Statistical Inference for Propagation Processes on Complex Networks

Die Methoden der Netzwerktheorie erfreuen sich wachsender Beliebtheit, da sie die Darstellung von komplexen Systemen durch Netzwerke erlauben. Diese werden nur mit einer Menge von Knoten erfasst, die durch Kanten verbunden werden. Derzeit verfügbare Methoden beschränken sich hauptsächlich auf die deskriptive Analyse der Netzwerkstruktur. In der hier vorliegenden Arbeit werden verschiedene Ansätze für die Inferenz über Prozessen in komplexen Netzwerken vorgestellt. Diese Prozesse beeinflussen messbare Größen in Netzwerkknoten und werden durch eine Menge von Zufallszahlen beschrieben. Alle vorgestellten Methoden sind durch praktische Anwendungen motiviert, wie die Übertragung von Lebensmittelinfektionen, die Verbreitung von Zugverspätungen, oder auch die Regulierung von genetischen Effekten. Zunächst wird ein allgemeines dynamisches Metapopulationsmodell für die Verbreitung von Lebensmittelinfektionen vorgestellt, welches die lokalen Infektionsdynamiken mit den netzwerkbasierten Transportwegen von kontaminierten Lebensmitteln zusammenführt. Dieses Modell ermöglicht die effiziente Simulationen verschiedener realistischer Lebensmittelinfektionsepidemien. Zweitens wird ein explorativer Ansatz zur Ursprungsbestimmung von Verbreitungsprozessen entwickelt. Auf Grundlage einer netzwerkbasierten Redefinition der geodätischen Distanz können komplexe Verbreitungsmuster in ein systematisches, kreisrundes Ausbreitungsschema projiziert werden. Dies gilt genau dann, wenn der Ursprungsnetzwerkknoten als Bezugspunkt gewählt wird. Die Methode wird erfolgreich auf den EHEC/HUS Epidemie 2011 in Deutschland angewandt. Die Ergebnisse legen nahe, dass die Methode die aufwändigen Standarduntersuchungen bei Lebensmittelinfektionsepidemien sinnvoll ergänzen kann. Zudem kann dieser explorative Ansatz zur Identifikation von Ursprungsverspätungen in Transportnetzwerken angewandt werden. Die Ergebnisse von umfangreichen Simulationsstudien mit verschiedenstensten Übertragungsmechanismen lassen auf eine allgemeine Anwendbarkeit des Ansatzes bei der Ursprungsbestimmung von Verbreitungsprozessen in vielfältigen Bereichen hoffen. Schließlich wird gezeigt, dass kernelbasierte Methoden eine Alternative für die statistische Analyse von Prozessen in Netzwerken darstellen können. Es wurde ein netzwerkbasierter Kern für den logistischen Kernel Machine Test entwickelt, welcher die nahtlose Integration von biologischem Wissen in die Analyse von Daten aus genomweiten Assoziationsstudien erlaubt. Die Methode wird erfolgreich bei der Analyse genetischer Ursachen für rheumatische Arthritis und Lungenkrebs getestet. Zusammenfassend machen die Ergebnisse der vorgestellten Methoden deutlich, dass die Netzwerk-theoretische Analyse von Verbreitungsprozessen einen wesentlichen Beitrag zur Beantwortung verschiedenster Fragestellungen in unterschiedlichen Anwendungen liefern kann

Usefulness of commercially available GPS data-loggers for tracking human movement and exposure to dengue virus

