Network Pharmacology Approaches for Understanding Traditional Chinese Medicine

Traditional Chinese medicine (TCM) has obvious efficacy on disease treatments and is a valuable source for novel drug discovery. However, the underlying mechanism of the pharmacological effects of TCM remains unknown because TCM is a complex system with multiple herbs and ingredients coming together as a prescription. Therefore, it is urgent to apply computational tools to TCM to understand the underlying mechanism of TCM theories at the molecular level and use advanced network algorithms to explore potential effective ingredients and illustrate the principles of TCM in system biological aspects. In this thesis, we aim to understand the underlying mechanism of actions in complex TCM systems at the molecular level by bioinformatics and computational tools. In study Ⅰ, a machine learning framework was developed to predict the meridians of the herbs and ingredients. Finally, we achieved high accuracy of the meridians prediction for herbs and ingredients, suggesting an association between meridians and the molecular features of ingredients and herbs, especially the most important features for machine learning models. Secondly, we proposed a novel network approach to study the TCM formulae by quantifying the degree of interactions of pairwise herb pairs in study Ⅱ using five network distance methods, including the closest, shortest, central, kernel, as well as separation. We demonstrated that the distance of top herb pairs is shorter than that of random herb pairs, suggesting a strong interaction in the human interactome. In addition, center methods at the ingredient level outperformed the other methods. It hints to us that the central ingredients play an important role in the herbs. Thirdly, we explored the associations between herbs or ingredients and their important biological characteristics in study III, such as properties, meridians, structures, or targets via clusters from community analysis of the multipartite network. We found that herbal medicines among the same clusters tend to be more similar in the properties, meridians. Similarly, ingredients from the same cluster are more similar in structure and protein target. In summary, this thesis intends to build a bridge between the TCM system and modern medicinal systems using computational tools, including the machine learning model for meridian theory, network modelling for TCM formulae, as well as multipartite network analysis for herbal medicines and their ingredients. We demonstrated that applying novel computational approaches on the integrated high-throughput omics would provide insights for TCM and accelerate the novel drug discovery as well as repurposing from TCM.Perinteinen kiinalainen lääketiede (TCM) on ilmeinen tehokkuus taudin hoidoissa ja on arvokas lähde uuden lääkkeen löytämiseen. TCM: n farmakologisten vaikutusten taustalla oleva mekanismi pysyy kuitenkin tuntemattomassa, koska TCM on monimutkainen järjestelmä, jossa on useita yrttejä ja ainesosia, jotka tulevat yhteen reseptilääkkeeksi. Siksi on kiireellistä soveltaa Laskennallisia työkaluja TCM: lle ymmärtämään TCM-teorioiden taustalla oleva mekanismi molekyylitasolla ja käyttävät kehittyneitä verkkoalgoritmeja tutkimaan mahdollisia tehokkaita ainesosia ja havainnollistavat TCM: n periaatteita järjestelmän biologisissa näkökohdissa. Tässä opinnäytetyössä pyrimme ymmärtämään monimutkaisten TCM-järjestelmien toimintamekanismia molekyylitasolla bioinformaattilla ja laskennallisilla työkaluilla. Tutkimuksessa kehitettiin koneen oppimiskehystä yrttien ja ainesosien meridialaisista. Lopuksi saavutimme korkean tarkkuuden meridiaaneista yrtteistä ja ainesosista, mikä viittaa meridiaaneihin ja ainesosien ja yrtteihin liittyvien molekyylipiirin välillä, erityisesti koneen oppimismalleihin tärkeimmät ominaisuudet. Toiseksi ehdoimme uuden verkon lähestymistavan TCM-kaavojen tutkimiseksi kvantitoimisella vuorovaikutteisten yrttiparien vuorovaikutuksen tutkimuksessa ⅱ käyttämällä viisi verkkoetäisyyttä, mukaan lukien lähin, lyhyt, keskus, ydin sekä erottaminen. Osoitimme, että ylä-yrttiparien etäisyys on lyhyempi kuin satunnaisten yrttiparien, mikä viittaa voimakkaaseen vuorovaikutukseen ihmisellä vuorovaikutteisesti. Lisäksi Center-menetelmät ainesosan tasolla ylittivät muut menetelmät. Se vihjeitä meille, että keskeiset ainesosat ovat tärkeässä asemassa yrtteissä. Kolmanneksi tutkimme yrttien tai ainesosien välisiä yhdistyksiä ja niiden tärkeitä biologisia ominaisuuksia tutkimuksessa III, kuten ominaisuudet, meridiaanit, rakenteet tai tavoitteet klustereiden kautta moniparite-verkoston yhteisön analyysistä. Löysimme, että kasviperäiset lääkkeet samoilla klusterien keskuudessa ovat yleensä samankaltaisia ominaisuuksissa, meridiaaneissa. Samoin saman klusterin ainesosat ovat samankaltaisempia rakenteissa ja proteiinin tavoitteessa. Yhteenvetona tämä opinnäytetyö aikoo rakentaa silta TCM-järjestelmän ja nykyaikaisten lääkevalmisteiden välillä laskentatyökaluilla, mukaan lukien Meridian-teorian koneen oppimismalli, TCM-kaavojen verkkomallinnus sekä kasviperäiset lääkkeet ja niiden ainesosat Osoitimme, että uusien laskennallisten lähestymistapojen soveltaminen integroidulle korkean suorituskyvyttömiehille tarjosivat TCM: n näkemyksiä ja nopeuttaisivat romaanin huumeiden löytöä sekä toistuvat TCM: stä

Metagenomic analysis of plant viruses associated with papaya ringspot disease in Carica papaya L. in Kenya

Carica papaya L. is an important fruit crop grown by small- and large-scale farmers in Kenya for local and export markets. However, its production is constrained by papaya ringspot disease (PRSD). The disease is believed to be caused by papaya ringspot virus (PRSV). Previous attempts to detect PRSV in papaya plants showing PRSD symptoms, using enzyme-linked immunosorbent assay (ELISA) and reverse transcriptase-polymerase chain reaction (RT-PCR) procedures with primers specific to PRSV, have not yielded conclusive results. Therefore, the nature of viruses responsible for PRSD was elucidated in papaya leaves collected from 22 counties through Illumina MiSeq next-generation sequencing (NGS) and validated by RT-PCR and Sanger sequencing. Viruses were detected in 38 out of the 48 leaf samples sequenced. Sequence analysis revealed the presence of four viruses: a Potyvirus named Moroccan watermelon mosaic virus (MWMV) and three viruses belonging to the genus Carlavirus. The Carlaviruses include cowpea mild mottle virus (CpMMV) and two putative Carlaviruses —closely related but distinct from cucumber vein-clearing virus (CuVCV) with amino acid and nucleotide sequence identities of 75.7–78.1 and 63.6–67.6%, respectively, in the coat protein genes. In reference to typical symptoms observed in the infected plants, the two putative Carlaviruses were named papaya mottle-associated virus (PaMV) and papaya mild mottle-associated virus (PaMMV). Surprisingly, and in contrast to previous studies conducted in other parts of world, PRSV was not detected. The majority of the viruses were detected as single viral infections, while a few were found to be infecting alongside another virus (for example, MWMV and PaMV). Furthermore, the NGS and RT-PCR analysis identified MWMV as being strongly associated with ringspot symptoms in infected papaya fruits. This study has provided the first complete genome sequences of these viruses isolated from papaya in Kenya, together with primers for their detection—thus proving to be an important step towards the design of long-term, sustainable disease management strategies

Revisiting a pollen-transmitted ilarvirus previously associated with angular mosaic of grapevine

