Explicit kinetic heterogeneity: mechanistic models for interpretation of labeling data of heterogeneous cell populations

Estimation of division and death rates of lymphocytes in different conditions is vital for quantitative understanding of the immune system. Deuterium, in the form of deuterated glucose or heavy water, can be used to measure rates of proliferation and death of lymphocytes in vivo. Inferring these rates from labeling and delabeling curves has been subject to considerable debate with different groups suggesting different mathematical models for that purpose. We show that the three models that are most commonly used are in fact mathematically identical and differ only in their interpretation of the estimated parameters. By extending these previous models, we here propose a more mechanistic approach for the analysis of data from deuterium labeling experiments. We construct a model of "kinetic heterogeneity" in which the total cell population consists of many sub-populations with different rates of cell turnover. In this model, for a given distribution of the rates of turnover, the predicted fraction of labeled DNA accumulated and lost can be calculated. Our model reproduces several previously made experimental observations, such as a negative correlation between the length of the labeling period and the rate at which labeled DNA is lost after label cessation. We demonstrate the reliability of the new explicit kinetic heterogeneity model by applying it to artificially generated datasets, and illustrate its usefulness by fitting experimental data. In contrast to previous models, the explicit kinetic heterogeneity model 1) provides a mechanistic way of interpreting labeling data; 2) allows for a non-exponential loss of labeled cells during delabeling, and 3) can be used to describe data with variable labeling length

Reconciling Estimates of Cell Proliferation from Stable Isotope Labeling Experiments.

Stable isotope labeling is the state of the art technique for in vivo quantification of lymphocyte kinetics in humans. It has been central to a number of seminal studies, particularly in the context of HIV-1 and leukemia. However, there is a significant discrepancy between lymphocyte proliferation rates estimated in different studies. Notably, deuterated (2)H2-glucose (D2-glucose) labeling studies consistently yield higher estimates of proliferation than deuterated water (D2O) labeling studies. This hampers our understanding of immune function and undermines our confidence in this important technique. Whether these differences are caused by fundamental biochemical differences between the two compounds and/or by methodological differences in the studies is unknown. D2-glucose and D2O labeling experiments have never been performed by the same group under the same experimental conditions; consequently a direct comparison of these two techniques has not been possible. We sought to address this problem. We performed both in vitro and murine in vivo labeling experiments using identical protocols with both D2-glucose and D2O. This showed that intrinsic differences between the two compounds do not cause differences in the proliferation rate estimates, but that estimates made using D2-glucose in vivo were susceptible to difficulties in normalization due to highly variable blood glucose enrichment. Analysis of three published human studies made using D2-glucose and D2O confirmed this problem, particularly in the case of short term D2-glucose labeling. Correcting for these inaccuracies in normalization decreased proliferation rate estimates made using D2-glucose and slightly increased estimates made using D2O; thus bringing the estimates from the two methods significantly closer and highlighting the importance of reliable normalization when using this technique

A Policy Maker’s Guide to Designing Payments for Ecosystem Services

Over the past five years, there has been increasing interest around the globe in payment schemes for the provision of ecosystem services, such as water purification, carbon sequestration, flood control, etc. Written for an Asian Development Bank project in China, this report provides a user-friendly guide to designing payments for the provision of ecosystem services. Part I explains the different types of ecosystem services, different ways of assessing their value, and why they are traditionally under-protected by law and policy. This is followed by an analysis of when payments for services are a preferable approach to other policy instruments. Part II explains the design issues underlying payments for services. These include identification of the service as well as potential buyers and sellers, the level of service needed, payment timing, payment type, and risk allocation. Part II contains a detailed analysis of the different types of payment mechanisms, ranging from general subsidy and certification to mitigation and offset payments. Part III explores the challenges to designing a payment scheme. These include the ability to monitor service provision, secure property rights, perverse incentives, supporting institutions, and poverty alleviation

Accelerated in vivo proliferation of memory phenotype CD4+ T-cells in human HIV-1 infection irrespective of viral chemokine co-receptor tropism.

CD4(+) T-cell loss is the hallmark of HIV-1 infection. CD4 counts fall more rapidly in advanced disease when CCR5-tropic viral strains tend to be replaced by X4-tropic viruses. We hypothesized: (i) that the early dominance of CCR5-tropic viruses results from faster turnover rates of CCR5(+) cells, and (ii) that X4-tropic strains exert greater pathogenicity by preferentially increasing turnover rates within the CXCR4(+) compartment. To test these hypotheses we measured in vivo turnover rates of CD4(+) T-cell subpopulations sorted by chemokine receptor expression, using in vivo deuterium-glucose labeling. Deuterium enrichment was modeled to derive in vivo proliferation (p) and disappearance (d*) rates which were related to viral tropism data. 13 healthy controls and 13 treatment-naive HIV-1-infected subjects (CD4 143-569 cells/ul) participated. CCR5-expression defined a CD4(+) subpopulation of predominantly CD45R0(+) memory cells with accelerated in vivo proliferation (p = 2.50 vs 1.60%/d, CCR5(+) vs CCR5(-); healthy controls; P<0.01). Conversely, CXCR4 expression defined CD4(+) T-cells (predominantly CD45RA(+) naive cells) with low turnover rates. The dominant effect of HIV infection was accelerated turnover of CCR5(+)CD45R0(+)CD4(+) memory T-cells (p = 5.16 vs 2.50%/d, HIV vs controls; P<0.05), naïve cells being relatively unaffected. Similar patterns were observed whether the dominant circulating HIV-1 strain was R5-tropic (n = 9) or X4-tropic (n = 4). Although numbers were small, X4-tropic viruses did not appear to specifically drive turnover of CXCR4-expressing cells (p = 0.54 vs 0.72 vs 0.44%/d in control, R5-tropic, and X4-tropic groups respectively). Our data are most consistent with models in which CD4(+) T-cell loss is primarily driven by non-specific immune activation

Recombination rate and selection strength in HIV intra-patient evolution

The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Here, we estimate the rate of recombination and the distribution of selection coefficients from time-resolved sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be r=1.4e-5 recombinations per site and generation. Furthermore, we provide evidence that selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible, as soon as data with higher time resolution and greater sample sizes is available.Comment: to appear in PLoS Computational Biolog

In search of hair damage using metabolomics?

YesHair fibres are extraordinary materials, not least because they are exquisitely formed by each of the 5 million or so hair follicles on our bodies and have functions that cross from physiology to psychology, but also because they have well known resistance to degradation as seen in hair surviving from archaeological and historical samples [1]. Hair fibres on the head grow at around 1cm each month, together totalling approximately 12km of growth per person per year. Each fibre is incredibly strong for its small diameter; with one fibre typically holding 100g and together a well-formed ponytail [allegedly] has the collective strength to support the weight of a small elephant! Hair – and from here I mean scalp hair – is under constant scrutiny by each of us; whether it be style, split ends, the first few grey hairs or the collection of hairs in the shower that should be firmly attached - leading to the fear that is hair loss