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Predictive coding is a fundamental function of the cortex. The predictive routing model proposes a neurophysiological implementation for predictive coding. Predictions are fed back from the deep-layer cortex via alpha/beta (8 to 30 Hz) oscillations. They inhibit the gamma (40 to 100 Hz) and spiking that feed sensory inputs forward. Unpredicted inputs arrive in circuits unprepared by alpha/beta, resulting in enhanced gamma and spiking. To test the predictive routing model and its role in consciousness, we collected data from intracranial recordings of macaque monkeys during passive presentation of auditory oddballs before and after propofol-mediated loss of consciousness (LOC). In line with the predictive routing model, alpha/beta oscillations in the awake state served to inhibit the processing of predictable stimuli. Propofol-mediated LOC eliminated alpha/beta modulation by a predictable stimulus in the sensory cortex and alpha/beta coherence between sensory and frontal areas. As a result, oddball stimuli evoked enhanced gamma power, late period (>200 ms from stimulus onset) spiking, and superficial layer sinks in the sensory cortex. LOC also resulted in diminished decodability of pattern-level prediction error signals in the higher-order cortex. Therefore, the auditory cortex was in a disinhibited state during propofol-mediated LOC. However, despite these enhanced feedforward responses in the auditory cortex, there was a loss of differential spiking to oddballs in the higher-order cortex. This may be a consequence of a loss of within-area and interareal spike-field coupling in the alpha/beta and gamma frequency bands. These results provide strong constraints for current theories of consciousness., Competing Interests: Competing interests statement:E.N.B. holds patents on anesthetic state monitoring and control. E.N.B. holds founding interest in PASCALL, a start-up developing physiological monitoring systems; receives royalties from intellectual property through Massachusetts General Hospital licensed to Masimo. The interests of E.N.B. were reviewed and are managed by Massachusetts General Hospital and Mass General Brigham in accordance with their conflict of interest policies.

Nanoparticle-based RNA delivery has shown great progress in recent years with the approval of two mRNA vaccines for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and a liver-targeted siRNA therapy. Here, we discuss the preclinical and clinical advancement of new generations of RNA delivery therapies along multiple axes. Improvements in cargo design such as RNA circularization and data-driven untranslated region optimization can drive better mRNA expression. New materials discovery research has driven improved delivery to extrahepatic targets such as the lung and splenic immune cells, which could lead to pulmonary gene therapy and better cancer vaccines, respectively. Other organs and even specific cell types can be targeted for delivery via conjugation of small molecule ligands, antibodies, or peptides to RNA delivery nanoparticles. Moreover, the immune response to any RNA delivery nanoparticle plays a crucial role in determining efficacy. Targeting increased immunogenicity without induction of reactogenic side effects is crucial for vaccines, while minimization of immune response is important for gene therapies. New developments have addressed each of these priorities. Last, we discuss the range of RNA delivery clinical trials targeting diverse organs, cell types, and diseases and suggest some key advances that may play a role in the next wave of therapies., Competing Interests: Competing interests statement:Both R.L. and D.G.A. have extremely extensive sets of patents including many in the RNA delivery space. For some examples, see: D.G.A.: US Patent App. 18/080,299 (J.W. is also an author on this patent application) US Patent 11,608,412 US Patent 11,603,396 US Patent 11,459,304 R.L.: US Patent 11,279,928 US Patent 10,933,139.

RNA interference (RNAi) therapeutics are an emerging class of medicines that selectively target mRNA transcripts to silence protein production and combat disease. Despite the recent progress, a generalizable approach for monitoring the efficacy of RNAi therapeutics without invasive biopsy remains a challenge. Here, we describe the development of a self-reporting, theranostic nanoparticle that delivers siRNA to silence a protein that drives cancer progression while also monitoring the functional activity of its downstream targets. Our therapeutic target is the transcription factor SMARCE1, which was previously identified as a key driver of invasion in early-stage breast cancer. Using a doxycycline-inducible shRNA knockdown in OVCAR8 ovarian cancer cells both in vitro and in vivo, we demonstrate that SMARCE1 is a master regulator of genes encoding proinvasive proteases in a model of human ovarian cancer. We additionally map the peptide cleavage profiles of SMARCE1-regulated proteases so as to design a readout for downstream enzymatic activity. To demonstrate the therapeutic and diagnostic potential of our approach, we engineered self-assembled layer-by-layer nanoparticles that can encapsulate nucleic acid cargo and be decorated with peptide substrates that release a urinary reporter upon exposure to SMARCE1-related proteases. In an orthotopic ovarian cancer xenograft model, theranostic nanoparticles were able to knockdown SMARCE1 which was in turn reported through a reduction in protease-activated urinary reporters. These LBL nanoparticles both silence gene products by delivering siRNA and noninvasively report on downstream target activity by delivering synthetic biomarkers to sites of disease, enabling dose-finding studies as well as longitudinal assessments of efficacy., Competing Interests: Competing interests statement:S.N.B. holds equity in Amplifyer Bio, Catalio Capital, Earli, Impilo Therapeutics, Matrisome Bio, Ochre Bio, Port Therapeutics, Ropirio Therapeutics, Satellite Bio, Sunbird Bio, and Vertex Pharmaceuticals, advises Danaher, Moderna, Pictet, and Xilio Therapeutics, and receives sponsored research funding from Johnson & Johnson, and Owlstone Medical. P.T.H. is the co-founder and member of the Board of LayerBio, Inc., a member of the Board of Alector Therapeutics, Focal Biomedical and the Board of Senda Biosciences, a Flagship company, and a former member of the Scientific Advisory Board of Moderna Therapeutics. The remaining authors declare no competing interests.

Competing Interests: Competing interests statement:The authors declare no competing interest.

The immune isolation of cells within devices has the potential to enable long-term protein replacement and functional cures for a range of diseases, without requiring immune suppressive therapy. However, a lack of vasculature and the formation of fibrotic capsules around cell immune-isolating devices limits oxygen availability, leading to hypoxia and cell death in vivo. This is particularly problematic for pancreatic islet cells that have high O 2 requirements. Here, we combine bioelectronics with encapsulated cell therapies to develop the first wireless, battery-free oxygen-generating immune-isolating device (O 2 -Macrodevice) for the oxygenation and immune isolation of cells in vivo. The system relies on electrochemical water splitting based on a water-vapor reactant feed, sustained by wireless power harvesting based on a flexible resonant inductive coupling circuit. As such, the device does not require pumping, refilling, or ports for recharging and does not generate potentially toxic side products. Through systematic in vitro studies with primary cell lines and cell lines engineered to secrete protein, we demonstrate device performance in preventing hypoxia in ambient oxygen concentrations as low as 0.5%. Importantly, this device has shown the potential to enable subcutaneous (SC) survival of encapsulated islet cells, in vivo in awake, freely moving, immune-competent animals. Islet transplantation in Type I Diabetes represents an important application space, and 1-mo studies in immune-competent animals with SC implants show that the O 2 -Macrodevice allows for survival and function of islets at high densities (~1,000 islets/cm 2 ) in vivo without immune suppression and induces normoglycemia in diabetic animals.

Multiple myeloma (MM), a hematologic malignancy that preferentially colonizes the bone marrow, remains incurable with a survival rate of 3 to 6 mo for those with advanced disease despite great efforts to develop effective therapies. Thus, there is an urgent clinical need for innovative and more effective MM therapeutics. Insights suggest that endothelial cells within the bone marrow microenvironment play a critical role. Specifically, cyclophilin A (CyPA), a homing factor secreted by bone marrow endothelial cells (BMECs), is critical to MM homing, progression, survival, and chemotherapeutic resistance. Thus, inhibition of CyPA provides a potential strategy to simultaneously inhibit MM progression and sensitize MM to chemotherapeutics, improving therapeutic response. However, inhibiting factors from the bone marrow endothelium remains challenging due to delivery barriers. Here, we utilize both RNA interference (RNAi) and lipid-polymer nanoparticles to engineer a potential MM therapy, which targets CyPA within blood vessels of the bone marrow. We used combinatorial chemistry and high-throughput in vivo screening methods to engineer a nanoparticle platform for small interfering RNA (siRNA) delivery to bone marrow endothelium. We demonstrate that our strategy inhibits CyPA in BMECs, preventing MM cell extravasation in vitro. Finally, we show that siRNA-based silencing of CyPA in a murine xenograft model of MM, either alone or in combination with the Food and Drug Administration (FDA)-approved MM therapeutic bortezomib, reduces tumor burden and extends survival. This nanoparticle platform may provide a broadly enabling technology to deliver nucleic acid therapeutics to other malignancies that home to bone marrow.

From proteins to chromosomes, polymers fold into specific conformations that control their biological function. Polymer folding has long been studied with equilibrium thermodynamics, yet intracellular organization and regulation involve energy-consuming, active processes. Signatures of activity have been measured in the context of chromatin motion, which shows spatial correlations and enhanced subdiffusion only in the presence of adenosine triphosphate. Moreover, chromatin motion varies with genomic coordinate, pointing toward a heterogeneous pattern of active processes along the sequence. How do such patterns of activity affect the conformation of a polymer such as chromatin? We address this question by combining analytical theory and simulations to study a polymer subjected to sequence-dependent correlated active forces. Our analysis shows that a local increase in activity (larger active forces) can cause the polymer backbone to bend and expand, while less active segments straighten out and condense. Our simulations further predict that modest activity differences can drive compartmentalization of the polymer consistent with the patterns observed in chromosome conformation capture experiments. Moreover, segments of the polymer that show correlated active (sub)diffusion attract each other through effective long-ranged harmonic interactions, whereas anticorrelations lead to effective repulsions. Thus, our theory offers nonequilibrium mechanisms for forming genomic compartments, which cannot be distinguished from affinity-based folding using structural data alone. As a first step toward exploring whether active mechanisms contribute to shaping genome conformations, we discuss a data-driven approach.

Cohesin folds mammalian interphase chromosomes by extruding the chromatin fiber into numerous loops. "Loop extrusion" can be impeded by chromatin-bound factors, such as CTCF, which generates characteristic and functional chromatin organization patterns. It has been proposed that transcription relocalizes or interferes with cohesin and that active promoters are cohesin loading sites. However, the effects of transcription on cohesin have not been reconciled with observations of active extrusion by cohesin. To determine how transcription modulates extrusion, we studied mouse cells in which we could alter cohesin abundance, dynamics, and localization by genetic "knockouts" of the cohesin regulators CTCF and Wapl. Through Hi-C experiments, we discovered intricate, cohesin-dependent contact patterns near active genes. Chromatin organization around active genes exhibited hallmarks of interactions between transcribing RNA polymerases (RNAPs) and extruding cohesins. These observations could be reproduced by polymer simulations in which RNAPs were moving barriers to extrusion that obstructed, slowed, and pushed cohesins. The simulations predicted that preferential loading of cohesin at promoters is inconsistent with our experimental data. Additional ChIP-seq experiments showed that the putative cohesin loader Nipbl is not predominantly enriched at promoters. Therefore, we propose that cohesin is not preferentially loaded at promoters and that the barrier function of RNAP accounts for cohesin accumulation at active promoters. Altogether, we find that RNAP is an extrusion barrier that is not stationary, but rather, translocates and relocalizes cohesin. Loop extrusion and transcription might interact to dynamically generate and maintain gene interactions with regulatory elements and shape functional genomic organization.

The COVID-19 pandemic has created a large population of patients who are slow to recover consciousness following mechanical ventilation and sedation in the intensive care unit. Few clinical scenarios are comparable. Possible exceptions are the rare patients in post-cardiac arrest coma with minimal to no structural brain injuries who recovered cognitive and motor functions after prolonged delays. A common electroencephalogram (EEG) signature seen in these patients is burst suppression [8]. Biophysical modeling has shown that burst suppression is likely a signature of a neurometabolic state that preserves basic cellular function "during states of lowered energy availability." These states likely act as a brain protective mechanism [9]. Similar EEG patterns are observed in the anoxia resistant painted turtle [24]. We present a conceptual analysis to interpret the brain state of COVID-19 patients suffering prolonged recovery of consciousness. We begin with the Ching model and integrate findings from other clinical scenarios and studies of the anoxia-tolerant physiology of the painted turtle. We postulate that prolonged recovery of consciousness in COVID-19 patients could reflect the effects of modest hypoxic injury to neurons and the unmasking of latent neuroprotective mechanisms in the human brain. This putative protective down-regulated state appears similar to that observed in the painted turtle and suggests new approaches to enhancing coma recovery [12].

Liver regeneration is a well-orchestrated process that is typically studied in animal models. Although previous animal studies have offered many insights into liver regeneration, human biology is less well understood. To this end, we developed a three-dimensional (3D) platform called structurally vascularized hepatic ensembles for analyzing regeneration (SHEAR) to model multiple aspects of human liver regeneration. SHEAR enables control over hemodynamic alterations to mimic those that occur during liver injury and regeneration and supports the administration of biochemical inputs such as cytokines and paracrine interactions with endothelial cells. We found that exposing the endothelium-lined channel to fluid flow led to increased secretion of regeneration-associated factors. Stimulation with relevant cytokines not only amplified the secretory response, but also induced cell-cycle entry of primary human hepatocytes (PHHs) embedded within the device. Further, we identified endothelial-derived mediators that are sufficient to initiate proliferation of PHHs in this context. Collectively, the data presented here underscore the importance of multicellular models that can recapitulate high-level tissue functions and demonstrate that the SHEAR device can be used to discover and validate conditions that promote human liver regeneration.

Community-acquired pneumonia (CAP) has been brought to the forefront of global health priorities due to the COVID-19 pandemic. However, classification of viral versus bacterial pneumonia etiology remains a significant clinical challenge. To this end, we have engineered a panel of activity-based nanosensors that detect the dysregulated activity of pulmonary host proteases implicated in the response to pneumonia-causing pathogens and produce a urinary readout of disease. The nanosensor targets were selected based on a human protease transcriptomic signature for pneumonia etiology generated from 33 unique publicly available study cohorts. Five mouse models of bacterial or viral CAP were developed to assess the ability of the nanosensors to produce etiology-specific urinary signatures. Machine learning algorithms were used to train diagnostic classifiers that could distinguish infected mice from healthy controls and differentiate those with bacterial versus viral pneumonia with high accuracy. This proof-of-concept diagnostic approach demonstrates a way to distinguish pneumonia etiology based solely on the host proteolytic response to infection.

