The rockefeller university

In the brain, fine-scale correlations combine to produce macroscopic patterns of activity. However, as experiments record from larger and larger populations, we approach a fundamental bottleneck: the number of correlations one would like to include in a model grows larger than the available data. In this undersampled regime, one must focus on a sparse subset of correlations; the optimal choice contains the maximum information about patterns of activity or, equivalently, minimizes the entropy of the inferred maximum entropy model. Applying this "minimax entropy" principle is generally intractable, but here we present an exact and scalable solution for pairwise correlations that combine to form a tree (a network without loops). Applying our method to over 1000 neurons in the mouse hippocampus, we find that the optimal tree of correlations reduces our uncertainty about the population activity by 14% (over 50 times more than a random tree). Despite containing only 0.1% of all pairwise correlations, this minimax entropy model accurately predicts the observed large-scale synchrony in neural activity and becomes even more accurate as the population grows. The inferred Ising model is almost entirely ferromagnetic (with positive interactions) and exhibits signatures of thermodynamic criticality. Together, these results suggest that a large amount of information may be compressed into a small number of correlations between neurons, and provide the tools for identifying the most important correlations in other complex living systems.

INTRODUCTION: Alzheimer's disease (AD) is characterized by amyloid-beta (A beta), hyperphosphorylated tau, chronic neuroinflammation, blood-brain barrier (BBB) damage, and synaptic dysfunction, leading to neuronal loss and cognitive deficits. Vascular proteins, including fibrinogen, extravasate into the brain, further contributing to damage and inflammation. Fibrinogen's interaction with A beta is well-established, but how this interaction contributes to synaptic dysfunction in AD is unknown. METHODS: Organotypic hippocampal cultures (OHC) were exposed to A beta 42 oligomers, fibrinogen, or A beta 42/fibrinogen complexes. Synaptotoxicity was analyzed by Western blot. A beta 42 oligomers, fibrinogen, or their complexes were intracerebroventricularly injected into mice. Histopathological AD markers, synaptotoxicity, neuroinflammation, and vascular markers were observed by Western blot and immunofluorescence. RESULTS: A beta 42/fibrinogen complexes led to synaptic loss, tau181 phosphorylation, neuroinflammation, and BBB disruption, independent of Mac1/CD11b receptor signaling. Blocking A beta 42/fibrinogen complex formation prevented synaptotoxicity. DISCUSSION: These findings indicate that the A beta 42/fibrinogen complex has a synergistic impact on hippocampal synaptotoxicity and neuroinflammation. Highlights Fibrinogen binds to the central region of A beta, forming a plasmin-resistant complex. The A beta/fibrinogen complex induces synaptotoxicity, inflammation, and BBB disruption. Synaptotoxicity induced by the complex is independent of Mac1 receptor signaling.

Failure to anticipate new forms of antibiotic resistance has led to resistance developing rapidly to virtually all antibiotics that have entered clinical use. Many of the most problematic types of resistance originated in the environment, where ancient arms races between antibiotic-producing microbes and their competitors have created vast arsenals of antibiotics and resistance. Seizing on the knowledge that resistance in nature is frequently a harbinger of future clinical resistance, we propose introducing an additional step into the antibiotic development process that exploits the susceptibility of development candidates to environmental resistance as a metric for prioritizing lead compounds and as a roadmap for their structural optimization. Using the antibiotic albicidin as a model, we show how the environmental resistome can guide the development of more resistance-tolerant leads. We used metagenomic surveys to identify resistance vulnerabilities for albicidin and guide the synthesis of analogs that evade the resistance threats. We found that natural albicidin analogs (congeners) were especially enriched in structural features that escape resistance, which inspired our syntheses and provided compelling evidence for the evolution of families of antibiotics in response to resistance in nature. The coupling of metagenomics-based resistance surveillance with structural optimizations of new antibiotics is a broadly applicable approach that is easily integrated into antibiotic development programs to generate compounds that are more resilient in the face of resistance.

How does growth encode form in developing organisms? Many different spatiotemporal growth profiles may sculpt tissues into the same target 3D shapes, but only specific growth patterns are observed in animal and plant development. In particular, growth profiles may differ in their degree of spatial variation and growth anisotropy; however, the criteria that distinguish observed patterns of growth from other possible alternatives are not understood. Here we exploit the mathematical formalism of quasiconformal transformations to formulate the problem of "growth pattern selection" quantitatively in the context of 3D shape formation by growing 2D epithelial sheets. We propose that nature settles on growth patterns that are the "simplest" in a certain way. Specifically, we demonstrate that growth pattern selection can be formulated as an optimization problem and solved for the trajectories that minimize spatiotemporal variation in areal growth rates and deformation anisotropy. The result is a complete prediction for the growth of the surface, including not only a set of intermediate shapes, but also a prediction for cell displacement along those surfaces in the process of growth. Optimization of growth trajectories for both idealized surfaces and those observed in nature show that relative growth rates can be uniformized at the cost of introducing anisotropy. Minimizing the variation of programmed growth rates can therefore be viewed as a generic mechanism for growth pattern selection and may help us to understand the prevalence of anisotropy in developmental programs.

Despite the fundamental importance of gut microbes, the genetic basis of their colonization remains largely unexplored. Here, by applying cross-species genotype-habitat association at the tree-of-life scale, we identify conserved microbial gene modules associated with gut colonization. Across thousands of species, we discovered 79 taxonomically diverse putative colonization factors organized into operonic and non-operonic modules. They include previously characterized colonization pathways such as autoinducer-2 biosynthesis and novel processes including tRNA modification and translation. In vivo functional validation revealed YigZ (IMPACT family) and tRNA hydroxylation protein-P (TrhP) are required for E. coli intestinal colonization. Overexpressing YigZ alone is sufficient to enhance colonization of the poorly colonizing MG1655 E. coli by >100-fold. Moreover, natural allelic variations in YigZ impact inter-strain colonization efficiency. Our findings highlight the power of large-scale comparative genomics in revealing the genetic basis of microbial adaptations. These broadly conserved colonization factors may prove critical for understanding gastrointestinal (GI) dysbiosis and developing therapeutics.

Broad immune responses are needed to mitigate viral evolution and escape. To induce antibodies against conserved receptor-binding domain (RBD) regions of SARS-like betacoronavirus (sarbecovirus) spike proteins that recognize SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs isolated from mosaic-8b-immunized rabbits, some on par with Pemgarda, the only currently FDA-approved therapeutic mAb. Deep mutational scanning, in vitro selection of spike resistance mutations, and single-particle cryo-electron microscopy structures of spike-antibody complexes demonstrated targeting of conserved RBD epitopes. Rabbit mAbs included critical D-gene segment RBD-recognizing features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment, thus demonstrating that the immune systems of humans and other mammals can utilize different antibody gene segments to arrive at similar modes of antigen recognition. These results suggest that animal models can be used to elicit anti-RBD mAbs with similar properties to those raised in humans, which can then be humanized for therapeutic use, and that mosaic RBD nanoparticle immunization coupled with multiplexed screening represents an efficient way to generate and select broadly cross-reactive therapeutic pan-sarbecovirus and pan-SARS-CoV-2 variant mAbs.

The most dynamic and repetitive regions of great ape genomes have traditionally been excluded from comparative studies(1-3). Consequently, our understanding of the evolution of our species is incomplete. Here we present haplotype-resolved reference genomes and comparative analyses of six ape species: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan and siamang. We achieve chromosome-level contiguity with substantial sequence accuracy (<1 error in 2.7 megabases) and completely sequence 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, to provide in-depth evolutionary insights. Comparative analyses enabled investigations of the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference genome. Such regions include newly minted gene families in lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes and subterminal heterochromatin. This resource serves as a comprehensive baseline for future evolutionary studies of humans and our closest living ape relatives.

Realistic paths to gene therapy for the X-linked bleeding disorder hemophilia started to materialize in the mid 1990s, resulting in disease correction in small and large animal models. Out of a diversity of approaches, in vivo adeno-associated viral (AAV) gene transfer to hepatocytes emerged as the most promising strategy, eventually forming the basis for multiple advanced clinical trials and regulatory approval of two products for the treatment of hemophilia B (coagulation factor IX deficiency) and one for hemophilia A (factor VIII deficiency). Ideally, gene therapy is effective with a single administration, thus providing therapeutic factor levels over a period of years, without the need for frequent injections. Overcoming multiple obstacles, some not predicted by preclinical studies, sustained partial to complete correction of coagulation for several years to an entire decade has now been documented in patients, with observation ongoing. A hyperactive form of FIX improved efficacy in hemophilia B, and superior engineered variants of FVIII are emerging. Nonetheless, challenges remain, including pre-existing immunity to AAV capsids, toxicities, inter-patient variability in response to treatment, and difficulty in obtaining durable therapeutic expression of FVIII. In alternative approaches, in vivo gene editing and ex vivo gene therapies targeting hemopoietic cells are in development.

Spermatogenesis is a key developmental process underlying the origination of newly evolved genes. However, rapid cell type-specific transcriptomic divergence of the Drosophila germline has posed a significant technical barrier for comparative single- cell RNA- sequencing studies. By quantifying a surprisingly strong correlation between species- and cell type-specific divergence in three closely related Drosophila species, we apply a statistical procedure to identify a core set of 198 genes that are highly predictive of cell type identity while remaining robust to species- specific differences that span over 25 to 30 My of evolution. We then utilize cell type classifications based on the 198- gene set to show how transcriptional divergence in cell type increases throughout spermatogenic developmental time. After validating these cross- species cell type classifications using RNA fluorescence in situ hybridization and imaging, we then investigate the influence of genome organization on the molecular evolution of spermatogenesis vis- a- vis transcriptional bursting. We first show altering transcriptional burst size contributes to premeiotic transcription and altering bursting frequency contributes to postmeiotic expression. We then report global differences in autosomal vs. X chromosomal transcription may arise in a developmental stage preceding full testis organogenesis by showing evolutionarily conserved decreases in X- linked transcription bursting kinetics in all examined somatic and germline cell types. Finally, we provide evidence supporting the cultivator model of de novo gene origination by demonstrating how the appearance of newly evolved testis- specific transcripts potentially provides short- range regulation of neighboring genes' transcriptional bursting properties during key stages of spermatogenesis.

The primary motor cortex (M1) is a central hub for motor learning and execution. M1 is composed of heterogeneous cell types with varying relationships to movement. Here, we tagged active neurons at different stages of motor task performance in mice and characterized cell type composition. We identified corticothalamic neurons (M1CT) as consistently enriched with training progression. Using two-photon calcium imaging, we found that M1CT activity is largely suppressed during movement, and this negative correlation augments with training. Increasing M1CT activity through closed-loop optogenetic manipulations during forelimb movement significantly hinders execution, an effect that became stronger with training. Similar manipulations, however, had little effect on locomotion. In contrast, M1 corticospinal neurons positively correlate with movement, with an increase during training. We uncovered that M1CT neurons suppress corticospinal activity via feedforward inhibition, also scaling with training. These results identify a permissive role of corticothalamic neurons in movement execution through disinhibition of corticospinal neurons.