Adventures in time and space: Nonlinearity and complexity of cytokine effects on stem cell fate decisions

Cytokines are central factors in the control of stem cell fate decisions and, as such, they are invaluable to those interested in the manipulation of stem and progenitor cells for clinical or research purposes. In their in vivo niches or in optimized cultures, stem cells are exposed to multiple cytokines, matrix proteins and other cell types that provide individual and combinatorial signals that influence their self‐renewal, proliferation and differentiation. Although the individual effects of cytokines are well‐characterized in terms of increases or decreases in stem cell expansion or in the production of specific cell lineages, their interactions are often overlooked. Factorial design experiments in association with multiple linear regression is a powerful multivariate approach to derive response‐surface models and to obtain a quantitative understanding of cytokine dose and interactions effects. On the other hand, cytokine interactions detected in stem cell processes can be difficult to interpret due to the fact that the cell populations examined are often heterogeneous, that cytokines can exhibit pleiotropy and redundancy and that they can also be endogenously produced. This perspective piece presents a list of possible biological mechanisms that can give rise to positive and negative two‐way factor interactions in the context of in vivo and in vitro stem cell‐based processes. These interpretations are based on insights provided by recent studies examining intra‐ and extra‐cellular signaling pathways in adult and embryonic stem cells. Cytokine interactions have been classified according to four main types of molecular and cellular mechanisms: (i) interactions due to co‐signaling; (ii) interactions due to sequential actions; (iii) interactions due to high‐dose saturation and inhibition; and (iv) interactions due to intercellular signaling networks. For each mechanism, possible patterns of regression coefficients corresponding to the cytokine main effects, quadratic effects and two‐way interactions effects are provided. Finally, directions for future mechanistic studies are presented. Biotechnol. Bioeng. 2010;106: 173–182. © 2010 Wiley Periodicals, Inc.     

Entamoeba invadens, encystation process and enolase

The reptilian parasite Entamoeba invadens is accepted as a model for the study of the Entamoeba encystation process. Here we describe the production and characterization of a mAb (B4F2), generated against a component of the E. invadens cyst wall. This mAb specifically recognizes a 48-kDa protein present in cytoplasmic vesicles of cells encysting for 24 h. In mature cysts (96 h), the antigen was detected on the cyst surface. By two-dimensional electrophoresis and mass spectrometry analysis, the B4F2 specific antigen was identified as enolase. Levels of enolase mRNA were increased in encysting cells and the B4F2 mAb was found to inhibit cyst formation. Therefore, these results strongly suggest a new role for enolase in E. invadens encystation, and the B4F2 mAb will be useful tool to study its role in the differentiation process.     

A Monomeric Photoconvertible Fluorescent Protein for Imaging of Dynamic Protein Localization

The use of green-to-red photoconvertible fluorescent proteins (FPs) enables researchers to highlight a subcellular population of a fusion protein of interest and to image its dynamics in live cells. In an effort to enrich the arsenal of photoconvertible FPs and to overcome the limitations imposed by the oligomeric structure of natural photoconvertible FPs, we designed and optimized a new monomeric photoconvertible FP. Using monomeric versions of Clavularia sp. cyan FP as template, we employed sequence-alignment-guided design to create a chromophore environment analogous to that shared by known photoconvertible FPs. The designed gene was synthesized and, when expressed in Escherichia coli, found to produce green fluorescent colonies that gradually switched to red after exposure to white light. We subjected this first-generation FP [named mClavGR1 (monomeric Clavularia-derived green-to-red photoconvertible 1)] to a combination of random and targeted mutageneses and screened libraries for efficient photoconversion using a custom-built system for illuminating a 10-cm Petri plate with 405-nm light. Following more than 15 rounds of library creation and screening, we settled on an optimized version, known as mClavGR2, that has eight mutations relative to mClavGR1. Key improvements of mClavGR2 relative to mClavGR1 include a 1.4-fold brighter red species, 1.8-fold higher photoconversion contrast, and dramatically improved chromophore maturation in E. coli. The monomeric status of mClavGR2 has been demonstrated by gel-filtration chromatography and the functional expression of a variety of mClavGR2 chimeras in mammalian cells. Furthermore, we have exploited mClavGR2 to determine the diffusion kinetics of the membrane protein intercellular adhesion molecule 1 both when the membrane is in contact with a T-lymphocyte expressing leukocyte-function-associated antigen 1 and when it is not. These experiments clearly establish that mClavGR2 is well suited for rapid photoconversion of protein subpopulations and subsequent tracking of dynamic changes in localization in living cells.     

Modelling the unpredictability of future biodiversity in ecological networks

We consider the question of how accurately we can hope to predict future biodiversity in a world in which many interacting species are at risk of extinction. Simple models assuming that species’ extinctions occur independently are easily analysed, but do not account for the fact that many species depend on or otherwise interact with each other. In this paper we evaluate the effect of explicitly incorporating ecological dependencies on the predictive ability of models of extinction. In particular, we compare a model in which species’ extinction rates increase because of the extinction of their prey to a model in which the same average rate increase takes place, but in which extinctions occur independently from species to species. One might expect that including this ecological information would make the prediction of future biodiversity more accurate, but instead we find that accounting for food web dependencies reveals greater uncertainty. The expected loss of biodiversity over time is similar between the two models, but the variance in future biodiversity is considerably higher in the model that includes species interactions. This increased uncertainty is because of the non-independence of species—the tendency of two species to respond similarly to the loss of a species on which both depend. We use simulations to show that this increase in variance is robust to many variations of the model, and that its magnitude should be largest in food webs that are highly dependent on a few basal species. Our results should hold whenever ecological dependencies cause most species’ extinction risks to covary positively, and illustrate how more information does not necessarily improve our ability to predict future biodiversity loss.     

Modeling growth and telomere dynamics in Saccharomyces cerevisiae

A general branching process is proposed to model a population of cells of the yeast Saccharomyces cerevisiae following loss of telomerase. Previously published experimental data indicate that a population of telomerase-deficient cells regain exponential growth after a period of slowing due to critical telomere shortening. The explanation for this phenomenon is that some cells engage telomerase-independent pathways to maintain telomeres that allow them to become “survivors.” Our model takes into account random variation in individual cell cycle times, telomere length, finite replicative lifespan of mother cells, and survivorship. We identify and estimate crucial parameters such as the probability of an individual cell becoming a survivor, and compare our model predictions to experimental data.     

Dynamical phase coexistence: A simple solution to the “savanna problem”

We introduce the concept of dynamical phase coexistence to provide a simple solution for a long-standing problem in theoretical ecology, the so-called “savanna problem”. The challenge is to understand why in savanna ecosystems trees and grasses coexist in a robust way with large spatiotemporal variability. We propose a simple model, a variant of the contact process (CP), which includes two key extra features: varying external (environmental/rainfall) conditions and tree age. The system fluctuates locally between a woodland and a grassland phase, corresponding to the active and absorbing phases of the underlying pure contact process. This leads to a highly variable stable phase characterized by patches of the woodland and grassland phases coexisting dynamically. We show that the mean time to tree extinction under this model increases as a power-law of system size and can be of the order of 10,000,000 years in even moderately sized savannas. Finally, we demonstrate that while local interactions among trees may influence tree spatial distribution and the order of the transition between woodland and grassland phases, they do not affect dynamical coexistence. We expect dynamical coexistence to be relevant in other contexts in physics, biology or the social sciences.     

Stochastic competitive exclusion in the maintenance of the naïve T cell repertoire

Recognition of antigens by the adaptive immune system relies on a highly diverse T cell receptor repertoire. The mechanism that maintains this diversity is based on competition for survival stimuli; these stimuli depend upon weak recognition of self-antigens by the T cell antigen receptor. We study the dynamics of diversity maintenance as a stochastic competition process between a pair of T cell clonotypes that are similar in terms of the self-antigens they recognise. We formulate a bivariate continuous-time Markov process for the numbers of T cells belonging to the two clonotypes. We prove that the ultimate fate of both clonotypes is extinction and provide a bound on mean extinction times. We focus on the case where the two clonotypes exhibit negligible competition with other T cell clonotypes in the repertoire, since this case provides an upper bound on the mean extinction times. As the two clonotypes become more similar in terms of the self-antigens they recognise, one clonotype quickly becomes extinct in a process resembling classical competitive exclusion. We study the limiting probability distribution for the bivariate process, conditioned on non-extinction of both clonotypes. Finally, we derive deterministic equations for the number of cells belonging to each clonotype as well as a linear Fokker-Planck equation for the fluctuations about the deterministic stable steady state.     

