) the conditions of the cell before infection affect the latent phenotype, i.e., the existing expression of cell restriction factors propitiates HIV latency, and existing expression of HIV proteins reduces HIV latency.

To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Model
Publication ID: 24997239 Submission Date: 18 Mar 2015 15:47:58 UTC Last Modification Date: 08 Apr 2016 18:53:31 UTC Creation Date: 30 Mar 2015 14:07:36 UTC
Mathematical expressions
Reactions
Kb Kv Kvc Kdv
Kc Kcv Kdc  
Physical entities
Compartments Species
cell V C  
Reactions (7)
 
 Kb  → [V];  
 
 Kv [V] → 2.0 × [V];   {V}
 
 Kvc [V] + [C] → [C];   {V} , {C}
 
 Kdv [V] → ;   {V}
 
 Kc  → [C];  
 
 Kcv [V] + [C] → [V];   {V} , {C}
 
 Kdc [C] → ;   {C}
 
Functions (2)
 
 Constant flux (irreversible) lambda(v, v)
 
 Michaellis Menten lambda(substrate, Km, Vmax, Vmax*substrate/(Km+substrate))
 
 cell Spatial dimensions: 3.0  Compartment size: 1.0
 
 V
Compartment: cell
Initial concentration: 1.0
 
 C
Compartment: cell
Initial concentration: 0.0
 
Kb (1)
 
   v
Value: 0.00134
Constant
 
Kv (2)
 
   Km
Value: 380.0
Constant
 
   Vmax
Value: 0.134
Constant
 
Kvc (1)
 
   k1
Value: 0.0295
Constant
 
Kdv (1)
 
   k1
Value: 6.85E-5
Constant
 
Kc (1)
 
   v
Value: 0.07
Constant
 
Kcv (1)
 
   k1
Value: 0.927
Constant
 
Kdc (1)
 
   k1
Value: 5.01E-5
Constant
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000573

Curator's comment: (updated: 31 Mar 2015 17:10:07 GMT)

Figure 2 of the reference publication has been reproduced here: deterministic simulations of concentration for 50 hours using two different initial conditions. For the upper curve V(0) = 5 and C(0) = 0, for the lower curve V(0) = 0 and C(0) = 0.

The simulation was done using Copasi v4.14 (Build 89) and the plot was generated using Gnuplot. The Copasi file of the model with simulation settings can be downloaded from the below link:

Additional file(s)
  • Aguilera 2014 – HIV latency. Interaction between HIV proteins and immune response:
    Copasi file of the model
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