Genetically Encoded Red Photosensitizers with Enhanced Phototoxicity

Genetically encoded photosensitizers are increasingly used as optogenetic tools to control cell fate or trigger intracellular processes. A monomeric red fluorescent protein called SuperNova has been recently developed, however, it demonstrates suboptimal characteristics in most phototoxicity-based applications. Here, we applied directed evolution to this protein and identified SuperNova2, a protein with S10R substitution that results in enhanced brightness, chromophore maturation and phototoxicity in bacterial and mammalian cell cultures.Genetically encoded photosensitizers are increasingly used as optogenetic tools to control cell fate or trigger intracellular processes. A monomeric red fluorescent protein called SuperNova has been recently developed, however, it demonstrates suboptimal characteristics in most phototoxicity-based applications. Here, we applied directed evolution to this protein and identified SuperNova2, a protein with S10R substitution that results in enhanced brightness, chromophore maturation and phototoxicity in bacterial and mammalian cell cultures

Deep diversification of an AAV capsid protein by machine learning.

Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data without biophysical modeling provide one route to accessing the full potential diversity of engineered proteins. Here we apply deep learning to design highly diverse adeno-associated virus 2 (AAV2) capsid protein variants that remain viable for packaging of a DNA payload. Focusing on a 28-amino acid segment, we generated 201,426 variants of the AAV2 wild-type (WT) sequence yielding 110,689 viable engineered capsids, 57,348 of which surpass the average diversity of natural AAV serotype sequences, with 12-29 mutations across this region. Even when trained on limited data, deep neural network models accurately predict capsid viability across diverse variants. This approach unlocks vast areas of functional but previously unreachable sequence space, with many potential applications for the generation of improved viral vectors and protein therapeutics

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured

All-sky search for gravitational-wave bursts in the second joint LIGO-Virgo run

We present results from a search for gravitational-wave bursts in the data collected by the LIGO and Virgo detectors between July 7, 2009 and October 20, 2010: data are analyzed when at least two of the three LIGO-Virgo detectors are in coincident operation, with a total observation time of 207 days. The analysis searches for transients of duration < 1 s over the frequency band 64-5000 Hz, without other assumptions on the signal waveform, polarization, direction or occurrence time. All identified events are consistent with the expected accidental background. We set frequentist upper limits on the rate of gravitational-wave bursts by combining this search with the previous LIGO-Virgo search on the data collected between November 2005 and October 2007. The upper limit on the rate of strong gravitational-wave bursts at the Earth is 1.3 events per year at 90% confidence. We also present upper limits on source rate density per year and Mpc^3 for sample populations of standard-candle sources. As in the previous joint run, typical sensitivities of the search in terms of the root-sum-squared strain amplitude for these waveforms lie in the range 5 10^-22 Hz^-1/2 to 1 10^-20 Hz^-1/2. The combination of the two joint runs entails the most sensitive all-sky search for generic gravitational-wave bursts and synthesizes the results achieved by the initial generation of interferometric detectors.Comment: 15 pages, 7 figures: data for plots and archived public version at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=70814&version=19, see also the public announcement at http://www.ligo.org/science/Publication-S6BurstAllSky

Beyond the Hypercube:Evolutionary Accessibility of Fitness Landscapes with Realistic Mutational Networks

Evolutionary pathways describe trajectories of biological evolution in the space of different variants of organisms (genotypes). The probability of existence and the number of evolutionary pathways that lead from a given genotype to a better-adapted genotype are important measures of accessibility of local fitness optima and the reproducibility of evolution. Both quantities have been studied in simple mathematical models where genotypes are represented as binary sequences of two types of basic units, and the network of permitted mutations between the genotypes is a hypercube graph. However, it is unclear how these results translate to the biologically relevant case in which genotypes are represented by sequences of more than two units, for example four nucleotides (DNA) or 20 amino acids (proteins), and the mutational graph is not the hypercube. Here we investigate accessibility of the best-adapted genotype in the general case of K > 2 units. Using computer generated and experimental fitness landscapes we show that accessibility of the global fitness maximum increases with K and can be much higher than for binary sequences. The increase in accessibility comes from the increase in the number of indirect trajectories exploited by evolution for higher K. As one of the consequences, the fraction of genotypes that are accessible increases by three orders of magnitude when the number of units K increases from 2 to 16 for landscapes of size N ∼ 106 genotypes. This suggests that evolution can follow many different trajectories on such landscapes and the reconstruction of evolutionary pathways from experimental data might be an extremely difficult task

A brief review of bioluminescent systems (2019)

Despite being widely used in reporter technologies, bioluminescent systems are largely understudied. Of at least forty different bioluminescent systems thought to exist in nature, molecular components of only seven light-emitting reactions are known, and the full biochemical pathway leading to light emission is only understood for two of them. Here, we provide a succinct overview of currently known bioluminescent systems highlighting available tools for research and discussing future applications

Exact correspondence between walk in nucleotide and protein sequence spaces

In the course of evolution, genes traverse the nucleotide sequence space, which translates to a trajectory of changes in the protein sequence in protein sequence space. The correspondence between regions of the nucleotide and protein sequence spaces is understood in general but not in detail. One of the unexplored questions is how many sequences a protein can reach with a certain number of nucleotide substitutions in its gene sequence. Here I propose an algorithm to calculate the volume of protein sequence space accessible to a given protein sequence as a function of the number of nucleotide substitutions made in the protein-coding sequence. The algorithm utilizes the power of the dynamic programming approach, and makes all calculations within a couple of seconds on a desktop computer. I apply the algorithm to green fluorescence protein, and get the number of sequences four times higher than estimated before. However, taking into account the astronomically huge size of the protein sequence space, the previous estimate can be considered as acceptable as an order of magnitude estimation. The proposed algorithm has practical applications in the study of evolutionary trajectories in sequence space.This work was supported by HHMI International Early Career Scientist Program (55007424), The MINECO (BFU2015-68723-P), Spanish Ministry of Economy and Competitiveness Centro de Excelencia Severo Ochoa 2013-2017 grant (SEV-2012-0208), Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat's AGAUR program (2014 SGR 0974), and European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013, ERC grant agreement 335980_EinME)