SARS-CoV-2 is a highly pathogenic virus that evades antiviral immunity by interfering with host protein synthesis, mRNA stability, and protein trafficking. The SARS-CoV-2 nonstructural protein 1 (Nsp1) uses its C-terminal domain to block the messenger RNA (mRNA) entry channel of the 40S ribosome to inhibit host protein synthesis. However, how SARS-CoV-2 circumvents Nsp1-mediated suppression for viral protein synthesis and if the mechanism can be targeted therapeutically remain unclear. Here, we show that N- and C-terminal domains of Nsp1 coordinate to drive a tuned ratio of viral to host translation, likely to maintain a certain level of host fitness while maximizing replication. We reveal that the stem-loop 1 (SL1) region of the SARS-CoV-2 5' untranslated region (5' UTR) is necessary and sufficient to evade Nsp1-mediated translational suppression. Targeting SL1 with locked nucleic acid antisense oligonucleotides inhibits viral translation and makes SARS-CoV-2 5' UTR vulnerable to Nsp1 suppression, hindering viral replication in vitro at a nanomolar concentration, as well as providing protection against SARS-CoV-2-induced lethality in transgenic mice expressing human ACE2. Thus, SL1 allows Nsp1 to switch infected cells from host to SARS-CoV-2 translation, presenting a therapeutic target against COVID-19 that is conserved among immune-evasive variants. This unique strategy of unleashing a virus' own virulence mechanism against itself could force a critical trade-off between drug resistance and pathogenicity., Competing Interests: The authors declare no competing interest., (Copyright © 2022 the Author(s). Published by PNAS.)

Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been challenging. Combination therapies play an important role in antiviral therapies, due to their improved efficacy and reduced toxicity. Recent approaches have applied deep learning to identify synergistic drug combinations for diseases with vast preexisting datasets, but these are not applicable to new diseases with limited combination data, such as COVID-19. Given that drug synergy often occurs through inhibition of discrete biological targets, here we propose a neural network architecture that jointly learns drug-target interaction and drug-drug synergy. The model consists of two parts: a drug-target interaction module and a target-disease association module. This design enables the model to utilize drug-target interaction data and single-agent antiviral activity data, in addition to available drug-drug combination datasets, which may be small in nature. By incorporating additional biological information, our model performs significantly better in synergy prediction accuracy than previous methods with limited drug combination training data. We empirically validated our model predictions and discovered two drug combinations, remdesivir and reserpine as well as remdesivir and IQ-1S, which display strong antiviral SARS-CoV-2 synergy in vitro. Our approach, which was applied here to address the urgent threat of COVID-19, can be readily extended to other diseases for which a dearth of chemical-chemical combination data exists., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Global containment of COVID-19 still requires accessible and affordable vaccines for low- and middle-income countries (LMICs). Recently approved vaccines provide needed interventions, albeit at prices that may limit their global access. Subunit vaccines based on recombinant proteins are suited for large-volume microbial manufacturing to yield billions of doses annually, minimizing their manufacturing cost. These types of vaccines are well-established, proven interventions with multiple safe and efficacious commercial examples. Many vaccine candidates of this type for SARS-CoV-2 rely on sequences containing the receptor-binding domain (RBD), which mediates viral entry to cells via ACE2. Here we report an engineered sequence variant of RBD that exhibits high-yield manufacturability, high-affinity binding to ACE2, and enhanced immunogenicity after a single dose in mice compared to the Wuhan-Hu-1 variant used in current vaccines. Antibodies raised against the engineered protein exhibited heterotypic binding to the RBD from two recently reported SARS-CoV-2 variants of concern (501Y.V1/V2). Presentation of the engineered RBD on a designed virus-like particle (VLP) also reduced weight loss in hamsters upon viral challenge., Competing Interests: Competing interest statement: L.E.C., K.R.L., and J.C.L. have filed patents related to the InSCyT system and methods. N.C.D., S.R.A., and J.C.L. have filed a patent related to the RBD-L452K-F490W sequence. K.R.L., L.E.C., and M.K.T. are current employees at Sunflower Therapeutics PBC. N.P.K., J.Y.W., and C.W. are named as inventors on patent applications filed by the University of Washington related to the I3-01 nanoparticle. N.P.K. is a co-founder, shareholder, paid consultant, and chair of the scientific advisory board of Icosavax, Inc. and has received an unrelated sponsored research agreement from Pfizer. J.C.L. has interests in Sunflower Therapeutics PBC, Pfizer, Honeycomb Biotechnologies, OneCyte Biotechnologies, QuantumCyte, Amgen, and Repligen. J.C.L.’s interests are reviewed and managed under MIT’s policies for potential conflicts of interest. J.M.S. is an employee of the Bill & Melinda Gates Medical Research Institute. H.K. is an employee of the Bill & Melinda Gates Foundation., (Copyright © 2021 the Author(s). Published by PNAS.)

Superspreaders, infected individuals who result in an outsized number of secondary cases, are believed to underlie a significant fraction of total SARS-CoV-2 transmission. Here, we combine empirical observations of SARS-CoV and SARS-CoV-2 transmission and extreme value statistics to show that the distribution of secondary cases is consistent with being fat-tailed, implying that large superspreading events are extremal, yet probable, occurrences. We integrate these results with interaction-based network models of disease transmission and show that superspreading, when it is fat-tailed, leads to pronounced transmission by increasing dispersion. Our findings indicate that large superspreading events should be the targets of interventions that minimize tail exposure., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

T cells exhibit remarkable sensitivity and selectivity in detecting and responding to agonist peptides (p) bound to MHC molecules in a sea of self pMHC molecules. Despite much work, understanding of the underlying mechanisms of distinguishing such ligands remains incomplete. Here, we quantify T cell discriminatory capacity using channel capacity, a direct measure of the signaling network's ability to discriminate between antigen-presenting cells (APCs) displaying either self ligands or a mixture of self and agonist ligands. This metric shows how differences in information content between these two types of peptidomes are decoded by the topology and rates of kinetic proofreading signaling steps inside T cells. Using channel capacity, we constructed numerically substantiated hypotheses to explain the discriminatory role of a recently identified slow LAT Y132 phosphorylation step. Our results revealed that in addition to the number and kinetics of sequential signaling steps, a key determinant of discriminatory capability is spatial localization of a minimum number of these steps to the engaged TCR. Biochemical and imaging experiments support these findings. Our results also reveal the discriminatory role of early negative feedback and necessary amplification conferred by late positive feedback., Competing Interests: The authors declare no competing interest.

Asymptomatic carriers of Plasmodium parasites hamper malaria control and eradication. Achieving malaria eradication requires ultrasensitive diagnostics for low parasite density infections (<100 parasites per microliter blood) that work in resource-limited settings (RLS). Sensitive point-of-care diagnostics are also lacking for nonfalciparum malaria, which is characterized by lower density infections and may require additional therapy for radical cure. Molecular methods, such as PCR, have high sensitivity and specificity, but remain high-complexity technologies impractical for RLS. Here we describe a CRISPR-based diagnostic for ultrasensitive detection and differentiation of Plasmodium falciparum , Plasmodium vivax , Plasmodium ovale , and Plasmodium malariae , using the nucleic acid detection platform SHERLOCK (specific high-sensitivity enzymatic reporter unlocking). We present a streamlined, field-applicable, diagnostic comprised of a 10-min SHERLOCK parasite rapid extraction protocol, followed by SHERLOCK for 60 min for Plasmodium species-specific detection via fluorescent or lateral flow strip readout. We optimized one-pot, lyophilized, isothermal assays with a simplified sample preparation method independent of nucleic acid extraction, and showed that these assays are capable of detection below two parasites per microliter blood, a limit of detection suggested by the World Health Organization. Our P. falciparum and P. vivax assays exhibited 100% sensitivity and specificity on clinical samples (5 P. falciparum and 10 P. vivax samples). This work establishes a field-applicable diagnostic for ultrasensitive detection of asymptomatic carriers as well as a rapid point-of-care clinical diagnostic for nonfalciparum malaria species and low parasite density P. falciparum infections., Competing Interests: Competing interest statement: J.J.C. is a cofounder and director of Sherlock Biosciences, which is a diagnostic company focused on CRISPR diagnostics. However, of note and relevance, Sherlock Biosciences does not have rights to or interest in global health applications, such as malaria diagnostics., (Copyright © 2020 the Author(s). Published by PNAS.)

