The Architecture of SARS-CoV-2 Transcriptome.

SARS-CoV-2 is a betacoronavirus responsible for the COVID-19 pandemic. Although the SARS-CoV-2 genome was reported recently, its transcriptomic architecture is unknown. Utilizing two complementary sequencing techniques, we present a high-resolution map of the SARS-CoV-2 transcriptome and epitranscriptome. DNA nanoball sequencing shows that the transcriptome is highly complex owing to numerous discontinuous transcription events. In addition to the canonical genomic and 9 subgenomic RNAs, SARS-CoV-2 produces transcripts encoding unknown ORFs with fusion, deletion, and/or frameshift. Using nanopore direct RNA sequencing, we further find at least 41 RNA modification sites on viral transcripts, with the most frequent motif, AAGAA. Modified RNAs have shorter poly(A) tails than unmodified RNAs, suggesting a link between the modification and the 3' tail. Functional investigation of the unknown transcripts and RNA modifications discovered in this study will open new directions to our understanding of the life cycle and pathogenicity of SARS-CoV-2.

A Genetically Defined Compartmentalized Striatal Direct Pathway for Negative Reinforcement.

The striosome compartment within the dorsal striatum has been implicated in reinforcement learning and regulation of motivation, but how striosomal neurons contribute to these functions remains elusive. Here, we show that a genetically identified striosomal population, which expresses the Teashirt family zinc finger 1 (Tshz1) and belongs to the direct pathway, drives negative reinforcement and is essential for aversive learning in mice. Contrasting a "conventional" striosomal direct pathway, the Tshz1 neurons cause aversion, movement suppression, and negative reinforcement once activated, and they receive a distinct set of synaptic inputs. These neurons are predominantly excited by punishment rather than reward and represent the anticipation of punishment or the motivation for avoidance. Furthermore, inhibiting these neurons impairs punishment-based learning without affecting reward learning or movement. These results establish a major role of striosomal neurons in behaviors reinforced by punishment and moreover uncover functions of the direct pathway unaccounted for in classic models.

Optogenetic Editing Reveals the Hierarchical Organization of Learned Action Sequences.

The organization of action into sequences underlies complex behaviors that are essential for organismal survival and reproduction. Despite extensive studies of innate sequences in relation to central pattern generators, how learned action sequences are controlled and whether they are organized as a chain or a hierarchy remain largely unknown. By training mice to perform heterogeneous action sequences, we demonstrate that striatal direct and indirect pathways preferentially encode different behavioral levels of sequence structure. State-dependent closed-loop optogenetic stimulation of the striatal direct pathway can selectively insert a single action element into the sequence without disrupting the overall sequence length. Optogenetic manipulation of the striatal indirect pathway completely removes the ongoing subsequence while leaving the following subsequence to be executed with the appropriate timing and length. These results suggest that learned action sequences are not organized in a serial but rather a hierarchical structure that is distinctly controlled by basal ganglia pathways.

The Striatum Organizes 3D Behavior via Moment-to-Moment Action Selection.

Many naturalistic behaviors are built from modular components that are expressed sequentially. Although striatal circuits have been implicated in action selection and implementation, the neural mechanisms that compose behavior in unrestrained animals are not well understood. Here, we record bulk and cellular neural activity in the direct and indirect pathways of dorsolateral striatum (DLS) as mice spontaneously express action sequences. These experiments reveal that DLS neurons systematically encode information about the identity and ordering of sub-second 3D behavioral motifs; this encoding is facilitated by fast-timescale decorrelations between the direct and indirect pathways. Furthermore, lesioning the DLS prevents appropriate sequence assembly during exploratory or odor-evoked behaviors. By characterizing naturalistic behavior at neural timescales, these experiments identify a code for elemental 3D pose dynamics built from complementary pathway dynamics, support a role for DLS in constructing meaningful behavioral sequences, and suggest models for how actions are sculpted over time.

Cell Reprogramming: The Many Roads to Success.

Cellular reprogramming experiments from somatic cell types have demonstrated the plasticity of terminally differentiated cell states. Recent efforts in understanding the mechanisms of cellular reprogramming have begun to elucidate the differentiation trajectories along the reprogramming processes. In this review, we focus mainly on direct reprogramming strategies by transcription factors and highlight the variables that contribute to cell fate conversion outcomes. We review key studies that shed light on the cellular and molecular mechanisms by investigating differentiation trajectories and alternative cell states as well as transcription factor regulatory activities during cell fate reprogramming. Finally, we highlight a few concepts that we believe require attention, particularly when measuring the success of cell reprogramming experiments.

Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields.

We report a noninvasive strategy for electrically stimulating neurons at depth. By delivering to the brain multiple electric fields at frequencies too high to recruit neural firing, but which differ by a frequency within the dynamic range of neural firing, we can electrically stimulate neurons throughout a region where interference between the multiple fields results in a prominent electric field envelope modulated at the difference frequency. We validated this temporal interference (TI) concept via modeling and physics experiments, and verified that neurons in the living mouse brain could follow the electric field envelope. We demonstrate the utility of TI stimulation by stimulating neurons in the hippocampus of living mice without recruiting neurons of the overlying cortex. Finally, we show that by altering the currents delivered to a set of immobile electrodes, we can steerably evoke different motor patterns in living mice.

Cryo-EM Structures of the Magnesium Channel CorA Reveal Symmetry Break upon Gating.

CorA, the major Mg(2+) uptake system in prokaryotes, is gated by intracellular Mg(2+) (KD ∼ 1-2 mM). X-ray crystallographic studies of CorA show similar conformations under Mg(2+)-bound and Mg(2+)-free conditions, but EPR spectroscopic studies reveal large Mg(2+)-driven quaternary conformational changes. Here, we determined cryo-EM structures of CorA in the Mg(2+)-bound closed conformation and in two open Mg(2+)-free states at resolutions of 3.8, 7.1, and 7.1 Å, respectively. In the absence of bound Mg(2+), four of the five subunits are displaced to variable extents (∼ 10-25 Å) by hinge-like motions as large as ∼ 35° at the stalk helix. The transition between a single 5-fold symmetric closed state and an ensemble of low Mg(2+), open, asymmetric conformational states is, thus, the key structural signature of CorA gating. This mechanism is likely to apply to other structurally similar divalent ion channels.

Targeting the m6A RNA modification pathway blocks SARS-CoV-2 and HCoV-OC43 replication.

N6-methyladenosine (m6A) is an abundant internal RNA modification, influencing transcript fate and function in uninfected and virus-infected cells. Installation of m6A by the nuclear RNA methyltransferase METTL3 occurs cotranscriptionally; however, the genomes of some cytoplasmic RNA viruses are also m6A-modified. How the cellular m6A modification machinery impacts coronavirus replication, which occurs exclusively in the cytoplasm, is unknown. Here we show that replication of SARS-CoV-2, the agent responsible for the COVID-19 pandemic, and a seasonal human ß-coronavirus HCoV-OC43, can be suppressed by depletion of METTL3 or cytoplasmic m6A reader proteins YTHDF1 and YTHDF3 and by a highly specific small molecule METTL3 inhibitor. Reduction of infectious titer correlates with decreased synthesis of viral RNAs and the essential nucleocapsid (N) protein. Sites of m6A modification on genomic and subgenomic RNAs of both viruses were mapped by methylated RNA immunoprecipitation sequencing (meRIP-seq). Levels of host factors involved in m6A installation, removal, and recognition were unchanged by HCoV-OC43 infection; however, nuclear localization of METTL3 and cytoplasmic m6A readers YTHDF1 and YTHDF2 increased. This establishes that coronavirus RNAs are m6A-modified and host m6A pathway components control ß-coronavirus replication. Moreover, it illustrates the therapeutic potential of targeting the m6A pathway to restrict coronavirus reproduction.

