The Goldbeter-Koshland switch in the first-order region and its response to dynamic disorder

In their classical work (Proc. Natl. Acad. Sci. USA, 1981, 78:6840-6844), Goldbeter and Koshland mathematically analyzed a reversible covalent modification system which is highly sensitive to the concentration of effectors. Its signal-response curve appears sigmoidal, constituting a biochemical switch. However, the switch behavior only emerges in the "zero-order region", i.e. when the signal molecule concentration is much lower than that of the substrate it modifies. In this work we showed that the switching behavior can also occur under comparable concentrations of signals and substrates, provided that the signal molecules catalyze the modification reaction in cooperation. We also studied the effect of dynamic disorders on the proposed biochemical switch, in which the enzymatic reaction rates, instead of constant, appear as stochastic functions of time. We showed that the system is robust to dynamic disorder at bulk concentration. But if the dynamic disorder is quasi-static, large fluctuations of the switch response behavior may be observed at low concentrations. Such fluctuation is relevant to many biological functions. It can be reduced by either increasing the conformation interconversion rate of the protein, or correlating the enzymatic reaction rates in the network.Comment: 23 pages, 4 figures, accepted by PLOS ON

Screen for Localized Proteins in Caulobacter crescentus

Precise localization of individual proteins is required for processes such as motility, chemotaxis, cell-cycle progression, and cell division in bacteria, but the number of proteins that are localized in bacterial species is not known. A screen based on transposon mutagenesis and fluorescence activated cell sorting was devised to identify large numbers of localized proteins, and employed in Caulobacter crescentus. From a sample of the clones isolated in the screen, eleven proteins with no previously characterized localization in C. crescentus were identified, including six hypothetical proteins. The localized hypothetical proteins included one protein that was localized in a helix-like structure, and two proteins for which the localization changed as a function of the cell cycle, suggesting that complex three-dimensional patterns and cell cycle-dependent localization are likely to be common in bacteria. Other mutants produced localized fusion proteins even though the transposon has inserted near the 5′ end of a gene, demonstrating that short peptides can contain sufficient information to localize bacterial proteins. The screen described here could be used in most bacterial species

From bit to it: How a complex metabolic network transforms information into living matter

Organisms live and die by the amount of information they acquire about their environment. The systems analysis of complex metabolic networks allows us to ask how such information translates into fitness. A metabolic network transforms nutrients into biomass. The better it uses information on available nutrient availability, the faster it will allow a cell to divide. I here use metabolic flux balance analysis to show that the accuracy I (in bits) with which a yeast cell can sense a limiting nutrient's availability relates logarithmically to fitness as indicated by biomass yield and cell division rate. For microbes like yeast, natural selection can resolve fitness differences of genetic variants smaller than 10-6, meaning that cells would need to estimate nutrient concentrations to very high accuracy (greater than 22 bits) to ensure optimal growth. I argue that such accuracies are not achievable in practice. Natural selection may thus face fundamental limitations in maximizing the information processing capacity of cells. The analysis of metabolic networks opens a door to understanding cellular biology from a quantitative, information-theoretic perspective

Stochastic Delay Accelerates Signaling in Gene Networks

The creation of protein from DNA is a dynamic process consisting of numerous reactions, such as transcription, translation and protein folding. Each of these reactions is further comprised of hundreds or thousands of sub-steps that must be completed before a protein is fully mature. Consequently, the time it takes to create a single protein depends on the number of steps in the reaction chain and the nature of each step. One way to account for these reactions in models of gene regulatory networks is to incorporate dynamical delay. However, the stochastic nature of the reactions necessary to produce protein leads to a waiting time that is randomly distributed. Here, we use queueing theory to examine the effects of such distributed delay on the propagation of information through transcriptionally regulated genetic networks. In an analytically tractable model we find that increasing the randomness in protein production delay can increase signaling speed in transcriptional networks. The effect is confirmed in stochastic simulations, and we demonstrate its impact in several common transcriptional motifs. In particular, we show that in feedforward loops signaling time and magnitude are significantly affected by distributed delay. In addition, delay has previously been shown to cause stable oscillations in circuits with negative feedback. We show that the period and the amplitude of the oscillations monotonically decrease as the variability of the delay time increases

Entrepreneurs' exit and paths to retirement : theoretical and empirical considerations

The number of ageing entrepreneurs in micro- and small-sized companies is rapidly increasing in Finland and other European Union countries. Over half a million jobs, in over one hundred thousand companies within the EU, are lost annually due to unsuccessful, predominantly retirement-related transfers of businesses. This challenge coincides with EU Grand Challenges and has been highlighted in the Entrepreneurship 2020 Action Plan (European Commission 2013). It has been estimated that in Finland, some 8000 jobs are lost yearly due to the ageing of entrepreneurs. Therefore, entrepreneur ageing has implications not only for the ageing individual but also for the company and the society at large. As entrepreneurs age it becomes more essential for them to start planning when and how they transition into retirement. While they may experience several exits and subsequent re-entries into working life via buying or starting new companies, exiting ones entrepreneurial career due to old age retirement differs from exits that occur earlier during the career. In this chapter, we provide a short overview of the entrepreneur retirement and exit literature from an age perspective. Furthermore, we present a theoretical conceptualization which combines entrepreneur retirement process with exit theories. This will enable scholars to better understand the retirement process, including decision-making, transitioning, and adjustment to retirement. We also provide empirical evidence using data collected among Finnish entrepreneurs in 2012 and 2015, where we outline the types of exits and assess several factors, including age, in association with exit intentions.fi=vertaisarvioitu|en=peerReviewed

