Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

What is Variation?01:14

What is Variation?

18.6K
Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
18.6K
Variation01:19

Variation

8.0K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
8.0K
Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

6.8K
Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...
6.8K
Variation of Atmospheric Pressure01:18

Variation of Atmospheric Pressure

4.2K
Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
Let p(y) be the atmospheric pressure at...
4.2K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.8K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.8K
Diversity of Archaea I01:30

Diversity of Archaea I

663
Archaea, a domain of single-celled microorganisms, are classified into five major phyla based on genetic and biochemical characteristics: Euryarchaeota, Crenarchaeota, Thaumarchaeota, Korarchaeota, and Nanoarchaeota. Among these, the phylum Euryarchaeota is notable for its remarkable diversity in morphology, metabolism, and ecological adaptations.Morphological and Metabolic DiversityMembers of Euryarchaeota exhibit a variety of cellular shapes, including rods and cocci. Their metabolic pathways...
663

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Species-level virome profiling reveals compositional differences in the gut prokaryotic DNA virome of people with HIV-1 on antiretroviral therapy.

Gut microbes reports·2026
Same author

Letter to the editor: When do rare events become expected in HIV drug resistance?

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin·2026
Same author

HIV-1 Sub-subtype A6 Remains Susceptible to Second-Generation Integrase Inhibitors With Limited Emergence of Resistance in Vitro.

Open forum infectious diseases·2026
Same author

Increased in-hospital mortality in immunocompromised individuals hospitalized with COVID-19 during the global pandemic, a multinational cohort study in the EuCARE project.

The Journal of infectious diseases·2026
Same author

HIV-1 viral load and reservoir size remain stable following SARS-CoV-2 mRNA vaccination in people with HIV.

HIV medicine·2026
Same author

Linking gut microbiome to HIV-1 reservoir size in people living with HIV.

Gut pathogens·2026

Related Experiment Video

Updated: Feb 6, 2026

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
11:10

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

12.8K

Structural Implications of Genotypic Variations in HIV-1 Integrase From Diverse Subtypes.

Leonard Rogers1, Adetayo E Obasa2,3, Graeme B Jacobs2

  • 1Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, United States.

Frontiers in Microbiology
|August 18, 2018
PubMed
Summary

Understanding HIV-1 integrase (IN) polymorphisms is key to INSTI effectiveness. Molecular modeling reveals how genetic variations impact drug resistance and IN function, crucial for developing new HIV therapies.

Keywords:
HIV-1 integraseHIV-1 subtypesdrug-resistancepolymorphismstrand transfer inhibitor

More Related Videos

Rapid Screening of HIV Reverse Transcriptase and Integrase Inhibitors
05:46

Rapid Screening of HIV Reverse Transcriptase and Integrase Inhibitors

Published on: April 9, 2014

18.4K
Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach
07:06

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

13.7K

Related Experiment Videos

Last Updated: Feb 6, 2026

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
11:10

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

12.8K
Rapid Screening of HIV Reverse Transcriptase and Integrase Inhibitors
05:46

Rapid Screening of HIV Reverse Transcriptase and Integrase Inhibitors

Published on: April 9, 2014

18.4K
Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach
07:06

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

13.7K

Area of Science:

  • Virology
  • Structural Biology
  • Drug Discovery

Background:

  • Human immunodeficiency virus type 1 (HIV-1) integrase (IN) is essential for viral replication.
  • Integrase strand transfer inhibitors (INSTIs) are a critical class of antiretroviral drugs.
  • Drug resistance mutations in HIV-1 IN can reduce INSTI efficacy.

Purpose of the Study:

  • To investigate the impact of HIV-1 IN polymorphisms on INSTI susceptibility.
  • To understand the molecular mechanisms underlying differential drug resistance patterns across HIV-1 subtypes.
  • To explore how genetic variations affect IN function and drug response.

Main Methods:

  • Utilized molecular modeling techniques.
  • Analyzed a recently reported medium-resolution cryo-electron microscopy (cryo-EM) structure of full-length HIV-1 IN.
  • Explored the structural impact of IN polymorphisms on the IN reaction mechanism and INSTI binding.

Main Results:

  • Identified structural differences in HIV-1 IN associated with drug resistance.
  • Demonstrated how IN polymorphisms can alter the enzyme's reaction mechanism and susceptibility to INSTIs.
  • Provided insights into subtype-specific resistance patterns.

Conclusions:

  • Structural insights from modeling and cryo-EM are vital for understanding INSTI resistance.
  • Genetic variations in HIV-1 IN significantly influence INSTI effectiveness.
  • Further research can guide the development of more effective HIV-1 therapies tailored to diverse patient populations.