The Dynamics of Transcriptional Activation by Hepatic Reprogramming Factors.

Specific combinations of two transcription factors (Hnf4α plus Foxa1, Foxa2, or Foxa3) can induce direct conversion of mouse fibroblasts into hepatocyte-like cells. However, the molecular mechanisms underlying hepatic reprogramming are largely unknown. Here, we show that the Foxa protein family members and Hnf4α sequentially and cooperatively bind to chromatin to activate liver-specific gene expression. Although all Foxa proteins bind to and open regions of closed chromatin as pioneer factors, Foxa3 has the unique potential of transferring from the distal to proximal regions of the transcription start site of target genes, binding RNA polymerase II, and co-traversing target genes. These distinctive characteristics of Foxa3 are essential for inducing the hepatic fate in fibroblasts. Similar functional coupling of transcription factors to RNA polymerase II may occur in other contexts whereby transcriptional activation can induce cell differentiation.

Oral Anticoagulants Beyond Warfarin.

Direct oral anticoagulants (DOACs) have largely replaced vitamin K antagonists, mostly warfarin, for the main indications for oral anticoagulation, prevention and treatment of venous thromboembolism, and prevention of embolic stroke in atrial fibrillation. While DOACs offer practical, fixed-dose anticoagulation in many patients, specific restrictions or contraindications may apply. DOACs are not sufficiently effective in high-thrombotic risk conditions such as antiphospholipid syndrome and mechanical heart valves. Patients with cancer-associated thrombosis may benefit from DOACs, but the bleeding risk, particularly in those with gastrointestinal or urogenital tumors, must be carefully weighed. In patients with frailty, excess body weight, and/or moderate-to-severe chronic kidney disease, DOACs must be cautiously administered and may require laboratory monitoring. Reversal agents have been developed and approved for life-threatening bleeding. In addition, the clinical testing of potentially safer anticoagulants such as factor XI(a) inhibitors is important to further optimize anticoagulant therapy in an increasingly elderly and frail population worldwide.

Genomic Answers for Kids: Toward more equitable access to genomic testing for rare diseases in rural populations.

Next-generation sequencing has revolutionized the speed of rare disease (RD) diagnoses. While clinical exome and genome sequencing represent an effective tool for many RD diagnoses, there is room to further improve the diagnostic odyssey of many RD patients. One recognizable intervention lies in increasing equitable access to genomic testing. Rural communities represent a significant portion of underserved and underrepresented individuals facing additional barriers to diagnosis and treatment. Primary care providers (PCPs) at local clinics, though sometimes suspicious of a potential benefit of genetic testing for their patients, have significant constraints in pursuing it themselves and rely on referrals to specialists. Yet, these referrals are typically followed by long waitlists and significant delays in clinical assessment, insurance clearance, testing, and initiation of diagnosis-informed care management. Not only is this process time intensive, but it also often requires multiple visits to urban medical centers for which distance may be a significant barrier to rural families. Therefore, providing early, "direct-to-provider" (DTP) local access to unrestrictive genomic testing is likely to help speed up diagnostic times and access to care for RD patients in rural communities. In a pilot study with a PCP clinic in rural Kansas, we observed a minimum 5.5 months shortening of time to diagnosis through the DTP exome sequencing program as compared to rural patients receiving genetic testing through the "traditional" PCP-referral-to-specialist scheme. We share our experience to encourage future partnerships beyond our center. Our efforts represent just one step in fostering greater diversity and equity in genomic studies.

RRM Transcription Factors Interact with NLRs and Regulate Broad-Spectrum Blast Resistance in Rice.