We report the characterization of a novel tri-segmented RNA virus infecting Mercurialis annua, a common crop weed and model species in plant science. The virus, named "Mercurialis latent virus" (MeLaV) was first identified in a mixed infection with the recently described Mercurialis orthotospovirus 1 (MerV1) on symptomatic plants grown in glasshouses in Lausanne (Switzerland). Both viruses were found to be transmitted by Thrips tabaci, which presumably help the inoculation of infected pollen in the case of MeLaV. Complete genome sequencing of the latter revealed a typical ilarviral architecture and close phylogenetic relationship with members of the Ilarvirus subgroup 1. Surprisingly, a short portion of MeLaV replicase was found to be identical to the partial sequence of grapevine angular mosaic virus (GAMV) reported in Greece in the early 1990s. However, we have compiled data that challenge the involvement of GAMV in angular mosaic of grapevine, and we propose alternative causal agents for this disorder. In parallel, three highly-conserved MeLaV isolates were identified in symptomatic leaf samples in The Netherlands, including a herbarium sample collected in 1991. The virus was also traced in diverse RNA sequencing datasets from 2013-2020, corresponding to transcriptomic analyses of M. annua and other plant species from five European countries, as well as metaviromics analyses of bees in Belgium. Additional hosts are thus expected for MeLaV, yet we argue that infected pollen grains have likely contaminated several sequencing datasets and may have caused the initial characterization of MeLaV as GAMV

Within-host microbial interactions and plant parasites: from pairwise interactions to the microbiome

Multicellular organisms are often host to a diverse community of mutualistic, commensal, and parasitic microbes, referred to collectively as the microbiome. The microbial community surrounding a parasite shapes both that parasite’s immediate phenotype and its evolutionary potential. This dissertation investigates this by focusing on how within-host interactions relate to disease at multiple levels, from interrogations of pairwise interactions to the microbiome. In this work, I used computational methods and lab- and field-based studies to examine the interactions between fungal species that coinfect plant host individuals and co-occur in plant host populations. At the individual level, I explored how interactions among fungal symbionts in the same host leaf alter parasite growth and host responses. Within host leaves, the growth of a parasite, R. solani, was influenced by coinfection with another parasite. This effect was further mediated by a third, asymptomatic fungal symbiont, highlighting the potential for higher-order interactions occurring among symbionts within a shared host. Multiple infection by these three fungal symbionts also impacted leaf survival and host biomass. I also simulated dual RNA-seq datasets, simultaneous gene expression sequencing of a pathogen and host during infection, to explore the challenges of investigating the molecular mechanisms underlying host-parasite interactions in non-model systems and proposed a workflow to follow to interrogate such systems. Scaling up to the population level, I explored how interactions between parasite, R. solani, and a mutualist affect parasite spread through a host population. While host individuals with the mutualist had higher biomass, populations in which the mutualist was present experienced higher peak parasite prevalence than populations in which the mutualist was absent. I further explored these fungal symbionts under field conditions, by investigating how the diversity and composition of the fungal community of leaves associate with disease symptoms. Symptoms of parasite, R. solani, were associated with lower fungal richness and diversity, as well as distinct fungal composition, compared to asymptomatic leaves or leaves symptomatic of other symptoms. Together, these results highlight the utility of multi-level approaches to disease ecology and evolution.Doctor of Philosoph

Molecular variability of cassava Bemisia tabaci and its effect on the epidemiology of cassava mosaic geminiviruses in Uganda

