Integration of host, pathogen and microbiome -omics data for studying infectious diseases

In an ever-growing worldwide population, human infectious diseases are an increasingly serious problem for public health. In particular, more than a million deaths and millions of infectious disease cases per year caused by fungal pathogens have been reported globally in recent years. Hence, more investments must be put into fungal research to overcome the problem. The opportunistic pathogen Candida albicans and the airborne Aspergillus fumigatus are the two most prevalent fungal pathogens causing serious issues in medical care units. Despite the recent advances in fungal research, there is little knowledge about the role of fungal metabolism in developing the infection when coexisting within the human body with microbial community members in different organs. This dissertation applied computational tools, and implemented systems biology approaches to uncover key factors in the colonization of the pathogens, especially C. albicans and A. fumigatus, from a systems biology perspective and unseen by wet-lab experiments alone. Next to multi-omics data analysis, a major effort was put into genome-scale metabolic models (GEMs) generation and analysis as a promising approach to shed light on the role of metabolism in developing the infection. In brief, this thesis sheds light on key factors leading to the inhibition or promotion of fungal growth. This especially includes the first available GEM reconstruction of C. albicans to theoretically study the intricate interaction of the fungus with the human host and the microbial community members. Lastly, a platform of 252 A. fumigatus GEMs at the strain resolution was generated. It revealed the phenotypic diversity of A. fumigatus strains isolated from different hospitals and farms in Germany and explained the contribution of the fungus to the shaping of the metabolic landscape of the lung microbiome in a favorable manner for fungal growth

Computational structure‐based drug design: Predicting target flexibility

The role of molecular modeling in drug design has experienced a significant revamp in the last decade. The increase in computational resources and molecular models, along with software developments, is finally introducing a competitive advantage in early phases of drug discovery. Medium and small companies with strong focus on computational chemistry are being created, some of them having introduced important leads in drug design pipelines. An important source for this success is the extraordinary development of faster and more efficient techniques for describing flexibility in three‐dimensional structural molecular modeling. At different levels, from docking techniques to atomistic molecular dynamics, conformational sampling between receptor and drug results in improved predictions, such as screening enrichment, discovery of transient cavities, etc. In this review article we perform an extensive analysis of these modeling techniques, dividing them into high and low throughput, and emphasizing in their application to drug design studies. We finalize the review with a section describing our Monte Carlo method, PELE, recently highlighted as an outstanding advance in an international blind competition and industrial benchmarks.We acknowledge the BSC-CRG-IRB Joint Research Program in Computational Biology. This work was supported by a grant from the Spanish Government CTQ2016-79138-R.J.I. acknowledges support from SVP-2014-068797, awarded by the Spanish Government.Peer ReviewedPostprint (author's final draft

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

METABOLIC MODELING AND OMICS-INTEGRATIVE ANALYSIS OF SINGLE AND MULTI-ORGANISM SYSTEMS: DISCOVERY AND REDESIGN

Computations and modeling have emerged as indispensable tools that drive the process of understanding, discovery, and redesign of biological systems. With the accelerating pace of genome sequencing and annotation information generation, the development of computational pipelines for the rapid reconstruction of high-quality genome-scale metabolic networks has received significant attention. These models provide a rich tapestry for computational tools to quantitatively assess the metabolic phenotypes for various systems-level studies and to develop engineering interventions at the DNA, RNA, or enzymatic level by careful tuning in the biophysical modeling frameworks. in silico genome-scale metabolic modeling algorithms based on the concept of optimization, along with the incorporation of multi-level omics information, provides a diverse array of toolboxes for new discovery in the metabolism of living organisms (which includes single-cell microbes, plants, animals, and microbial ecosystems) and allows for the reprogramming of metabolism for desired output(s). Throughout my doctoral research, I used genome-scale metabolic models and omics-integrative analysis tools to study how microbes, plants, animal, and microbial ecosystems respond or adapt to diverse environmental cues, and how to leverage the knowledge gleaned from that to answer important biological questions. Each chapter in this dissertation will provide a detailed description of the methodology, results, and conclusions from one specific research project. The research works presented in this dissertation represent important foundational advance in Systems Biology and are crucial for sustainable development in food, pharmaceuticals and bioproduction of the future. Advisor: Rajib Sah

Protein Deimination and Extracellular Vesicle Profiles in Antarctic Seabirds

Pelagic seabirds are amongst the most threatened of all avian groups. They face a range of immunological challenges which seem destined to increase due to environmental changes in their breeding and foraging habitats, affecting prey resources and exposure to pollution and pathogens. Therefore, the identification of biomarkers for the assessment of their health status is of considerable importance. Peptidylarginine deiminases (PADs) post-translationally convert arginine into citrulline in target proteins in an irreversible manner. PAD-mediated deimination can cause structural and functional changes in target proteins, allowing for protein moonlighting in physiological and pathophysiological processes. PADs furthermore contribute to the release of extracellular vesicles (EVs), which play important roles in cellular communication. In the present study, post-translationally deiminated protein and EV profiles of plasma were assessed in eight seabird species from the Antarctic, representing two avian orders: Procellariiformes (albatrosses and petrels) and Charadriiformes (waders, auks, gulls and skuas). We report some differences between the species assessed, with the narrowest EV profiles of 50−200 nm in the northern giant petrel Macronectes halli, and the highest abundance of larger 250−500 nm EVs in the brown skua Stercorarius antarcticus. The seabird EVs were positive for phylogenetically conserved EV markers and showed characteristic EV morphology. Post-translational deimination was identified in a range of key plasma proteins critical for immune response and metabolic pathways in three of the bird species under study; the wandering albatross Diomedea exulans, south polar skua Stercorarius maccormicki and northern giant petrel. Some differences in Gene Ontology (GO) biological and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for deiminated proteins were observed between these three species. This indicates that target proteins for deimination may differ, potentially contributing to a range of physiological functions relating to metabolism and immune response, as well as to key defence mechanisms. PAD protein homologues were identified in the seabird plasma by Western blotting via cross-reaction with human PAD antibodies, at an expected 75 kDa size. This is the first study to profile EVs and to identify deiminated proteins as putative novel plasma biomarkers in Antarctic seabirds. These biomarkers may be further refined to become useful indicators of physiological and immunological status in seabirds—many of which are globally threatened

