Mathematical Modeling of Hepatitis C Prevalence Reduction with Antiviral Treatment Scale-Up in Persons Who Inject Drugs in Metropolitan Chicago

Background/Aim

New direct-acting antivirals (DAAs) provide an opportunity to combat hepatitis C virus (HCV) infection in persons who inject drugs (PWID). Here we use a mathematical model to predict the impact of a DAA-treatment scale-up on HCV prevalence among PWID and the estimated cost in metropolitan Chicago.

Methods

To estimate the HCV antibody and HCV-RNA (chronic infection) prevalence among the metropolitan Chicago PWID population, we used empirical data from three large epidemiological studies. Cost of DAAs is assumed $50,000 per person.

Results

Approximately 32,000 PWID reside in metropolitan Chicago with an estimated HCV-RNA prevalence of 47% or 15,040 cases. Approximately 22,000 PWID (69% of the total PWID population) attend harm reduction (HR) programs, such as syringe exchange programs, and have an estimated HCV-RNA prevalence of 30%. There are about 11,000 young PWID (<30 years old) with an estimated HCV-RNA prevalence of 10% (PWID in these two subpopulations overlap). The model suggests that the following treatment scale-up is needed to reduce the baseline HCV-RNA prevalence by one-half over 10 years of treatment [cost per year, min-max in millions]: 35 per 1,000 [$50-$77] in the overall PWID population, 19 per 1,000 [$20-$26] for persons in HR programs, and 5 per 1,000 [$3-$4] for young PWID.

Conclusions

Treatment scale-up could dramatically reduce the prevalence of chronic HCV infection among PWID in Chicago, who are the main reservoir for on-going HCV transmission. Focusing treatment on PWID attending HR programs and/or young PWID could have a significant impact on HCV prevalence in these subpopulations at an attainable cost.     

Apoptotic Platelet Events Are Not Observed in Severe von Willebrand Disease-Type 2B Mutation p.V1316M

Thrombocytopenia and increased platelet clearance observed in von Willebrand disease-type 2B (VWD-2B) may be explained by platelet apoptosis triggered by the constitutive binding of VWF to its receptor, glycoprotein Ib (GPIb). Apoptosis was assessed in platelets from two patients with a severe VWD-2B mutation VWF/p.V1316M and from mice transiently expressing VWF/p.V1316M. We now report that the VWD-2B mutation VWF/p.V1316M which binds spontaneously to its receptor GPIbα does not induce apoptosis. In 2 unrelated patients (P1 and P2) exhibiting different VWF plasma levels (70% and 36%, respectively, compared with normal pooled human plasma given as 100%), inner transmembrane depolarization of mitochondria, characteristic of apoptotic events was undetectable in platelets, whether washed or in whole blood. No or a moderate phosphatidyl serine (PS) exposure as measured by annexin-V staining was observed for P1 and P2, respectively. Expression of pro-apoptotic proteins Bak and Bax, and caspase-3 activity were similar to control platelets. In the VWD-2B mouse model expressing high levels of mVWF/p.V1316M (423%), similar to what is found in inflammatory pathologies, no significant difference was observed between mice expressing mVWF/WT and mVWF/p.V1316M. These results strongly argue against apoptosis as a mechanism for the thrombocytopenia of severe VWD-2B exhibiting the VWF/p.V1316M mutation.     

Not Just an Oil Slick: How the Energetics of Protein-Membrane Interactions Impacts the Function and Organization of Transmembrane Proteins

The membrane environment, its composition, dynamics, and remodeling, have been shown to participate in the function and organization of a wide variety of transmembrane (TM) proteins, making it necessary to study the molecular mechanisms of such proteins in the context of their membrane settings. We review some recent conceptual advances enabling such studies, and corresponding computational models and tools designed to facilitate the concerted experimental and computational investigation of protein-membrane interactions. To connect productively with the high resolution achieved by cognate experimental approaches, the computational methods must offer quantitative data at an atomistically detailed level. We show how such a quantitative method illuminated the mechanistic importance of a structural characteristic of multihelical TM proteins, that is, the likely presence of adjacent polar and hydrophobic residues at the protein-membrane interface. Such adjacency can preclude the complete alleviation of the well-known hydrophobic mismatch between TM proteins and the surrounding membrane, giving rise to an energy cost of residual hydrophobic mismatch. The energy cost and biophysical formulation of hydrophobic mismatch and residual hydrophobic mismatch are reviewed in the context of their mechanistic role in the function of prototypical members of multihelical TM protein families: 1), LeuT, a bacterial homolog of mammalian neurotransmitter sodium symporters; and 2), rhodopsin and the β1- and β2-adrenergic receptors from the G-protein coupled receptor family. The type of computational analysis provided by these examples is poised to translate the rapidly growing structural data for the many TM protein families that are of great importance to cell function into ever more incisive insights into mechanisms driven by protein-ligand and protein-protein interactions in the membrane environment.     