Bemisia tabaci (Genn.) is the vector of cassava mosaic geminiviruses (CMGs), which are the main production constraint to cassava, both in Uganda and elsewhere in Africa. A severe form of cassava mosaic disease (CMD) was responsible for the devastation of cassava in Uganda beginning in the late 1980s. In subsequent years the severe CMD epidemic spread throughout Uganda, and to neighbouring countries, causing devastating effects to cassava production, and its geographical range continues to expand with the pandemic. To further understand the virus-vector dynamics involved in the spread of CMD in the post epidemic zone in Uganda, we investigated the current distribution of B. tabaci genotypes in selected cassava-growing regions. Additionally, the relationship between the vector genotypes and distribution of CMGs in the post-epidemic zone was examined also. CMD-affected cassava leaves were collected from 3 to 5 month-old cassava plants, and B. tabaci adults and fourth instar nymphs were collected from cassava and twenty-two other plant species occurring adjacent to the sampled cassava fields. The mitochondrial cytochrome oxidase I (mtCOI) sequence was used to establish the genotype of B. tabaci adults and nymphs associated with the sampled plant species. African cassava mosaic virus (ACMV) and East African cassava mosaic virus-Uganda 2 (EACMV-UG2) were confirmed to be present in the post-epidemic zone in Uganda, as reported previously. As expected, EACMV-UG2 predominated. However, unlike previous observations in which EACMV-UG2 was consistently associated with the severe disease phenotype, in this study EACMV-UG2 occurred almost equally in the severely and mildly diseased plants. Phylogenetic analyses of Ugandan B. tabaci genotypes (mtCOI) revealed that their closest relatives were other Old World genotypes, as might be expected. Two previously reported B. tabaci genotype clusters, Uganda 1 (Ug1) and Uganda 2 (Ug2), at ~8% nt divergence, were confirmed to occur on cassava in the post-epidemic zone. However, Ug1 occurred more frequently (83%) than Ug2 (17%), and no definite association was established of a particular vector genotype with cassava plants exhibiting the severe disease phenotype, in contrast to the B. tabaci genotype distribution and association with the CMGs reported there at the height of the spread of the severe CMD epidemic. Based on the presence of B. tabaci fourth instar nymphs, the Ug1 genotypes colonized five additional non-cassava plant species: Manihot glaziovii, Jatropha gossypifolia, Euphorbia heterophylla, Aspilia africana and Abelmoschus esculentus, suggesting that in Uganda the Ug1 genotypes are not restricted to cassava. However, no Ug2 genotypes were detected on the non-cassava plant species sampled. This study revealed also the presence in Uganda of five distinct previously unrecorded B. tabaci genotype clusters, Uganda 3 (Ug3), Uganda 4 (Ug4), Uganda 5 (Ug5), Uganda 6 (Ug6) and Uganda 7 (Ug7), and a sweetpotato colonizing genotype cluster, designated Uganda 8 (Ug8), among the collective Ugandan B. tabaci populations. Ug3 was the only exemplar representing one cluster, which was unlike any previously described genotype in Uganda or elsewhere, and diverged at 8%, 10% and 17% from Ug1, Ug2 and Ug8, respectively. The Ug3 genotypes colonized a single species, Ocimum gratissimum. Ug4, Ug5, Ug6 and Ug7 formed four closely related sub-clusters (93-97% nt identity), and diverged from one another by 1-7%, and by 15-18% from Ug1, Ug2, Ug3 and Ug8, respectively. The Ug4 genotypes had as their closest relatives (at 97-99% nt identity) previously reported B. tabaci from okra in the Ivory Coast, whereas, the Ug5 and Ug6 genotypes shared 95-99% and 99% nt identity, respectively, with their closest relatives from the Mediterranean-North Africa- Middle East (MED-NAFR-ME) region, which also includes the well studied B and Q biotypes. The Ug7 genotypes were closely related (at 98-99% nt identity) to B. tabaci from Reunion Island in the Indian Ocean. The Ug4, Ug5, Ug6 and Ug7 genotypes were identified on 54%, 8%, 8%, and 31% of the sampled plants species, respectively. Ug4 were most polyphagous, followed by Ug7 and Ug6. However, none of the new five genotypes (Ug3-Ug7) was found associated with, or colonizing, xx cassava or sweetpotato plants in this study. Squash plants colonized by the Ug6 and Ug7 genotypes, both members of the B biotype/B-like cluster, developed the silvering phenotype, while those colonized by the Ug4 genotypes (most closely related to a non-B like genotype from okra in the Ivory Coast) did not. In addition to colonizing sweetpotato, the Ug8 genotypes also colonized Lycopersicon esculentum and L nepetifolia

