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1. Surfactant mechanism of gene activation by transcriptional activation domains of sequence-specific factors

   Bradley K. Broyles1, Tamara Y. (July 2022, Nature structural molecular biology)

   Sara Osman Carolina Perdigoto (Ed.)

   Gene expression in all eukaryotes depends critically on the function of transcriptional activation domains of gene activator proteins. The conventional model for activation domain (AD) function is the direct physical recruitment of specific coactivators and transcriptional machinery components. However, ADs are short and astronomically variable sequences, with up to 10^24 possible interchangeable sequence variants for a single gene activator; each variant is intrinsically disordered in structure and interacts with its targets with low specificity and affinity. How these peptides recruit their targets is becoming increasingly difficult to explain, exposing a massive knowledge gap in molecular biology. Here, we show that the single required characteristic of ADs—consistent with their extreme variability, intrinsic structural disorder, and near-stochastic interaction mode—is an amphiphilic aromatic–acidic surfactant-like property. We propose that the AD surfactant, by triggering the local gene-promoter chromatin phase transition, catalyzes the formation of “transcription factory” condensates. We demonstrate that the presence of tryptophan and aspartic acid residues in the AD sequence is sufficient for in vivo functionality, even when present only as a single pair of residues within a 20-amino-acid sequence containing nothing more than additional 18 glycine residues. We demonstrate that the amphipathic α-helix structure, suggested previously as beneficial for AD function, is actually detrimental, and breaking this helix by inserting prolines significantly increases activation domain functionality. The proposed surfactant action mechanism based on near-stochastic interactions implied by the minimalistic activation domains changes not only the paradigm for the explanation of gene activation but also the fundamental biochemistry paradigm based on the specificity of sequence-to-structure-to-functional-interaction. The mechanism of activity regulation by near-stochastic allosteric interactions could easily be applied to other biological processes. 

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2. Identification of plant transcriptional activation domains

   https://doi.org/10.1038/s41586-024-07707-3  

   Morffy, Nicholas; Van_den_Broeck, Lisa; Miller, Caelan; Emenecker, Ryan J; Bryant, John A; Lee, Tyler M; Sageman-Furnas, Katelyn; Wilkinson, Edward G; Pathak, Sunita; Kotha, Sanjana R; et al (August 2024, Nature)

   Gene expression in Arabidopsis is regulated by more than 1,900 transcription factors (TFs), which have been identified genome-wide by the presence of well-conserved DNA-binding domains. Activator TFs contain activation domains (ADs) that recruit coactivator complexes; however, for nearly all Arabidopsis TFs, we lack knowledge about the presence, location and transcriptional strength of their ADs1. To address this gap, here we use a yeast library approach to experimentally identify Arabidopsis ADs on a proteome-wide scale, and find that more than half of the Arabidopsis TFs contain an AD. We annotate 1,553 ADs, the vast majority of which are, to our knowledge, previously unknown. Using the dataset generated, we develop a neural network to accurately predict ADs and to identify sequence features that are necessary to recruit coactivator complexes. We uncover six distinct combinations of sequence features that result in activation activity, providing a framework to interrogate the subfunctionalization of ADs. Furthermore, we identify ADs in the ancient AUXIN RESPONSE FACTOR family of TFs, revealing that AD positioning is conserved in distinct clades. Our findings provide a deep resource for understanding transcriptional activation, a framework for examining function in intrinsically disordered regions and a predictive model of ADs. 

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3. Diffusion control in biochemical specificity

   https://doi.org/10.1016/j.bpj.2022.03.005  

   Alejo, Jose L.; Kempes, Christopher P.; Adamala, Katarzyna P. (April 2022, Biophysical Journal)

   Biochemical specificity is critical in enzyme function, evolution, and engineering. Here we employ an established kinetic model to dissect the effects of reactant geometry and diffusion on product formation speed and accuracy in the presence of cognate (correct) and near-cognate (incorrect) substrates. Using this steady-state model for spherical geometries, we find that, for distinct kinetic regimes, the speed and accuracy of the reactions are optimized on different regions of the geometric landscape. From this model we deduce that accuracy can be strongly dependent on reactant geometric properties even for chemically limited reactions. Notably, substrates with a specific geometry and reactivity can be discriminated by the enzyme with higher efficacy than others through purely diffusive effects. For similar cognate and near-cognate substrate geometries (as is the case for polymerases or the ribosome), we observe that speed and accuracy are maximized in opposing regions of the geometric landscape. We also show that, in relevant environments, diffusive effects on accuracy can be substantial even far from extreme kinetic conditions. Finally, we find how reactant chemical discrimination and diffusion can be related to simultaneously optimize steady-state flux and accuracy. These results highlight how diffusion and geometry can be employed to enhance reaction speed and discrimination, and similarly how they impose fundamental restraints on these quantities. 

