Arbovirus Coinfection
Arbovirus Coinfection - Related Videos
05:22
A Multiplex Serological Assay for the Detection of Antibody Responses to Arboviruses
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2025
Multiplex fluorescence immunoassays are becoming a reference for serology testing. Their application, however, is limited by the complexity and time-consuming bead-analyte coupling processes. This report presents a semi-automated, reproducible multiplex microsphere bead coupling protocol that is comparable to the standard method while considerably reducing time to results.
06:02
Arbovirus Infections As Screening Tools for the Identification of Viral Immunomodulators and Host Antiviral Factors
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Cited by 8 •
2018
Here, we present the protocols to identify 1) virus-encoded immunomodulators that promote arbovirus replication and 2) eukaryotic host factors that restrict arbovirus replication. These fluorescence- and luminescence-based methods allow researchers to rapidly obtain quantitative readouts of arbovirus replication in simplistic assays with low signal-to-noise ratios.
09:02
An Experimental Model to Study Tuberculosis-Malaria Coinfection upon Natural Transmission of Mycobacterium tuberculosis and Plasmodium berghei
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Cited by 17 •
2014
Tuberculosis and malaria are two of the most prevalent infections in humans and major causes of morbidity and mortality in impoverished populations in the tropics. We established an experimental model system to study outcome of malaria-tuberculosis coinfection in mice after challenge with both pathogens via their natural route of infection.
10:35
Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus
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Cited by 3 •
2020
The presented protocol can determine the vector competence of Aedes aegypti mosquito populations for a given virus, such as Zika, in a containment setting.
05:45
Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example
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Cited by 15 •
2020
We previously validated a protocol for amplicon-based whole genome Usutu virus (USUV) sequencing on a nanopore sequencing platform. Here, we describe the methods used in more detail and determine the error rate of the nanopore R10 flow cell.
FAQs
When two viruses replicate in shared tissues, they may compete for cellular resources or replication opportunities, potentially changing the amount or distribution of each virus. In contrast, complementation occurs when one virus supplies functions that support another. These interactions can alter infection patterns and transmission potential, making mixed infections more complex than infections caused by either virus alone.
Shared tissues create opportunities for viruses to interact directly or indirectly within the same host or arthropod vector. Replication in these locations can influence which virus becomes more abundant and how efficiently each persists. This tissue-level context helps explain why overlapping infections may produce outcomes that differ from those observed when the viruses occur separately.
A mixed infection can modify host immune responses in ways that affect both viruses. Changes in immune activity may influence viral replication, disease patterns, or the balance between coinfecting strains. Assessing these effects is important because the clinical or epidemiological outcome may not reflect the behavior of either virus in isolation.
Sequencing viral genomes provides genetic information from the viruses present in a mixed infection. Researchers can compare sequence differences and genetic markers to distinguish coinfecting strains rather than treating the sample as a single viral population. This approach supports more accurate identification of mixed infections and clarifies which viral genomes are associated with the observed sample.
Comparing genetic markers across viral genomes can reveal relationships among strains and help trace their origins. In molecular epidemiology, these comparisons connect coinfecting viruses with broader patterns of viral circulation. The resulting information can improve interpretation of transmission patterns and help determine whether genetically distinct viruses entered the same host or vector through overlapping exposure.
Coinfection can complicate the interpretation of surveillance results and diagnostic findings because more than one virus may be present in a sample or population. Genetic analysis helps detect and distinguish the contributing strains, supporting a more accurate account of circulating viruses. Better recognition of mixed infections can strengthen assessments of disease patterns and transmission.
Genomic comparisons can support evaluation of risks related to public health, vector control, and vaccine development. By identifying coinfecting strains and tracing their origins, researchers can interpret transmission more accurately and recognize patterns that might otherwise be missed. These findings provide scientific context for deciding how mixed infections should be monitored and investigated.
Genetics research examines whether interactions among coinfecting viruses influence viral evolution. Sequencing and comparison of genetic markers can reveal relationships among strains and provide evidence for studying how mixed infections relate to changing viral populations. This perspective connects individual coinfection events with broader questions about strain emergence, circulation, and the genetic patterns observed in molecular epidemiology.