Stochastic modelling of cellular populations: Effects of latency and feedbackl

[cat]L'objectiu principal d'aquesta tesi doctoral és l'estudi de l'efecte de les fluctuacions en poblacions acoblades en sistemes biològics, on cèl·lules en estat latent juguen un paper important. Intentant trobar el significat biològic de la dinàmica dels sistemes. Els punts específics que volem abordar i la organització de la tesi estan explicats a continuació. En el Capítol 2, estudiem el comportament de les poblacions de cèl·lules amb estructura jeràrquica des del punt de vista de les propietats d'estabilitat, En particular: - 1. Divisió simètrica contra asimètrica en el compartiment de les cèl·lules mare. Estudiem la robustesa de les poblacions amb estructura jeràrquica, depenent de si les cèl·lules mare es divideixen simètricament, asimètricament o de les dues maneres. Estudiem com la divisió simètrica afecta a l'estabilitat de la població, ja que això té una gran importància en la progressió del càncer. - 2. La competició entre dues poblacions amb diferents tipus de divisió de les cèl·lules mare. Això és crucial per trobar estratègies òptimes que maximitzin la robustesa (supervivència a llarg termini, resistència a invasions i habilitat per invadir) de poblacions amb estructura jeràrquica. - 3. La influència de paràmetres com son la duplicació i el ritme de mort de cèl·lules mare, el temps de vida mitjà de les cèl·lules completament diferenciades, la longitud de les cadenes de diferenciació i les fluctuacions al compartiment de les cèl·lules mare en la robustesa i arquitectura òptima de les cascades de diferenciació. En el Capítol 3 presentem un model homogeni de combinació de HAART amb teràpies d'activació de les cèl·lules latents del VIH-1 a la sang. Estem interessats en: - 1. L'efecte del ritme d'activació de les cèl·lules latents en el temps mitjà de vida de la infecció. En particular analitzem si les teràpies basades en incrementar aquest ritme són capaces de suprimir la infecció en un temps raonable. - 2. La importància de l'eficiència de les teràpies antiretrovirals, incloent els casos límit en que l'eficàcia és del 100%, en la quantitat de càrrega viral. - 3. La formulació d'una teoria asimptòtica basada en l'aproximació semi-clàssica amb aproximacions quasi estacionàries per descriure la dinàmica del procés. La precisió d'aquest mètode asimptòtic és comparat amb simulacions multi-scale proposades pel Cao et al. En el Capítol 4, estenem el model proposat pel Rong i el Perelson a un model no homogeni de la dinàmica del VIH-1 en el corrent sanguini, considerant que les cèl·lules i els virus no estan distribuïts de manera uniforme en la sang. Els punts específics que volem estudiar són: - 1. El mecanisme que fa que apareguin els episodis de virèmia per sobre els límits de detecció, coneguts com viral blips. En particular volem investigar si són producte de fluctuacions estocàstiques degudes a la inhomogenietat o un altre mecanisme ha de ser considerat. - 2. Si l'aparició dels viral blips està afectada pels procediments duts a terme en el laboratori, com el temps d'espera entre les extraccions i les observacions. - 3. Si la probabilitat, l'amplitud i la freqüència dels viral blips es veu afectada pels diferents possibles tipus de producció viral, és a dir, continua vs burst. En el Capítol 5 presentem i discutim els resultats obtinguts, i comparem, quan és possible, amb altres models o amb resultats experimentals, i discutim el treball que deixem pel futur. Els detalls relatius a qüestions metodològiques, això com una introducció a la modelització estocàstica fent servir equacions mestres es donen en els apèndixs. Per a aquells que no estan familiaritzats amb els models basats en equacions mestres, l'autor recomana llegir primer l'apèndix A que proporciona la base matemàtica per entendre el capítol 2. Els Apèndixs B, C i D juntament amb l'Apèndix A donen la base matemàtica necessària per seguir el capítol 3 i el capítol 4

Infectious Disease in the Workplace: Quantifying Uncertainty in Transmission.

Understanding disease transmission in the workplace is essential for protecting workers. To model disease outbreaks, the small populations in many workplaces require that stochastic effects are considered, which results in higher uncertainty. The aim of this study was to quantify and interpret the uncertainty inherent in such circumstances. We assessed how uncertainty of an outbreak in workplaces depends on i) the infection dynamics in the community, ii) the workforce size, iii) spatial structure in the workplace, iv) heterogeneity in susceptibility of workers, and v) heterogeneity in infectiousness of workers. To address these questions, we developed a multiscale model: A deterministic model to predict community transmission, and a stochastic model to predict workplace transmission. We extended this basic workplace model to allow for spatial structure, and heterogeneity in susceptibility and infectiousness in workers. We found a non-monotonic relationship between the workplace transmission rate and the coefficient of variation (CV), which we use as a measure of uncertainty. Increasing community transmission, workforce size and heterogeneity in susceptibility decreased the CV. Conversely, increasing the level of spatial structure and heterogeneity in infectiousness increased the CV. However, when the model predicts bimodal distributions, for example when community transmission is low and workplace transmission is high, the CV fails to capture this uncertainty. Overall, our work informs modellers and policy makers on how model complexity impacts outbreak uncertainty. In particular: workforce size, community and workplace transmission, spatial structure and individual heterogeneity contribute in a specific and individual manner to the predicted workplace outbreak size distribution

Stochastic modelling of the eradication of the HIV-1 infection by stimulation of latently infected cells in patients under highly active anti-retroviral therapy

