@article{955, abstract = {Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components.}, author = {Friedlander, Tamar and Prizak, Roshan and Barton, Nicholas H and Tkacik, Gasper}, issn = {20411723}, journal = {Nature Communications}, number = {1}, publisher = {Nature Publishing Group}, title = {{Evolution of new regulatory functions on biophysically realistic fitness landscapes}}, doi = {10.1038/s41467-017-00238-8}, volume = {8}, year = {2017}, } @article{1358, abstract = {Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements.}, author = {Friedlander, Tamar and Prizak, Roshan and Guet, Calin C and Barton, Nicholas H and Tkacik, Gasper}, journal = {Nature Communications}, publisher = {Nature Publishing Group}, title = {{Intrinsic limits to gene regulation by global crosstalk}}, doi = {10.1038/ncomms12307}, volume = {7}, year = {2016}, } @misc{9718, author = {Friedlander, Tamar and Mayo, Avraham E. and Tlusty, Tsvi and Alon, Uri}, publisher = {Public Library of Science}, title = {{Supporting information text}}, doi = {10.1371/journal.pcbi.1004055.s001}, year = {2015}, } @article{1827, abstract = {Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved.}, author = {Friedlander, Tamar and Mayo, Avraham and Tlusty, Tsvi and Alon, Uri}, journal = {PLoS Computational Biology}, number = {3}, publisher = {Public Library of Science}, title = {{Evolution of bow-tie architectures in biology}}, doi = {10.1371/journal.pcbi.1004055}, volume = {11}, year = {2015}, } @misc{9773, author = {Friedlander, Tamar and Mayo, Avraham E. and Tlusty, Tsvi and Alon, Uri}, publisher = {Public Library of Science}, title = {{Evolutionary simulation code}}, doi = {10.1371/journal.pcbi.1004055.s002}, year = {2015}, } @article{1815, abstract = {Many membrane channels and receptors exhibit adaptive, or desensitized, response to a strong sustained input stimulus, often supported by protein activity-dependent inactivation. Adaptive response is thought to be related to various cellular functions such as homeostasis and enlargement of dynamic range by background compensation. Here we study the quantitative relation between adaptive response and background compensation within a modeling framework. We show that any particular type of adaptive response is neither sufficient nor necessary for adaptive enlargement of dynamic range. In particular a precise adaptive response, where system activity is maintained at a constant level at steady state, does not ensure a large dynamic range neither in input signal nor in system output. A general mechanism for input dynamic range enlargement can come about from the activity-dependent modulation of protein responsiveness by multiple biochemical modification, regardless of the type of adaptive response it induces. Therefore hierarchical biochemical processes such as methylation and phosphorylation are natural candidates to induce this property in signaling systems.}, author = {Tamar Friedlander and Brenner, Naama}, journal = {Mathematical Biosciences and Engineering}, number = {2}, pages = {515 -- 526}, publisher = {Arizona State University}, title = {{Adaptive response and enlargement of dynamic range}}, doi = {10.3934/mbe.2011.8.515}, volume = {8}, year = {2011}, } @article{1825, abstract = {Many membrane channels and receptors exhibit adaptive, or desensitized, response to a strong sustained input stimulus. A key mechanism that underlies this response is the slow, activity-dependent removal of responding molecules to a pool which is unavailable to respond immediately to the input. This mechanism is implemented in different ways in various biological systems and has traditionally been studied separately for each. Here we highlight the common aspects of this principle, shared by many biological systems, and suggest a unifying theoretical framework. We study theoretically a class of models which describes the general mechanism and allows us to distinguish its universal from system-specific features. We show that under general conditions, regardless of the details of kinetics, molecule availability encodes an averaging over past activity and feeds back multiplicatively on the system output. The kinetics of recovery from unavailability determines the effective memory kernel inside the feedback branch, giving rise to a variety of system-specific forms of adaptive response—precise or input-dependent, exponential or power-law—as special cases of the same model. }, author = {Tamar Friedlander and Brenner, Naama}, journal = {PNAS}, number = {52}, pages = {22558 -- 22563}, publisher = {National Academy of Sciences}, title = {{Adaptive response by state-dependent inactivation}}, doi = {10.1073/pnas.0902146106 }, volume = {106}, year = {2009}, } @article{1826, abstract = {Proliferating cell populations at steady-state growth often exhibit broad protein distributions with exponential tails. The sources of this variation and its universality are of much theoretical interest. Here we address the problem by asymptotic analysis of the population balance equation. We show that the steady-state distribution tail is determined by a combination of protein production and cell division and is insensitive to other model details. Under general conditions this tail is exponential with a dependence on parameters consistent with experiment. We discuss the conditions for this effect to be dominant over other sources of variation and the relation to experiments.}, author = {Tamar Friedlander and Brenner, Naama}, journal = {Physical Review Letters}, number = {1}, publisher = {American Physical Society}, title = {{Cellular properties and population asymptotics in the population balance equation}}, doi = {10.1103/PhysRevLett.101.018104}, volume = {101}, year = {2008}, }