Combinatorial Control through Allostery

Galstyan, Vahe; Funk, Luke; Einav, Tal; Phillips, Rob

doi:10.1021/acs.jpcb.8b12517

Cited by 12 publications

(9 citation statements)

References 38 publications

(98 reference statements)

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“…The outcome of our study is a set of hypothesized regulatory architectures as characterized by a suite of binding sites for RNAP, repressors, and activators, as well as the extremely potent binding energy matrices. We do not assume, a priori, that a particular collection of such binding sites is AND, OR, or any other logic (Galstyan et al, 2019). Figure 6(A) provides a shorthand notation that conveniently characterizes the di erent kinds of regulatory architectures found in bacteria.…”

Section: Elucidating Individual Promotersmentioning

confidence: 99%

Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time

Ireland

Beeler

Flores-Bautista

et al. 2020

eLife

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Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium Escherichia coli, for ≈ 65% of promoters we remain ignorant of their regulation. Until we crack this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method, Reg-Seq, that links massively-parallel reporter assays with mass spectrometry to produce a base pair resolution dissection of more than 100 E. coli promoters in 12 growth conditions. We demonstrate that the method recapitulates known regulatory information. Then, we examine regulatory architectures for more than 80 promoters which previously had no known regulatory information. In many cases, we also identify which transcription factors mediate their regulation. This method clears a path for highly multiplexed investigations of the regulatory genome of model organisms, with the potential of moving to an array of microbes of ecological and medical relevance.

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Section: Elucidating Individual Promotersmentioning

confidence: 99%

Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time

Ireland

Beeler

Flores-Bautista

et al. 2020

eLife

Self Cite

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“…Combinatorial encoding is an alternative mechanism for absolute discrimination, not investigated here, in which the set of signaling components involved encode the ligand identity and enable a specific response (87,88). This mechanism is particularly effective for responding differently to different combinations of extracellular ligands (6,89,90), but can also be used to achieve absolute discrimination in crosstalk signaling systems (61). Reports of functional roles for pSTAT1 homodimers and complexes involving pSTAT3 or pSTAT5 may indicate combinatorial encoding, and future investigation may reveal additional complexities in signal processing for Type I IFNs (39,82,86).…”

Section: Discussionmentioning

confidence: 99%

Determinants of Ligand Specificity and Functional Plasticity in Type I Interferon Signaling

et al. 2021

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The Type I Interferon family of cytokines all act through the same cell surface receptor and induce phosphorylation of the same subset of response regulators of the STAT family. Despite their shared receptor, different Type I Interferons have different functions during immune response to infection. In particular, they differ in the potency of their induced anti-viral and anti-proliferative responses in target cells. It remains not fully understood how these functional differences can arise in a ligand-specific manner both at the level of STAT phosphorylation and the downstream function. We use a minimal computational model of Type I Interferon signaling, focusing on Interferon-α and Interferon-β. We validate the model with quantitative experimental data to identify the key determinants of specificity and functional plasticity in Type I Interferon signaling. We investigate different mechanisms of signal discrimination, and how multiple system components such as binding affinity, receptor expression levels and their variability, receptor internalization, short-term negative feedback by SOCS1 protein, and differential receptor expression play together to ensure ligand specificity on the level of STAT phosphorylation. Based on these results, we propose phenomenological functional mappings from STAT activation to downstream anti-viral and anti-proliferative activity to investigate differential signal processing steps downstream of STAT phosphorylation. We find that the negative feedback by the protein USP18, which enhances differences in signaling between Interferons via ligand-dependent refractoriness, can give rise to functional plasticity in Interferon-α and Interferon-β signaling, and explore other factors that control functional plasticity. Beyond Type I Interferon signaling, our results have a broad applicability to questions of signaling specificity and functional plasticity in signaling systems with multiple ligands acting through a bottleneck of a small number of shared receptors.

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“…approaches: (1) using chemistry and biochemistry to emulate circuit components or cellular automata, and (2) employing a large number of molecules to explore a combinatorial space in parallel. Examples for the first include reaction-diffusion systems, 7 Belousov-Zhabotinsky oscillatory reaction, 8 memristive polymers, 9 and transcription regulation for cellular signaling, 10,11 and other chemical and biochemical analogs of logic gates. 12,13 In the second category of parallelized computing, we find microfluidic devices, 14 nanofabricated networks, [15][16][17] and adaptive amoebal networks.…”

Section: Progress and Potentialmentioning

confidence: 99%

A molecular computing approach to solving optimization problems via programmable microdroplet arrays

Guo

Friederich

Cao

et al. 2021

Matter

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The search for novel forms of computing to the dominant von Neumann model-based approach is important as it will enable different classes of problems to be solved. Molecular computers are a promising alternative to semiconductor-based computers given their potential biocompatibility and cost advantages. The vast space of chemical reactions makes molecules a tunable, scalable, and energy-efficient computational vehicle. In molecular computers, memory and processing units can be combined into a single, inherently parallelized device. Here, we present a microdroplet array molecular computer to solve combinatorial optimization problems by employing an Ising Hamiltonian to map problems heuristically to droplet-droplet interactions. The droplets represent binary digits and problems are encoded in intra-and inter-droplet reactions. We propose two implementations: first, a hybrid classical-molecular computer that enforces inter-droplet constraints in a classical computer and, second, a purely molecular computer where the problem is entirely pre-programmed in the nearest-neighbor droplet reactions.

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Combinatorial Control through Allostery

Cited by 12 publications

References 38 publications

Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time

Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time

Determinants of Ligand Specificity and Functional Plasticity in Type I Interferon Signaling

A molecular computing approach to solving optimization problems via programmable microdroplet arrays

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