Designing cell-targeted therapeutic proteins reveals the interplay between domain connectivity and cell binding.

The therapeutic efficacy of cytokines is often hampered by severe side effects due to their undesired binding to healthy cells. One strategy for overcoming this obstacle is to tether cytokines to antibodies or antibody fragments for targeted cell delivery. However, how to modulate the geometric configuration and relative binding affinity of the two domains for optimal activity remains an outstanding question. As a result, many antibody-cytokine complexes do not achieve the desired level of cell-targeted binding and activity. Here, we address these design issues by developing a computational model to simulate the dynamics and binding kinetics of natural and engineered fusion proteins such as antibody-cytokine complexes. To verify the model, we developed a modular system in which an antibody fragment and a cytokine are conjugated via a DNA linker that allows for programmable linker geometry and protein spatial configuration. By assembling and testing several anti-CD20 antibody fragment-interferon ? complexes, we showed that varying the linker length and cytokine binding affinity controlled the magnitude of cell-targeted signaling activation in a manner that agreed with the model predictions, which were expressed as dose-signaling response curves. The simulation results also revealed that there is a range of cytokine binding affinities that would achieve optimal therapeutic efficacy. This rapid prototyping platform will facilitate the rational design of antibody-cytokine complexes for improved therapeutic outcomes.

Dynamics simulations for engineering macromolecular interactions.

The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20,000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

Whole-genome sequencing of the efficient industrial fuel-ethanol fermentative Saccharomyces cerevisiae strain CAT-1.

The Saccharomyces cerevisiae strains widely used for industrial fuel-ethanol production have been developed by selection, but their underlying beneficial genetic polymorphisms remain unknown. Here, we report the draft whole-genome sequence of the S. cerevisiae strain CAT-1, which is a dominant fuel-ethanol fermentative strain from the sugarcane industry in Brazil. Our results indicate that strain CAT-1 is a highly heterozygous diploid yeast strain, and the ~12-Mb genome of CAT-1, when compared with the reference S228c genome, contains ~36,000 homozygous and ~30,000 heterozygous single nucleotide polymorphisms, exhibiting an uneven distribution among chromosomes due to large genomic regions of loss of heterozygosity (LOH). In total, 58 % of the 6,652 predicted protein-coding genes of the CAT-1 genome constitute different alleles when compared with the genes present in the reference S288c genome. The CAT-1 genome contains a reduced number of transposable elements, as well as several gene deletions and duplications, especially at telomeric regions, some correlated with several of the physiological characteristics of this industrial fuel-ethanol strain. Phylogenetic analyses revealed that some genes were likely associated with traits important for bioethanol production. Identifying and characterizing the allelic variations controlling traits relevant to industrial fermentation should provide the basis for a forward genetics approach for developing better fermenting yeast strains.

Shaping the Future of Research: a perspective from junior scientists.

The landscape of scientific research and funding is in flux as a result of tight budgets, evolving models of both publishing and evaluation, and questions about training and workforce stability. As future leaders, junior scientists are uniquely poised to shape the culture and practice of science in response to these challenges. A group of postdocs in the Boston area who are invested in improving the scientific endeavor, planned a symposium held on October 2 (nd) and 3 (rd), 2014, as a way to join the discussion about the future of US biomedical research. Here we present a report of the proceedings of participant-driven workshops and the organizers' synthesis of the outcomes.

The bacterial carbon-fixing organelle is formed by shell envelopment of preassembled cargo.

BACKGROUND: Cyanobacteria play a significant role in the global carbon cycle. In Synechococcuselongatus, the carbon-fixing enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is concentrated into polyhedral, proteinaceous compartments called carboxysomes. METHODOLOGY/PRINCIPAL FINDINGS: Using live cell fluorescence microscopy, we show that carboxysomes are first detected as small seeds of RuBisCO that colocalize with existing carboxysomes. These seeds contain little or no shell protein, but increase in RuBisCO content over several hours, during which time they are exposed to the solvent. The maturing seed is then enclosed by shell proteins, a rapid process that seals RuBisCO from the cytosol to establish a distinct, solvent-protected microenvironment that is oxidizing relative to the cytosol. These closure events can be spatially and temporally coincident with the appearance of a nascent daughter RuBisCO seed. CONCLUSIONS/SIGNIFICANCE: Carboxysomes assemble in a stepwise fashion, inside-to-outside, revealing that cargo is the principle organizer of this compartment's biogenesis. Our observations of the spatial relationship of seeds to previously formed carboxysomes lead us to propose a model for carboxysome replication via sequential fission, polymerization, and encapsulation of their internal cargo.