scholarly journals SweetOrigins: Extracting Evolutionary Information from Glycans

2020 ◽  
Author(s):  
Daniel Bojar ◽  
Rani K. Powers ◽  
Diogo M. Camacho ◽  
James J. Collins
Keyword(s):  
Machine Learning ◽  
Phylogenetic Trees ◽  
Capsular Polysaccharide ◽  
Molecular Mimicry ◽  
Language Model ◽  
Major Influence ◽  
Evolutionary Information ◽  
Biological Processes ◽  
Host Pathogen Interactions ◽  
Host Pathogen

AbstractGlycans, the most diverse biopolymer and crucial for many biological processes, are shaped by evolutionary pressures stemming in particular from host-pathogen interactions. While this positions glycans as being essential for understanding and targeting host-pathogen interactions, their considerable diversity and a lack of methods has hitherto stymied progress in leveraging their predictive potential. Here, we utilize a curated dataset of 12,674 glycans from 1,726 species to develop and apply machine learning methods to extract evolutionary information from glycans. Our deep learning-based language model SweetOrigins provides evolution-informed glycan representations that we utilize to discover and investigate motifs used for molecular mimicry-mediated immune evasion by commensals and pathogens. Novel glycan alignment methods enable us to identify and contextualize virulence-determining motifs in the capsular polysaccharide of Staphylococcus aureus and Acinetobacter baumannii. Further, we show that glycan-based phylogenetic trees contain most of the information present in traditional 16S rRNA-based phylogenies and improve on the differentiation of genetically closely related but phenotypically divergent species, such as Bacillus cereus and Bacillus anthracis. Leveraging the evolutionary information inherent in glycans with machine learning methodology is poised to provide further – critically needed – insights into host-pathogen interactions, sequence-to-function relationships, and the major influence of glycans on phenotypic plasticity.

scholarly journals Trends in mathematical modeling of host–pathogen interactions

2019 ◽  
Vol 77 (3) ◽  
pp. 467-480 ◽  
Author(s):  
Jan Ewald ◽  
Patricia Sieber ◽  
Ravindra Garde ◽  
Stefan N. Lang ◽  
Stefan Schuster ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Spatial Modeling ◽  
Molecular Mimicry ◽  
Spatial Scales ◽  
Host Pathogen Interactions ◽  
Modeling Approaches ◽  
Current Trends ◽  
Host Pathogen ◽  
Temporal And Spatial ◽  
Abstraction Levels

AbstractPathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host–pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.

scholarly journals Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions

2018 ◽  
Vol 82 (2) ◽  
Author(s):  
Hyun Jae Lee ◽  
Athina Georgiadou ◽  
Thomas D. Otto ◽  
Michael Levin ◽  
Lachlan J. Coin ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Lessons Learned ◽  
The Body ◽  
Major Influence ◽  
Rna Expression ◽  
Host Pathogen Interactions ◽  
Host Pathogen ◽  
Analytical Approaches ◽  
Transcriptomic Studies

SUMMARYTranscriptomics, the analysis of genome-wide RNA expression, is a common approach to investigate host and pathogen processes in infectious diseases. Technical and bioinformatic advances have permitted increasingly thorough analyses of the association of RNA expression with fundamental biology, immunity, pathogenesis, diagnosis, and prognosis. Transcriptomic approaches can now be used to realize a previously unattainable goal, the simultaneous study of RNA expression in host and pathogen, in order to better understand their interactions. This exciting prospect is not without challenges, especially as focus moves from interactionsin vitrounder tightly controlled conditions to tissue- and systems-level interactions in animal models and natural and experimental infections in humans. Here we review the contribution of transcriptomic studies to the understanding of malaria, a parasitic disease which has exerted a major influence on human evolution and continues to cause a huge global burden of disease. We consider malaria a paradigm for the transcriptomic assessment of systemic host-pathogen interactions in humans, because much of the direct host-pathogen interaction occurs within the blood, a readily sampled compartment of the body. We illustrate lessons learned from transcriptomic studies of malaria and how these lessons may guide studies of host-pathogen interactions in other infectious diseases. We propose that the potential of transcriptomic studies to improve the understanding of malaria as a disease remains partly untapped because of limitations in study design rather than as a consequence of technological constraints. Further advances will require the integration of transcriptomic data with analytical approaches from other scientific disciplines, including epidemiology and mathematical modeling.