Natural infections and vaccination with a pathogen typically stimulate the production of potent antibodies specific for the pathogen through a Darwinian evolutionary process known as affinity maturation. Such antibodies provide protection against reinfection by the same strain of a pathogen. A highly mutable virus, like HIV or influenza, evades recognition by these strain-specific antibodies via the emergence of new mutant strains. A vaccine that elicits antibodies that can bind to many diverse strains of the virus-known as broadly neutralizing antibodies (bnAbs)-could protect against highly mutable pathogens. Despite much work, the mechanisms by which bnAbs emerge remain uncertain. Using a computational model of affinity maturation, we studied a wide variety of vaccination strategies. Our results suggest that an effective strategy to maximize bnAb evolution is through a sequential immunization protocol, wherein each new immunization optimally increases the pressure on the immune system to target conserved antigenic sites, thus conferring breadth. We describe the mechanisms underlying why sequentially driving the immune system increasingly further from steady state, in an optimal fashion, is effective. The optimal protocol allows many evolving B cells to become bnAbs via diverse evolutionary paths., Competing Interests: The authors declare no competing interest.

The recent advent of immune checkpoint inhibitor (CPI) antibodies has revolutionized many aspects of cancer therapy, but the efficacy of these breakthrough therapeutics remains limited, as many patients fail to respond for reasons that still largely evade understanding. An array of studies in human patients and animal models has demonstrated that local signaling can generate strongly immunosuppressive microenvironments within tumors, and emerging evidence suggests that delivery of immunostimulatory molecules into tumors can have therapeutic effects. Nanoparticle formulations of these cargoes offer a promising way to maximize their delivery and to enhance the efficacy of checkpoint inhibitors. We developed a modular nanoparticle system capable of encapsulating an array of immunostimulatory oligonucleotides that, in some cases, greatly increase their potency to activate inflammatory signaling within immune cells in vitro. We hypothesized that these immunostimulatory nanoparticles could suppress tumor growth by activating similar signaling in vivo, and thereby also improve responsiveness to immune checkpoint inhibitor antibody therapies. We found that our engineered nanoparticles carrying a CpG DNA ligand of TLR9 can suppress tumor growth in several animal models of various cancers, resulting in an abscopal effect on distant tumors, and improving responsiveness to anti-CTLA4 treatment with combinatorial effects after intratumoral administration. Moreover, by incorporating tumor-homing peptides, immunostimulatory nucleotide-bearing nanoparticles facilitate antitumor efficacy after systemic intravenous (i.v.) administration., Competing Interests: Competing interest statement: S.N.B. holds equity in Glympse Bio and Impilo Therapeutics, is a director at Vertex, consults for Cristal, Maverick, and Moderna, and receives sponsored research funding from Johnson & Johnson., (Copyright © 2020 the Author(s). Published by PNAS.)

Coulomb interactions play a major role in determining the thermodynamics, structure, and dynamics of condensed-phase systems, but often present significant challenges. Computer simulations usually use periodic boundary conditions to minimize corrections from finite cell boundaries but the long range of the Coulomb interactions generates significant contributions from distant periodic images of the simulation cell, usually calculated by Ewald sum techniques. This can add significant overhead to computer simulations and hampers the development of intuitive local pictures and simple analytic theory. In this paper, we present a general framework based on local molecular field theory to accurately determine the contributions from long-ranged Coulomb interactions to the potential of mean force between ionic or apolar hydrophobic solutes in dilute aqueous solutions described by standard classical point charge water models. The simplest approximation leads to a short solvent (SS) model, with truncated solvent-solvent and solute-solvent Coulomb interactions and long-ranged but screened Coulomb interactions only between charged solutes. The SS model accurately describes the interplay between strong short-ranged solute core interactions, local hydrogen-bond configurations, and long-ranged dielectric screening of distant charges, competing effects that are difficult to capture in standard implicit solvent models., Competing Interests: The authors declare no competing interest.

Primary human hepatocytes (PHHs) are an essential tool for modeling drug metabolism and liver disease. However, variable plating efficiencies, short lifespan in culture, and resistance to genetic manipulation have limited their use. Here, we show that the pyrrolizidine alkaloid retrorsine improves PHH repopulation of chimeric mice on average 10-fold and rescues the ability of even poorly plateable donor hepatocytes to provide cells for subsequent ex vivo cultures. These mouse-passaged (mp) PHH cultures overcome the marked donor-to-donor variability of cryopreserved PHH and remain functional for months as demonstrated by metabolic assays and infection with hepatitis B virus and Plasmodium falciparum mpPHH can be efficiently genetically modified in culture, mobilized, and then recultured as spheroids or retransplanted to create highly humanized mice that carry a genetically altered hepatocyte graft. Together, these advances provide flexible tools for the study of human liver disease and evaluation of hepatocyte-targeted gene therapy approaches., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

To separate replicated sister chromatids during mitosis, eukaryotes and prokaryotes have structural maintenance of chromosome (SMC) condensin complexes that were recently shown to organize chromosomes by a process known as DNA loop extrusion. In rapidly dividing bacterial cells, the process of separating sister chromatids occurs concomitantly with ongoing transcription. How transcription interferes with the condensin loop-extrusion process is largely unexplored, but recent experiments have shown that sites of high transcription may directionally affect condensin loop extrusion. We quantitatively investigate different mechanisms of interaction between condensin and elongating RNA polymerases (RNAPs) and find that RNAPs are likely steric barriers that can push and interact with condensins. Supported by chromosome conformation capture and chromatin immunoprecipitation for cells after transcription inhibition and RNAP degradation, we argue that translocating condensins must bypass transcribing RNAPs within ∼1 to 2 s of an encounter at rRNA genes and within ∼10 s at protein-coding genes. Thus, while individual RNAPs have little effect on the progress of loop extrusion, long, highly transcribed operons can significantly impede the extrusion process. Our data and quantitative models further suggest that bacterial condensin loop extrusion occurs by 2 independent, uncoupled motor activities; the motors translocate on DNA in opposing directions and function together to enlarge chromosomal loops, each independently bypassing steric barriers in their path. Our study provides a quantitative link between transcription and 3D genome organization and proposes a mechanism of interactions between SMC complexes and elongating transcription machinery relevant from bacteria to higher eukaryotes., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

Zika virus (ZIKV) is a neurotropic and neurovirulent arbovirus that has severe detrimental impact on the developing human fetal brain. To date, little is known about the factors required for ZIKV infection of human neural cells. We identified ZIKV host genes in human pluripotent stem cell (hPSC)-derived neural progenitors (NPs) using a genome-wide CRISPR-Cas9 knockout screen. Mutations of host factors involved in heparan sulfation, endocytosis, endoplasmic reticulum processing, Golgi function, and interferon activity conferred resistance to infection with the Uganda strain of ZIKV and a more recent North American isolate. Host genes essential for ZIKV replication identified in human NPs also provided a low level of protection against ZIKV in isogenic human astrocytes. Our findings provide insights into host-dependent mechanisms for ZIKV infection in the highly vulnerable human NP cells and identify molecular targets for potential therapeutic intervention., Competing Interests: Conflict of interest statement: R.J. is a cofounder of Fate Therapeutics, Fulcrum Therapeutics and Omega Therapeutics. I.B. and L.G. are cofounders of E25Bio, Inc.

