Host Killing Index
Host Killing Index - Related Videos
04:29
Assessment of Opsonophagocytic Killing Activity against Bacterial Pathogens
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2025
The video shows an in vitro opsonophagocytic killing assay using a co-culture of human neutrophils with Streptococcus pneumoniae. Antibodies and complement proteins facilitate opsonization of the bacteria, enabling neutrophils to recognize and kill bacteria, showing successful neutrophil opsonophagocytic activity.
03:41
Isolation of Intracellular Pathogenic Bacteria from Infected Host Cells
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2026
Source: Sigal, N., et al. RNA Purification from Intracellularly Grown Listeria monocytogenes in Macrophage Cells. J. Vis. Exp. (2016).This video demonstrates the isolation of internalized pathogenic bacteria from infected bone marrow-derived macrophages (BMDMs). Bacteria are allowed to attach to host cells, and unattached bacteria are washed away. After internalization, an antibiotic is added to eliminate non-internalized bacteria. The host cells are lysed, centrifuged, and the supernatant is...
03:42
In Vitro Evaluation of Bacterial Killing by Neonatal Mouse Splenic Phagocytes
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2026
Source: Seman, B. G., et.al. Neonatal Imaging Model of Gram-Negative Bacterial Sepsis. J. Vis. Exp. (2020)This video demonstrates the isolation of neutrophils and inflammatory monocytes from neonatal mouse spleens and their application in a luminescent bacterial killing assay. It covers mechanical dissociation, red blood cell lysis, magnetic bead–based cell enrichment, bacterial incubation, and antibiotic protection. Timed luminescence readings indicate initial bacterial internalization...
09:49
Antigen Specific In Vivo Killing Assay using CFSE Labeled Target Cells
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Cited by 38 •
2010
Many infections elicit a strong CTL response, but occasionally, the quantity of responding cells does not correlate to control of the pathogen1. One measure of CTL quality is their ability to kill specifically2. CFSE labeling of target cells can be used to investigate this CTL response quality in vivo3,4.
04:15
Extracting Host Cell Lysate from Infected Host Cells Cultured in a Permeable Membrane System
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2025
This video demonstrates a permeable membrane insert system to investigate the impact of bacterial toxins on host cells in a controlled and isolated manner. This approach allows for the selective exposure of the cells to the toxins while maintaining a physical separation that mimics the natural host-pathogen interaction.
FAQs
The measured endpoint determines what the comparison reveals. A survival-based result reflects how many host cells remain viable after exposure, whereas a growth-based result reflects how much the host population expands relative to the untreated control. In either case, a larger reduction indicates stronger performance, but interpretation should remain tied to the specific endpoint used.
Different lethal interactions can produce similar index values even when their mechanisms differ. Productive infection, toxin delivery, or another engineered interaction may each reduce host viability or population expansion. Connecting the measured effect with the agent’s design helps researchers determine whether a strong result reflects the intended mechanism and guides refinement of engineered constructs.
A killing response is meaningful only in relation to the intended host. Comparing responses across relevant host systems can show whether an agent acts selectively or performs broadly. This information helps bioengineers connect construct features with host recognition and effectiveness, while identifying candidates whose activity better matches the desired biological target.
The evaluation requires an exposed host population and an untreated control measured under the corresponding comparison conditions. Researchers then assess host survival or growth in both groups and determine the extent of reduction associated with exposure. This workflow supports direct comparison among engineered constructs, treatments, or strains without treating an untreated baseline as evidence of killing.
Measurements can guide optimization of treatment conditions by showing whether a selected agent produces the desired reduction in host survival or population expansion. Researchers can compare candidate treatments or engineered designs under the conditions being studied, then prioritize combinations that show stronger performance against the intended host and use the results to support further development.
In bioengineering, the metric helps evaluate bacteriophages, antimicrobial systems, and genetically modified agents. Researchers can compare constructs, treatments, or strains, link design features to biological performance, and select candidates for additional study. The resulting comparisons also help clarify efficacy and host specificity, making the index useful for both design evaluation and treatment development.