Not Just an Oil Slick: How the Energetics of Protein-Membrane Interactions Impacts the Function and Organization of Transmembrane Proteins

The membrane environment, its composition, dynamics, and remodeling, have been shown to participate in the function and organization of a wide variety of transmembrane (TM) proteins, making it necessary to study the molecular mechanisms of such proteins in the context of their membrane settings. We review some recent conceptual advances enabling such studies, and corresponding computational models and tools designed to facilitate the concerted experimental and computational investigation of protein-membrane interactions. To connect productively with the high resolution achieved by cognate experimental approaches, the computational methods must offer quantitative data at an atomistically detailed level. We show how such a quantitative method illuminated the mechanistic importance of a structural characteristic of multihelical TM proteins, that is, the likely presence of adjacent polar and hydrophobic residues at the protein-membrane interface. Such adjacency can preclude the complete alleviation of the well-known hydrophobic mismatch between TM proteins and the surrounding membrane, giving rise to an energy cost of residual hydrophobic mismatch. The energy cost and biophysical formulation of hydrophobic mismatch and residual hydrophobic mismatch are reviewed in the context of their mechanistic role in the function of prototypical members of multihelical TM protein families: 1), LeuT, a bacterial homolog of mammalian neurotransmitter sodium symporters; and 2), rhodopsin and the β1- and β2-adrenergic receptors from the G-protein coupled receptor family. The type of computational analysis provided by these examples is poised to translate the rapidly growing structural data for the many TM protein families that are of great importance to cell function into ever more incisive insights into mechanisms driven by protein-ligand and protein-protein interactions in the membrane environment.     

Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges

Environmental heterogeneity is considered to be one of the main factors associated with biodiversity given that areas with highly heterogeneous environments can host more species due to their higher number of available niches. In this view, spatial variability extracted from remotely sensed images has been used as a proxy of species diversity, as these data provide an inexpensive means of deriving environmental information for large areas in a consistent and regular manner. The aim of this review is to provide an overview of the state of the art in the use of spectral heterogeneity for estimating species diversity. We will examine a number of issues related to this theme, dealing with: i) the main sensors used for biodiversity monitoring, ii) scale matching problems between remotely sensed and field diversity data, iii) spectral heterogeneity measurement techniques, iv) types of species taxonomic diversity measures and how they influence the relationship between spectral and species diversity, v) spectral versus genetic diversity, and vi) modeling procedures for relating spectral and species diversity. Our review suggests that remotely sensed spectral heterogeneity information provides a crucial baseline for rapid estimation or prediction of biodiversity attributes and hotspots in space and time.     

Conformational rearrangements to the intracellular open states of the LeuT and ApcT transporters are modulated by common mechanisms

Recent crystallographic studies revealed that five transporter families without much sequence similarities among them have similar structure folds to LeuT, a bacterial neurotransmitter:sodium symporter homolog. The LeuT fold is characterized by an internal twofold structural pseudosymmetry. The transport cycle of some members of each of these families is dependent on a sodium gradient across the membrane, whereas in some others the role of sodium is mimicked by proton. We report on the identification of common structure-dynamics elements of the transporters with LeuT fold, which are recognizable in the conformational transitions related to function. The findings from comparative computational modeling and simulation studies of LeuT, and ApcT from the amino acid-polyamine-organocation transporter family define the intramolecular mechanisms by which Na⁺ binding couples to the transport process, and single out the lead/active role of TM1a in the transition to inward-open conformation. These mechanistic insights are derived in the context of collaborative investigations of LeuT dynamics with both single-molecule fluorescence and simulations that have produced excellent agreement of the dynamic details, and are found to be generalizable across the transporter families and to transcend sequence and motif similarities.     

Amino acid starvation sensitizes cancer cells to proteasome inhibition

We explored the crosstalk between protein degradation and synthesis in cancer cells. The tumorigenic cell line, MCF7, showed enhanced proteasome activity compared to the nontumorigenic line, MCF10A. Although there was no difference in the sensitivity of MCF7 and MCF10A cells to proteasome inhibition in complete growth medium, combining proteasome inhibition with amino acid deprivation led to reduced protein synthesis and survival of MCF7 cells, with a lesser effect on MCF10A cells. Additional cancer cell lines (including CAG and A431) could be strongly sensitized to proteasome inhibition by concomitant amino acid deprivation, whereas others were completely resistant to proteasome inhibition. We hypothesize that protein catabolism contributes to the pool of free amino acids available for protein synthesis, leading to a crucial role of the proteasome in cell survival during amino acid depletion, in some tumor cell lines.     

Comparative cross-species alternative splicing in plants

Alternative splicing (AS) can add significantly to genome complexity. Plants are thought to exhibit less AS than animals. An algorithm, based on expressed sequence tag (EST) pairs gapped alignment, was developed that takes advantage of the relatively small intron and exon size in plants and directly compares pairs of ESTs to search for AS. EST pairs gapped alignment was first evaluated in Arabidopsis (Arabidopsis thaliana), rice (Oryza sativa), and tomato (Solanum lycopersicum) for which annotated genome sequence is available and was shown to accurately predict splicing events. The method was then applied to 11 plant species that include 17 cultivars for which enough ESTs are available. The results show a large, 3.7-fold difference in AS rates between plant species with Arabidopsis and rice in the lower range and lettuce (Lactuca sativa) and sorghum (Sorghum bicolor) in the upper range. Hence, compared to higher animals, plants show a much greater degree of variety in their AS rates and in some plant species the rates of animal and plant AS are comparable although the distribution of AS types may differ. In eudicots but not monocots, a correlation between genome size and AS rates was detected, implying that in eudicots the mechanisms that lead to larger genomes are a driving force for the evolution of AS.     

Intracellular cysteine residues in the tail of MHC class I proteins are crucial for extracellular recognition by leukocyte Ig-like receptor 1

The activity of NK cells is regulated by activating receptors that recognize mainly stress-induced ligands and by inhibitory receptors that recognize mostly MHC class I proteins on target cells. Comparing the cytoplasmic tail sequences of various MHC class I proteins revealed the presence of unique cysteine residues in some of the MHC class I molecules which are absent in others. To study the role of these unique cysteines, we performed site specific mutagenesis, generating MHC class I molecules lacking these cysteines, and demonstrated that their expression on the cell surface was impaired. Surprisingly, we demonstrated that these cysteines are crucial for the surface binding of the leukocyte Ig-like receptor 1 inhibitory receptor to the MHC class I proteins, but not for the binding of the KIR2DL1 inhibitory receptor. In addition, we demonstrated that the cysteine residues in the cytoplasmic tail of MHC class I proteins are crucial for their egress from the endoplasmic reticulum and for their palmitoylation, thus probably affecting their expression on the cell surface. Finally, we show that the cysteine residues are important for proper extracellular conformation. Thus, although the interaction between leukocyte Ig-like receptor 1 and MHC class I proteins is formed between two extracellular surfaces, the intracellular components of MHC class I proteins play a crucial role in this recognition.     

On the dynamic nature of the transition state for protein-protein association as determined by double-mutant cycle analysis and simulation

The process of protein-protein association starts with their random collision, which may develop into an encounter complex followed by a transition state and final complex formation. Here we aim to experimentally characterize the nature of the transition state of protein-protein association for three different protein-protein interactions; Barnase-Barstar, TEM1-BLIP and IFNalpha2-IFNAR2, and use the data to model the transition state structures. To model the transition state, we determined inter-protein distance-constraints of the activated complex by using double mutant cycles (DMC) assuming that interacting residues are spatially close. Significant DeltaDeltaG(double dagger)(int) values were obtained only between residues on Barnase and Barstar. However, introducing specific mutations that optimize the charge complementarity between BLIP and TEM1 resulted in the introduction of significant DeltaDeltaG(double dagger)(int) values also between residues of these two proteins. While electrostatic interactions make major contributions towards stabilizing the transition state, we show two examples where steric hindrance exerts an effect on the transition state as well. To model the transition-state structures from the experimental DeltaDeltaG(double dagger)(int) values, we introduced a method for structure perturbation, searching for those inter-protein orientations that best support the experimental DeltaDeltaG(double dagger)(int) values. Two types of transition states were found, specific as observed for Barnase-Barstar and the electrostatically optimized TEM1-BLIP mutants, and diffusive as shown for wild-type TEM1-BLIP and IFNalpha2-IFNAR2. The specific transition states are characterized by defined inter-protein orientations, which cannot be modeled for the diffusive transition states. Mutations introduced through rational design can change the transition state from diffusive to specific. Together, these data provide a structural view of the mechanism allowing rates of association to differ by five orders of magnitude between different protein complexes.