Page not found

HIV and HTLV Molecular and Cell Biology


HIV and HTLV Molecular and Cell Biology

These researchers are using MSI resources for two projects.

  • HIV Reverse Transcriptase-Mediated Mutagenesis: HIV-1 has a high mutation rate, which contributes to its ability to evade the host immune system, limits the efficacy of antiretroviral drugs, and drives the emergence of drug resistance. Drug resistance conferring mutations as well as other viral mutations are primarily attributed to the error-prone nature of reverse transcriptase (RT). An intentional increase in RT-mediated mutations decreases virus infectivity by increasing the mutation rate to a level that is not able to maintain survival of the virus population. The potency by which HIV-1 infectivity can be decreased by increasing RT-mediated errors has led to an initiative to discover small molecules that may increase the HIV-1 mutation rate. An interdisciplinary collaborative team has been assembled to conduct discovery studies to identify new small molecules that increase RT-mediated errors, use molecular analyses to identify the mechanism(s) by which small molecules increase the HIV mutation rate and result in virus extinction, and to assess the mechanism of RT-mediated mutation using biochemical methods. Through preliminary studies, the researchers have identified four small molecules that increase RT-mediated mutations. In order to elucidate the structure-activity relationship driving this increase and to optimize this activity, they are first pursuing discovery studies to identify small molecules that can increase RT-mediated errors. The antiviral and mutagenic activities of these molecules will be assessed in cell culture. Second, they will examine the mechanism by which small molecules induce mutations and cause virus extinction in HIV-1 using cell culture methodologies. Here they will examine small molecules that they have already discovered as well as any lead molecules that they identify. Third, they will investigate the mechanism of action using biochemical methods to elucidate the mechanistic basis for increased RT-mediated mutation. Successful completion of these studies will provide deeper insight into the mechanisms of RT-mediated viral mutagenesis and its impact on viral replication and extinction.
  • HTLV-1 Particle Analysis and Gag Interactions: Human T-cell leukemia virus (HTLV-1) infects about 20 million individuals worldwide and is the etiological agent of an adult T-cell leukemia/lymphoma (ATLL). It can also result in an inflammatory disease syndrome called HTLV-1-associated myelopathy (HAM)/tropical spastic paraparesis (TSP). Prevalence rates for HTLV-1 infection in the general population are greater than 1% in the Caribbean Basin, Central Africa, and South Japan. HTLV-1 is notorious for being difficult to study in cell culture, which has prohibited a rigorous analysis of how these viruses replicate in cells, including the steps involved in retrovirus assembly. The details for how retrovirus particle assembly occurs are poorly understood even for other more tractable retroviral systems. Using a tractable model system, state-of-the-art biophysical approaches, and an interdisciplinary research team, these researchers have made novel observations that form the basis for this project. The researchers are beginning to investigate questions related to HTLV-1 particle size, Gag stoichiometry in particles, and HTLV-1 Gag interactions in living cells using multiple experimental approaches. In particular, they will apply cryo-electron microscopy/tomography (cryo-EM/ET), total internal reflection fluorescence (TIRF) microscopy, and the novel single-molecule technology of fluorescence fluctuation spectroscopy (FFS) to investigate questions related to particle size and Gag stoichiometry, Gag targeting to membrane, and HTLV-1 particle biogenesis. The results from these studies should provide further insight into fundamental aspects of HTLV-1 and retrovirus particle assembly, which may aid in developing therapeutics.

Return to this PI's main page.

Group name: 

Wildlife in the Serengeti

Camera traps, which are motion- or heat-activated automatic cameras, are revolutionizing how researchers can study ecosystems, since they are noninvasive, relatively inexpensive, and are capable of monitoring large areas and diverse species. A few years ago, members of the research group of MSI...

Tracking Pollution Sources in Urban Water Systems

Maintaining the health of urban waterways is an ongoing battle. Urban areas, due to their high population densities, have a number of challenges in maintaining clean water. While sewage systems have been managed so that pollutants are largely controlled, the contribution of pollutants from other...

Global Land Model Development


Global Land Model Development: Time to Shift From a Plant Functional Type to a Plant Functional Trait Approach

This project will advance global land models by shifting from the current plant functional type approach to one that better utilizes what is known about the importance and variability of plant traits, within a framework of simultaneously improving fundamental physiological relations that are at the core of model carbon cycling algorithms. A primary goal for earth system modeling is to make accurate predictions of the future trajectory of the climate system, based on a mechanistic understanding of processes regulating fluxes of mass and energy among system components. Land plays an important role in modifying the earth's mass and energy balance, as a critical link in the global cycling of carbon, among others. Land surface models have developed to include mechanistic representations of vegetation physiology, carbon and nutrient dynamics in plants and soils, how they might respond to changing climate and chemistry, and how those changes might feedback to influence changes in atmospheric greenhouse gases themselves. This project addresses these processes.