A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, whether they are unconstrained therapeutic transplants, migrating cells during tumor metastasis, or cell populations induced by an immunological response, the role of oxygen in their fate and function is known to be pivotal albeit not well understood in vivo. To address such a challenge in the case of generation of a bioartificial pancreas, we have combined fluorine magnetic resonance imaging and unsupervised machine learning to monitor over time the spatial arrangement and the oxygen content of implants encapsulating pancreatic islets that are unconstrained in the intraperitoneal (IP) space of healthy and diabetic mice. Statistically significant trends in the postimplantation temporal dependence of oxygen content between aggregates of 0.5-mm or 1.5-mm alginate microcapsules were identified in vivo by looking at their dispersity as well as arrangement in clusters of different size and estimating oxygen content on a pixel-by-pixel basis from thousands of 2D images. Ultimately, we found that this dependence is stronger for decreased implant capsule size consistent with their tendency to also induce a larger immunological response. Beyond the bioartificial pancreas, this work provides a framework for the simultaneous spatiotemporal tracking and oxygen sensing of other cell populations and biomaterials that change over time to better understand and improve therapeutic design across diverse applications such as cellular transplant therapy, treatments preventing metastatic formation, and modulators for improving immunologic response, for all of which oxygen is a major mechanistic component., Competing Interests: Conflict of interest statement: D.G.A. and R.L. are founding scientists of Sigilon Therapeutics, a biotech company based in Cambridge, MA.

Circulating tumor cells (CTCs) play a fundamental role in cancer progression. However, in mice, limited blood volume and the rarity of CTCs in the bloodstream preclude longitudinal, in-depth studies of these cells using existing liquid biopsy techniques. Here, we present an optofluidic system that continuously collects fluorescently labeled CTCs from a genetically engineered mouse model (GEMM) for several hours per day over multiple days or weeks. The system is based on a microfluidic cell sorting chip connected serially to an unanesthetized mouse via an implanted arteriovenous shunt. Pneumatically controlled microfluidic valves capture CTCs as they flow through the device, and CTC-depleted blood is returned back to the mouse via the shunt. To demonstrate the utility of our system, we profile CTCs isolated longitudinally from animals over 4 days of treatment with the BET inhibitor JQ1 using single-cell RNA sequencing (scRNA-Seq) and show that our approach eliminates potential biases driven by intermouse heterogeneity that can occur when CTCs are collected across different mice. The CTC isolation and sorting technology presented here provides a research tool to help reveal details of how CTCs evolve over time, allowing studies to credential changes in CTCs as biomarkers of drug response and facilitating future studies to understand the role of CTCs in metastasis., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

Improved biomarkers are needed for prostate cancer, as the current gold standards have poor predictive value. Tests for circulating prostate-specific antigen (PSA) levels are susceptible to various noncancer comorbidities in the prostate and do not provide prognostic information, whereas physical biopsies are invasive, must be performed repeatedly, and only sample a fraction of the prostate. Injectable biosensors may provide a new paradigm for prostate cancer biomarkers by querying the status of the prostate via a noninvasive readout. Proteases are an important class of enzymes that play a role in every hallmark of cancer; their activities could be leveraged as biomarkers. We identified a panel of prostate cancer proteases through transcriptomic and proteomic analysis. Using this panel, we developed a nanosensor library that measures protease activity in vitro using fluorescence and in vivo using urinary readouts. In xenograft mouse models, we applied this nanosensor library to classify aggressive prostate cancer and to select predictive substrates. Last, we coformulated a subset of nanosensors with integrin-targeting ligands to increase sensitivity. These targeted nanosensors robustly classified prostate cancer aggressiveness and outperformed PSA. This activity-based nanosensor library could be useful throughout clinical management of prostate cancer, with both diagnostic and prognostic utility., Competing Interests: Conflict of interest statement: J.S.D. and S.N.B. are listed as inventors on a patent application related to this work. A.D.W. is currently an employee of Glympse Bio. S.N.B. is a shareholder of and consultant to Glympse Bio.

Mammalian chromatin is spatially organized at many scales showing two prominent features in interphase: ( i ) alternating regions (1-10 Mb) of active and inactive chromatin that spatially segregate into different compartments, and ( ii ) domains (<1 Mb), that is, regions that preferentially interact internally [topologically associating domains (TADs)] and are central to gene regulation. There is growing evidence that TADs are formed by active extrusion of chromatin loops by cohesin, whereas compartmentalization is established according to local chromatin states. Here, we use polymer simulations to examine how loop extrusion and compartmental segregation work collectively and potentially interfere in shaping global chromosome organization. A model with differential attraction between euchromatin and heterochromatin leads to phase separation and reproduces compartmentalization as observed in Hi-C. Loop extrusion, essential for TAD formation, in turn, interferes with compartmentalization. Our integrated model faithfully reproduces Hi-C data from puzzling experimental observations where altering loop extrusion also led to changes in compartmentalization. Specifically, depletion of chromatin-associated cohesin reduced TADs and revealed finer compartments, while increased processivity of cohesin strengthened large TADs and reduced compartmentalization; and depletion of the TAD boundary protein CTCF weakened TADs while leaving compartments unaffected. We reveal that these experimental perturbations are special cases of a general polymer phenomenon of active mixing by loop extrusion. Our results suggest that chromatin organization on the megabase scale emerges from competition of nonequilibrium active loop extrusion and epigenetically defined compartment structure., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Maternal Zika virus (ZIKV) infection during pregnancy is recognized as the cause of an epidemic of microcephaly and other neurological anomalies in human fetuses. It remains unclear how ZIKV accesses the highly vulnerable population of neural progenitors of the fetal central nervous system (CNS), and which cell types of the CNS may be viral reservoirs. In contrast, the related dengue virus (DENV) does not elicit teratogenicity. To model viral interaction with cells of the fetal CNS in vitro, we investigated the tropism of ZIKV and DENV for different induced pluripotent stem cell-derived human cells, with a particular focus on microglia-like cells. We show that ZIKV infected isogenic neural progenitors, astrocytes, and microglia-like cells (pMGLs), but was only cytotoxic to neural progenitors. Infected glial cells propagated ZIKV and maintained ZIKV load over time, leading to viral spread to susceptible cells. DENV triggered stronger immune responses and could be cleared by neural and glial cells more efficiently. pMGLs, when cocultured with neural spheroids, invaded the tissue and, when infected with ZIKV, initiated neural infection. Since microglia derive from primitive macrophages originating in proximity to the maternal vasculature, they may act as a viral reservoir for ZIKV and establish infection of the fetal brain. Infection of immature neural stem cells by invading microglia may occur in the early stages of pregnancy, before angiogenesis in the brain rudiments. Our data are also consistent with ZIKV and DENV affecting the integrity of the blood-brain barrier, thus allowing infection of the brain later in life., Competing Interests: Conflict of interest statement: R.J. is a cofounder of Fate Therapeutics, Fulcrum Therapeutics, and Omega Therapeutics. R.J. and reviewer H.S. were coauthors on a meeting summary report published in 2015. They are not research collaborators.