<p>Abstract</p> <p>Background</p> <p>Our understanding of the effects of human movement on dengue virus spread remains limited in part due to the lack of precise tools to monitor the time-dependent location of individuals. We determined the utility of a new, commercially available, GPS data-logger for long-term tracking of human movements in Iquitos, Peru. We conducted a series of evaluations focused on GPS device attributes key to reliable use and accuracy. GPS observations from two participants were later compared with semi-structured interview data to assess the usefulness of GPS technology to track individual mobility patterns.</p> <p>Results</p> <p>Positional point and line accuracy were 4.4 and 10.3 m, respectively. GPS wearing mode increased spatial point error by 6.9 m. Units were worn on a neck-strap by a carpenter and a moto-taxi driver for 14-16 days. The application of a clustering algorithm (I-cluster) to the raw GPS positional data allowed the identification of locations visited by each participant together with the frequency and duration of each visit. The carpenter moved less and spent more time in more fixed locations than the moto-taxi driver, who visited more locations for a shorter period of time. GPS and participants' interviews concordantly identified 6 common locations, whereas GPS alone identified 4 locations and participants alone identified 10 locations. Most (80%) of the locations identified by participants alone were places reported as visited for less than 30 minutes.</p> <p>Conclusion</p> <p>The present study demonstrates the feasibility of a novel, commercially available GPS data-logger for long-term tracking of humans and shows the potential of these units to quantify mobility patterns in relationship with dengue virus transmission risk in a tropical urban environment. Cost, battery life, size, programmability and ease of wear are unprecedented from previously tested units, proving the usefulness of GPS-dataloggers for linking movement of individuals and transmission risk of dengue virus and other infectious agents, particularly in resource-poor settings.</p

Targeted elimination of species-rich larval habitats can rapidly collapse arbovirus vector mosquito populations at hotel compounds in Zanzibar

Understanding the dynamics of larval habitat utilization by mosquito communities is crucial for the design of efficient environmental control strategies. The authors investigated the structure of mosquito communities found at hotel compounds in Zanzibar, networks of mosquito interactions with larval habitats and robustness of mosquito communities to elimination of larval habitats. A total of 23 698 mosquitoes comprising 26 species in six genera were found. Aedes aegypti (n = 16 207), Aedes bromeliae/Aedes lillie (n = 1340), Culex quinquefasciatus (n = 1300) and Eretmapodites quinquevitattus (n = 659) were the most dominant species. Ecological network analyses revealed the presence of dominant, larval habitat generalist species (e.g., A. aegypti), exploiting virtually all types of water holding containers and few larval habitat specialist species (e.g., Aedes natalensis, Orthopodomyia spp). Simulations of mosquito community robustness to systematic elimination of larval habitats indicate that mosquito populations are highly sensitive to elimination of larval habitats sustaining higher mosquito species diversity. This study provides insights on potential foci of future mosquito-borne arboviral disease outbreaks in Zanzibar and underscores the need for detailed knowledge on the ecological function of larval habitats for effective mosquito control by larval sources management.Danida Fellowship Centrehttp://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2915am2022Zoology and Entomolog

Transcriptional Regulation and Epigenetic Mechanisms Underlying Host-Parasite Interactions in Human Malaria

Human malaria is one of the most important infectious diseases and a major cause of death and poverty worldwide. It is caused by protozoan parasites of the genus Plasmodium that are transmitted by the bites of mosquitoes of the genus Anopheles. The parasites Plasmodium falciparum and the mosquitoes Anopheles gambiae are the leading figures of this global burden, which disproportionally affects Africa and children under the age of five. To fulfill development and to achieve adaptation to changing environments in the human and mosquito hosts, Plasmodium parasites are capable of drastic transcriptional switches. The Anopheles mosquitoes are the main vectors for human malaria, and they can display phenotypic variability in life history traits, including vector competence or responses against Plasmodium. Yet, the transcriptional regulation underlying host parasite interactions in human malaria, particularly based on epigenetic mechanisms and regarding the life cycle in the mosquito, remain almost completely unknown. In this doctoral thesis, we have applied multi-omic approaches and bioinformatic analyses to investigate the regulatory genome of both P. falciparum and A. gambiae mosquitoes, associated with the Plasmodium development and interactions within hosts, and with the responses of Anopheles mosquitoes to the parasitic infection. We have integrated genomic, epigenomic and transcriptomic approach to unveil relevant cis-regulatory elements and to assay the relationship between gene expression levels and chromatin-related mechanisms, such as histone marks or chromatin accessibility levels. We applied different techniques to these organisms, integrating RNA-seq, ChIP-seq and ATAC-seq for the first time. We reported the positive correlation between transcription and chromatin accessibility by ATAC-seq or active histone marks by ChIP-seq. We also identified thousands of active regulatory sequences, including enhancer candidates, that appeared to be linked to Plasmodium developmental transitions or clonally variant gene expression within humans, or that in the case of mosquitoes seemed to be specific to tissues or Plasmodium infection status. Ultimately, these allowed us to predict cognate transcription factors. Altogether, we provide evidence for genome-wide mechanisms and regulatory regions that may be involved in the dynamic transcriptional regulation underlying host-parasite interactions between malaria parasites and the human and mosquito hosts. This is much required in the context of current efforts against malaria, to inform existing and new mosquito-control and anti-malaria strategies