Nucleotide-binding site leucine-rich repeat (NLR) receptors perceive pathogen effectors and trigger plant immunity. However, the mechanisms underlying NLR-triggered defense responses remain obscure. The recently discovered Pigm locus in rice encodes a cluster of NLRs, including PigmR, which confers broad-spectrum resistance to blast fungus. Here, we identify PIBP1 (PigmR-INTERACTING and BLAST RESISTANCE PROTEIN 1), an RRM (RNA-recognition motif) protein that specifically interacts with PigmR and other similar NLRs to trigger blast resistance. PigmR-promoted nuclear accumulation of PIBP1 ensures full blast resistance. We find that PIBP1 and a homolog, Os06 g02240, bind DNA and function as unconventional transcription factors at the promoters of the defense genes OsWAK14 and OsPAL1, activating their expression. Knockout of PIBP1 and Os06 g02240 greatly attenuated blast resistance. Collectively, our study discovers previously unappreciated RRM transcription factors that directly interact with NLRs to activate plant defense, establishing a direct link between transcriptional activation of immune responses with NLR-mediated pathogen perception.

Parkinson's-linked LRRK2-G2019S derails AMPAR trafficking, mobility, and composition in striatum with cell-type and subunit specificity.

Parkinson's disease (PD) is a multifactorial disease that affects multiple brain systems and circuits. While defined by motor symptoms caused by degeneration of brainstem dopamine neurons, debilitating non-motor abnormalities in fronto-striatal-based cognitive function are common, appear early, and are initially independent of dopamine. Young adult mice expressing the PD-associated G2019S missense mutation in Lrrk2 also exhibit deficits in fronto-striatal-based cognitive tasks. In mice and humans, cognitive functions require dynamic adjustments in glutamatergic synapse strength through cell-surface trafficking of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid-type glutamate receptors (AMPARs), but it is unknown how LRRK2 mutation impacts dynamic features of AMPAR trafficking in striatal projection neurons (SPNs). Here, we used Lrrk2G2019S knockin mice to show that surface AMPAR subunit stoichiometry is altered biochemically and functionally in mutant SPNs in dorsomedial striatum to favor the incorporation of GluA1 over GluA2. GluA1-containing AMPARs were resistant to internalization from the cell surface, leaving an excessive accumulation of GluA1 on the surface within and outside synapses. This negatively impacted trafficking dynamics that normally support synapse strengthening, as GluA1-containing AMPARs failed to increase at synapses in response to a potentiating stimulus and showed significantly reduced surface mobility. Surface GluA2-containing AMPARs were expressed at normal levels in synapses, indicating subunit-selective impairment. Abnormal surface accumulation of GluA1 was independent of PKA activity and was limited to D1R SPNs. Since LRRK2 mutation is thought to be part of a common PD pathogenic pathway, our data suggest that sustained, striatal cell-type specific changes in AMPAR composition and trafficking contribute to cognitive or other impairments associated with PD.

Purely elastic turbulence in pressure-driven channel flows.

Solutions of long, flexible polymer molecules are complex fluids that simultaneously exhibit fluid-like and solid-like behavior. When subjected to an external flow, dilute polymer solutions exhibit elastic turbulence-a unique, chaotic flow state absent in Newtonian fluids, like water. Unlike its Newtonian counterpart, elastic turbulence is caused by polymer molecules stretching and aligning in the flow, and can occur at vanishing inertia. While experimental realizations of elastic turbulence are well-documented, there is currently no understanding of its mechanism. Here, we present large-scale direct numerical simulations of elastic turbulence in pressure-driven flows through straight channels. We demonstrate that the transition to elastic turbulence is sub-critical, giving rise to spot-like flow structures that, further away from the transition, eventually spread throughout the domain. We provide evidence that elastic turbulence is organized around unstable coherent states that are localized close to the channel midplane.

In vivo functional phenotypes from a computational epistatic model of evolution.

