Biology subjects

Weitz, J.

Publications and source records attributed to Weitz, J..

4 recordsLinked to original sources

bioRxiv2018

Systematic biases in disease forecasting - the role of behavior change

In a simple susceptible-infected-recovered (SIR) model, the initial speed at which infected cases increase is indicative of the long-term trajectory of the outbreak. Yet during real-world outbreaks, individuals may modify their behavior and take preventative steps to reduce infection risk. As a consequence, the relationship between the initial rate of spread and the final case count may become tenuous. Here, we evaluate this hypothesis by comparing the dynamics arising from a simple SIR epidemic model with those from a modified SIR model in which individuals reduce contacts as a function of the current or cumulative number of cases. Dynamics with behavior change exhibit significantly reduced final case counts even though the initial speed of disease spread is nearly identical for both of the models. We show that this difference in final size projections depends critically in the behavior change of individuals. These results also provide a rationale for integrating behavior change into iterative forecast models. Hence, we propose to use a Kalman filter to update models with and without behavior change as part of iterative forecasts. When the ground truth outbreak includes behavior change, sequential predictions using a simple SIR model perform poorly despite repeated observations while predictions using the modified SIR model are able to correct for initial forecast errors. These findings highlight the value of incorporating behavior change into baseline epidemic and dynamic forecast models.

epidemiology↗

bioRxiv2018

Exploring how generation intervals link strength and speed of epidemics

Infectious-disease outbreaks are often characterized by the reproductive number and exponential rate of growth r. provides information about out-break control and predicted final size. Directly estimating is difficult, while r can often be estimated from incidence data. These quantities are linked by the generation interval - the time between when an individual is infected by an infector, and when that infector was infected. It is often infeasible to ob-tain the exact shape of a generation-interval distribution, and to understand how this shape affects estimates of . We show that estimating generation interval mean and variance provides insight into the relationship between and r. We use examples based on Ebola, rabies and measles to explore approximations based on gamma-distributed generation intervals, and find that use of these simple approximations are often sufficient to capture the r- relationship and provide robust estimates of .

epidemiology↗

bioRxiv2018

Heterogeneous Viral Strategies Promote Coexistence in Virus-Microbe Systems

Viruses of microbes, including bacterial viruses (phage), archaeal viruses, and eukaryotic viruses, can influence the fate of individual microbes and entire populations. Here, we model distinct modes of virus-host interactions and study their impact on the abundance and diversity of both viruses and their microbial hosts. We consider two distinct viral populations infecting the same microbial population via two different strategies: lytic and chronic. A lytic strategy corresponds to viruses that exclusively infect and lyse their hosts to release new virions. A chronic strategy corresponds to viruses that infect hosts and then continually release new viruses via a budding process without cell lysis. The chronic virus can also be passed on to daughter cells during cell division. The long-term association of virus and microbe in the chronic mode drives differences in selective pressures with respect to the lytic mode. We utilize invasion analysis of the corresponding nonlinear differential equation model to study the ecology and evolution of heterogenous viral strategies. We first investigate stability of equilibria, and characterize oscillatory and bistable dynamics in some parameter regions. Then, we derive fitness quantities for both virus types and investigate conditions for competitive exclusion and coexistence. In so doing we find unexpected results, including a regime in which the chronic virus requires the lytic virus for survival and invasion.

ecology↗

bioRxiv2017

Mir-132 controls beta cell proliferation and survival in mouse model through the PTEN/AKT/FOXO3 signaling

Aim and hypothesismicroRNAs (miRNAs) play an integral role in maintaining beta cell function and identity. Deciphering their targets and precise role, however, remains a challenge. In this study we aimed to identify miRNAs and their downstream targets involved in regeneration of islet beta cells following partial pancreatectomy in mice.\n\nMethodsRNA from laser capture microdissected (LCM) islets of partially pancreatectomized and sham-operated mice were profiled with microarrays to identify putative miRNAs implicated in control of beta cell regeneration. Altered expression of selected miRNAs, including miR-132, was verified by RT-PCR. Potential targets of miR-132 were seleced through bioinformatic data mining. Predicted miR-132 targets were validated for their changed RNA and protein expression levels and signaling upon miR-132 knockdown or overexpression in MIN6 cells. The ability of miR-132 to foster beta cell proliferation in vivo was further assessed in pancreatectomized miR-132-/- and control mice.\n\nResultsPartial pancreatectomy significantly increased the number of BrdU+/insulin+ positive islet cells. Microarray profiling revealed 14 miRNAs, including miR-132 and -141, to be significantly upregulated in LCM islets of partially pancreatectomized compared to LCM islets of control mice. In the same comparison miR-760 was the only miRNA found to be downregulated. Changed expression of these miRNAs in islets of partially pancreatectomized mice was confirmed by RT-PCR only in the case of miR-132 and -141. Based on previous knowledge of its function, we chose to focus our attention on miR-132. Downregulation of miR-132 in MIN6 cells reduced proliferation while enhancing the expression of proapoptic genes, which was instead reduced in miR-132 overexpression MIN6 cells. Microarray profiling, RT-PCR and immunoblotting of miR-132 overexpressing MIN6 cells revealed their downregulated expression of Pten, with concomitant increased levels of pro-proliferative factors phospho-Akt and phospho-Creb as well as inactivation of pro-apoptotic Foxo3 via its phosphorylation. Finally, we show that regeneration of beta cells following partial pancreatectomy was reduced in miR-132-/- mice compared to control mice.\n\nConclusions/InterpretationsOur study provides compelling evidence for upregulation of miR-132 being critical for regeneration of mouse islet beta cells in vivo through downregulation of its target Pten. Hence, the miR-132/Pten/Akt/Foxo3 signaling pathway may represent a suitable target to enhance beta cell mass.\n\nResearch in ContextWhat is already known?\n\nO_LISeveral miRNAs, including miR-132, are known to regulate beta cell function and mass in several mouse models of diabetes db/db, ob/ob and high fat-diet.\nC_LI\n\nWhat is the key question?\n\nO_LIWhich are miRNAs implicated in control of beta cell regeneration upon partial pancreatectomy and how?\nC_LI\n\nWhat are the new findings?\n\nO_LImiR-132 is critical to promote regeneration of mouse beta cells in vivo following partial pancreatectomy\nC_LIO_LIIn vitro studies in mouse MIN6 cells indicate that miR-132 fosters beta cell proliferation by down-regulating the expression of phosphatase Pten, thereby tilting the balance between anti-apoptotic factor Akt and pro-apoptotic factor Foxo3 activities towards proliferation through regulation of their phosphorylation.\nC_LI\n\nHow might this impact on clinical practice in the foreseeable future?\n\nO_LIThese findings strengthen the rationale for targeting the expression of miR-132 to increase beta cell mass in vivo (type 2 diabetes) or ex-vivo (islet transplantation in type 1 diabetes) for the treatment of diabetes.\nC_LI

cell biology↗