Post-translational protein deimination signatures in sea lamprey (Petromyzon marinus) plasma and plasma-extracellular vesicles

Lampreys are a jawless vertebrate species belonging to an ancient vertebrate lineage that diverged from a common ancestor with humans ~500 million years ago. The sea lamprey (Petromyzon marinus) has a filter feeding ammocoete larval stage that metamorphoses into a parasitic adult, feeding both on teleost and elasmobranch fish. Lampreys are a valuable comparative model species for vertebrate immunity and physiology due to their unique phylogenetic position, unusual adaptive immune system, and physiological adaptions such as tolerance to salinity changes and urea. Peptidylarginine deiminases (PADs) are a phylogenetically conserved enzyme family which catalyses post-translational deimination/citrullination in target proteins, enabling proteins to gain new functions (moonlighting). The identification of deiminated protein targets in species across phylogeny may provide novel insights into post-translational regulation of physiological and pathophysiological processes. Extracellular vesicles (EVs) are membrane vesicles released from cells that carry cargos of small molecules and proteins for cellular communication, involved in both normal and pathological processes. The current study identified deimination signatures in proteins of both total plasma and plasma-EVs in sea lamprey and furthermore reports the first characterisation of plasma-EVs in lamprey. EVs were poly-dispersed in the size range of 40–500 nm, similar to what is observed in other taxa, positive for CD63 and Flotillin-1. Plasma-EV morphology was confirmed by transmission electron microscopy. Assessment of deimination/citrullination signatures in lamprey plasma and plasma-EVs, revealed 72 deimination target proteins involved in immunity, metabolism and gene regulation in whole plasma, and 37 target proteins in EVs, whereof 24 were shared targets. Furthermore, the presence of deiminated histone H3, indicative of gene-regulatory mechanisms and also a marker of neutrophil extracellular trap formation (NETosis), was confirmed in lamprey plasma. Functional protein network analysis revealed some differences in KEGG and GO pathways of deiminated proteins in whole plasma compared with plasma-EVs. For example, while common STRING network clusters in plasma and plasma-EVs included Peptide chain elongation, Viral mRNA translation, Glycolysis and gluconeogenesis, STRING network clusters specific for EVs only included: Cellular response to heat stress, Muscle protein and striated muscle thin filament, Nucleosome, Protein processing in endoplasmic reticulum, Nucleosome and histone deacetylase complex. STRING network clusters specific for plasma were: Adipokinetic hormone receptor activity, Fibrinogen alpha/beta chain family, peptidase S1A, Glutathione synthesis and recycling-arginine, Fructose 1,6-bisphosphate metabolic process, Carbon metabolism and lactate dehydrogenase activity, Post-translational protein phosphorylation, Regulation of insulin-like growth factor transport and clotting cascade. Overall, for the EV citrullinome, five STRING network clusters, 10 KEGG pathways, 15 molecular GO pathways and 29 Reactome pathways were identified, compared with nine STRING network clusters, six KEGG pathways, two Molecular GO pathways and one Reactome pathway specific for whole plasma; while further pathways were shared. The reported findings indicate that major pathways relevant for immunity and metabolism are targets of deimination in lamprey plasma and plasma-EVs, with some differences, and may help elucidating roles for the conserved PAD enzyme family in regulation of immune and metabolic function throughout phylogeny

Integrative transcriptomic profiling of mRNA, miRNA, circRNA, and lncRNA in alveolar macrophages isolated from PRRSV-infected porcine

IntroductionThe porcine reproductive and respiratory syndrome virus (PRRSV) continues to pose a significant threat to the global swine industry, attributed largely to its immunosuppressive properties and the chronic nature of its infection. The absence of effective vaccines and therapeutics amplifies the urgency to deepen our comprehension of PRRSV’s intricate pathogenic mechanisms. Previous transcriptomic studies, although informative, are partially constrained by their predominant reliance on in vitro models or lack of long-term infections. Moreover, the role of circular RNAs (circRNAs) during PRRSV invasion is yet to be elucidated.MethodsIn this study, we employed an in vivo approach, exposing piglets to a PRRSV challenge over varied durations of 3, 7, or 21 days. Subsequently, porcine alveolar macrophages were isolated for a comprehensive transcriptomic investigation, examining the expression patterns of mRNAs, miRNAs, circRNAs, and long non-coding RNAs (lncRNAs).ResultsDifferentially expressed RNAs from all four categories were identified, underscoring the dynamic interplay among these RNA species during PRRSV infection. Functional enrichment analyses indicate that these differentially expressed RNAs, as well as their target genes, play a pivotal role in immune related pathways. For the first time, we integrated circRNAs into the lncRNA-miRNA-mRNA relationship, constructing a competitive endogenous RNA (ceRNA) network. Our findings highlight the immune-related genes, CTLA4 and SAMHD1, as well as their associated miRNAs, lncRNAs, and circRNAs, suggesting potential therapeutic targets for PRRS. Importantly, we corroborated the expression patterns of selected RNAs through RT-qPCR, ensuring consistency with our transcriptomic sequencing data.DiscussionThis study sheds lights on the intricate RNA interplay during PRRSV infection and provides a solid foundation for future therapeutic strategizing