Co-infections as Modulators of Disease Outcome: Minor Players or Major Players?
Priti Devi1,2, Azka Khan1, Partha Chattopadhyay1,2
1INtegrative GENomics of HOst-PathogEn Laboratory, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.
Abstract:
Human host and pathogen interaction is dynamic in nature and often modulated by co-pathogens with a functional role in delineating the physiological outcome of infection. Co-infection may present either as a pre-existing pathogen which is accentuated by the introduction of a new pathogen or may appear in the form of new infection acquired secondarily due to a compromised immune system. Using diverse examples of co-infecting pathogens such as Human Immunodeficiency Virus, Mycobacterium tuberculosis and Hepatitis C Virus, we have highlighted the role of co-infections in modulating disease severity and clinical outcome. This interaction happens at multiple hierarchies, which are inclusive of stress and immunological responses and together modulate the disease severity. Already published literature provides much evidence in favor of the occurrence of co-infections during SARS-CoV-2 infection, which eventually impacts the Coronavirus disease-19 outcome. The availability of biological models like 3D organoids, mice, cell lines and mathematical models provide us with an opportunity to understand the role and mechanism of specific co-infections. Exploration of multi-omics-based interactions across co-infecting pathogens may provide deeper insights into their role in disease modulation.
Insights
Co-infections dynamically alter disease outcomes by influencing host-pathogen interactions. Understanding these complex interactions is crucial for managing infectious diseases and improving patient prognoses.
Area of Science:
- Infectious Diseases
- Immunology
- Pathogen Interactions
Background:
- Host-pathogen interactions are dynamic and influenced by co-infecting pathogens.
- Co-infections can exacerbate existing infections or arise secondary to immune compromise.
- Examples include Human Immunodeficiency Virus, Mycobacterium tuberculosis, and Hepatitis C Virus.
Purpose of the Study:
- To highlight the role of co-infections in modulating disease severity and clinical outcomes.
- To discuss the impact of co-infections on infections like SARS-CoV-2.
- To emphasize the importance of understanding co-infection mechanisms.
Main Methods:
- Review of existing literature on co-infections.
- Discussion of biological models (3D organoids, mice, cell lines) and mathematical models for studying co-infections.
- Exploration of multi-omics approaches for deeper insights.
Main Results:
- Co-infections modulate disease severity through stress and immunological responses.
- Evidence suggests co-infections impact Coronavirus disease-19 outcomes.
- Interaction occurs at multiple hierarchical levels.
Conclusions:
- Co-infections significantly influence the physiological outcomes of infections.
- Biological and mathematical models are essential for elucidating co-infection mechanisms.
- Multi-omics research offers promising avenues for understanding co-infection dynamics.
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