Heart rate variability changes in business process outsourcing employees working in shifts

Background and Objectives

Irregular and poor quality sleep is common in business process outsourcing (BPO) employees due to continuous shift working. The influence of this on the cardiac autonomic activity was investigated by the spectral analysis of heart rate variability (HRV).

Methods

36 night shift BPO employees (working from 22:00 to 06:00h) and 36 age and sex matched day shift BPO employees (working from 08:00 to 16:00h) were recruited for the study. Five minute electrocardiogram (ECG) was recorded in all the subjects. Heart rate variability was analyzed by fast Fourier transformation using RMS Vagus HRV software. The results were analyzed using Mann Whitney U test, Student t-test, Wilcoxon signed rank test and were expressed as mean ± SD.

Results

Sleepiness was significantly higher among night shift workers as measured by Epworth Sleepiness Scale (p<0.001). Night shift BPO employees were found to have a trend towards lower values of vagal parameters - HF power (ms²), and higher values of sympathovagal parameters like LF Power (ms²) and the LF/HF power (%) suggesting decreased vagal activity and sympathetic over activity, when compared to day shift employees. However, HRV parameters did not vary significantly between the day shift employees and night shift workers baseline values, and also within the night shift group.

Interpretation and Conclusion

Night shift working increased the heart rate and shifted the sympathovagal balance towards sympathetic dominance and decreased vagal parameters of HRV. This is an indicator of unfavorable change in the myocardial system, and thus shows increased risk of cardiovascular disease among the night shift employees.     

森林资源质量状况评价方法及其在川西米亚罗林区的应用

为明确每一森林小班内森林资源的质量状况,以便为林场采取合理的森林经营措施提供科学依据。以森林小班调查内容为基础,借鉴前人的研究成果,结合专家咨询,构建了一套森林资源质量状况的评价指标体系,并提出了简便易行、贴近生产实践的森林资源质量状况评价方法。评价指标体系由森林的自然性、森林生产力的维持能力和森林群落的结构完整性与稳定性3个方面构成,包括林分起源、龄组、林分密度等15个评价指标。采用层次分析法、专家咨询法确定各评价指标的权重值,并引入黄金分割理论,结合专家意见、相关标准规范划分了各评价指标的评价级别及其得分。整个林场森林资源质量状况等级根据森林小班评价结果的加权得出。以川西林业局管辖的301林场和303林场为例进行了评价试用,结果表明:301林场的一级质量小班数比例为45.65%,森林资源质量状况评价得分为0.59,评价级别为二级(一般);303林场的一级质量小班数比例为64.80%,森林资源质量状况评价得分为0.63,评价级别为一级(好)。结合有关研究成果和研究区域的实际情况,认为评价结果能较客观地反映森林资源质量的真实状况,评价方法具有较强的实用性。探讨了本方法在森林资源质量状况评价研究中的优缺点。     

The standard of neutrality: still flapping in the breeze?

Neutrality plays an important role as a null model in evolutionary biology. Recent theoretical advances suggest that neutrality is not a unitary concept, and we identify three distinct forms of neutrality. Eu‐neutrality means that types do not differ in any measurable way and is thus the idealized form of neutrality. However, individuals or species that do differ in important ways can behave neutrally under some circumstances, both broadening and complicating the applicability of the concept of neutrality. Our second two types of neutrality address two quite different forms of context‐dependent neutrality. Circum‐neutrality means that two character states have the same direct effect on fitness but do not evolve neutrally because of differences in their circumstances. Iso‐neutrality means that two types are equivalent in some population or ecological contexts but not in others, producing an isocline. Confounding of these different definitions has created significant confusion about which models are truly neutral, why some models behave neutrally even when there are large differences in reproductive outputs, and what these different views of neutrality mean to practicing biologists. These complications call into question the acceptance of neutral models as null models and suggest that a better approach is to compare the predictions of models that differ in sources of stochasticity and degree of selection.