Endemicity and prevalence of multipartite viruses under heterogeneous between-host transmission

Multipartite viruses replicate through a puzzling evolutionary strategy. Their genome is segmented into two or more parts, and encapsidated in separate particles that appear to propagate independently. Completing the replication cycle, however, requires the full genome, so that a systemic infection of a host requires the concurrent presence of several particles. This represents an apparent evolutionary drawback of multipartitism, while its advantages remain unclear. A transition from monopartite to multipartite viral forms has been described in vitro under conditions of high multiplicity of infection, suggesting that cooperation between defective mutants is a plausible evolutionary pathway towards multipartitism. However, it is unknown how the putative advantages that multipartitism might enjoy at the microscopic level affect its epidemiology, or if an explicit advantange is needed to explain its ecological persistence. To disentangle which mechanisms might contribute to the rise and fixation of multipartitism, we investigate the interaction between viral spreading dynamics and host population structure. We set up a compartmental model of the spread of a virus in its different forms and explore its epidemiology using both analytical and numerical techniques. We uncover that the impact of host contact structure on spreading dynamics entails a rich phenomenology of ecological relationships that includes cooperation, competition, and commensality. We find that multipartitism might rise to fixation even in the absence of explicit microscopic advantages. Multipartitism allows the virus to colonize environments that could not be invaded by the monopartite form, facilitated by homogeneous contacts among hosts. We conjecture that these features might have led to an increase in the diversity and prevalence of multipartite viral forms concomitantly with the expansion of agricultural practices.Comment: 27 pages, 4 figures, 1 tabl

Systems Biology Graphical Notation: Process Description language Level 1

Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Diagrams, the Entity Relationship Diagrams and the Activity Flow Diagrams. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Process Diagram has been publicly released. Software support for SBGN Process Diagram was developed concurrently with its specification in order to speed-up public adoption. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps

Systems Biology Graphical Notation: Process Description language Level 1

Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Diagrams, the Entity Relationship Diagrams and the Activity Flow Diagrams. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Process Diagram has been publicly released. Software support for SBGN Process Diagram was developed concurrently with its specification in order to speed-up public adoption. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps

The Cellular and Physiological Basis for Lung Repair and Regeneration: Past, Present, and Future.

The respiratory system, which includes the trachea, airways, and distal alveoli, is a complex multi-cellular organ that intimately links with the cardiovascular system to accomplish gas exchange. In this review and as members of the NIH/NHLBI-supported Progenitor Cell Translational Consortium, we discuss key aspects of lung repair and regeneration. We focus on the cellular compositions within functional niches, cell-cell signaling in homeostatic health, the responses to injury, and new methods to study lung repair and regeneration. We also provide future directions for an improved understanding of the cell biology of the respiratory system, as well as new therapeutic avenues

Semiparametric inference of effective reproduction number dynamics from wastewater pathogen surveillance data

Concentrations of pathogen genomes measured in wastewater have recently become available as a new data source to use when modeling the spread of infectious diseases. One promising use for this data source is inference of the effective reproduction number, the average number of individuals a newly infected person will infect. We propose a model where new infections arrive according to a time-varying immigration rate which can be interpreted as a compound parameter equal to the product of the proportion of susceptibles in the population and the transmission rate. This model allows us to estimate the effective reproduction number from concentrations of pathogen genomes while avoiding difficult to verify assumptions about the dynamics of the susceptible population. As a byproduct of our primary goal, we also produce a new model for estimating the effective reproduction number from case data using the same framework. We test this modeling framework in an agent-based simulation study with a realistic data generating mechanism which accounts for the time-varying dynamics of pathogen shedding. Finally, we apply our new model to estimating the effective reproduction number of SARS-CoV-2 in Los Angeles, California, using pathogen RNA concentrations collected from a large wastewater treatment facility.Comment: 23 pages, 6 figures in main te

Defining Lineage Potential and Fate Behaviour of Progenitors During Pancreas Development

The studentship and some of the consumables used to generate data for this thesis were funded by Medical Research Counci

Inflammatory Response as a Mechanism of Perinatal Programming: Long-term Impact on Pulmonary and Renal Function?