Computational models of evolution are valuable for understanding the dynamics of sequence variation, to infer phylogenetic relationships or potential evolutionary pathways and for biomedical and industrial applications. Despite these benefits, few have validated their propensities to generate outputs with in vivo functionality, which would enhance their value as accurate and interpretable evolutionary algorithms. We demonstrate the power of epistasis inferred from natural protein families to evolve sequence variants in an algorithm we developed called sequence evolution with epistatic contributions (SEEC). Utilizing the Hamiltonian of the joint probability of sequences in the family as fitness metric, we sampled and experimentally tested for in vivo [Formula: see text]-lactamase activity in Escherichia coli TEM-1 variants. These evolved proteins can have dozens of mutations dispersed across the structure while preserving sites essential for both catalysis and interactions. Remarkably, these variants retain family-like functionality while being more active than their wild-type predecessor. We found that depending on the inference method used to generate the epistatic constraints, different parameters simulate diverse selection strengths. Under weaker selection, local Hamiltonian fluctuations reliably predict relative changes to variant fitness, recapitulating neutral evolution. SEEC has the potential to explore the dynamics of neofunctionalization, characterize viral fitness landscapes, and facilitate vaccine development.

Charge barriers in the kidney elimination of engineered nanoparticles.

The renal elimination pathway is increasingly harnessed to reduce nonspecific accumulation of engineered nanoparticles within the body and expedite their clinical applications. While the size of nanoparticles is recognized as crucial for their passive filtration through the glomerulus due to its limited pore size, the influence of nanoparticle charge on their transport and interactions within the kidneys remains largely elusive. Herein, we report that the proximal tubule and peritubular capillary, rather than the glomerulus, serve as primary charge barriers to the transport of charged nanoparticles within the kidney. Employing a series of ultrasmall, renal-clearable gold nanoparticles (AuNPs) with precisely engineered surface charge characteristics as multimodal imaging agents, we have tracked their distribution and retention across various kidney components following intravenous administration. Our results reveal that retention in the proximal tubules is governed not by the nanoparticle's zeta-potential, but by direct Coulombic interactions between the positively charged surface ligands of the AuNPs and the negatively charged microvilli of proximal tubules. However, further enhancing these interactions leads to increased binding of the positively charged AuNPs to the peritubular capillaries during the initial phase of elimination, subsequently facilitating their slow passage through the glomeruli and interaction with tubular components in a charge-selective manner. By identifying these two critical charge-dependent barriers in the renal transport of nanoparticles, our findings offer a fundamental insight for the design of renal nanomedicines tailored for selective targeting within the kidney, laying down a foundation for developing targeting renal nanomedicines for future kidney disease management in the clinics.

Efficiency and resilience of cooperation in asymmetric social dilemmas.

Direct reciprocity is a powerful mechanism for cooperation in social dilemmas. The very logic of reciprocity, however, seems to require that individuals are symmetric, and that everyone has the same means to influence each others' payoffs. Yet in many applications, individuals are asymmetric. Herein, we study the effect of asymmetry in linear public good games. Individuals may differ in their endowments (their ability to contribute to a public good) and in their productivities (how effective their contributions are). Given the individuals' productivities, we ask which allocation of endowments is optimal for cooperation. To this end, we consider two notions of optimality. The first notion focuses on the resilience of cooperation. The respective endowment distribution ensures that full cooperation is feasible even under the most adverse conditions. The second notion focuses on efficiency. The corresponding endowment distribution maximizes group welfare. Using analytical methods, we fully characterize these two endowment distributions. This analysis reveals that both optimality notions favor some endowment inequality: More productive players ought to get higher endowments. Yet the two notions disagree on how unequal endowments are supposed to be. A focus on resilience results in less inequality. With additional simulations, we show that the optimal endowment allocation needs to account for both the resilience and the efficiency of cooperation.

Direct observation correlates NFκB cRel in B cells with activating and terminating their proliferative program.