HIV controllers (HCs) are individuals who can naturally control HIV infection, partially due to potent HIV-specific CD8+ T cell responses. Here, we examined the hypothesis that superior function of CD8+ T cells from HCs is encoded by their T cell receptors (TCRs). We compared the functional properties of immunodominant HIV-specific TCRs obtained from HLA-B*2705 HCs and chronic progressors (CPs) following expression in primary T cells. T cells transduced with TCRs from HCs and CPs showed equivalent induction of epitope-specific cytotoxicity, cytokine secretion, and antigen-binding properties. Transduced T cells comparably, albeit modestly, also suppressed HIV infection in vitro and in humanized mice. We also performed extensive molecular dynamics simulations that provided a structural basis for similarities in cytotoxicity and epitope cross-reactivity. These results demonstrate that the differential abilities of HIV-specific CD8+ T cells from HCs and CPs are not genetically encoded in the TCRs alone and must depend on additional factors., Competing Interests: The authors declare no conflict of interest.

HIV is a highly mutable virus, and over 30 years after its discovery, a vaccine or cure is still not available. The isolation of broadly neutralizing antibodies (bnAbs) from HIV-infected patients has led to renewed hope for a prophylactic vaccine capable of combating the scourge of HIV. A major challenge is the design of immunogens and vaccination protocols that can elicit bnAbs that target regions of the virus's spike proteins where the likelihood of mutational escape is low due to the high fitness cost of mutations. Related challenges include the choice of combinations of bnAbs for therapy. An accurate representation of viral fitness as a function of its protein sequences (a fitness landscape), with explicit accounting of the effects of coupling between mutations, could help address these challenges. We describe a computational approach that has allowed us to infer a fitness landscape for gp160, the HIV polyprotein that comprises the viral spike that is targeted by antibodies. We validate the inferred landscape through comparisons with experimental fitness measurements, and various other metrics. We show that an effective antibody that prevents immune escape must selectively bind to high escape cost residues that are surrounded by those where mutations incur a low fitness cost, motivating future applications of our landscape for immunogen design., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Downstream metabolic events can contribute to the lethality of drugs or agents that interact with a primary cellular target. In bacteria, the production of reactive oxygen species (ROS) has been associated with the lethal effects of a variety of stresses including bactericidal antibiotics, but the relative contribution of this oxidative component to cell death depends on a variety of factors. Experimental evidence has suggested that unresolvable DNA problems caused by incorporation of oxidized nucleotides into nascent DNA followed by incomplete base excision repair contribute to the ROS-dependent component of antibiotic lethality. Expression of the chimeric periplasmic-cytoplasmic MalE-LacZ 72-47 protein is an historically important lethal stress originally identified during seminal genetic experiments that defined the SecY-dependent protein translocation system. Multiple, independent lines of evidence presented here indicate that the predominant mechanism for MalE-LacZ lethality shares attributes with the ROS-dependent component of antibiotic lethality. MalE-LacZ lethality requires molecular oxygen, and its expression induces ROS production. The increased susceptibility of mutants sensitive to oxidative stress to MalE-LacZ lethality indicates that ROS contribute causally to cell death rather than simply being produced by dying cells. Observations that support the proposed mechanism of cell death include MalE-LacZ expression being bacteriostatic rather than bactericidal in cells that overexpress MutT, a nucleotide sanitizer that hydrolyzes 8-oxo-dGTP to the monophosphate, or that lack MutM and MutY, DNA glycosylases that process base pairs involving 8-oxo-dGTP. Our studies suggest stress-induced physiological changes that favor this mode of ROS-dependent death., Competing Interests: Conflict of interest statement: J.J.C. is a scientific cofounder and Scientific Advisory Board chair of EnBiotix, Inc., a start-up focused on antibiotic development.

Brain tumor-initiating cells (BTICs) have been identified as key contributors to therapy resistance, recurrence, and progression of diffuse gliomas, particularly glioblastoma (GBM). BTICs are elusive therapeutic targets that reside across the blood-brain barrier, underscoring the urgent need to develop novel therapeutic strategies. Additionally, intratumoral heterogeneity and adaptations to therapeutic pressure by BTICs impede the discovery of effective anti-BTIC therapies and limit the efficacy of individual gene targeting. Recent discoveries in the genetic and epigenetic determinants of BTIC tumorigenesis offer novel opportunities for RNAi-mediated targeting of BTICs. Here we show that BTIC growth arrest in vitro and in vivo is accomplished via concurrent siRNA knockdown of four transcription factors (SOX2, OLIG2, SALL2, and POU3F2) that drive the proneural BTIC phenotype delivered by multiplexed siRNA encapsulation in the lipopolymeric nanoparticle 7C1. Importantly, we demonstrate that 7C1 nano-encapsulation of multiplexed RNAi is a viable BTIC-targeting strategy when delivered directly in vivo in an established mouse brain tumor. Therapeutic potential was most evident via a convection-enhanced delivery method, which shows significant extension of median survival in two patient-derived BTIC xenograft mouse models of GBM. Our study suggests that there is potential advantage in multiplexed targeting strategies for BTICs and establishes a flexible nonviral gene therapy platform with the capacity to channel multiplexed RNAi schemes to address the challenges posed by tumor heterogeneity., Competing Interests: Conflict of interest statement: D.G.A. and R.L. have filed intellectual property protection related to the 7C1 nanoparticle. D.Y. has an evaluation agreement with Cell Signaling Technology regarding the use of the CellSimpleTM Cell Analyzer and reagents. The authors declare that they have no further competing interests.

The immune system consists of many specialized cell populations that communicate with each other to achieve systemic immune responses. Our analyses of various measured immune cell population frequencies in healthy humans and their responses to diverse stimuli show that human immune variation is continuous in nature, rather than characterized by discrete groups of similar individuals. We show that the same three key combinations of immune cell population frequencies can define an individual's immunotype and predict a diverse set of functional responses to cytokine stimulation. We find that, even though interindividual variations in specific cell population frequencies can be large, unrelated individuals of younger age have more homogeneous immunotypes than older individuals. Across age groups, cytomegalovirus seropositive individuals displayed immunotypes characteristic of older individuals. The conceptual framework for defining immunotypes suggested by our results could guide the development of better therapies that appropriately modulate collective immunotypes, rather than individual immune components., Competing Interests: The authors declare no conflict of interest.

Nucleic acid therapeutics are limited by inefficient delivery to target tissues and cells and by an incomplete understanding of how nanoparticle structure affects biodistribution to off-target organs. Although thousands of nanoparticle formulations have been designed to deliver nucleic acids, most nanoparticles have been tested in cell culture contexts that do not recapitulate systemic in vivo delivery. To increase the number of nanoparticles that could be tested in vivo, we developed a method to simultaneously measure the biodistribution of many chemically distinct nanoparticles. We formulated nanoparticles to carry specific nucleic acid barcodes, administered the pool of particles, and quantified particle biodistribution by deep sequencing the barcodes. This method distinguished previously characterized lung- and liver- targeting nanoparticles and accurately reported relative quantities of nucleic acid delivered to tissues. Barcode sequences did not affect delivery, and no evidence of particle mixing was observed for tested particles. By measuring the biodistribution of 30 nanoparticles to eight tissues simultaneously, we identified chemical properties promoting delivery to some tissues relative to others. Finally, particles that distributed to the liver also silenced gene expression in hepatocytes when formulated with siRNA. This system can facilitate discovery of nanoparticles targeting specific tissues and cells and accelerate the study of relationships between chemical structure and delivery in vivo.

The covalent modification of therapeutic biomolecules has been broadly explored, leading to a number of clinically approved modified protein drugs. These modifications are typically intended to address challenges arising in biopharmaceutical practice by promoting improved stability and shelf life of therapeutic proteins in formulation, or modifying pharmacokinetics in the body. Toward these objectives, covalent modification with poly(ethylene glycol) (PEG) has been a common direction. Here, a platform approach to biopharmaceutical modification is described that relies on noncovalent, supramolecular host-guest interactions to endow proteins with prosthetic functionality. Specifically, a series of cucurbit[7]uril (CB[7])-PEG conjugates are shown to substantially increase the stability of three distinct protein drugs in formulation. Leveraging the known and high-affinity interaction between CB[7] and an N-terminal aromatic residue on one specific protein drug, insulin, further results in altering of its pharmacological properties in vivo by extending activity in a manner dependent on molecular weight of the attached PEG chain. Supramolecular modification of therapeutic proteins affords a noncovalent route to modify its properties, improving protein stability and activity as a formulation excipient. Furthermore, this offers a modular approach to append functionality to biopharmaceuticals by noncovalent modification with other molecules or polymers, for applications in formulation or therapy., Competing Interests: R.L. and J.H. are co-founders of Kala Pharmaceuticals, Inc.

Strategies to elicit Abs that can neutralize diverse strains of a highly mutable pathogen are likely to result in a potent vaccine. Broadly neutralizing Abs (bnAbs) against HIV have been isolated from patients, proving that the human immune system can evolve them. Using computer simulations and theory, we study immunization with diverse mixtures of variant antigens (Ags). Our results show that particular choices for the number of variant Ags and the mutational distances separating them maximize the probability of inducing bnAbs. The variant Ags represent potentially conflicting selection forces that can frustrate the Darwinian evolutionary process of affinity maturation. An intermediate level of frustration maximizes the chance of evolving bnAbs. A simple model makes vivid the origin of this principle of optimal frustration. Our results, combined with past studies, suggest that an appropriately chosen permutation of immunization with an optimally designed mixture (using the principles that we describe) and sequential immunization with variant Ags that are separated by relatively large mutational distances may best promote the evolution of bnAbs., Competing Interests: The authors declare no conflict of interest.

Dopamine (DA) promotes wakefulness, and DA transporter inhibitors such as dextroamphetamine and methylphenidate are effective for increasing arousal and inducing reanimation, or active emergence from general anesthesia. DA neurons in the ventral tegmental area (VTA) are involved in reward processing, motivation, emotion, reinforcement, and cognition, but their role in regulating wakefulness is less clear. The current study was performed to test the hypothesis that selective optogenetic activation of VTA DA neurons is sufficient to induce arousal from an unconscious, anesthetized state. Floxed-inverse (FLEX)-Channelrhodopsin2 (ChR2) expression was targeted to VTA DA neurons in DA transporter (DAT)-cre mice (ChR2+ group; n = 6). Optical VTA stimulation in ChR2+ mice during continuous, steady-state general anesthesia (CSSGA) with isoflurane produced behavioral and EEG evidence of arousal and restored the righting reflex in 6/6 mice. Pretreatment with the D1 receptor antagonist SCH-23390 before optical VTA stimulation inhibited the arousal responses and restoration of righting in 6/6 ChR2+ mice. In control DAT-cre mice, the VTA was targeted with a viral vector lacking the ChR2 gene (ChR2- group; n = 5). VTA optical stimulation in ChR2- mice did not restore righting or produce EEG changes during isoflurane CSSGA in 5/5 mice. These results provide compelling evidence that selective stimulation of VTA DA neurons is sufficient to induce the transition from an anesthetized, unconscious state to an awake state, suggesting critical involvement in behavioral arousal., Competing Interests: The authors declare no conflict of interest.

Vaccines have had broad medical impact, but existing vaccine technologies and production methods are limited in their ability to respond rapidly to evolving and emerging pathogens, or sudden outbreaks. Here, we develop a rapid-response, fully synthetic, single-dose, adjuvant-free dendrimer nanoparticle vaccine platform wherein antigens are encoded by encapsulated mRNA replicons. To our knowledge, this system is the first capable of generating protective immunity against a broad spectrum of lethal pathogen challenges, including H1N1 influenza, Toxoplasma gondii, and Ebola virus. The vaccine can be formed with multiple antigen-expressing replicons, and is capable of eliciting both CD8(+) T-cell and antibody responses. The ability to generate viable, contaminant-free vaccines within days, to single or multiple antigens, may have broad utility for a range of diseases.

The orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas-based knockouts and RNA-interference-based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.

A human gut-on-a-chip microdevice was used to coculture multiple commensal microbes in contact with living human intestinal epithelial cells for more than a week in vitro and to analyze how gut microbiome, inflammatory cells, and peristalsis-associated mechanical deformations independently contribute to intestinal bacterial overgrowth and inflammation. This in vitro model replicated results from past animal and human studies, including demonstration that probiotic and antibiotic therapies can suppress villus injury induced by pathogenic bacteria. By ceasing peristalsis-like motions while maintaining luminal flow, lack of epithelial deformation was shown to trigger bacterial overgrowth similar to that observed in patients with ileus and inflammatory bowel disease. Analysis of intestinal inflammation on-chip revealed that immune cells and lipopolysaccharide endotoxin together stimulate epithelial cells to produce four proinflammatory cytokines (IL-8, IL-6, IL-1β, and TNF-α) that are necessary and sufficient to induce villus injury and compromise intestinal barrier function. Thus, this human gut-on-a-chip can be used to analyze contributions of microbiome to intestinal pathophysiology and dissect disease mechanisms in a controlled manner that is not possible using existing in vitro systems or animal models.

Advances in nanomedicine are providing sophisticated functions to precisely control the behavior of nanoscale drugs and diagnostics. Strategies that coopt protease activity as molecular triggers are increasingly important in nanoparticle design, yet the pharmacokinetics of these systems are challenging to understand without a quantitative framework to reveal nonintuitive associations. We describe a multicompartment mathematical model to predict strategies for ultrasensitive detection of cancer using synthetic biomarkers, a class of activity-based probes that amplify cancer-derived signals into urine as a noninvasive diagnostic. Using a model formulation made of a PEG core conjugated with protease-cleavable peptides, we explore a vast design space and identify guidelines for increasing sensitivity that depend on critical parameters such as enzyme kinetics, dosage, and probe stability. According to this model, synthetic biomarkers that circulate in stealth but then activate at sites of disease have the theoretical capacity to discriminate tumors as small as 5 mm in diameter-a threshold sensitivity that is otherwise challenging for medical imaging and blood biomarkers to achieve. This model may be adapted to describe the behavior of additional activity-based approaches to allow cross-platform comparisons, and to predict allometric scaling across species.

