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Single-cell CRISPR screens enable the exploration of mammalian gene function and genetic regulatory networks. However, use of this technology has been limited by reliance on indirect indexing of single-guide RNAs (sgRNAs). Here we present direct-capture Perturb-seq, a versatile screening approach in which expressed sgRNAs are sequenced alongside single-cell transcriptomes. Direct-capture Perturb-seq enables detection of multiple distinct sgRNA sequences from individual cells and thus allows pooled single-cell CRISPR screens to be easily paired with combinatorial perturbation libraries that contain dual-guide expression vectors. We demonstrate the utility of this approach for high-throughput investigations of genetic interactions and, leveraging this ability, dissect epistatic interactions between cholesterol biogenesis and DNA repair. Using direct capture Perturb-seq, we also show that targeting individual genes with multiple sgRNAs per cell improves efficacy of CRISPR interference and activation, facilitating the use of compact, highly active CRISPR libraries for single-cell screens. Last, we show that hybridization-based target enrichment permits sensitive, specific sequencing of informative transcripts from single-cell RNA-seq experiments. Single-cell CRISPR screens are readily multiplexed and scaled with an improved version of Perturb-seq.

Ribosome profiling has revealed pervasive but largely uncharacterized translation outside of canonical coding sequences (CDSs). In this work, we exploit a systematic CRISPR-based screening strategy to identify hundreds of noncanonical CDSs that are essential for cellular growth and whose disruption elicits specific, robust transcriptomic and phenotypic changes in human cells. Functional characterization of the encoded microproteins reveals distinct cellular localizations, specific protein binding partners, and hundreds of microproteins that are presented by the human leukocyte antigen system. We find multiple microproteins encoded in upstream open reading frames, which form stable complexes with the main, canonical protein encoded on the same messenger RNA, thereby revealing the use of functional bicistronic operons in mammals. Together, our results point to a family of functional human microproteins that play critical and diverse cellular roles.

Measurement has a special role in quantum theory 1 : by collapsing the wavefunction, it can enable phenomena such as teleportation 2 and thereby alter the ‘arrow of time’ that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space–time 3 – 10 that go beyond the established paradigms for characterizing phases, either in or out of equilibrium 11 – 13 . For present-day noisy intermediate-scale quantum (NISQ) processors 14 , the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping 9 , 15 – 17 to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling 3 , 4 to measurement-induced teleportation 18 . We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors. Measurement-induced phases of quantum information have been observed in a system of 70 superconducting qubits.

Undesired coupling to the surrounding environment destroys long-range correlations in quantum processors and hinders coherent evolution in the nominally available computational space. This noise is an outstanding challenge when leveraging the computation power of near-term quantum processors 1 . It has been shown that benchmarking random circuit sampling with cross-entropy benchmarking can provide an estimate of the effective size of the Hilbert space coherently available 2 – 8 . Nevertheless, quantum algorithms’ outputs can be trivialized by noise, making them susceptible to classical computation spoofing. Here, by implementing an algorithm for random circuit sampling, we demonstrate experimentally that two phase transitions are observable with cross-entropy benchmarking, which we explain theoretically with a statistical model. The first is a dynamical transition as a function of the number of cycles and is the continuation of the anti-concentration point in the noiseless case. The second is a quantum phase transition controlled by the error per cycle; to identify it analytically and experimentally, we create a weak-link model, which allows us to vary the strength of the noise versus coherent evolution. Furthermore, by presenting a random circuit sampling experiment in the weak-noise phase with 67 qubits at 32 cycles, we demonstrate that the computational cost of our experiment is beyond the capabilities of existing classical supercomputers. Our experimental and theoretical work establishes the existence of transitions to a stable, computationally complex phase that is reachable with current quantum processors. By implementing random circuit sampling, experimental and theoretical results establish the existence of transitions to a stable, computationally complex phase that is reachable with current quantum processors.

Viral infection triggers activation of the integrated stress response (ISR). In response to viral double-stranded RNA (dsRNA), RNA-activated protein kinase (PKR) phosphorylates the translation initiation factor eIF2, converting it from a translation initiator into a potent translation inhibitor and this restricts the synthesis of viral proteins. Phosphorylated eIF2 (eIF2-P) inhibits translation by binding to eIF2’s dedicated, heterodecameric nucleotide exchange factor eIF2B and conformationally inactivating it. We show that the NSs protein of Sandfly Fever Sicilian virus (SFSV) allows the virus to evade the ISR. Mechanistically, NSs tightly binds to eIF2B (K D  = 30 nM), blocks eIF2-P binding, and rescues eIF2B GEF activity. Cryo-EM structures demonstrate that SFSV NSs and eIF2-P directly compete, with the primary NSs contacts to eIF2Bα mediated by five ‘aromatic fingers’. NSs binding preserves eIF2B activity by maintaining eIF2B’s conformation in its active A-State. Viral infection triggers the integrated stress response (ISR) by phosphorylation of the translation initiation factor eIF2 which becomes an inhibitor of eIF2B. Here the authors show that the NSs protein of Sandfly Fever Sicilian virus allows evasion of the ISR by blocking eIF2-P binding to eIF2B.

Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators 1 , 2 . Unlocking the full potential of such systems towards this goal requires flexible initial state preparation, precise time evolution and extensive probes for final state characterization. Here we present a quantum simulator comprising 69 superconducting qubits that supports both universal quantum gates and high-fidelity analogue evolution, with performance beyond the reach of classical simulation in cross-entropy benchmarking experiments. This hybrid platform features more versatile measurement capabilities compared with analogue-only simulators, which we leverage here to reveal a coarsening-induced breakdown of Kibble–Zurek scaling predictions 3 in the XY model, as well as signatures of the classical Kosterlitz–Thouless phase transition 4 . Moreover, the digital gates enable precise energy control, allowing us to study the effects of the eigenstate thermalization hypothesis 5 , 6 – 7 in targeted parts of the eigenspectrum. We also demonstrate digital preparation of pairwise-entangled dimer states, and image the transport of energy and vorticity during subsequent thermalization in analogue evolution. These results establish the efficacy of superconducting analogue–digital quantum processors for preparing states across many-body spectra and unveiling their thermalization dynamics. A hybrid analogue–digital quantum simulator is used to demonstrate beyond-classical performance in benchmarking experiments and to study thermalization phenomena in an XY quantum magnet, including the breakdown of Kibble–Zurek scaling predictions and signatures of the Kosterlitz–Thouless phase transition.

Indistinguishability of particles is a fundamental principle of quantum mechanics 1 . For all elementary and quasiparticles observed to date—including fermions, bosons and Abelian anyons—this principle guarantees that the braiding of identical particles leaves the system unchanged 2 , 3 . However, in two spatial dimensions, an intriguing possibility exists: braiding of non-Abelian anyons causes rotations in a space of topologically degenerate wavefunctions 4 – 8 . Hence, it can change the observables of the system without violating the principle of indistinguishability. Despite the well-developed mathematical description of non-Abelian anyons and numerous theoretical proposals 9 – 22 , the experimental observation of their exchange statistics has remained elusive for decades. Controllable many-body quantum states generated on quantum processors offer another path for exploring these fundamental phenomena. Whereas efforts on conventional solid-state platforms typically involve Hamiltonian dynamics of quasiparticles, superconducting quantum processors allow for directly manipulating the many-body wavefunction by means of unitary gates. Building on predictions that stabilizer codes can host projective non-Abelian Ising anyons 9 , 10 , we implement a generalized stabilizer code and unitary protocol 23 to create and braid them. This allows us to experimentally verify the fusion rules of the anyons and braid them to realize their statistics. We then study the prospect of using the anyons for quantum computation and use braiding to create an entangled state of anyons encoding three logical qubits. Our work provides new insights about non-Abelian braiding and, through the future inclusion of error correction to achieve topological protection, could open a path towards fault-tolerant quantum computing. A unitary protocol for braiding projective non-Abelian Ising anyons in a generalized stabilizer code is implemented on a superconducting processor, allowing for verification of their fusion rules and realization of their exchange statistics.

Résumé Objectif Création d’un programme d’éducation thérapeutique en douleur chronique (PETDC). Matériel et méthodes Pour créer le PETDC, nous avons utilisé un processus en quatre étapes. Résultats Cinq groupes de patients bénéficient du programme annuellement. Sur la base de leur propre évaluation, les patients ont déclaré que leur connaissance de la douleur chronique s’était améliorée (2,8 à 24 %). La mesure de la satisfaction du PETDC était de 8,67/10. Conclusion Le PETDC aide les patients douloureux chroniques à acquérir et à maintenir les compétences dont ils ont besoin pour mieux gérer leur vie.

We report a new shortwave infrared (SWIR) retrieval of the column-averaged HDO/H2 O ratio from the Japanese Greenhouse Gases Observing Satellite (GOSAT). From synthetic simulation studies, we have estimated that the inferred δD values will typically have random errors between 20[per thousand] (desert surface and 30° solar zenith angle) and 120[per thousand] (conifer surface and 60° solar zenith angle). We find that the retrieval will have a small but significant sensitivity to the presence of cirrus clouds, the HDO a priori profile shape and atmospheric temperature, which has the potential of introducing some regional-scale biases in the retrieval. From comparisons to ground-based column observations from the Total Carbon Column Observing Network (TCCON), we find differences between δD from GOSAT and TCCON of around -30[per thousand] for northern hemispheric sites which increase up to -70[per thousand] for Australian sites. The bias for the Australian sites significantly reduces when decreasing the spatial co-location criteria, which shows that spatial averaging contributes to the observed differences over Australia. The GOSAT retrievals allow mapping the global distribution of δD and its variations with season, and we find in our global GOSAT retrievals the expected strong latitudinal gradients with significant enhancements over the tropics. The comparisons to the ground-based TCCON network and the results of the global retrieval are very encouraging, and they show that δD retrieved from GOSAT should be a useful product that can be used to complement datasets from thermal-infrared sounder and ground-based networks and to extend the δD dataset from SWIR retrievals established from the recently ended SCIAMACHY mission.