Comparison of quality-of-care measures in U.S. patients with end-stage renal disease secondary to lupus nephritis vs. other causes

BACKGROUND: Patients with end-stage renal disease (ESRD) due to lupus nephritis (LN-ESRD) may be followed by multiple providers (nephrologists and rheumatologists) and have greater opportunities to receive recommended ESRD-related care. We aimed to examine whether LN-ESRD patients have better quality of ESRD care compared to other ESRD patients. METHODS: Among incident patients (7/05–9/11) with ESRD due to LN (n = 6,594) vs. other causes (n = 617,758), identified using a national surveillance cohort (United States Renal Data System), we determined the association between attributed cause of ESRD and quality-of-care measures (pre-ESRD nephrology care, placement on the deceased donor kidney transplant waitlist, and placement of permanent vascular access). Multivariable logistic and Cox proportional hazards models were used to estimate adjusted odds ratios (ORs) and hazard ratios (HRs). RESULTS: LN-ESRD patients were more likely than other ESRD patients to receive pre-ESRD care (71% vs. 66%; OR = 1.68, 95% CI 1.57-1.78) and be placed on the transplant waitlist in the first year (206 vs. 86 per 1000 patient-years; HR = 1.42, 95% CI 1.34–1.52). However, only 24% had a permanent vascular access (fistula or graft) in place at dialysis start (vs. 36%; OR = 0.63, 95% CI 0.59–0.67). CONCLUSIONS: LN-ESRD patients are more likely to receive pre-ESRD care and have better access to transplant, but are less likely to have a permanent vascular access for dialysis, than other ESRD patients. Further studies are warranted to examine barriers to permanent vascular access placement, as well as morbidity and mortality associated with temporary access, in patients with LN-ESRD

Agency, Values, and Well-Being: A Human Development Model

This paper argues that feelings of agency are linked to human well-being through a sequence of adaptive mechanisms that promote human development, once existential conditions become permissive. In the first part, we elaborate on the evolutionary logic of this model and outline why an evolutionary perspective is helpful to understand changes in values that give feelings of agency greater weight in shaping human well-being. In the second part, we test the key links in this model with data from the World Values Surveys using ecological regressions and multi-level models, covering some 80 societies worldwide. Empirically, we demonstrate evidence for the following sequence: (1) in response to widening opportunities of life, people place stronger emphasis on emancipative values, (2) in response to a stronger emphasis on emancipative values, feelings of agency gain greater weight in shaping people’s life satisfaction, (3) in response to a greater impact of agency feelings on life satisfaction, the level of life satisfaction itself rises. Further analyses show that this model is culturally universal because taking into account the strength of a society’s western tradition does not render insignificant these adaptive linkages. Precisely because of its universality, this is indeed a ‘human’ development model in a most general sense

‘Glocal’ Robustness Analysis and Model Discrimination for Circadian Oscillators

To characterize the behavior and robustness of cellular circuits with many unknown parameters is a major challenge for systems biology. Its difficulty rises exponentially with the number of circuit components. We here propose a novel analysis method to meet this challenge. Our method identifies the region of a high-dimensional parameter space where a circuit displays an experimentally observed behavior. It does so via a Monte Carlo approach guided by principal component analysis, in order to allow efficient sampling of this space. This ‘global’ analysis is then supplemented by a ‘local’ analysis, in which circuit robustness is determined for each of the thousands of parameter sets sampled in the global analysis. We apply this method to two prominent, recent models of the cyanobacterial circadian oscillator, an autocatalytic model, and a model centered on consecutive phosphorylation at two sites of the KaiC protein, a key circadian regulator. For these models, we find that the two-sites architecture is much more robust than the autocatalytic one, both globally and locally, based on five different quantifiers of robustness, including robustness to parameter perturbations and to molecular noise. Our ‘glocal’ combination of global and local analyses can also identify key causes of high or low robustness. In doing so, our approach helps to unravel the architectural origin of robust circuit behavior. Complementarily, identifying fragile aspects of system behavior can aid in designing perturbation experiments that may discriminate between competing mechanisms and different parameter sets

A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12

Monoclonal antibodies represent some of the most promising molecular targeted immunotherapies. However, understanding mechanisms by which tumors evade elimination by the immune system of the host presents a significant challenge for developing effective cancer immunotherapies. The interaction of cancer cells with the host is a complex process that is distributed across a variety of time and length scales. The time scales range from the dynamics of protein refolding (i.e., microseconds) to the dynamics of disease progression (i.e., years). The length scales span the farthest reaches of the human body (i.e., meters) down to the range of molecular interactions (i.e., nanometers). Limited ranges of time and length scales are used experimentally to observe and quantify changes in physiology due to cancer. Translating knowledge obtained from the limited scales observed experimentally to predict patient response is an essential prerequisite for the rational design of cancer immunotherapies that improve clinical outcomes. In studying multiscale systems, engineers use systems analysis and design to identify important components in a complex system and to test conceptual understanding of the integrated system behavior using simulation. The objective of this review is to summarize interactions between the tumor and cell-mediated immunity from a multiscale perspective. Interleukin-12 and its role in coordinating antibody-dependent cell-mediated cytotoxicity is used illustrate the different time and length scale that underpin cancer immunoediting. An underlying theme in this review is the potential role that simulation can play in translating knowledge across scales