Existing models represent the global distribution of vegetation types using the Plant Functional Type concept. Plant Functional Types are classes of plant species with similar evolutionary and life history with presumably similar responses to environmental conditions like CO2, water and nutrient availability. Fixed properties for each Plant Functional Type are specified through a collection of physiological parameters, or traits. These traits, mostly physiological in nature (e.g., leaf nitrogen and longevity) are used in model algorithms to estimate ecosystem properties and/or drive calculated process rates. In most models, 5 to 15 functional types represent terrestrial vegetation; in essence, they assume there are a total of only 5 to 15 different kinds of plants on the entire globe. This assumption of constant plant traits captured within the functional type concept has serious limitations, as a single set of traits does not reflect trait variation observed within and between species and communities. While this simplification was necessary decades past, substantial improvement is now possible. Rather than assigning a small number of constant parameter values to all grid cells in a model, procedures will be developed that predict a frequency distribution of values for any given grid cell. Thus, the mean and variance, and how these change with time, will inform and improve model performance.

The trait-based approach will improve land modeling by: incorporating patterns and heterogeneity of traits into model parameterization, thus evolving away from a framework that considers large areas of vegetation to have near identical trait values; utilizing what is know about trait-trait, -soil, and -climate relations to improve algorithms used to predict processes at multiple stages; and allowing for improved treatment of physiological responses to environment (such as temperature and/or CO2 response of photosynthesis or respiration).

Return to this PI’s main page.

Group name: 

Data Retention and Protection

The following policies pertain to specific systems managed by MSI. The specific elements of this policy and MSI's data policies in general are consistent with the University policy on data management and are therefore applicable to the transfer and storage of data on MSI resources. */ Data...

A New Metal-Organic Framework for Catalysis

Chemists are often interested in developing new catalysts that will improve the efficiency of chemical reactions. They can look to nature to provide examples when designing these new materials. Metalloporphyrins are a class of metal complexes that appear a great deal in biological systems. These...


The GenomeTools genome analysis system is a free collection of bioinformatics tools (in the realm of genome informatics) combined into a single binary. It is based on a C library named “libgenometools” which consists of several modules.


From the software web site : Although there are a large number of programs in this package, they belong to three groups: (1) Traditional similarity searching programs: fasta36 , fastx36 , fasty36 , tfastx36 , tfasty36 , ssearch36 , ggsearch36 , and glsearch36 ; (2) Programs for searching with short fragments: fasts36 , fastf36 , tfasts36 , tfastf36 , and fastm36 ; (3) A program for finding non-overlapping local align- ments: lalign36 . Programs that start with fast search protein databases, while tfast programs search translated DNA databases. Table I gives a brief description of the programs...

Protein-protein and protein-substrate specificity



Protein-Protein and Protein-Substrate Specificity in Two Unique Membrane Bound Proteins

This researcher is working on the characterization of protein-protein and protein-substrate recognition/specificity by sweet taste receptors and organic anion transporting polypeptides (Oatps), respectively. In each case, the protein structures have been constructed by homology modeling for use in structure based hypothesis generation. Of interest for the sweet taste receptor is the extracellular hydrophilic domain and its interaction with both small ligands and, more importantly, with the sweet-tasting protein brazzein. Protein-protein docking and molecular dynamics are used to understand how brazzein binds and elicits its sweet taste, with interest in surface complimentarity and backbone flexibility. The computational work is being used to drive mutagenesis studies on brazzein. The Oatp project is concerned with small molecule transport selectivity across the cell membrane. Oatps appear to be members of the large Major Facilitator Superfamily (MFS) of transporters which this researcher has used for modeling. This project uses small molecule docking and dynamics, pharmacophore modeling, and 3D-QSAR.


The Oatp project is concerned with small-molecule transport selectivity across the cell membrane. Oatps appear to be members of the large Major Facilitator Superfamily (MFS) of transporters, three of which have known three-dimensional structures. All three structures have been used to generate a homology model of Oatp member 1c1, which is being used to guide mutagenesis studies. In addition, the researcher is using small molecule docking and dynamics, pharmacophore modeling, and 3D-QSAR to understand and predict substrate selectivity for transport across various tissue types. The MSI tools/software used for these studies include homology modeling, molecular dynamics, sequence analysis, pharmacophore modeling, comparative molecular field analysis (CoMFA), and DFT and semi-empirical small molecule modeling.

Group name: 

Mental Maze Solving: A Study of the Visuospatial Processes in the Human Brain Using Functional Magnetic Resonance Imaging


Mental Maze Solving: A Study of the Visuospatial Processes in the Human Brain Using Functional Magnetic Resonance Imaging

Previous studies have investigated the processes that take place in the nervous system during visuospatial tasks using maze solving as a paradigm. Specifically, psychophysical experiments in humans and primates have shown that mental transversing of the maze path occurs when subjects are required to find the exit of a maze displayed on a computer screen. Neural recordings from the parietal lobes of monkeys have shown that neural activity during this task is related to various features of the maze. A commonly used estimation method, termed the population vector, uses neural activity to predict the direction of the maze that the monkey is tracing.

In this research, functional Magnetic Resonance Imaging (fMRI) is used to record the brain activity of healthy human subjects during maze solving. Preliminary results have shown that this activity correlates with this task, similar to the findings in other primates. The current analysis extends these results by studying the interactions of the activities in volumetric pixels (voxels) recorded in the brain. Specifically, the fMRI signal from each voxel will be prewhitened using an ARIMA model to avoid spurious results. The prewhitened time series will be cross-correlated to discover patterns of significant functional connectivities. The significant connections will then be used to define the edges of a network within the brain, while the voxels will be its vertices. Various measures of this network, such as the degree of each vertex, the centrality, and others will be analyzed in relation to the experimental covariates.

Return to this PI's main page.

Group name: