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  1. Abstract Background and Aims

    Phosphoenolpyruvate (PEP) carboxylase (PEPC) catalyses the irreversible carboxylation of PEP with bicarbonate to produce oxaloacetate. This reaction powers the carbon-concentrating mechanism (CCM) in plants that perform C4 photosynthesis. This CCM is generally driven by a single PEPC gene product that is highly expressed in the cytosol of mesophyll cells. We found two C4 grasses, Panicum miliaceum and Echinochloa colona, that each have two highly expressed PEPC genes. We characterized the kinetic properties of the two most abundant PEPCs in E. colona and P. miliaceum to better understand how the enzyme’s amino acid structure influences its function.


    Coding sequences of the two most abundant PEPC proteins in E. colona and P. miliaceum were synthesized by GenScript and were inserted into bacteria expression plasmids. Point mutations resulting in substitutions at conserved amino acid residues (e.g. N-terminal serine and residue 890) were created via site-directed PCR mutagenesis. The kinetic properties of semi-purified plant PEPCs from Escherichia coli were analysed using membrane-inlet mass spectrometry and a spectrophotometric enzyme-coupled reaction.

    Key Results

    The two most abundant P. miliaceum PEPCs (PmPPC1 and PmPPC2) have similar sequence identities (>95 %), and as a result had similar kinetic properties. The two most abundant E. colona PEPCsmore »(EcPPC1 and EcPPC2) had identities of ~78 % and had significantly different kinetic properties. The PmPPCs and EcPPCs had different responses to allosteric inhibitors and activators, and substitutions at the conserved N-terminal serine and residue 890 resulted in significantly altered responses to allosteric regulators.


    The two, significantly expressed C4Ppc genes in P. miliaceum were probably the result of genomes combining from two closely related C4  Panicum species. We found natural variation in PEPC’s sensitivity to allosteric inhibition that seems to bypass the conserved 890 residue, suggesting alternative evolutionary pathways for increased malate tolerance and other kinetic properties.

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  2. Free, publicly-accessible full text available August 1, 2024
  3. Free, publicly-accessible full text available July 1, 2024
  4. Abstract

    Squeezed light has long been used to enhance the precision of a single optomechanical sensor. An emerging set of proposals seeks to use arrays of optomechanical sensors to detect weak distributed forces, for applications ranging from gravity-based subterranean imaging to dark matter searches; however, a detailed investigation into the quantum-enhancement of this approach remains outstanding. Here, we propose an array of entanglement-enhanced optomechanical sensors to improve the broadband sensitivity of distributed force sensing. By coherently operating the optomechanical sensor array and distributing squeezing to entangle the optical fields, the array of sensors has a scaling advantage over independent sensors (i.e.,$$\sqrt{M}\to M$$MM, whereMis the number of sensors) due to coherence as well as joint noise suppression due to multi-partite entanglement. As an illustration, we consider entanglement-enhancement of an optomechanical accelerometer array to search for dark matter, and elucidate the challenge of realizing a quantum advantage in this context.

  5. Free, publicly-accessible full text available June 1, 2024
  6. Free, publicly-accessible full text available April 1, 2024
  7. Abstract

    The ubiquitous cellular heterogeneity underlying many organism-level phenotypes raises questions about what factors drive this heterogeneity and how these complex heterogeneous systems evolve. Here, we use single-cell expression data from a Prairie rattlesnake (Crotalus viridis) venom gland to evaluate hypotheses for signaling networks underlying snake venom regulation and the degree to which different venom gene families have evolutionarily recruited distinct regulatory architectures. Our findings suggest that snake venom regulatory systems have evolutionarily co-opted trans-regulatory factors from extracellular signal-regulated kinase and unfolded protein response pathways that specifically coordinate expression of distinct venom toxins in a phased sequence across a single population of secretory cells. This pattern of co-option results in extensive cell-to-cell variation in venom gene expression, even between tandemly duplicated paralogs, suggesting this regulatory architecture has evolved to circumvent cellular constraints. While the exact nature of such constraints remains an open question, we propose that such regulatory heterogeneity may circumvent steric constraints on chromatin, cellular physiological constraints (e.g., endoplasmic reticulum stress or negative protein–protein interactions), or a combination of these. Regardless of the precise nature of these constraints, this example suggests that, in some cases, dynamic cellular constraints may impose previously unappreciated secondary constraints on the evolution of genemore »regulatory networks that favors heterogeneous expression.

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  8. The ability to predict and understand complex molecular motions occurring over diverse timescales ranging from picoseconds to seconds and even hours in biological systems remains one of the largest challenges to chemical theory. Markov state models (MSMs), which provide a memoryless description of the transitions between different states of a biochemical system, have provided numerous important physically transparent insights into biological function. However, constructing these models often necessitates performing extremely long molecular simulations to converge the rates. Here, we show that by incorporating memory via the time-convolutionless generalized master equation (TCL-GME) one can build a theoretically transparent and physically intuitive memory-enriched model of biochemical processes with up to a three order of magnitude reduction in the simulation data required while also providing a higher temporal resolution. We derive the conditions under which the TCL-GME provides a more efficient means to capture slow dynamics than MSMs and rigorously prove when the two provide equally valid and efficient descriptions of the slow configurational dynamics. We further introduce a simple averaging procedure that enables our TCL-GME approach to quickly converge and accurately predict long-time dynamics even when parameterized with noisy reference data arising from short trajectories. We illustrate the advantages of the TCL-GMEmore »using alanine dipeptide, the human argonaute complex, and FiP35 WW domain.« less
    Free, publicly-accessible full text available March 21, 2024
  9. Free, publicly-accessible full text available February 1, 2024
  10. Abstract Background

    Snake venoms are trophic adaptations that represent an ideal model to examine the evolutionary factors that shape polymorphic traits under strong natural selection. Venom compositional variation is substantial within and among venomous snake species. However, the forces shaping this phenotypic complexity, as well as the potential integrated roles of biotic and abiotic factors, have received little attention. Here, we investigate geographic variation in venom composition in a wide-ranging rattlesnake (Crotalus viridis viridis) and contextualize this variation by investigating dietary, phylogenetic, and environmental variables that covary with venom.


    Using shotgun proteomics, venom biochemical profiling, and lethality assays, we identify 2 distinct divergent phenotypes that characterize major axes of venom variation in this species: a myotoxin-rich phenotype and a snake venom metalloprotease (SVMP)-rich phenotype. We find that dietary availability and temperature-related abiotic factors are correlated with geographic trends in venom composition.


    Our findings highlight the potential for snake venoms to vary extensively within species, for this variation to be driven by biotic and abiotic factors, and for the importance of integrating biotic and abiotic variation for understanding complex trait evolution. Links between venom variation and variation in biotic and abiotic factors indicate that venom variation likely results from substantial geographic variationmore »in selection regimes that determine the efficacy of venom phenotypes across populations and snake species. Our results highlight the cascading influence of abiotic factors on biotic factors that ultimately shape venom phenotype, providing evidence for a central role of local selection as a key driver of venom variation.

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