Made in America: fictions of genetic industry

This dissertation focuses on contemporary American fiction that explores the intertwined histories of genetics and industrialism. I argue that Jeffrey Eugenides, Louise Erdrich, and Richard Powers interpret industrial and scientific texts from the early twentieth century to tell a previously untold history of the era. Emphasizing the connections between emerging understandings of genetics and new methods of manufacturing, they present the story of how the gene made life seem buildable. These writers trace fantasies of the literal mass production of Americans, exposing how immigrants, Native Americans, and women became particular targets of an industrial impulse toward standardization. Yet the novels in my study also recover an alternative history of the gene, in which it possesses a range of abilities enabling it to resist efforts to industrialize not just social, but also organismal, life. Genes are portrayed in these fictions as agents of transformation as well as replication, thus inspiring optimism about the possibility of unsettling the future of corporate capitalism in American life. Chapter One argues that Jeffrey Eugenides' Middlesex draws parallels between Henry Ford's factory, Thomas Hunt Morgan's genetic laboratory, and the Stephanides family lineage to show how naturally occurring mutations subvert the pursuit of exact reproduction. Chapter Two examines Louise Erdrich's Tracks, and its portrayal of the Pinkham Medicine Company's commercial hybridization of plants. Pointing to the genetic reversion that often accompanies hybridity, Erdrich undermines Pinkham's efforts to cultivate a uniform American populace from diverse racial roots. Chapter Three discusses Richard Powers' depiction of corporatization in Gain, focusing on Procter and Gamble's pursuit of self-perpetuation by crossing not merely into legal, but also embodied, personhood. Turning to chromosomal chiasmus as a mechanism that makes reproduction a process inherently variable, and therefore unstable, Powers portrays the genetic body as a dubious model for corporate longevity. Taken together, my central texts address the relationship between fiction and history, literature and science, and human and industrial reproduction.2017-11-18T00:00:00

Predictive Learning from Real-World Medical Data: Overcoming Quality Challenges

Randomized controlled trials (RCTs) are pivotal in medical research, notably as the gold standard, but face challenges, especially with specific groups like pregnant women and newborns. Real-world data (RWD), from sources like electronic medical records and insurance claims, complements RCTs in areas like disease risk prediction and diagnosis. However, RWD's retrospective nature leads to issues such as missing values and data imbalance, requiring intensive data preprocessing. To enhance RWD's quality for predictive modeling, this thesis introduces a suite of algorithms developed to automatically resolve RWD's low-quality issues for predictive modeling. In this study, the AMI-Net method is first introduced, innovatively treating samples as bags with various feature-value pairs and unifying them in an embedding space using a multi-instance neural network. It excels in handling incomplete datasets, a frequent issue in real-world scenarios, and shows resilience to noise and class imbalances. AMI-Net's capability to discern informative instances minimizes the effects of low-quality data. The enhanced version, AMI-Net+, improves instance selection, boosting performance and generalization. However, AMI-Net series initially only processes binary input features, a constraint overcome by AMI-Net3, which supports binary, nominal, ordinal, and continuous features. Despite advancements, challenges like missing values, data inconsistencies, and labeling errors persist in real-world data. The AMI-Net series also shows promise for regression and multi-task learning, potentially mitigating low-quality data issues. Tested on various hospital datasets, these methods prove effective, though risks of overfitting and bias remain, necessitating further research. Overall, while promising for clinical studies and other applications, ensuring data quality and reliability is crucial for these methods' success

Chronic thromboembolic pulmonary vascular disease: physiological concepts and genetic predisposition

Chronic thromboembolic pulmonary hypertension (CTEPH) is an uncommon sequela of acute pulmonary embolism and, untreated, leads to right ventricular (RV) failure and death. Despite its growing recognition, methods for the detection of early RV insufficiency and prediction of clinical deterioration, important to optimum preservation of RV function, are currently suboptimal. Furthermore, underlying genetic predisposition to CTEPH, unexplained by defective fibrinolysis, remains largely unexplored. The RV’s physiological response to chronic thromboembolic obstruction is arguably best described by RV pressure volume loops which, historically, are best obtained using the conductance catheter. Although invasive, conductance has an indisputable advantage over current imaging modalities; catheters measure dynamic ventricular pressure and volume throughout the cardiac cycle. Using this technique, abnormal RV pressure volume loops are demonstrated in response to chronic thrombotic obstruction, independent of resting haemodynamic criteria diagnostic of CTEPH. Pressure volume differences and accrual of an exercise gas exchange deficit further suggest early ‘subclinical’ RV adaptation. The genetic architecture of CTEPH is also explored using high-throughput sequencing of unrelated patients. This shows that rare DNA variants in CTEPH that are predicted to harbour deleterious effects are not over-represented in fibrinolytic pathways. Finally, prognostication in CTEPH is evaluated using a clinical deterioration model which is shown to be predicted by patient-reported outcomes at diagnosis. In conclusion, RV and pulmonary circulatory function in chronic thromboembolic pulmonary vascular disease are inadequately characterised by existing routine methods. Links between the observed physiological deficits, risk of clinical deterioration and abnormal genetic architecture warrant further evaluation in this rare disease.Open Acces

Endocannabinoid System Modulation By Natural Products From Ancient Medicinal Plants

Herbal drugs have been important for the treatment of multiple pathological conditions since ancient times. A multitude of historical texts document the importance of plant-based therapies, but the therapeutic effectiveness of many described applications remains questionable. Concomitantly, the pharmacological properties and the associated chemistry of many herbal drugs described in ancient texts remain poorly studied. The development of modern pharmacology and analytical tools in the past century has led to the discovery of a plethora of novel plant-derived compounds and propelled advancements in medicine and pharmacology. The identification of (-)-trans-Δ9-tetrahydrocannabinol (THC) as the active principle of Cannabis sativa L., triggered research activities conductive to the elucidation of the endocannabinoid system (ECS). The ECS is a major modulatory system involved in a variety of physiological functions including the regulation of appetite, pain perception, memory, mood, and the modulation of inflammation and immune responses. A deregulation of the ECS is commonly associated with pathological conditions such as mood disorders, pain, inflammation, and neurodegenerative and immune diseases. Therefore, identifying target specific agonists, antagonists and inhibitors constitutes a promising strategy to tackle these conditions. The inhibition of fatty acid amide hydrolase (FAAH), the major enzyme involved in the termination of endocannabinoid signalling via the degradation of the endocannabinoid anandamide (AEA), represents a pharmacological strategy to treat conditions such as anxiety, depression or metabolic disorders. Besides the main cannabinoid type-1 (CB1) receptors, activation of cannabinoid type-2 (CB2) receptors represents as well an interesting pharmacological approach to treat diverse disorders such as diabetes, and neurodegenerative and immune diseases. Therefore, the main aim of this doctoral thesis was to identify and characterize plant-derived compounds able to target and modulate specific components of the ECS. As a starting point to address this objective, a plant extract library of drug samples mainly associated with the herbal drugs described in Dioscorides’ De Materia Medica (DMM; ex Matthioli, 1568) was built up. The extracts were tested for in vitro inhibition of FAAH and affinity towards CB2 receptors. In addition, as an indication of non-specific cytotoxicity, their antiproliferative activity was evaluated. For the screened extracts, the possible relationship between investigated bioactivity and plant phylogeny was first questioned. From the results of the FAAH inhibition screening, it emerged that extracts with significant FAAH inhibitory activity are phylogenetically clustered, as they are associated preponderantly with herbal drugs derived from the Fabaceae family. Isoflavonoids and prenylated derivatives, secondary metabolites commonly produced in Fabaceae, were proposed as potential FAAH inhibitors. Among the isoflavonoids tested, the prenylated luteone and neobavaisoflavone proved to be highly potent, selective, competitive and reversible FAAH inhibitors at the nanomolar range. In addition, preliminary results from the screening of the extract library towards CB2 receptors suggested the identification of sesquiterpene coumarins as a new class of CB2 receptor ligands at the low micromolar range. In conclusion, in this thesis project we have identified two classes of natural products showing in vitro pharmacological interaction with the ECS. Moreover, the compounds may prove promising scaffolds for the development of new therapeutic agents with anti-inflammatory, anti-nociceptive, anxiolytic, anti-diabetic or immunomodulatory activities