Spatiotemporal Structure of Host-Pathogen Interactions in a Metapopulation

2009 ◽  
Vol 174 (3) ◽  
pp. 308
Author(s):  
Soubeyrand ◽  
Laine ◽  
Hanski ◽  
Penttinen
Keyword(s):  
Host Pathogen Interactions ◽  
Spatiotemporal Structure ◽  
Host Pathogen

scholarly journals A Systems Biology Approach to Identify Essential Epigenetic Regulators for Specific Biological Processes in Plants

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 364
Author(s):  
Rachel M. McCoy ◽  
Russell Julian ◽  
Shoban R. V. Kumar ◽  
Rajeev Ranjan ◽  
Kranthi Varala ◽  
...  
Keyword(s):  
Machine Learning ◽  
Network Inference ◽  
Root Apical Meristem ◽  
Environmental Cues ◽  
Biological Processes ◽  
Learning Network ◽  
Meristem Development ◽  
Epigenetic Regulator ◽  
Gene Regulatory ◽  
Epigenetic Regulators

Upon sensing developmental or environmental cues, epigenetic regulators transform the chromatin landscape of a network of genes to modulate their expression and dictate adequate cellular and organismal responses. Knowledge of the specific biological processes and genomic loci controlled by each epigenetic regulator will greatly advance our understanding of epigenetic regulation in plants. To facilitate hypothesis generation and testing in this domain, we present EpiNet, an extensive gene regulatory network (GRN) featuring epigenetic regulators. EpiNet was enabled by (i) curated knowledge of epigenetic regulators involved in DNA methylation, histone modification, chromatin remodeling, and siRNA pathways; and (ii) a machine-learning network inference approach powered by a wealth of public transcriptome datasets. We applied GENIE3, a machine-learning network inference approach, to mine public Arabidopsis transcriptomes and construct tissue-specific GRNs with both epigenetic regulators and transcription factors as predictors. The resultant GRNs, named EpiNet, can now be intersected with individual transcriptomic studies on biological processes of interest to identify the most influential epigenetic regulators, as well as predicted gene targets of the epigenetic regulators. We demonstrate the validity of this approach using case studies of shoot and root apical meristem development.

scholarly journals Porcine small intestinal organoids as a model to explore ETEC–host interactions in the gut

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Bjarne Vermeire ◽  
Liara M. Gonzalez ◽  
Robert J. J. Jansens ◽  
Eric Cox ◽  
Bert Devriendt
Keyword(s):  
Intestinal Epithelial ◽  
Gut Health ◽  
Functional Responses ◽  
Host Pathogen Interactions ◽  
Epithelial Surface ◽  
Host Interactions ◽  
Intestinal Organoids ◽  
Host Pathogen ◽  
Small Intestinal

AbstractSmall intestinal organoids, or enteroids, represent a valuable model to study host–pathogen interactions at the intestinal epithelial surface. Much research has been done on murine and human enteroids, however only a handful studies evaluated the development of enteroids in other species. Porcine enteroid cultures have been described, but little is known about their functional responses to specific pathogens or their associated virulence factors. Here, we report that porcine enteroids respond in a similar manner as in vivo gut tissues to enterotoxins derived from enterotoxigenic Escherichia coli, an enteric pathogen causing postweaning diarrhoea in piglets. Upon enterotoxin stimulation, these enteroids not only display a dysregulated electrolyte and water balance as shown by their swelling, but also secrete inflammation markers. Porcine enteroids grown as a 2D-monolayer supported the adhesion of an F4+ ETEC strain. Hence, these enteroids closely mimic in vivo intestinal epithelial responses to gut pathogens and are a promising model to study host–pathogen interactions in the pig gut. Insights obtained with this model might accelerate the design of veterinary therapeutics aimed at improving gut health.

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