Modeling HPV early promoter regulation

Frequency response in splicing regulation under mRNA auto-depletion control

Nowadays, there exists a huge literature about stochastic model of transcriptional and translational control in gene networks. However, results related to post-transcriptional regulation via splicing and its connection with transcriptional and translational regulation are almost missing in the current literature and only related to the steady state moments investigation. Nowadays, it is becoming of paramount importance the need for modeling post-transcriptional regulation via splicing especially for DNA viruses or retroviruses. However, there exists only few studies in the literature about splicing regulation and none of them investigate its behavior in the frequency domain that can unveil important features of dynamical stochastic systems that cannot be revealed by the sole steady state moment investigation. The aim of this work is to theoretically investigate a simple gene network subject to splicing regulation with negative feedback control, implemented through mRNA auto-depletion under a frequency domain perspective. This study showed the pivotal role of the burst size, enhancing the noise power spectrum, as well as the splicing conversion rates capable to increase and decrease the noise power spectrum in the pre-mRNA and mRNA, respectively, for high values of conversion rates. Importantly, it shows the capability of the mRNA autodepletion control to modulate the noise as a frequency-dependent amplifying control as a function of the negative feedback strengths.

Frequency analysis of splicing regulation

In the past decades, mathematical modelers developed a huge literature to model and analyze gene networks under both deterministic and stochastic formalisms. Such literature is predominantly focused on modeling transcriptional and translational regulation, while the development of proper mathematical frameworks to model and study post-transcriptional regulation via splicing and its connection with transcriptional and translational regulation are almost missing. Nowadays, it is becoming of paramount importance the need for modeling post-transcriptional regulation via splicing especially for bacteria or viruses. However, current literature is focused on investigating splicing regulation at steady state and none of them have the purpose to investigate gene networks behavior in the frequency domain, thus providing only a partial investigation about the system dynamical response. The aim of this work is to theoretically investigate a simple gene network subjects to splicing regulation with/without negative feedback control under a frequency domain perspective. This study showed the pivotal role of the burst size, as well as splicing conversion rates to modulate the noise and the power spectrum response. It also shows an interesting behavior under the frequency domain induced by the merging effect of burst size, splicing conversion rates and negative feedback strength.

A Human Papillomavirus Early Promoter Minimal Model: Viral Population and Stochasticity

HPV infection starts with the activation of the early promoter (EP) regulatory core and the replication of the viral particles to around 10-100 per cell at the beginning of the infection. For this reason, understanding the deterministic and stochastic role of the population number of viruses inside the cell is of pivotal importance to understand the regulation of the EP and the viral latency.The aim of this study is to extend a recently published minimal model of the EP transcriptional regulation in order to consider the effect of the viral population on gene regulation, to perform the bifurcation analysis and to understand the role of the stochasticity at the beginning of the infection.The bifurcation analysis showed how modeling the viral population number is pivotal to exhibit a bistable behavior, potentially linked to the viral latency. Moreover, the viral population number was identified as an important source of stochasticity, which is of paramount importance to drive the bistable switching mechanism in the first stages of infection.

A Minimal Stochastic Model of Transcriptional and Splicing Regulation

In the past decades an extensive mathematical literature was developed to model and analyze gene networks under both deterministic and stochastic formalisms. However, such literature is predominantly focused to deal with the modeling of transcriptional and translational regulation, but results related to post-transcriptional regulation and its connection with transcriptional regulation are poorly investigated. However, it is becoming of paramount importance the need for modeling post-transcriptional regulation via splicing especially for minor organisms or viruses.The aim of this study is to propose a first general basic modeling scheme for modeling gene expression via alternative splicing and investigating the basic deterministic and stochastic features of the pre-mRNA, mRNAs and proteins under different biological conditions.This first study showed the dynamical properties of alternative splicing, the faster kinetics of the pre-mRNA compared to the mRNA and the importance to stochastically model gene networks when considering the post-transcriptional regulation.

Stochastic modeling of human papillomavirusearly promoter gene regulation

High risk forms of human papillomaviruses (HPVs) promote cancerous lesions and are implicated in almost all cervical cancer. Of particular relevance to cancer progression is regulation of the early promoter that controls gene expression in the initial phases of infection and can eventually lead to pre-cancer progression. Our goal was to develop a stochastic model to investigate the control mechanisms that regulate gene expression from the HPV early promoter. Our model integrates modules that account for transcriptional, post-transcriptional, translational and post-translational regulation of E1 and E2 early genes to form a functioning gene regulatory network. Each module consists of a set of biochemical steps whose stochastic evolution is governed by a chemical Master Equation and can be simulated using the Gillespie algorithm. To investigate the role of noise in gene expression, we compared our stochastic simulations with solutions to ordinary differential equations for the mean behavior of the system that are valid under the conditions of large molecular abundances and quasi-equilibrium for fast reactions. The model produced results consistent with known HPV biology. Our simulation results suggest that stochasticity plays a pivotal role in determining the dynamics of HPV gene expression. In particular, the combination of positive and negative feedback regulation generates stochastic bursts of gene expression. Analysis of the model reveals that regulation at the promoter affects burst amplitude and frequency, whereas splicing is more specialized to regulate burst frequency. Our results also suggest that splicing enhancers are a significant source of stochasticity in pre-mRNA abundance and that the number of viruses infecting the host cell represents a third important source of stochasticity in gene expression.