The signal-to-noise ratio (SNR), a commonly used measure of fidelity in physical systems, is defined as the ratio of the squared amplitude or variance of a signal relative to the variance of the noise. This definition is not appropriate for neural systems in which spiking activity is more accurately represented as point processes. We show that the SNR estimates a ratio of expected prediction errors and extend the standard definition to one appropriate for single neurons by representing neural spiking activity using point process generalized linear models (PP-GLM). We estimate the prediction errors using the residual deviances from the PP-GLM fits. Because the deviance is an approximate χ(2) random variable, we compute a bias-corrected SNR estimate appropriate for single-neuron analysis and use the bootstrap to assess its uncertainty. In the analyses of four systems neuroscience experiments, we show that the SNRs are -10 dB to -3 dB for guinea pig auditory cortex neurons, -18 dB to -7 dB for rat thalamic neurons, -28 dB to -14 dB for monkey hippocampal neurons, and -29 dB to -20 dB for human subthalamic neurons. The new SNR definition makes explicit in the measure commonly used for physical systems the often-quoted observation that single neurons have low SNRs. The neuron's spiking history is frequently a more informative covariate for predicting spiking propensity than the applied stimulus. Our new SNR definition extends to any GLM system in which the factors modulating the response can be expressed as separate components of a likelihood function.

Multidrug resistance (MDR) in cancer cells is a substantial limitation to the success of chemotherapy. Here, we describe facile means to overcome resistance by silencing the multidrug resistance protein 1 (MRP1), before chemotherapeutic drug delivery in vivo with a single local application. Our platform contains hydrogel embedded with dark-gold nanoparticles modified with 5-fluorouracil (5-FU)-intercalated nanobeacons that serve as an ON/OFF molecular nanoswitch triggered by the increased MRP1 expression within the tumor tissue microenvironment. This nanoswitch can sense and overcome MDR prior to local drug release. The nanobeacons comprise a 5-FU intercalated DNA hairpin, which is labeled with a near-infrared (NIR) dye and a dark-quencher. The nanobeacons are designed to open and release the intercalated drug only upon hybridization of the DNA hairpin to a complementary target, an event that restores fluorescence emission due to nanobeacons conformational reorganization. Despite the cross-resistance to 5-FU, more than 90% tumor reduction is achieved in vivo in a triple-negative breast cancer model following 80% MRP1 silencing compared with the continuous tumor growth following only drug or nanobeacon administration. Our approach can be applied to reverse cross-resistance to other chemotherapeutic drugs and restore treatment efficacy. As a universal nanotheranostic probe, this platform can pave the way to early cancer detection and treatment.

Since its discovery and isolation, exogenous insulin has dramatically changed the outlook for patients with diabetes. However, even when patients strictly follow an insulin regimen, serious complications can result as patients experience both hyperglycemic and hypoglycemic states. Several chemically or genetically modified insulins have been developed that tune the pharmacokinetics of insulin activity for personalized therapy. Here, we demonstrate a strategy for the chemical modification of insulin intended to promote both long-lasting and glucose-responsive activity through the incorporation of an aliphatic domain to facilitate hydrophobic interactions, as well as a phenylboronic acid for glucose sensing. These synthetic insulin derivatives enable rapid reversal of blood glucose in a diabetic mouse model following glucose challenge, with some derivatives responding to repeated glucose challenges over a 13-h period. The best-performing insulin derivative provides glucose control that is superior to native insulin, with responsiveness to glucose challenge improved over a clinically used long-acting insulin derivative. Moreover, continuous glucose monitoring reveals responsiveness matching that of a healthy pancreas. This synthetic approach to insulin modification could afford both long-term and glucose-mediated insulin activity, thereby reducing the number of administrations and improving the fidelity of glycemic control for insulin therapy. The described work is to our knowledge the first demonstration of a glucose-binding modified insulin molecule with glucose-responsive activity verified in vivo.

The enormous genetic diversity and mutability of HIV has prevented effective control of this virus by natural immune responses or vaccination. Evolution of the circulating HIV population has thus occurred in response to diverse, ultimately ineffective, immune selection pressures that randomly change from host to host. We show that the interplay between the diversity of human immune responses and the ways that HIV mutates to evade them results in distinct sets of sequences defined by similar collectively coupled mutations. Scaling laws that relate these sets of sequences resemble those observed in linguistics and other branches of inquiry, and dynamics reminiscent of neural networks are observed. Like neural networks that store memories of past stimulation, the circulating HIV population stores memories of host-pathogen combat won by the virus. We describe an exactly solvable model that captures the main qualitative features of the sets of sequences and a simple mechanistic model for the origin of the observed scaling laws. Our results define collective mutational pathways used by HIV to evade human immune responses, which could guide vaccine design.

Rapid eye movement (REM) sleep is an important component of the natural sleep/wake cycle, yet the mechanisms that regulate REM sleep remain incompletely understood. Cholinergic neurons in the mesopontine tegmentum have been implicated in REM sleep regulation, but lesions of this area have had varying effects on REM sleep. Therefore, this study aimed to clarify the role of cholinergic neurons in the pedunculopontine tegmentum (PPT) and laterodorsal tegmentum (LDT) in REM sleep generation. Selective optogenetic activation of cholinergic neurons in the PPT or LDT during non-REM (NREM) sleep increased the number of REM sleep episodes and did not change REM sleep episode duration. Activation of cholinergic neurons in the PPT or LDT during NREM sleep was sufficient to induce REM sleep.

Classical nonparametric spectral analysis uses sliding windows to capture the dynamic nature of most real-world time series. This universally accepted approach fails to exploit the temporal continuity in the data and is not well-suited for signals with highly structured time-frequency representations. For a time series whose time-varying mean is the superposition of a small number of oscillatory components, we formulate nonparametric batch spectral analysis as a Bayesian estimation problem. We introduce prior distributions on the time-frequency plane that yield maximum a posteriori (MAP) spectral estimates that are continuous in time yet sparse in frequency. Our spectral decomposition procedure, termed spectrotemporal pursuit, can be efficiently computed using an iteratively reweighted least-squares algorithm and scales well with typical data lengths. We show that spectrotemporal pursuit works by applying to the time series a set of data-derived filters. Using a link between Gaussian mixture models, l1 minimization, and the expectation-maximization algorithm, we prove that spectrotemporal pursuit converges to the global MAP estimate. We illustrate our technique on simulated and real human EEG data as well as on human neural spiking activity recorded during loss of consciousness induced by the anesthetic propofol. For the EEG data, our technique yields significantly denoised spectral estimates that have significantly higher time and frequency resolution than multitaper spectral estimates. For the neural spiking data, we obtain a new spectral representation of neuronal firing rates. Spectrotemporal pursuit offers a robust spectral decomposition framework that is a principled alternative to existing methods for decomposing time series into a small number of smooth oscillatory components.

Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that drive rapid population growth and carcinogenesis. Cancer genomics demonstrates that these few driver mutations occur alongside thousands of random passenger mutations--a natural consequence of cancer's elevated mutation rate. Some passengers are deleterious to cancer cells, yet have been largely ignored in cancer research. In population genetics, however, the accumulation of mildly deleterious mutations has been shown to cause population meltdown. Here we develop a stochastic population model where beneficial drivers engage in a tug-of-war with frequent mildly deleterious passengers. These passengers present a barrier to cancer progression describable by a critical population size, below which most lesions fail to progress, and a critical mutation rate, above which cancers melt down. We find support for this model in cancer age-incidence and cancer genomics data that also allow us to estimate the fitness advantage of drivers and fitness costs of passengers. We identify two regimes of adaptive evolutionary dynamics and use these regimes to understand successes and failures of different treatment strategies. A tumor's load of deleterious passengers can explain previously paradoxical treatment outcomes and suggest that it could potentially serve as a biomarker of response to mutagenic therapies. The collective deleterious effect of passengers is currently an unexploited therapeutic target. We discuss how their effects might be exacerbated by current and future therapies.