Antibody responses require the proliferative expansion of B cells controlled by affinity-dependent signals. Yet, proliferative bursts are heterogeneous, varying between 0 and 8 divisions in response to the same stimulus. NFκB cRel is activated in response to immune stimulation in B cells and is genetically required for proliferation. Here, we asked whether proliferative heterogeneity is controlled by natural variations in cRel abundance. We developed a fluorescent reporter mTFP1-cRel for the direct observation of cRel in live proliferating B cells. We found that cRel is heterogeneously distributed among naïve B cells, which are enriched for high expressors in a heavy-tailed distribution. We found that high cRel expressors show faster activation of the proliferative program, but do not sustain it well, with population expansion decaying earlier. With a mathematical model of the molecular network, we showed that cRel heterogeneity arises from balancing positive feedback by autoregulation and negative feedback by its inhibitor IκBε, confirmed by mouse knockouts. Using live-cell fluorescence microscopy, we showed that increased cRel primes B cells for early proliferation via higher basal expression of the cell cycle driver cMyc. However, peak cMyc induction amplitude is constrained by incoherent feedforward regulation, decoding the fold change of cRel activity to terminate the proliferative burst. This results in a complex nonlinear, nonmonotonic relationship between cRel expression and the extent of proliferation. These findings emphasize the importance of direct observational studies to complement gene knockout results and to learn about quantitative relationships between biological processes and their key regulators in the context of natural variations.

Modeling direct air carbon capture and storage in a 1.5 °C climate future using historical analogs.

Limiting the rise in global temperature to 1.5 °C will rely, in part, on technologies to remove CO2 from the atmosphere. However, many carbon dioxide removal (CDR) technologies are in the early stages of development, and there is limited data to inform predictions of their future adoption. Here, we present an approach to model adoption of early-stage technologies such as CDR and apply it to direct air carbon capture and storage (DACCS). Our approach combines empirical data on historical technology analogs and early adoption indicators to model a range of feasible growth pathways. We use these pathways as inputs to an integrated assessment model (the Global Change Analysis Model, GCAM) and evaluate their effects under an emissions policy to limit end-of-century temperature change to 1.5 °C. Adoption varies widely across analogs, which share different strategic similarities with DACCS. If DACCS growth mirrors high-growth analogs (e.g., solar photovoltaics), it can reach up to 4.9 GtCO2 removal by midcentury, compared to as low as 0.2 GtCO2 for low-growth analogs (e.g., natural gas pipelines). For these slower growing analogs, unabated fossil fuel generation in 2050 is reduced by 44% compared to high-growth analogs, with implications for energy investments and stranded assets. Residual emissions at the end of the century are also substantially lower (by up to 43% and 34% in transportation and industry) under lower DACCS scenarios. The large variation in growth rates observed for different analogs can also point to policy takeaways for enabling DACCS.

Robust multivariable Mendelian randomization based on constrained maximum likelihood.

Mendelian randomization (MR) is a powerful tool for causal inference with observational genome-wide association study (GWAS) summary data. Compared to the more commonly used univariable MR (UVMR), multivariable MR (MVMR) not only is more robust to the notorious problem of genetic (horizontal) pleiotropy but also estimates the direct effect of each exposure on the outcome after accounting for possible mediating effects of other exposures. Despite promising applications, there is a lack of studies on MVMR's theoretical properties and robustness in applications. In this work, we propose an efficient and robust MVMR method based on constrained maximum likelihood (cML), called MVMR-cML, with strong theoretical support. Extensive simulations demonstrate that MVMR-cML performs better than other existing MVMR methods while possessing the above two advantages over its univariable counterpart. An application to several large-scale GWAS summary datasets to infer causal relationships between eight cardiometabolic risk factors and coronary artery disease (CAD) highlights the usefulness and some advantages of the proposed method. For example, after accounting for possible pleiotropic and mediating effects, triglyceride (TG), low-density lipoprotein cholesterol (LDL), and systolic blood pressure (SBP) had direct effects on CAD; in contrast, the effects of high-density lipoprotein cholesterol (HDL), diastolic blood pressure (DBP), and body height diminished after accounting for other risk factors.