Human Papillomavirus Early Promoter Regulatory Core as a Bistable Switch

High risk human papillomavirus (HPV) can induce cervical and oropharyngeal cancerous lesions. Different HPV strains, as well as still unknown mechanisms can be associated to a range of biochemical parameters that can importantly affect the HPV gene expression dynamics. For this reason, it is of pivotal importance to investigate how parameters variation can induce interesting behaviors such as viral latency in place of the normal gene replication activity. The aim of this study is to perform bifurcation analysis on a minimal model of the early promoter regulatory core controlled by E2 transcriptional regulation. The bifurcation analysis showed how E2 regulation can induce a bistability on the early promoter gene expression that could explain the interplay between viral latency and gene replication regimen.

Sensitivity Analysis of a Model of Human Papillomavirus Late Promoter Regulation

A mathematical model of Human Papillomavirus late promoter regulation was recently developed, able to predict the main features of HPV gene expression during cellular differentiation under productive infection. A sensitivity analysis is performed to characterize the influence of transcriptional, post-transcriptional and translational regulations on the viral species related to E1, E2, E4 and Li genes. Sensitivity analysis indicates strong influence of parameters related to transcriptional and translational regulation. It also shows a strong influence on the parameters related to post-transcriptional regulation, showing the importance of modeling splicing regulation to well describe the biology of the late promoter.

Stochastic Modeling of the Co-Regulation between Early and E8 Promoters in Human Papillomavirus

High risk HPV can induce cervical and oropharyngeal cancerous Iesions. The initial phase of the infection is characterized by a fine regulation of the viral DNA replication, in order to maintain 10-100 DNA copies per cell. Such regulation is primarily controlled by El and E2 proteins produced by the early promoter. The recently discovered E8 promoter is capable to co-regulate the early one in order to maintain a low and constant viral DNA copy number.The aim of this study is to develop a novel stochastic mathematical model of the co-regulation between the E8 and the early promoter, with the main purpose to rigorously show the E8 promoter capability to finely regulate the HPV transcripts which control the DNA replication in the first stages of the infection.The model, condensing the biological knowledge present in literature, describes the interaction between the two promoters and shows how the E8 co-regulation is capable to reject the stochastic noise of E2 gene expression to a higher extent than the early promoter negative auto-feedback. This proves the capability of the E8 promoter to finely control the HPV genomes copy number.

Modeling HPV Late Promoter Regulation

High risk HPV can induce cervical and oropharyngeal Iesions. HPV productive infection is strictly linked by differentiation-dependent control of the late promoter. This latter produces HPV transcripts at different epithelial layers through a complex post-transcriptional control. The aim of this study is to develop a novel mathematical model of the late promoter condensing the biological knowledge present in literature. The model describes the interaction among primary transcript, spliced transcripts and their proteins and includes the major splicing mechanisms. When used as an in silico tool it shows the crucial role of splicing regulation to explain the HPV gene expression. Novel testing hypothesis are then formulated to uncover this still elusive but pivotal promoter.

Modeling the dynamics of chromosomal alteration progression in cervical cancer: A computational model

Computational modeling has been applied to simulate the heterogeneity of cancer behavior. The development of Cervical Cancer (CC) is a process in which the cell acquires dynamic behavior from non-deleterious and deleterious mutations, exhibiting chromosomal alterations as a manifestation of this dynamic. To further determine the progression of chromosomal alterations in precursor lesions and CC, we introduce a computational model to study the dynamics of deleterious and non-deleterious mutations as an outcome of tumor progression. The analysis of chromosomal alterations mediated by our model reveals that multiple deleterious mutations are more frequent in precursor lesions than in CC. Cells with lethal deleterious mutations would be eliminated, which would mitigate cancer progression; on the other hand, cells with non-deleterious mutations would become dominant, which could predispose them to cancer progression. The study of somatic alterations through computer simulations of cancer progression provides a feasible pathway for insights into the transformation of cell mechanisms in humans. During cancer progression, tumors may acquire new phenotype traits, such as the ability to invade and metastasize or to become clinically important when they develop drug resistance. Non-deleterious chromosomal alterations contribute to this progression.

In vivo Antitumor Effect of an HPV-specific Promoter driving IL-12 Expression in an HPV 16-positive Murine Model of Cervical Cancer

Human papillomavirus (HPV) is a DNA virus that infects epithelial cells and has been implicated in the development of cervical cancer. Few therapeutic strategies have been designed for the treatment of cervical intraepithelial neoplasia, a precursor of cervical cancer. In these early stages, the HPV E2 protein is the most important viral factor involved in viral gene expression and plays crucial roles during the vegetative viral cycle in epithelial cells. Papillomavirus E2 binds specifically to palindromic ACCN₆GGT sequences, referred to as the E2 binding sites (E2BS), which are concentrated within the viral long control region, and which are responsible for regulation of the HPV protein's expression. Here, we consider E2BS as a candidate sequence to induce the expression of antiviral therapeutic genes selectively in HPV-infected cells expressing the E2 protein. This study focuses on the use of an HPV-specific promoter comprised of four E2BS to drive the expression of IL-12, leading to an antitumor effect in an HPV-positive murine tumor model. The therapeutic strategy was implemented via viral gene therapy using adenoviral vectors with recombinant E2 and IL-12 genes and E2BS-IL-12. We demonstrate that the HPV-specific promoter E2BS is functional in vitro and in vivo through transactivation of HPV E2 transcription factor.