HIV-1 infected patients are effectively treated with highly active anti-retroviral therapy (HAART). Whilst HAART is successful in keeping the disease at bay with average levels of viral load well below the detection threshold of standard clinical assays, it fails to completely eradicate the infection, which persists due to the emergence of a latent reservoir with a half-life time of years and is immune to HAART. This implies that life-long administration of HAART is, at the moment, necessary for HIV-1-infected patients, which is prone to drug resistance and cumulative side effects as well as imposing a considerable financial burden on developing countries, those more afflicted by HIV, and public health systems. The development of therapies which specifically aim at the removal of this latent reservoir has become a focus of much research. A proposal for such therapy consists of elevating the rate of activation of the latently infected cells: by transferring cells from the latently infected reservoir to the active infected compartment, more cells are exposed to the anti-retroviral drugs thus increasing their effectiveness. In this paper, we present a stochastic model of the dynamics of the HIV-1 infection and study the effect of the rate of latently infected cell activation on the average extinction time of the infection. By analysing the model by means of an asymptotic approximation using the semi-classical quasi steady state approximation (QSS), we ascertain that this therapy reduces the average life-time of the infection by many orders of magnitudes. We test the accuracy of our asymptotic results by means of direct simulation of the stochastic process using a hybrid multi-scale Monte Carlo scheme

LIM protein Ajuba promotes liver cell proliferation through its involvement in DNA replication and DNA damage control.

The LIM-domain protein Ajuba is associated with cell proliferation, a fundamental process of tissue regeneration and cancer. We report that in the liver, Ajuba expression is increased during regeneration and in tumor cells and tissues. Knockout of Ajuba using CRISPR/Cas9 is embryonic lethal in mice. shRNA targeting of Ajuba reduces cell proliferation, delays cell entry into S-phase, reduces cell survival and tumor growth in vivo, and increases expression of the DNA damage marker γH2AX. Ajuba binding partners include proteins involved in DNA replication and damage, such as SKP2, MCM2, MCM7 and RPA70. Taken together, our data support that Ajuba promotes liver cell proliferation associated with development, regeneration, and tumor growth and is involved in DNA replication and damage repair

Loss of claudin-3 impairs hepatic metabolism, biliary barrier function and cell proliferation in the murine liver.

BACKGROUND & AIMS Tight junctions in the liver are essential to maintain the blood-biliary-barrier, however the functional contribution of individual tight junction proteins to barrier- and metabolic homeostasis remains largely unexplored. Here, we describe the cell type specific expression of tight junction genes in the murine liver, and explore the regulation and functional importance of the transmembrane protein claudin-3 in liver metabolism, barrier function and cell proliferation. METHODS The cell type specific expression of hepatic tight junction genes is described using our mouse liver single cell sequencing dataset. Differential gene expression in Cldn3-/- and Cldn3+/+ livers was assessed in young and aged mice by RNA-seq and hepatic tissue was analysed for lipid content and bile acid composition. A surgical model of partial hepatectomy (PHx) was used to induce liver cell proliferation. RESULTS Claudin-3 is a highly expressed tight junction protein found in the liver and is expressed predominantly in hepatocytes and cholangiocytes. The histology of Cldn3-/- livers showed no overt phenotype, and the canalicular tight junctions appeared intact. Nevertheless, by RNAseq we detected a downregulation of metabolic pathways in the livers of Cldn3-/- young and aged mice as well as a decrease in lipid content and a weakened biliary-barrier for primary bile acids, such as TCA, TCDCA and TMCA. Coinciding with defects in the biliary barrier and lower lipid metabolism, there was a diminished hepatocyte proliferative response in Cldn3-/- mice following PHx. CONCLUSION Our data shows that in the liver, claudin-3 is necessary to maintain metabolic homeostasis, retention of bile acids, and optimal hepatocyte proliferation during liver regeneration

ILC3s restrict the dissemination of intestinal bacteria to safeguard liver regeneration after surgery.

It is generally believed that environmental or cutaneous bacteria are the main origin of surgical infections. Therefore, measures to prevent postoperative infections focus on optimizing hygiene and improving asepsis and antisepsis. In a large cohort of patients with infections following major surgery, we identified that the causative bacteria are mainly of intestinal origin. Postoperative infections of intestinal origin were also found in mice undergoing partial hepatectomy. CCR6+ group 3 innate lymphoid cells (ILC3s) limited systemic bacterial spread. Such bulwark function against host invasion required the production of interleukin-22 (IL-22), which controlled the expression of antimicrobial peptides in hepatocytes, thereby limiting bacterial spread. Using genetic loss-of-function experiments and punctual depletion of ILCs, we demonstrate that the failure to restrict intestinal commensals by ILC3s results in impaired liver regeneration. Our data emphasize the importance of endogenous intestinal bacteria as a source for postoperative infection and indicate ILC3s as potential new targets

Modelling strategies to organize healthcare workforce during pandemics: Application to COVID-19.

Protection of the healthcare workforce is of paramount importance for the care of patients in the setting of a pandemic such as coronavirus disease 2019 (COVID-19). Healthcare workers are at increased risk of becoming infected. The ideal organisational strategy to protect the workforce in a situation in which social distancing cannot be maintained remains to be determined. In this study, we have mathematically modelled strategies for the employment of the hospital workforce with the goal of simulating the health and productivity of the workers. The models were designed to determine if desynchronization of medical teams by dichotomizing the workers may protect the workforce. Our studies model workforce productivity and the efficiency of home office applied to the case of COVID-19. The results reveal that a desynchronization strategy in which two medical teams work alternating for 7 days increases the available workforce

Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks.

Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing-with its unique statistical properties-became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates) to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca