Lymphocyte kinetics: the interpretation of labelling data

Lymphocyte radiosensitivity: An extension to the linear-quadratic model?

BACKGROUND AND PURPOSE

The linear-quadratic (LQ) model has been pivotal for evaluating the effects of radiation on cells, but it is primarily characterized by linear responses, which has exhibited limitations when applied to lymphocyte data. The present research aims to address these limitations and to explore an alternative model extended from the conventional LQ model.

MATERIALS AND METHODS

Literature providing lymphocyte counts from assays investigating apoptosis and survival after in vitro irradiation was selected. To address the nonlinearity in lymphocyte responses to radiation, we developed a saturation model characterized by a negative exponential relationship between radiation dose and cellular response. We compared the performance of this saturation model against that of conventional models, including the LQ model and its variants (linear model LM and linear-quadratic-cubic model LQC), as well as the repair-misrepair (RMR) model. The models were evaluated based on prediction-residual plots, residual standard errors, and the Akaike information criterion (AIC). We applied the saturation model to two additional datasets: (1) a dataset from the existing literature that assessed stimulated and unstimulated human lymphocytes exposed to gamma irradiation in vitro and (2) a novel dataset involving T lymphocytes from rodent spleens after exposure to various radiation types (X-rays and protons).

RESULTS

The literature (n = 15 out of 2342) showed that lymphocyte apoptosis varies with dose, time and experimental conditions. The saturation model had a lower AIC of 718 compared to the LM, LQ, LQC and RMR models (AIC of 728, 720, 720 and 734, respectively). The saturation model had a lower residual error and more consistent error distribution. Integrating time as a covariate, the saturation model also had a better AIC for demonstrating time-dependent variations in lymphocyte responses after irradiation. For datasets involving unstimulated lymphocytes before irradiation, the saturation model provided a more accurate fit than did the LM, LQ, and RMR models. In these cases, the fit of the saturation model was comparable to that of the LQC model but offered an advantage when extrapolating to higher doses, where the LQC model might underestimate survival. For stimulated lymphocytes, which are radioresistant, all the models approximated the LM. Both the LQ and saturation models indicated greater radiosensitivity to protons in vitro.

CONCLUSION

The new "saturation model" performed better than the LQ model in quantifying lymphocyte apoptosis and survival, estimating time dependency and assessing the role of radiation modalities or lymphocyte stimulation. Further experiments are warranted to experimentally explore the validity of the saturation model as a promising alternative in the clinical setting.

Differentiation marker-negative CD4+ T cells persist after yellow fever virus vaccination and contribute to durable memory

Factors that contribute to durable immunological memory remain incompletely understood. In our longitudinal analyses of CD4+ T cell responses to the yellow fever virus (YFV) vaccine by peptide-MHC tetramers, we unexpectedly found naïve phenotype virus-specific CD4+ T cells that persisted months to years after immunization. These Marker negative T cells (TMN) lacked CD95, CXCR3, CD11a, and CD49d surface protein expression, distinguishing them from previously discovered stem-cell memory T cells. Functionally, they resembled genuine naïve T cells upon in vitro stimulation. Single-cell TCR sequencing detected expanded clonotypes within the TMN subset and identified a shared repertoire with memory and effector T cells. T cells expressing TMN-associated TCRs were rare before vaccination, suggesting their expansion following vaccination. Longitudinal tracking of YFV-specific responses over the subsequent years revealed superior stability of the TMN subset and their association with the longevity of the overall population. The identification of these long-lived, antigen-experienced T cells may inform the design of durable T cell-based vaccines and engineered T cell therapies.

Modeling T Cell Fate

Many of the pathways that underlie the diversification of naive T cells into effector and memory subsets, and the maintenance of these populations, remain controversial. In recent years a variety of experimental tools have been developed that allow us to follow the fates of cells and their descendants. In this review we describe how mathematical models provide a natural language for describing the growth, loss, and differentiation of cell populations. By encoding mechanistic descriptions of cell behavior, models can help us interpret these new datasets and reveal the rules underpinning T cell fate decisions, both at steady state and during immune responses.

The journey of neutropoiesis: how complex landscapes in bone marrow guide continuous neutrophil lineage determination

Neutrophils are the most abundant white blood cell, and they differentiate in homeostasis in the bone marrow from hematopoietic stem cells (HSCs) via multiple intermediate progenitor cells into mature cells that enter the circulation. Recent findings support a continuous model of differentiation in the bone marrow of heterogeneous HSCs and progenitor populations. Cell fate decisions at the levels of proliferation and differentiation are enforced through expression of lineage-determining transcription factors and their interactions, which are influenced by intrinsic (intracellular) and extrinsic (extracellular) mechanisms. Neutrophil homeostasis is subjected to positive-feedback loops, stemming from the gut microbiome, as well as negative-feedback loops resulting from the clearance of apoptotic neutrophils by mature macrophages. Finally, the cellular kinetics regarding the replenishing of the mature neutrophil pool is discussed in light of recent contradictory data.

Turnover of Murine Cytomegalovirus-Expanded CD8+ T Cells Is Similar to That of Memory Phenotype T Cells and Independent of the Magnitude of the Response

The potential of memory T cells to provide protection against reinfection is beyond question. Yet, it remains debated whether long-term T cell memory is due to long-lived memory cells. There is ample evidence that blood-derived memory phenotype CD8⁺ T cells maintain themselves through cell division, rather than through longevity of individual cells. It has recently been proposed, however, that there may be heterogeneity in the lifespans of memory T cells, depending on factors such as exposure to cognate Ag. CMV infection induces not only conventional, contracting T cell responses, but also inflationary CD8⁺ T cell responses, which are maintained at unusually high numbers, and are even thought to continue to expand over time. It has been proposed that such inflating T cell responses result from the accumulation of relatively long-lived CMV-specific memory CD8⁺ T cells. Using in vivo deuterium labeling and mathematical modeling, we found that the average production rates and expected lifespans of mouse CMV-specific CD8⁺ T cells are very similar to those of bulk memory-phenotype CD8⁺ T cells. Even CMV-specific inflationary CD8⁺ T cell responses that differ 3-fold in size were found to turn over at similar rates.

Quantification of T-cell dynamics during latent cytomegalovirus infection in humans

Cytomegalovirus (CMV) infection has a major impact on the T-cell pool, which is thought to be associated with ageing of the immune system. The effect on the T-cell pool has been interpreted as an effect of CMV on non-CMV specific T-cells. However, it remains unclear whether the effect of CMV could simply be explained by the presence of large, immunodominant, CMV-specific memory CD8+ T-cell populations. These have been suggested to establish through gradual accumulation of long-lived cells. However, little is known about their maintenance. We investigated the effect of CMV infection on T-cell dynamics in healthy older adults, and aimed to unravel the mechanisms of maintenance of large numbers of CMV-specific CD8+ T-cells. We studied the expression of senescence, proliferation, and apoptosis markers and quantified the in vivo dynamics of CMV-specific and other memory T-cell populations using in vivo deuterium labelling. Increased expression of late-stage differentiation markers by CD8+ T-cells of CMV+ versus CMV- individuals was not solely explained by the presence of large, immunodominant CMV-specific CD8+ T-cell populations. The lifespans of circulating CMV-specific CD8+ T-cells did not differ significantly from those of bulk memory CD8+ T-cells, and the lifespans of bulk memory CD8+ T-cells did not differ significantly between CMV- and CMV+ individuals. Memory CD4+ T-cells of CMV+ individuals showed increased expression of late-stage differentiation markers and decreased Ki-67 expression. Overall, the expression of senescence markers on T-cell populations correlated positively with their expected in vivo lifespan. Together, this work suggests that i) large, immunodominant CMV-specific CD8+ T-cell populations do not explain the phenotypical differences between CMV+ and CMV- individuals, ii) CMV infection hardly affects the dynamics of the T-cell pool, and iii) large numbers of CMV-specific CD8+ T-cells are not due to longer lifespans of these cells.

The Rules of Human T Cell Fate in vivo

The processes governing lymphocyte fate (division, differentiation, and death), are typically assumed to be independent of cell age. This assumption has been challenged by a series of elegant studies which clearly show that, for murine cells in vitro, lymphocyte fate is age-dependent and that younger cells (i.e., cells which have recently divided) are less likely to divide or die. Here we investigate whether the same rules determine human T cell fate in vivo. We combined data from in vivo stable isotope labeling in healthy humans with stochastic, agent-based mathematical modeling. We show firstly that the choice of model paradigm has a large impact on parameter estimates obtained using stable isotope labeling i.e., different models fitted to the same data can yield very different estimates of T cell lifespan. Secondly, we found no evidence in humans in vivo to support the model in which younger T cells are less likely to divide or die. This age-dependent model never provided the best description of isotope labeling; this was true for naïve and memory, CD4⁺ and CD8⁺ T cells. Furthermore, this age-dependent model also failed to predict an independent data set in which the link between division and death was explored using Annexin V and deuterated glucose. In contrast, the age-independent model provided the best description of both naïve and memory T cell dynamics and was also able to predict the independent dataset.

Current estimates of T cell kinetics in humans

Stable isotope labeling is a generally applicable method of quantifying cell dynamics. Its advent has opened up the way for the quantitative study of T cells in humans. However, the literature is confusing as estimates vary by orders of magnitude between studies. In this short review we aim to explain the reasons for the discrepancies in estimates, clarify which estimates have been superseded and why and highlight the current best estimates. We focus on stable isotope labeling of T cell subsets in healthy humans.

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Current best estimates of the proliferation and production of CD4⁺ and CD8⁺ T cell subsets.

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Explanation of why estimates vary between studies and which estimates have been superseded.

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Discussion of the implications of model choice.

Depletion of B cells rejuvenates the peripheral B-cell compartment but is insufficient to restore immune competence in aging

Aging is associated with increasing prevalence and severity of infections caused by a decline in bone marrow (BM) lymphopoiesis and reduced B‐cell repertoire diversity. The current study proposes a strategy to enhance immune responsiveness in aged mice and humans, through rejuvenation of the B lineage upon B‐cell depletion. We used hCD20Tg mice to deplete peripheral B cells in old and young mice, analyzing B‐cell subsets, repertoire and cellular functions in vitro, and immune responsiveness in vivo. Additionally, elderly patients, previously treated with rituximab healthy elderly and young individuals, were vaccinated against hepatitis B (HBV) after undergoing a detailed analysis for B‐cell compartments. B‐cell depletion in old mice resulted in rejuvenated B‐cell population that was derived from de novo synthesis in the bone marrow. The rejuvenated B cells exhibited a "young"‐like repertoire and cellular responsiveness to immune stimuli in vitro. Yet, mice treated with B‐cell depletion did not mount enhanced antibody responses to immunization in vivo, nor did they survive longer than control mice in "dirty" environment. Consistent with these results, peripheral B cells from elderly depleted patients showed a "young"‐like repertoire, population dynamics, and cellular responsiveness to stimulus. Nevertheless, the response rate to HBV vaccination was similar between elderly depleted and nondepleted subjects, although antibody titers were higher in depleted patients. This study proposes a proof of principle to rejuvenate the peripheral B‐cell compartment in aging, through B‐cell depletion. Further studies are warranted in order to apply this approach for enhancing humoral immune responsiveness among the elderly population.

Current best estimates for the average lifespans of mouse and human leukocytes: reviewing two decades of deuterium-labeling experiments

Deuterium is a non-toxic, stable isotope that can safely be administered to humans and mice to study their cellular turnover rates in vivo. It is incorporated into newly synthesized DNA strands during cell division, without interference with the kinetics of cells, and the accumulation and loss of deuterium in the DNA of sorted (sub-)populations of leukocytes can be used to estimate their cellular production rates and lifespans. In the past two decades, this powerful technology has been used to estimate the turnover rates of various types of leukocytes. Although it is the most reliable technique currently available to study leukocyte turnover, there are remarkable differences between the cellular turnover rates estimated by some of these studies. We have recently established that part of this variation is due to (a) difficulties in estimating deuterium availability in some deuterium-labeling studies, and (b) assumptions made by the mathematical models employed to fit the data. Being aware of these two problems, we here aim to approach a consensus on the life expectancies of different types of T cells, B cells, monocytes, and neutrophils in mice and men. We address remaining outstanding problems whenever appropriate and discuss for which immune subpopulations we currently have too little information to draw firm conclusions about their turnover.

On certain two-signal perspectives of lymphocyte activation and inactivation, thymic G-quadruplexes, and the role of aggregation in self/not-self discrimination

Distinctive "two signal" paths in immunology, taken by researchers with different academic backgrounds, seem to have both contained facets of the truth. Having been influenced by education at a medical school where Almroth Wright's early contributions were not forgotten, the author's "path less followed" led to views that began to gain recognition late in the twentieth century when the intimate relationship between innate and acquired immunity became more apparent.

Modeling the immune response to HIV infection

The interplay between immune response and HIV is intensely studied via mathematical modeling, with significant insights but few direct answers. In this short review, we highlight advances and knowledge gaps across different aspects of immunity. In particular, we identify the innate immune response and its role in priming the adaptive response as ripe for modeling. The latter have been the focus of most modeling studies, but we also synthesize key outstanding questions regarding effector mechanisms of cellular immunity and development of broadly neutralizing antibodies. Thus far, most modeling studies aimed to infer general immune mechanisms; we foresee that significant progress will be made next by detailed quantitative fitting of models to data, and prediction of immune responses.

Human TSCM cell dynamics in vivo are compatible with long-lived immunological memory and stemness

Adaptive immunity relies on the generation and maintenance of memory T cells to provide protection against repeated antigen exposure. It has been hypothesised that a self-renewing population of T cells, named stem cell-like memory T (TSCM) cells, are responsible for maintaining memory. However, it is not clear if the dynamics of TSCM cells in vivo are compatible with this hypothesis. To address this issue, we investigated the dynamics of TSCM cells under physiological conditions in humans in vivo using a multidisciplinary approach that combines mathematical modelling, stable isotope labelling, telomere length analysis, and cross-sectional data from vaccine recipients. We show that, unexpectedly, the average longevity of a TSCM clone is very short (half-life < 1 year, degree of self-renewal = 430 days): far too short to constitute a stem cell population. However, we also find that the TSCM population is comprised of at least 2 kinetically distinct subpopulations that turn over at different rates. Whilst one subpopulation is rapidly replaced (half-life = 5 months) and explains the rapid average turnover of the bulk TSCM population, the half-life of the other TSCM subpopulation is approximately 9 years, consistent with the longevity of the recall response. We also show that this latter population exhibited a high degree of self-renewal, with a cell residing without dying or differentiating for 15% of our lifetime. Finally, although small, the population was not subject to excessive stochasticity. We conclude that the majority of TSCM cells are not stem cell-like but that there is a subpopulation of TSCM cells whose dynamics are compatible with their putative role in the maintenance of T cell memory.

Age is not just a number: Naive T cells increase their ability to persist in the circulation over time

The processes regulating peripheral naive T-cell numbers and clonal diversity remain poorly understood. Conceptually, homeostatic mechanisms must fall into the broad categories of neutral (simple random birth–death models), competition (regulation of cell numbers through quorum-sensing, perhaps via limiting shared resources), adaptation (involving cell-intrinsic changes in homeostatic fitness, defined as net growth rate over time), or selection (involving the loss or outgrowth of cell populations deriving from intercellular variation in fitness). There may also be stably maintained heterogeneity within the naive T-cell pool. To distinguish between these mechanisms, we confront very general models of these processes with an array of experimental data, both new and published. While reduced competition for homeostatic stimuli may impact cell survival or proliferation in neonates or under moderate to severe lymphopenia, we show that the only mechanism capable of explaining multiple, independent experimental studies of naive CD4⁺ and CD8⁺ T-cell homeostasis in mice from young adulthood into old age is one of adaptation, in which cells act independently and accrue a survival or proliferative advantage continuously with their post-thymic age. However, aged naive T cells may also be functionally impaired, and so the accumulation of older cells via ‘conditioning through experience’ may contribute to reduced immune responsiveness in the elderly.

The body maintains large populations of naive T cells, a type of white blood cell that is able to respond specifically to pathogens. This arsenal is essential for our capacity to fight novel infections throughout our lifespan, and their numbers remain quite stable despite a gradual decline in the production of new naive T cells as we age. However, the mechanisms that underlie this stability are not well understood. In this study, we address this problem by testing a variety of potential mechanisms, each framed as a mathematical model, against multiple datasets obtained from experiments performed in mice. Our analysis supports a mechanism by which naïve T cells gradually increase their ability to survive the longer they reside in the circulation. Paradoxically, however, naïve T cells may also lose their ability to respond effectively to infections as they age. Together, these processes may drive the accumulation of older, functionally impaired T cells, potentially at the expense of younger and more immunologically potent cells, as we age.

Analysing Temporal Dynamics of T Cell Division in vivo Using Ki67 and BrdU Co-labelling by Flow Cytometry

This protocol was developed to increase the richness of information available from in vivo T cell proliferation studies. DNA labelling techniques such as BrdU incorporation allow precise control of label administration and withdrawal, so that the division history of a population can be tracked in detail over long timeframes (days-weeks). Ki67 is expressed in the nucleus of dividing cells, and is retained for a short time (3-4 days) after division ( Gossel et al., 2017 ); therefore acting as a molecular clock to identify cells that have recently divided. Combining these two techniques allows the integration of current and historical proliferation information from individual cells within a population. This data can subsequently be used to probe population dynamics by fitting mathematical models of proliferation ( Gossel et al., 2017 ).

Dynamics of Recent Thymic Emigrants in Young Adult Mice

The peripheral naive T-cell pool is generally thought to consist of a subpopulation of recent thymic emigrants (RTEs) and a subpopulation of mature naive (MN) T cells with different dynamics. Thymus transplantation and adoptive transfer studies in mice have provided contradicting results, with some studies suggesting that RTEs are relatively short-lived cells, while another study suggested that RTEs have a survival advantage. We here estimate the death rates of RTE and MN T cells by performing both thymus transplantations and deuterium labeling experiments in mice of at least 12 weeks old, an age at which the size of the T-cell pool has stabilized. For CD4⁺ T cells, we found the total loss rate from the RTE compartment (by death and maturation) to be fourfold faster than that of MN T cells. We estimate the death rate of CD4⁺ RTE to be 0.046 per day, which is threefold faster than the total loss rate from the MN T-cell compartment. For CD8⁺ T cells, we found no evidence for kinetic differences between RTE and MN T cells. Thus, our data support the notion that in young adult mice, CD4⁺ RTE are relatively short-lived cells within the naive CD4⁺ T-cell pool.

Leukemia-cell proliferation and disease progression in patients with early stage chronic lymphocytic leukemia

The clinical course of patients with recently diagnosed early stage chronic lymphocytic leukemia (CLL) is highly variable. We examined the relationship between CLL-cell birth rate and treatment-free survival (TFS) in 97 patients with recently diagnosed, Rai stage 0-II CLL in a blinded, prospective study, using in vivo 2H2O labeling. Birth rates ranged from 0.07 to 1.31% new cells per day. With median follow-up of 4.0 years, 33 subjects (34%) required treatment by NCI criteria. High-birth rate was observed in 44% of subjects and was significantly associated with shorter TFS, unmutated IGHV status and expression of ZAP70 and of CD38. In multivariable modeling considering age, gender, Rai stage, expression of ZAP70 or CD38, IGHV mutation status and FISH cytogenetics, only CLL-cell birth rate and IGHV mutation status met criteria for inclusion. Hazard ratios were 3.51 (P=0.002) for high-birth rate and 4.93 (P<0.001) for unmutated IGHV. The association between elevated birth rate and shorter TFS was observed in subjects with either mutated or unmutated IGHVs, and the use of both markers was a better predictor of TFS than either parameter alone. Thus, an increased CLL birth rate in early stage disease is a strong predictor of disease progression and earlier treatment.

Physiologically Based Simulations of Deuterated Glucose for Quantifying Cell Turnover in Humans

In vivo [6,6-²H₂]-glucose labeling is a state-of-the-art technique for quantifying cell proliferation and cell disappearance in humans. However, there are discrepancies between estimates of T cell proliferation reported in short (1-day) versus long (7-day) ²H₂-glucose studies and very-long (9-week) ²H₂O studies. It has been suggested that these discrepancies arise from underestimation of true glucose exposure from intermittent blood sampling in the 1-day study. Label availability in glucose studies is normally approximated by a “square pulse” (Sq pulse). Since the body glucose pool is small and turns over rapidly, the availability of labeled glucose can be subject to large fluctuations and the Sq pulse approximation may be very inaccurate. Here, we model the pharmacokinetics of exogenous labeled glucose using a physiologically based pharmacokinetic (PBPK) model to assess the impact of a more complete description of label availability as a function of time on estimates of CD4+ and CD8+ T cell proliferation and disappearance. The model enabled us to predict the exposure to labeled glucose during the fasting and de-labeling phases, to capture the fluctuations of labeled glucose availability caused by the intake of food or high-glucose beverages, and to recalculate the proliferation and death rates of immune cells. The PBPK model was used to reanalyze experimental data from three previously published studies using different labeling protocols. Although using the PBPK enrichment profile decreased the 1-day proliferation estimates by about 4 and 7% for CD4 and CD8+ T cells, respectively, differences with the 7-day and 9-week studies remained significant. We conclude that the approximations underlying the “square pulse” approach—recently suggested as the most plausible hypothesis—only explain a component of the discrepancy in published T cell proliferation rate estimates.

Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background

Cell proliferation is the common characteristic of all biological systems. The immune system insures the maintenance of body integrity on the basis of a continuous production of diversified T lymphocytes in the thymus. This involves processes of proliferation, differentiation, selection, death and migration of lymphocytes to peripheral tissues, where proliferation also occurs upon antigen recognition. Quantification of cell proliferation dynamics requires specific experimental methods and mathematical modelling. Here, we assess the impact of genetics and aging on the immune system by investigating the dynamics of proliferation of T lymphocytes across their differentiation through thymus and spleen in mice. Our investigation is based on single-cell multicolour flow cytometry analysis revealing the active incorporation of a thymidine analogue during S phase after pulse-chase-pulse experiments in vivo, versus cell DNA content. A generic mathematical model of state transition simulates through Ordinary Differential Equations (ODEs) the evolution of single cell behaviour during various durations of labelling. It allows us to fit our data, to deduce proliferation rates and estimate cell cycle durations in sub-populations. Our model is simple and flexible and is validated with other durations of pulse/chase experiments. Our results reveal that T cell proliferation is highly heterogeneous but with a specific “signature” that depends upon genetic origins, is specific to cell differentiation stages in thymus and spleen and is altered with age. In conclusion, our model allows us to infer proliferation rates and cell cycle phase durations from complex experimental 5-ethynyl-2'-deoxyuridine (EdU) data, revealing T cell proliferation heterogeneity and specific signatures.

We assess the impact of genetics and aging on immune system dynamics by investigating the dynamics of proliferation of T lymphocytes across their differentiation through thymus and spleen in mice. Understanding cell proliferation dynamics requires specific experimental methods and mathematical modelling. Our investigation is based upon single-cell multicolour flow cytometry analysis thereby revealing the active incorporation in DNA of a thymidine analogue during S phase after pulse-chase experiments in vivo, versus cell DNA content. A generic mathematical model that simulates the evolution of single cell behaviour during the experiment allows us to fit our data, to deduce proliferation rates and mean cell cycle phase durations in sub-populations. This reveals that T cell proliferation is constrained by genetic influences, declines with age, and is specific to cell differentiation stage, revealing a specific “signature” of cell proliferation. Our model is simple and flexible and can be used with other pulse/chase experiments.

Memory CD4 T cell subsets are kinetically heterogeneous and replenished from naive T cells at high levels

Characterising the longevity of immunological memory requires establishing the rules underlying the renewal and death of peripheral T cells. However, we lack knowledge of the population structure and how self-renewal and de novo influx contribute to the maintenance of memory compartments. Here, we characterise the kinetics and structure of murine CD4 T cell memory subsets by measuring the rates of influx of new cells and using detailed timecourses of DNA labelling that also distinguish the behaviour of recently divided and quiescent cells. We find that both effector and central memory CD4 T cells comprise subpopulations with highly divergent rates of turnover, and show that inflows of new cells sourced from the naive pool strongly impact estimates of memory cell lifetimes and division rates. We also demonstrate that the maintenance of CD4 T cell memory subsets in healthy mice is unexpectedly and strikingly reliant on this replenishment.

Mathematics in modern immunology

Mathematical and statistical methods enable multidisciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. We collect a representative sample of studies in T-cell biology that illustrate the benefits of modelling–experimental collaborations and that have proven valuable or even groundbreaking. We conclude that it is possible to find excellent examples of synergy between mathematical modelling and experiment in immunology, which have brought significant insight that would not be available without these collaborations, but that much remains to be discovered.

B Cell Development in the Bone Marrow Is Regulated by Homeostatic Feedback Exerted by Mature B Cells

Cellular homeostasis in the B cell compartment is strictly imposed to balance cell production and cell loss. However, it is not clear whether B cell development in the bone marrow is an autonomous process or subjected to regulation by the peripheral B cell compartment. To specifically address this question, we used mice transgenic for human CD20, where effective depletion of B lineage cells is obtained upon administration of mouse anti-human CD20 antibodies, in the absence of any effect on other cell lineages and/or tissues. We followed the kinetics of B cell return to equilibrium by BrdU labeling and flow cytometry and analyzed the resulting data by mathematical modeling. Labeling was much faster in depleted mice. Compared to control mice, B cell-depleted mice exhibited a higher proliferation rate in the pro-/pre-B compartment, and higher cell death and lower differentiation in the immature B cell compartment. We validated the first result by analysis of the expression of Ki67, the nuclear protein expressed in proliferating cells, and the second using Annexin V staining. Collectively, our results suggest that B lymphopoiesis is subjected to homeostatic feedback mechanisms imposed by mature B cells in the peripheral compartment.

Temporal fate mapping reveals age-linked heterogeneity in naive T lymphocytes in mice

Understanding how our T-cell compartments are maintained requires knowledge of their population dynamics, which are typically quantified over days to weeks using the administration of labels incorporated into the DNA of dividing cells. These studies present snapshots of homeostatic dynamics and have suggested that lymphocyte populations are heterogeneous with respect to rates of division and/or death, although resolving the details of such heterogeneity is problematic. Here we present a method of studying the population dynamics of T cells in mice over timescales of months to years that reveals heterogeneity in rates of division and death with respect to the age of the host at the time of thymic export. We use the transplant conditioning drug busulfan to ablate hematopoetic stem cells in young mice but leave the peripheral lymphocyte compartments intact. Following their reconstitution with congenically labeled (donor) bone marrow, we followed the dilution of peripheral host T cells by donor-derived lymphocytes for a year after treatment. Describing these kinetics with mathematical models, we estimate rates of thymic production, division and death of naive CD4 and CD8 T cells. Population-averaged estimates of mean lifetimes are consistent with earlier studies, but we find the strongest support for a model in which both naive T-cell pools contain kinetically distinct subpopulations of older host-derived cells with self-renewing capacity that are resistant to displacement by naive donor lymphocytes. We speculate that these incumbent cells are conditioned or selected for increased fitness through homeostatic expansion into the lymphopenic neonatal environment.

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 ²H₂-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.

Stable isotope labeling is used to quantify the rate at which living cells proliferate and die in humans. It has been central to a number of seminal studies, particularly in viral infections such as HIV-1, and leukemia. However, different labels (deuterated water or deuterated glucose) yield different estimates for the rate of cell proliferation and loss; this hampers our understanding and weakens our confidence in this important technique. We performed in vitro and in vivo experiments as well as a new analysis of existing data to directly compare the two labels. This reveals that a major source of the discrepancy lies in the difficulty of assessing deuterated glucose availability. We reconcile published studies and provide recommendations to avoid this problem in the future.

Modeling T cell responses to antigenic challenge

T cell responses are a crucial part of the adaptive immune system in the fight against infections. This article discusses the use of mathematical models for understanding the dynamics of cytotoxic T lymphocyte (CTL) responses against viral infections. Complementing experimental research, mathematical models have been very useful for exploring new hypotheses, interpreting experimental data, and for defining what needs to be measured to improve understanding. This review will start with minimally parameterized models of CTL responses, which have generated some valuable insights into basic dynamics and correlates of control. Subsequently, more biological complexity is incorporated into this modeling framework, examining different mechanisms of CTL expansion, different effector activities, and the influence of T cell help. Models and results are discussed in the context of data from specific infections.

Protection versus pathology in aviremic and high viral load HIV-2 infection-the pivotal role of immune activation and T-cell kinetics

Background. Many human immunodeficiency virus (HIV)–2-infected individuals remain aviremic and behave as long-term non-progressors but some progress to AIDS. We hypothesized that immune activation and T-cell turnover would be critical determinants of non-progressor/progressor status.

Methods. We studied 37 subjects in The Gambia, West Africa: 10 HIV-negative controls, 10 HIV-2-infected subjects with low viral loads (HIV-2-LV), 7 HIV-2-infected subjects with high viral loads (HIV-2-HV), and 10 with HIV-1 infection. We measured in vivo T-cell turnover using deuterium-glucose labeling, and correlated results with T-cell phenotype (by flow cytometry) and T-cell receptor excision circle (TREC) abundance.

Results. Immune activation (HLA-DR/CD38 coexpression) differed between groups with a significant trend: controls <HIV-2-LV <HIV-1 <HIV-2-HV (P < .01 for all cell types). A similar trend was observed in the pattern of in vivo turnover of memory CD4⁺ and CD8⁺ T-cells and TREC depletion in naive CD4⁺ T-cells, although naive T-cell turnover was relatively unaffected by either infection. T-cell turnover, immune activation, and progressor status were closely associated.

Conclusions. HIV-2 non-progressors have low rates of T-cell turnover (both CD4⁺ and CD8⁺) and minimal immune activation; high viral load HIV-2 progressors had high values, similar to or exceeding those in HIV-1 infection.

Can non-lytic CD8+ T cells drive HIV-1 escape?

The CD8+ T cell effector mechanisms that mediate control of HIV-1 and SIV infections remain poorly understood. Recent work suggests that the mechanism may be primarily non-lytic. This is in apparent conflict with the observation that SIV and HIV-1 variants that escape CD8+ T cell surveillance are frequently selected. Whilst it is clear that a variant that has escaped a lytic response can have a fitness advantage compared to the wild-type, it is less obvious that this holds in the face of non-lytic control where both wild-type and variant infected cells would be affected by soluble factors. In particular, the high motility of T cells in lymphoid tissue would be expected to rapidly destroy local effects making selection of escape variants by non-lytic responses unlikely. The observation of frequent HIV-1 and SIV escape poses a number of questions. Most importantly, is the consistent observation of viral escape proof that HIV-1- and SIV-specific CD8+ T cells lyse infected cells or can this also be the result of non-lytic control? Additionally, the rate at which a variant strain escapes a lytic CD8+ T cell response is related to the strength of the response. Is the same relationship true for a non-lytic response? Finally, the potential anti-viral control mediated by non-lytic mechanisms compared to lytic mechanisms is unknown. These questions cannot be addressed with current experimental techniques nor with the standard mathematical models. Instead we have developed a 3D cellular automaton model of HIV-1 which captures spatial and temporal dynamics. The model reproduces in vivo HIV-1 dynamics at the cellular and population level. Using this model we demonstrate that non-lytic effector mechanisms can select for escape variants but that outgrowth of the variant is slower and less frequent than from a lytic response so that non-lytic responses can potentially offer more durable control.

The interplay between viruses and the immune system cannot always be studied with current experimental techniques or commonly used mathematical models. Consequently, many important questions remain unanswered. The questions we wished to address fall into this category. Recent evidence strongly suggests that CD8+ T cells control SIV, and potentially HIV-1, primarily by secreting anti-viral factors rather than by killing infected cells. However, this does not seem compatible with the common observation that HIV and SIV evolve to escape the immune response. Soluble anti-viral factors, like RANTES which protects uninfected cells from infection, would be expected to inhibit both wild-type and variant virus. Furthermore, the high speed and motility of T cells in lymphoid tissue will increase homogeneity and again decrease the likelihood that an escape variant can have a selective advantage in the face of non-lytic control. We wanted to understand whether viral escape is proof that HIV-1- and SIV-specific CD8+ T cells kill infected cells, determine the factors that facilitate viral escape, and investigate the comparative efficiency of lytic and non-lytic responses in controlling viral infections. Here we develop an elaborate but robust computational framework that captures T cell kinetics and spatial interactions in lymphoid tissue to addresses these important questions.

Mesenchymal stromal cell turnover in the normal adult lung revisited

We have employed a simple and robust noninvasive method of continuous in vivo long-term bromodeoxyuridine (BrdU) labeling to analyze lung mesenchymal stromal cell turnover in adult mice in the steady state. Mathematical modeling of BrdU uptake in flow cytometrically sorted CD45negCD31negSca-1poslung cells following long-term feeding of BrdU to mice in their drinking water reveals that lung mesenchymal stromal cells cycle continuously throughout life. Analysis of BrdU incorporation during long-term feeding and during chasing (delabeling) following replacement of BrdU-water with normal water shows that the CD45negCD31negSca-1poslung mesenchymal stromal cell compartment turns over at a rate of ∼2.26% per day with a time to half-cycled of 44 days, an estimated cell proliferation rate of 0.004/day, and a cell death rate of 0.018/day.

Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches

Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology.

Closing the gap between T-cell life span estimates from stable isotope-labeling studies in mice and humans

Life span estimates can be sensitive to the duration of stable isotope label administration, explaining discrepancies in the literature. Multiexponential models are needed to obtain reliable leukocyte life span estimates.

Evaluation of in vivo T cell kinetics: use of heavy isotope labelling in type 1 diabetes

CD4(+) memory cell development is dependent upon T cell receptor (TCR) signal strength, antigen dose and the cytokine milieu, all of which are altered in type 1 diabetes (T1D). We hypothesized that CD4(+) T cell turnover would be greater in type 1 diabetes subjects compared to controls. In vitro studies of T cell function are unable to evaluate dynamic aspects of immune cell homoeostasis. Therefore, we used deuterium oxide ((2) H(2)O) to assess in vivo turnover of CD4(+) T cell subsets in T1D (n = 10) and control subjects (n = 10). Serial samples of naive, memory and regulatory (T(reg)) CD4(+) T cell subsets were collected and enrichment of deoxyribose was determined by gas chromatography-mass spectrometry (GC-MS). Quantification of T cell turnover was performed using mathematical models to estimate fractional enrichment (f, n = 20), turnover rate (k, n = 20), proliferation (p, n = 10) and disappearance (d*, n = 10). Although turnover of T(regs) was greater than memory and naive cells in both controls and T1D subjects, no differences were seen between T1D and controls in T(reg) or naive kinetics. However, turnover of CD4(+) memory T cells was faster in those with T1D compared to control subjects. Measurement and modelling of incorporated deuterium is useful for evaluating the in vivo kinetics of immune cells in T1D and could be incorporated into studies of the natural history of disease or clinical trials designed to alter the disease course. The enhanced CD4(+) memory T cell turnover in T1D may be important in understanding the pathophysiology and potential treatments of autoimmune diabetes.

Quantifying T lymphocyte turnover

Peripheral T cell populations are maintained by production of naive T cells in the thymus, clonal expansion of activated cells, cellular self-renewal (or homeostatic proliferation), and density dependent cell life spans. A variety of experimental techniques have been employed to quantify the relative contributions of these processes. In modern studies lymphocytes are typically labeled with 5-bromo-2'-deoxyuridine (BrdU), deuterium, or the fluorescent dye carboxy-fluorescein diacetate succinimidyl ester (CFSE), their division history has been studied by monitoring telomere shortening and the dilution of T cell receptor excision circles (TRECs) or the dye CFSE, and clonal expansion has been documented by recording changes in the population densities of antigen specific cells. Proper interpretation of such data in terms of the underlying rates of T cell production, division, and death has proven to be notoriously difficult and involves mathematical modeling. We review the various models that have been developed for each of these techniques, discuss which models seem most appropriate for what type of data, reveal open problems that require better models, and pinpoint how the assumptions underlying a mathematical model may influence the interpretation of data. Elaborating various successful cases where modeling has delivered new insights in T cell population dynamics, this review provides quantitative estimates of several processes involved in the maintenance of naive and memory, CD4(+) and CD8(+) T cell pools in mice and men.

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.

Loss of CD4⁺ T-cells is the cardinal feature of HIV/AIDS, resulting in pathological susceptibility to opportunistic infections. Mechanisms underlying CD4-depletion remain unclear, although the role of chronic immune activation is now well-recognized. Selectivity of the virus for its co-receptor target (either chemokine-receptor CCR5 or CXCR4) is also pivotal. We explored the relationship between these two factors by directly measuring in vivo proliferation rates of CD4⁺ T-cell subpopulations according to their expression of chemokine-receptors and the tropism of circulating virus in clinically-well people with HIV infection, and healthy human controls. We used stable isotope labeling with deuterium-labeled glucose to quantify proliferation and disappearance rate constants of CD4⁺ T-cells sorted by CCR5, CXCR4 and CD45R0/RA expression. We found that CCR5-expression defines a high turnover subpopulation which is therefore likely to be preferentially infected and produce more (CCR5-tropic) virus. CXCR4-tropic viruses induced a similar pattern of proliferation as R5-tropic strains, with no apparent selectivity for viral strains to induce proliferation in their targeted subpopulations. This study is significant in providing directly-measured in vivo human data supporting postulates generated in ex vivo human studies and SIV models suggesting that non-specific factors, such as immune activation, rather than cell-specific cytotoxicity, are dominant drivers for HIV pathogenesis.

Quantitating lymphocyte homeostasis in vivo in humans using stable isotope tracers

Humans have a remarkable ability to maintain relatively constant lymphocyte numbers across many decades, from puberty to old-age, despite a multitude of infectious and other challenges and a dramatic decline in thymic output. This phenomenon, lymphocyte homeostasis, is achieved by matching the production, death, and phenotype transition rates across a network of varied lymphocyte subpopulations. Understanding this process in humans depends on the ability to measure in vivo rates of lymphocyte production and loss. Such investigations have been greatly facilitated by the advent of stable isotope labeling approaches, which use the rate of incorporation of a tracer into cellular DNA as a marker of cell division. Two labeling approaches are commonly employed, one using deuterium-labeled glucose and the other using deuterium-labeled water, also known as heavy water ((2)H(2)O). Here we describe the application of these two labeling techniques for measurement of human in vivo lymphocyte kinetics through the four phases of investigation: labeling, -sampling, analysis, and interpretation.

A mechanistic model for bromodeoxyuridine dilution naturally explains labelling data of self-renewing T cell populations

Bromodeoxyuridine (BrdU) is widely used in immunology to detect cell division, and several mathematical models have been proposed to estimate proliferation and death rates of lymphocytes from BrdU labelling and de-labelling curves. One problem in interpreting BrdU data is explaining the de-labelling curves. Because shortly after label withdrawal, BrdU+ cells are expected to divide into BrdU+ daughter cells, one would expect a flat down-slope. As for many cell types, the fraction of BrdU+ cells decreases during de-labelling, previous mathematical models had to make debatable assumptions to be able to account for the data. We develop a mechanistic model tracking the number of divisions that each cell has undergone in the presence and absence of BrdU, and allow cells to accumulate and dilute their BrdU content. From the same mechanistic model, one can naturally derive expressions for the mean BrdU content (MBC) of all cells, or the MBC of the BrdU+ subset, which is related to the mean fluorescence intensity of BrdU that can be measured in experiments. The model is extended to include subpopulations with different rates of division and death (i.e. kinetic heterogeneity). We fit the extended model to previously published BrdU data from memory T lymphocytes in simian immunodeficiency virus-infected and uninfected macaques, and find that the model describes the data with at least the same quality as previous models. Because the same model predicts a modest decline in the MBC of BrdU+ cells, which is consistent with experimental observations, BrdU dilution seems a natural explanation for the observed down-slopes in self-renewing populations.

Modelling deuterium labelling of lymphocytes with temporal and/or kinetic heterogeneity

To study the kinetics of lymphocytes, models have divided the cell population into subpopulations with different turnover rates. These have been called 'kinetic heterogeneity models' so as to distinguish them from 'temporal heterogeneity models', in which a cell population may have different turnover rates at different times, e.g. when resting versus when activated. We model labelling curves for temporally heterogeneous populations, and predict that they exhibit equal biphasic up- and downslopes. We show when cells divide only once upon activation, these slopes are dominated by the slowest exponent, yielding underestimates of the average turnover rate. When cells undergo more than one division, the labelling curves allow fitting of the two exponential slopes in the temporal heterogeneity model. The same data can also be described with a two-compartment kinetic heterogeneity model. In both instances, the average turnover rate is correctly estimated. Because both models assume a different cell biology but describe the data equally well, the parameters of either model have no simple biological interpretation, as each parameter could reflect a combination of parameters of another biological process. Thus, even if there are sufficient data to reliably estimate all exponentials, one can only accurately estimate an average turnover rate. We illustrate these issues by re-fitting labelling data from healthy and HIV-infected individuals.

Models and methods for analysis of lymphocyte repertoire generation, development, selection and evolution

T and B cell receptor repertoires are diversified by variable region gene rearrangement and selected based on functionality and lack of self-reactivity. Repertoires can also be defined based on phenotype and function rather than receptor specificity - such as the diversity of T helper cell subsets. Natural killer (NK) cell repertoires, in which each cell expresses a randomly chosen subset of its inhibitory receptor genes, and is educated based on self-MHC recognition by yet unknown mechanisms, are also phenotypic repertoires. Studying the generation, development and selection of lymphocyte repertoires, and their functions during immune responses, is essential for understanding the function of the immune system in healthy individuals and in immune deficient, autoimmune or cancer patients. The study of lymphocyte repertoires will enable clinical immunologists to develop better therapeutic monoclonal antibodies, vaccines, transplantation donor-recipient matching protocols, and other immune intervention strategies. The recent development of high-throughput methods for repertoire data collection - from multicolor flow cytometry through single-cell imaging to deep sequencing - presents us now, for the first time, with the ability to analyze and compare large samples of lymphocyte repertoires in health, aging and disease. The exponential growth of these datasets, however, challenges the theoretical immunology community to develop methods for data organization and analysis. Furthermore, the need to test hypotheses regarding immune function, and generate predictions regarding the outcomes of medical interventions, necessitates the development of complex mathematical and computational models, covering processes on multiple scales, from the genetic and molecular to the cellular and system scales.

Measurement of proliferation and disappearance of regulatory T cells in human studies using deuterium-labeled glucose

The in vivo proliferation and disappearance kinetics of lymphocytes may be estimated in humans from rates of deuterium-labeled glucose ((2)H(2)-glucose) incorporation into DNA. This protocol describes its application to regulatory T cells (Treg). Because Treg divide frequently, (2)H(2)-glucose is a suitable precursor, achieving high levels of enrichment over a short period. Being nonradioactive and readily administered, it is appropriate for human studies.There are four phases to the method: labeling, sampling, analysis and modeling. Labeling consists of administration of (2)H(2)-glucose, either intravenously or orally; during this phase, small blood samples are taken to monitor plasma glucose enrichment. Sampling occurs over the ensuing ∼3 weeks; PBMC are collected and sorted according to surface marker expression. Cell separation can be achieved by fluorescence-activated cell sorting (FACS) using CD4, CD45RA and CD25 to define memory Treg (CD4(+)CD25(hi)), or by a combination of magnetic bead separation and FACS. Analysis consists of DNA extraction, hydrolysis, derivatization to the pentafluoro tri-acetate (PFTA) derivative, and quantitation of deuterium content by gas-chromatography mass-spectrometry (GC/MS). The ratio of deuterium enrichment in cellular DNA relative to plasma glucose is used to derive the fraction of new cells in the sorted population, and this is modeled as a function of time to derive proliferation and disappearance kinetics.

Human cytomegalovirus-specific CD8(+) T-cell expansions contain long-lived cells that retain functional capacity in both young and elderly subjects

The immune response to human cytomegalovirus (HCMV) infection is characterized by the accumulation of HCMV-specific CD8(+) T cells, particularly in the elderly; such expansions may impair immune responses to other pathogens. We investigated mechanisms underlying HCMV-specific expansions in 12 young and 21 old healthy subjects (although not all analyses were performed on all subjects). Phenotypically, HCMV-pentamer(+) CD8(+) T cells were characterized by marked Vβ restriction, advanced differentiation (being predominantly CD27(-) CD28(-) ), and variable CD45RO/RA expression. Although more common and larger in older subjects, expansions had similar phenotypic characteristics in the young. In one old subject, repeated studies demonstrated stability in size and Vβ distribution of pentamer(+) populations over 6 years. We tested whether HCMV-specific CD8(+) T-cell expansions arose from accelerated proliferation or extended lifespan by in vivo labelling with deuterated glucose and ex vivo Ki-67 expression. Uptake of deuterated glucose was lower in pentamer(+) cells than in pentamer(-) CD8(+) CD45RO(+) or CD8(+) CD45RA(+) cells in three old subjects, consistent with reduced proliferation and extended lifespan. Similarly Ki-67 labelling showed no evidence for increased proliferation in HCMV-specific CD8(+) expansions in older subjects, although pentamer(-) CD45RA(+) cells from young donors expressed very little Ki-67. We investigated Bcl-2 and CD95 as possible anti-apoptotic mediators, but neither was associated with pentamer-positivity. To investigate whether expansion represents a compensatory response to impaired functionality, we performed two tests of functionality, peptide-stimulated proliferation and CD107 expression; both were intact in pentamer(+) cells. Our data suggest that HCMV-specific CD8(+) expansions in older subjects accumulate by extended lifespan, rather than accelerated proliferation.

Explicit kinetic heterogeneity: mathematical models for interpretation of deuterium labeling 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 most common models, which are based on quite different biological assumptions, actually predict mathematically identical labeling curves with one parameter for the exponential up and down slope, and one parameter defining the maximum labeling level. By extending these previous models, we here propose a novel 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 novel 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.

Understanding of cellular processes is impossible without quantitative estimates of how quickly cells in an organism divide and die. The most widely used approach to measure rates of cell turnover in humans is by labeling dividing cells with deuterium given in the form of deuterated glucose or heavy water. Surprisingly, quantitative estimates of the rates of cell turnover obtained from accumulation and decay of the labeled nucleotides in the cell population varied between different studies. We demonstrate that these differences were not likely to arise because of different mathematical models used in data fitting, since the previously used models have an identical mathematical structure. We extend these previous models to allow for cell populations with different rates of turnover and show how such a new explicit kinetic heterogeneity model can be applied to simulated and experimental data. The new model opens a new way of interpreting data from deuterium labeling experiments and will likely lead to new insights into how infections and/or treatments affect cell turnover in humans.

Measurement of ribosomal RNA turnover in vivo by use of deuterium-labeled glucose

BACKGROUND

Most methods for estimation of rates of RNA production are not applicable in human in vivo clinical studies. We describe here an approach for measuring ribosomal RNA turnover in vivo using [6,6-(2)H(2)]-glucose as a precursor for de novo RNA synthesis. Because this method involves neither radioactivity nor toxic metabolites, it is suitable for human studies.

METHODS

For method development in vitro, a lymphocyte cell line (PM1) was cultured in the presence of [6,6-(2)H(2)]-glucose. RNA was extracted, hydrolyzed enzymatically to ribonucleosides, and derivatized to either the aldonitrile tetra-acetate or the pentafluoro triacetate derivative of the pentose before GC-MS. We identified optimum derivatization and analysis conditions and demonstrated quantitative incorporation of deuterium from glucose into RNA of dividing cells.

RESULTS

Pilot clinical studies demonstrated the applicability of this approach to blood leukocytes and solid tissues. A patient with chronic lymphocytic leukemia received [6,6-(2)H(2)]-glucose (1 g/kg) orally in aliquots administered every 30 min for a period of 10 h. When we analyzed CD3(-) B cells that had been purified by gradient centrifugation and magnetic-bead adhesion, we observed deuterium enrichment, a finding consistent with a ribosomal RNA production rate of about 7%/day, despite the slow division rates observed in concurrent DNA-labeling analysis. Similarly, in 2 patients with malignant infiltration of lymph nodes, administration of [6,6-(2)H(2)]-glucose (by intravenous infusion for 24 h) before excision biopsy allowed estimation of DNA and RNA turnover in lymph node samples.

CONCLUSIONS

Our study results demonstrate the proof-of-principle that deuterium-labeled glucose may be used to analyze RNA turnover, in addition to DNA production/cell proliferation, in clinical samples.

Why does the thymus involute? A selection-based hypothesis

Thymic involution remains a fundamental mystery in immunology. Here we present an argument that this seemingly counterproductive behavior may have evolved to allow for peripheral selection of a T-cell repertoire during young-adult life, optimized for fighting infections and avoiding reaction to self. Age-associated decline in immune function may be viewed as an unfortunate side effect of this selective process. Thus, the key to understanding thymic involution might lie in a more quantitative understanding of T-cell homeostasis in the periphery.

Dynamics of cell proliferation and apoptosis reflect different life strategies in hydrothermal vent and cold seep vestimentiferan tubeworms

Deep-sea vestimentiferan tubeworms, which live in symbiosis with bacteria, exhibit different life strategies according to their habitat. At unstable and relatively short-lived hydrothermal vents, they grow extremely fast, whereas their close relatives at stable and long-persisting cold seeps grow slowly and live up to 300 years. Growth and age differences are thought to occur because of ecological and physiological adaptations. However, the underlying mechanisms of cell proliferation and death, which are closely linked to homeostasis, growth, and longevity, are unknown. Here, we show by immunohistochemical and ultrastructural cell cycle analyses that cell proliferation activities of the two species studied are higher than in any other characterized invertebrate, being only comparable with tumor and wound-healing processes. The slow growth in Lamellibrachia luymesi from cold seeps results from balanced activities of proliferation and apoptosis in the epidermis. In contrast, Riftia pachyptila from hydrothermal vents grows fast because apoptosis is down-regulated in this tissue. The symbiont-housing organ, the trophosome, exhibits a complex cell cycle and terminal differentiation pattern in both species, and growth is regulated by proliferation. These mechanisms have similarities to the up- and down-regulation of proliferation or apoptosis in various types of tumor, although they occur in healthy animals in this study, thus providing significant insights into the underlying mechanisms of growth and longevity.

Lymphocyte kinetics in health and disease

Quantitative understanding of immunology requires the development of experimental and mathematical techniques for estimation of rates of division and death of lymphocytes under different conditions. Here, we review the advantages and limitations of several labelling methods that are currently used to quantify turnover of lymphocytes in vivo. In addition to highlighting insights into lymphocyte kinetics which have recently been gained thanks to the development of novel techniques, we discuss important directions for future experimental and theoretical work in the field of lymphocyte turnover.

Modelling naive T-cell homeostasis: consequences of heritable cellular lifespan during ageing

Within an individual, the population of mature naive T cells is maintained throughout life by both input from the thymus and homeostatic proliferation in the periphery. Here, we develop a mathematical model of this process of naive T-cell homeostasis, and use it to explore questions of lifespan, inheritance and receptor repertoire during ageing. By assuming lifespan is largely determined by a heritable trait reset on mitosis, we show that homeostatic proliferation leads naturally to a longer lived population with age. A plausible candidate for the heritable trait influencing lifespan is T-cell receptor affinity for major histocompatibility molecules loaded with self-peptides. Concurrently with increasing lifespan, receptor diversity decreases with age, thus quantitatively linking these two phenomena. These results depend on the thymus involuting with age so that homeostatic proliferation becomes the dominant mode of replacement of the naive T-cell repertoire.

Detection of UVBR-sensitive and -tolerant bacteria in surface waters of the western North Pacific

In order to evaluate the effects of solar ultraviolet radiation (UVR) on eubacterial community composition, we examined the tolerance of eubacterial phylotypes to solar UV radiation in surface waters of the western North Pacific during September 2005. Bromodeoxyuridine (BrdU), a halogenated thymine analogue, was used for labeling newly synthesized DNA in proliferating cells. Thymine dimers (TD), which are specifically formed in DNA by biologically harmful ultraviolet B radiation (UVBR; 280-315nm), were also applied to detect UVB damaged genomes selectively. PCR-denaturing gradient gel electrophoresis (PCR-DGGE) on the labeled samples revealed that UVBR-resistant cells showing active synthesis of DNA without accumulating TD, varied among phylotypes. In addition, UVBR-sensitive band positions with TD indicated inter-specific variations in sensitivity to UVBR. Phylogenetic analysis revealed that 12 DNA sequences were classified into eight phylogenetic groups: three Roseobacter, one Sphingomonas, two Gammaproteobacteria, one Actinobacteria, one Synechococcus, two Prochlorococcus, one plastid and one another group. A UVBR-resistant phylotype was affiliated to Erythrobacter sp. (previously designated as Sphingomonas sp.), which was distributed in warmer waters from the south of Oyashio to Kuroshio regions. A UVBR-sensitive phylotype was affiliated to Pseudoalteromonas sp. in Gammaproteobacteria. Dominant heterotrophic eubacteria were composed of both sensitive and resistant phylotypes. This is the first report on TD accumulated eubacterial phylotypes in oceanic surface waters.

In vivo dynamics of stable chronic lymphocytic leukemia inversely correlate with somatic hypermutation levels and suggest no major leukemic turnover in bone marrow

Although accumulating evidence indicates that chronic lymphocytic leukemia (CLL) is a disease with appreciable cell dynamics, it remains uncertain whether this also applies to patients with stable disease. In this study, (2)H(2)O was administered to a clinically homogeneous cohort of nine stable, untreated CLL patients. CLL dynamics in blood and bone marrow were determined and compared with normal B-cell dynamics in blood from five healthy individuals who underwent a similar (2)H(2)O labeling protocol. Average CLL turnover rates (0.08-0.35% of the clone per day) were approximately 2-fold lower than average B-cell turnover rates from healthy individuals (0.34-0.89%), whereas the rate at which labeled CLL cells in blood disappeared (0.00-0.39% of B cells per day) was approximately 10-fold lower compared with labeled B cells from healthy individuals (1.57-4.24% per day). Leukemic cell turnover variables inversely correlated with the level of somatic hypermutation of the CLL clone (IgVH mutations). Although CLL cells in bone marrow had a higher level of label enrichment than CLL cells in blood, no difference between proliferation rates and proapoptotic and antiapoptotic profiles of CLL cells from these compartments was observed. These data suggest that, in stable disease, there is a biological relationship between the degree of somatic hypermutation of the CLL clone and its dynamics in vivo. Furthermore, in contrast to lymph nodes, the bone marrow does not seem to be a major CLL proliferation site.