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4. Evolution of weak cooperative interactions for biological specificity

   https://doi.org/10.1073/pnas.1815912115  

   Gao, Ang; Shrinivas, Krishna; Lepeudry, Paul; Suzuki, Hiroshi I.; Sharp, Phillip A.; Chakraborty, Arup K. (November 2018, Proceedings of the National Academy of Sciences)

   A hallmark of biological systems is that particular functions and outcomes are realized in specific contexts, such as when particular signals are received. One mechanism for mediating specificity is described by Fisher’s “lock and key” metaphor, exemplified by enzymes that bind selectively to a particular substrate via specific finely tuned interactions. Another mechanism, more prevalent in multicellular organisms, relies on multivalent weak cooperative interactions. Its importance has recently been illustrated by the recognition that liquid-liquid phase transitions underlie the formation of membraneless condensates that perform specific cellular functions. Based on computer simulations of an evolutionary model, we report that the latter mechanism likely became evolutionarily prominent when a large number of tasks had to be performed specifically for organisms to function properly. We find that the emergence of weak cooperative interactions for mediating specificity results in organisms that can evolve to accomplish new tasks with fewer, and likely less lethal, mutations. We argue that this makes the system more capable of undergoing evolutionary changes robustly, and thus this mechanism has been repeatedly positively selected in increasingly complex organisms. Specificity mediated by weak cooperative interactions results in some useful cross-reactivity for related tasks, but at the same time increases susceptibility to misregulation that might lead to pathologies. 

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5. Synthetic Biology Tool Development Advances Predictable Gene Expression in the Metabolically Versatile Soil Bacterium Rhodopseudomonas palustris

   https://doi.org/10.3389/fbioe.2022.800734  

   Immethun, Cheryl M.; Kathol, Mark; Changa, Taity; Saha, Rajib (March 2022, Frontiers in Bioengineering and Biotechnology)

   Harnessing the unique biochemical capabilities of non-model microorganisms would expand the array of biomanufacturing substrates, process conditions, and products. There are non-model microorganisms that fix nitrogen and carbon dioxide, derive energy from light, catabolize methane and lignin-derived aromatics, are tolerant to physiochemical stresses and harsh environmental conditions, store lipids in large quantities, and produce hydrogen. Model microorganisms often only break down simple sugars and require low stress conditions, but they have been engineered for the sustainable manufacture of numerous products, such as fragrances, pharmaceuticals, cosmetics, surfactants, and specialty chemicals, often by using tools from synthetic biology. Transferring complex pathways has proven to be exceedingly difficult, as the cofactors, cellular conditions, and energy sources necessary for this pathway to function may not be present in the host organism. Utilization of unique biochemical capabilities could also be achieved by engineering the host; although, synthetic biology tools developed for model microbes often do not perform as designed in other microorganisms. The metabolically versatile Rhodopseudomonas palustris CGA009, a purple non-sulfur bacterium, catabolizes aromatic compounds derived from lignin in both aerobic and anaerobic conditions and can use light, inorganic, and organic compounds for its source of energy. R. palustris utilizes three nitrogenase isozymes to fulfill its nitrogen requirements while also generating hydrogen. Furthermore, the bacterium produces two forms of RuBisCo in response to carbon dioxide/bicarbonate availability. While this potential chassis harbors many beneficial traits, stable heterologous gene expression has been problematic due to its intrinsic resistance to many antibiotics and the lack of synthetic biology parts investigated in this microbe. To address these problems, we have characterized gene expression and plasmid maintenance for different selection markers, started a synthetic biology toolbox specifically for the photosynthetic R. palustris , including origins of replication, fluorescent reporters, terminators, and 5′ untranslated regions, and employed the microbe’s endogenous plasmid for exogenous protein production. This work provides essential synthetic biology tools for engineering R. palustris ’ many unique biochemical processes and has helped define the principles for expressing heterologous genes in this promising microbe through a methodology that could be applied to other non-model microorganisms. 

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