RATIONALE: Temporal changes in the fetal environment, such as malnutrition and placental insufficiency induce intrauterine growth restriction (IUGR) and lead to a permanent changes of physiological processes later in life. Interestingly, epidemiological studies demonstrated an impairment of lung and renal function in young infants subsequent to IUGR. Complementary, experimental studies showed that IUGR induces a perinatal programming of the developing lung with persisting impairment of pulmonary structure and function. Besides IUGR, early postnatal hyperalimentation (pHA) is discussed as a crucial factor of IUGR-associated diseases. Both extracellular matrix (ECM) and inflammatory processes have been shown to be dysregulated following IUGR and early pHA. However, the underlying molecular mechanisms of IUGR-associated diseases and the potential linkage of ECM and inflammation have not been addressed so far. Therefore, the ultimate goal of this project was to elucidate the role of regulation of ECM and inflammatory cytokines subsequent to IUGR and early pHA. AIMS: There are three specific aims: (1) to analyze the role of the TGF-β signaling in lung development subsequent to IUGR, (2) to determine the regulation of inflammatory cytokines and ECM-molecules in lungs subsequent to IUGR, and (3) to characterize the pathomechanistic role of early pHA using the example of the kidney. METHODS: Two simultaneous sets of animal experiments were used. One animal model addressed pre- and postnatal nutritional intervention, the other was restricted to postnatal interventions only: (A) IUGR was induced in Wister rats by isocaloric low protein diet (8% casein; IUGR) during gestation. The control group received normal protein diet (17% casein; Co). At birth the litter size was reduced to 6 male pups to induce early pHA. During lactation the mothers of both groups were fed standard chow. (B) Early pHA was induced by litter size reduction to 6 (LSR6) or 10 (LSR10) male neonates. Home-cage control (HCC; mean litter size of 16) animals without any postnatal manipulation during lactation were included. At postnatal day (P) 28 as well as P70 animals underwent whole body plethysmography and in addition metabolic cages at P70. Serum and samples of lungs and kidney were obtained at P1, P12, P21, P42, and P70 for mRNA extraction, protein extraction as well as histological analyses. RESULTS: Both respiratory system resistance and compliance were impaired subsequent to IUGR at P28; this impairment was even more significant at P70. (1) These changes were accompanied by persistent attenuated activity of the TGF-β signaling, assessed by phosphorylation of Smad2 and Smad3. Expression analysis of TGF-β-regulated ECM components in the lungs of IUGR animals at P1, such as collagen I, elastin, and tenascin N, revealed a significant deregulation. Consistently, in vitro inhibition of TGF-β signaling in NIH/3T3, MLE 12 and endothelial cells by adenovirus-delivered Smad7 demonstrated a direct effect on the expression of ECM components. Interestingly, however, not just a deregulation of ECM components was detected at P1, but also attenuated apoptotic processes, e.g. decreased cleavage of PARP. (2) Since the TGF-β signaling has potent anti-inflammatory effects, we next determined the dynamic expression of pro-inflammatory and pro-fibrotic markers as well of ECM components in the lung subsequent to IUGR at P1, P42 and P70. The expression of ECM components and metabolizing enzymes was markedly deregulated and the deposition of collagen I was strikingly increased at P70. Concomitantly to the pro-fibrotic processes in the lung subsequent to IUGR, the expression of inflammatory cytokines and both the activity and the expression of target genes of Stat3 signaling were dynamically regulated, with unaltered or decreased expression at P1 and significantly increased expression art P70. (3) Assessment of renal function at postnatal day 70 revealed decreased glomerular filtration rate, proteinuria, and increased fractional sodium and potassium secretion following early pHA (LSR6). Moreover, the deposition of ECM molecules, such as collagen I, was increased. Interestingly, despite the elevated expression of pro-inflammatory leptin and IL-6 expression the phosphorylation of Stat3 and ERK1/2 in the kidney, however, was decreased after LSR6. In accordance, neuropeptide Y (NPY) gene expression – sympathetic co-neurotransmitter regulated by Stat3 signaling – was down-regulated. In accordance, suppressor of cytokine signaling (SOCS)3 protein expression, an inhibitor of Stat3 and Erk1/2 signaling, was strongly elevated and colocalized with NPY. Interestingly, NPY is co- localized with SOCS3 in the distal tubules in the cortex and outer medulla, and in the proximal tubules, but no expression of SOCS3 was detectable in glomeruli. CONCLUSION: Taken together, IUGR has a direct and strong negative impact on respiratory resistance and compliance of the lung. There are two major underlying mechanisms linking IUGR and deregulation of ECM: first, the attenuated TGF-β signaling during late lung development; and second, the increased expression of inflammatory cytokines subsequent to IUGR. In addition, the missing anti-inflammatory effect of TGF-β signaling could contribute to the increased inflammatory response following IUGR. Furthermore we demonstrated that early pHA leads to organ-intrinsic increased expression of NPY via a postreceptor-leptin-receptor leptin resistance. This leptin resistance could contribute to the observed profibrotic processes, and ultimately to a long-term impairment of renal function. Thus, both IUGR and early postnatal hyperalimentation have a strong impact on perinatal programming of multi-organ inflammatory response

Neuromorphic analogue VLSI

Neuromorphic systems emulate the organization and function of nervous systems. They are usually composed of analogue electronic circuits that are fabricated in the complementary metal-oxide-semiconductor (CMOS) medium using very large-scale integration (VLSI) technology. However, these neuromorphic systems are not another kind of digital computer in which abstract neural networks are simulated symbolically in terms of their mathematical behavior. Instead, they directly embody, in the physics of their CMOS circuits, analogues of the physical processes that underlie the computations of neural systems. The significance of neuromorphic systems is that they offer a method of exploring neural computation in a medium whose physical behavior is analogous to that of biological nervous systems and that operates in real time irrespective of size. The implications of this approach are both scientific and practical. The study of neuromorphic systems provides a bridge between levels of understanding. For example, it provides a link between the physical processes of neurons and their computational significance. In addition, the synthesis of neuromorphic systems transposes our knowledge of neuroscience into practical devices that can interact directly with the real world in the same way that biological nervous systems do