VIRUS-INDUCED CHANGES IN NUCLEAR PROTEINS AND MEMBRANES IN \u3cem\u3eNICOTIANA BENTHAMIANA\u3c/em\u3e CELLS

Viruses rely on host proteins to complete their life cycles. This results in alterations to normal cell physiology to processes which benefit viral processes such as replication and movement to other cells. This may involve the relocalization of host proteins away from their original subcellular targets to sites which may benefit the virus, a process that is not as well understood as it relates to the nucleus. To identify nuclear proteins that may be involved in such processes, a library of random Nicotiana benthamiana cDNAs were expressed as GFP fusions in a transgenic marker lines expressing a histone 2B:RFP nuclear marker. Of the 1,087 proteins screened, 355 were found to be associated with the nucleus. These nuclear proteins were then expressed in plants infected with sonchus yellow net virus, a betanucleorhabdovirus which forms its replication complex in the nucleus. Of the 355 nuclear-associated proteins, 15 were found to relocalize in response to SYNV infection, and to test if this phenomenon was virus-specific, these proteins were then expressed in plants infected with tobacco etch virus (TEV), a potyvirus which replicates in the cytoplasm. Of these 16 proteins, 6 were found to show both general and virus-specific localization patterns between the two viruses. To gain insight into the cellular tropism of SYNV, a cell map was generated in order determine the effect of this virus on membranes in N. benthamiana tissues. Finally, sowthistle yellow vein virus (SYVV), another betanucleorhabdovirus and classical model virus, was identified in the wild for the first time in over 30 years. Sequence and phylogenetic analysis confirmed the identity of this virus with historical laboratory isolates. The availability of SYVV will facilitate future studies that compare the effect of rhabdovirus infection on host nuclear proteins and membranes

Plant virus epidemiology: applications and prospects for mathematical modeling and analysis to improve understanding and disease control

In recent years, mathematical modeling has increasingly been used to complement experimental and observational studies of biological phenomena across different levels of organization. In this article, we consider the contribution of mathematical models developed using a wide range of techniques and uses to the study of plant virus disease epidemics. Our emphasis is on the extent to which models have contributed to answering biological questions and indeed raised questions related to the epidemiology and ecology of plant viruses and the diseases caused. In some cases, models have led to direct applications in disease control, but arguably their impact is better judged through their influence in guiding research direction and improving understanding across the characteristic spatiotemporal scales of plant virus epidemics. We restrict this article to plant virus diseases for reasons of length and to maintain focus even though we recognize that modeling has played a major and perhaps greater part in the epidemiology of other plant pathogen taxa, including vector-borne bacteria and phytoplasmas

EDNA-host: Detection of global plant viromes using high throughput sequencing

The aim of this research was to develop the concept of host-specific virome detection methods. Three model systems were selected roses, cucurbits, and water. EDNA MiFi was used to generate pathogen electronic probes (E-probes) for the detection of viruses in-silico and in-vitro using field samples for validation. The selected three host model allows a comprehensive detection system for specifically targeting the three pre-determined host viromes (117 plant viruses). This research also presents a validation of the analytical sensitivity determining the in-vitro limit of detection (10pg) quantified for a specific set of E-probes (ArMV-RNA2 60nt). The database of EDNA-Rose MiFi includes E-probes (523) specifically designed to detect 22 reported viruses infecting roses worldwide. The EDNA-Cucurbits MiFi includes E-probes (412) for 15 reported viruses. Finally, the MiFi database EDNA-Water is composed of a selection of highly specific E-probes (1730) for 80 reported viruses within the genera Potexvirus, Tobamovirus, and Tombusvirus. The detection of the presence of multiple viruses in a host is challenging. Hence, the relevance of developing and applying a broad detection system to detect viruses out of a virome in a sample. The application of EDNA-Host extends to plant virus detection to all staple crops, virus-free certification programs, breeding, veterinary and life sciences