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186 records · Page 11

Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis

Counterfactual inference is a useful tool for comparing outcomes of interventions on complex systems. It requires us to represent the system in form of a structural causal model, complete with a causal diagram, probabilistic assumptions on exogenous variables, and functional assignments. Specifying such models can be extremely difficult in practice. The process requires substantial domain expertise, and does not scale easily to large systems, multiple systems, or novel system modifications. At the same time, many application domains, such as molecular biology, are rich in structured causal knowledge that is qualitative in nature. This manuscript proposes a general approach for querying a causal knowledge graph with a causal question and converting the qualitative result into a quantitative structural causal model that can learn from data to answer the question. Here, we demonstrate the feasibility, accuracy and versatility of this approach using two case studies in systems biology. The first demonstrates the appropriateness of the underlying assumptions and the accuracy of the results. The second demonstrates the versatility of the approach by querying a knowledge base for the molecular determinants of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced cytokine storm and performing counterfactual inference to predict the causal effect of medical countermeasures for severely ill COVID-19 patients.

60 APPLIED LIFE SCIENCES↗

Transmission history of SARS-CoV-2 in humans and white-tailed deer

The emergence of a novel pathogen in a susceptible population can cause rapid spread of infection. High prevalence of SARS-CoV-2 infection in white-tailed deer ( Odocoileus virginianus ) has been reported in multiple locations, likely resulting from several human-to-deer spillover events followed by deer-to-deer transmission. Knowledge of the risk and direction of SARS-CoV-2 transmission between humans and potential reservoir hosts is essential for effective disease control and prioritisation of interventions. Using genomic data, we reconstruct the transmission history of SARS-CoV-2 in humans and deer, estimate the case finding rate and attempt to infer relative rates of transmission between species. We found no evidence of direct or indirect transmission from deer to human. However, with an estimated case finding rate of only 4.2%, spillback to humans cannot be ruled out. The extensive transmission of SARS-CoV-2 within deer populations and the large number of unsampled cases highlights the need for active surveillance at the human–animal interface.

60 APPLIED LIFE SCIENCES↗

Varroa destructor mites vector and transmit pathogenic honey bee viruses acquired from an artificial diet

The ectoparasitic mite Varroa destructor is one of the most destructive pests of the honey bee (Apis mellifera) and the primary biotic cause of colony collapse in many regions of the world. These mites inflict physical injury on their honey bee hosts from feeding on host hemolymph and fat body cells/cellular components, and serve as the vector for deadly honey bee viruses, including Deformed wing virus (DWV) and the related Varroa destructor virus-1 (VDV-1) (i.e., DWV-like viruses). Studies focused on elucidating the dynamics of Varroa-mediated vectoring and transmission of DWV-like viruses may be confounded by viruses present in ingested host tissues or the mites themselves. Here we describe a system that includes an artificial diet free of insect tissue-derived components for maintaining Varroa mites for in vitro experimentation. Using this system, together with the novel engineered cDNA clone-derived genetically tagged VDV-1 and wild-type DWV, we demonstrated for the first time that Varroa mites provided an artificial diet supplemented with engineered viruses for 36 hours could acquire and transmit sufficient numbers of virus particles to establish an infection in virus-naïve hosts. While the in vitro system described herein provides for only up to five days of mite survival, precluding study of the long-term impacts of viruses on mite health, the system allows for extensive insights into the dynamics of Varroa-mediated vectoring and transmission of honey bee viruses.

59 BASIC BIOLOGICAL SCIENCES↗

Four principles to establish a universal virus taxonomy

A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne (e.g., “arboviruses”), infecting a certain type of host (e.g., “mycoviruses,” “bacteriophages”) or displaying specific pathogenicity (e.g., “human immunodeficiency viruses”), may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent.

59 BASIC BIOLOGICAL SCIENCES↗

Air Dehumidification using Ionic Liquid-Based Fiber Bundle Membrane Contactor

Air dehumidification is essential since excess moisture in the buildings causes discomfort to the occupants, encourages the production of air pathogens such as mold or mildew, and causes corrosion and rotting that degrade building materials. Existing moisture removal processes are mainly focused on condensation and desiccant (liquid or solid) techniques with direct contact between air and desiccant. However, these methods are energy-intensive, or desiccant might be lost or cause corrosion in the process. The main objective of this study is to investigate an ionic liquid-based liquid desiccant absorber based on a membrane fiber bundle. The novel system consists of membrane contactors containing bundles of 10,000 polypropylene fibers. The fiber bundles have 0.3 micron diameter, with ionic liquid flowing inside, and air flowing outside. The fibers provide a high contact area among phases: 1.4 m2 contact surface area in a 0.00015 m3 volume. The ionic liquid as a sorbent stipulates the selectivity for air, prevents the loss of solvent in the operation due to negligible volatility, provides fast diffusion due to low viscosity compared to common ionic liquids, and has high affinity and solubility in water. The dehumidification capacity of the membrane technology was experimentally investigated. The experimental results show that the ionic-liquid based membrane system can effectively remove excess moisture from the air. The novel fiber bundle dehumidification system has a system volume of 0.00798 m3 (7.98 L) and active heat and mass transfer surface area of 8.4 m2. It achieved an average dehumidification of 320 ± 25 W with a volumetric air flowrate of 3.1 m3/min (108 ft3/min).

Turnaoglu, Tugba↗

CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting

With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.

60 APPLIED LIFE SCIENCES↗