The rockefeller university

Invariant object recognition-the ability to recognize objects across size, rotation, or context-is fundamental for making sense of a dynamic visual world. Though traditionally studied in primates, emerging evidence suggests rodents recognize objects across a range of identity-preserving transformations. We demonstrate that rats robustly perform visual object recognition and explore a neural pathway that may underlie this capacity by developing a pipeline from high-throughput behavior training to cellular resolution imaging in awake, head-fixed animals. Leveraging our optical approach, we systematically profile neurons in primary and higher-order visual areas and their spatial organization. We find that rat visual cortex exhibits several features similar to those observed in the primate ventral stream but also marked deviations, suggesting species-specific differences in how brains solve visual object recognition. This work reinforces the sophisticated visual abilities of rats and offers the technical foundation to use them as a powerful model for mechanistic perception.

A search is presented for fractionally charged particles with charges below 1e, using their small energy loss in the tracking detector as a key variable to observe a signal. The analyzed dataset corresponds to an integrated luminosity of 138 fb(-1) of proton-proton collisions collected at root s = 13 TeV in 2016-2018 at the CERN LHC. This is the first search at the LHC for new particles with a charge between e/3 and 0.9e, including an extension of previous results at a charge of 2e/3. Masses up to 640 GeV and charges as low as e/3 are excluded at 95% confidence level. These are the most stringent limits to date for the considered Drell-Yan-like production mode.

Nanobodies are single domain antibody variants proving themselves to be compelling tools for research, disease diagnostics, and as therapeutics targeting a myriad of disease agents. However, despite this potential, their mechanisms of paratope presentation and structural stabilization have not been fully explored. Here, we show that unlike monoclonal antibodies, a nanobody repertoire maximizes sampling of an antigen surface by binding a single antigen in at least three different orientations, which are correlated with their paratope composition. Structure-guided reengineering of several nanobodies reveals that a single point mutation within the paratope or a highly conserved region of a nanobody's framework 3 (FR3) can markedly improve antigen affinity, nanobody stability, or both. Conversely, we show the negative impact on antigen affinity when "over-stabilizing"nanobodies. Collectively our results provide a universal strategy to tune a nanobody's affinity by modifying specific residues that can readily be applied to guide nanobody optimization and functionalization.

Chronic hepatitis B virus (HBV) infection is an incurable pathogen responsible for causing liver disease and hepatocellular carcinoma. During the genesis of infection, HBV establishes an independent minichromosome consisting of the viral covalently closed circular DNA (cccDNA) genome and host histones. The viral X gene must be expressed immediately upon infection to induce degradation of the host silencing factor, the Smc5/6 complex. However, the relationship between cccDNA chromatinization and X gene transcription remains poorly understood. By establishing a reconstituted viral minichromosome platform, we found that nucleosome occupancy in cccDNA regulates X transcription. We corroborated these findings in situ and further showed that the chromatin-destabilizing molecule CBL137 inhibits full-length X transcription and HBV infection in primary human hepatocytes. Our results shed light on a long-standing paradox and represent a potential therapeutic approach for the treatment of chronic HBV infection.

The yellow fever virus 17D (YFV-17D) live attenuated vaccine is considered one of the most successful vaccines ever generated associated with high antiviral immunity, yet the signaling mechanisms that drive the response in infected cells are not understood. Here, we provide a molecular understanding of how metabolic stress and innate immune responses are linked to drive type I IFN expression in response to YFV-17D infection. Comparison of YFV-17D replication with its parental virus, YFV-Asibi, and a related dengue virus revealed that IFN expression requires RIG-I-like Receptor signaling through MAVS, as expected. However, YFV-17D uniquely induces mitochondrial respiration and major metabolic perturbations, including hyperactivation of electron transport to fuel ATP synthase. Mitochondrial hyperactivity generates reactive oxygen species (ROS) including peroxynitrite, blocking of which abrogated MAVS oligomerization and IFN expression in non-immune cells without reducing YFV-17D replication. Scavenging ROS in YFV-17D-infected human dendritic cells increased cell viability yet globally prevented expression of IFN signaling pathways. Thus, adaptation of YFV-17D for high growth imparts mitochondrial hyperactivity to meet energy demands, resulting in generation of ROS as the critical messengers that convert a blunted IFN response into maximal activation of innate immunity essential for vaccine effectiveness.

The last decades have brought a rapid expansion of the number of primary disorders related to the polyubiquitination pathways in humans. Most of these disorders manifest with two seemingly contradictory clinical phenotypes: autoinflammation, immunodeficiency, or both. We provide an overview of the molecular pathogenesis of these disorders, and their role in inflammation and infection. By focusing on data from human genetic diseases, we explore the complexities of the polyubiquitination pathways and the corresponding clinical phenotypes of their deficiencies. We offer a road map for the discovery of new genetic etiologies. By considering the triggers that induce inflammation, we propose autoinflammation and immunodeficiency as continuous clinical phenotypes.

BackgroundOnly a limited number of biomarkers guide personalized management of pancreatic neuroendocrine tumors (PanNETs). Transcriptome profiling of microRNA (miRs) and mRNA has shown value in segregating PanNETs and identifying patients more likely to respond to treatment. Because miRs are key regulators of mRNA expression, we sought to integrate expression data from both RNA species into miR-mRNA interaction networks to advance our understanding of PanNET biology.MethodsWe used deep miR/mRNA sequencing on six low-grade/high-risk, well-differentiated PanNETs compared with seven non-diseased tissues to identify differentially expressed miRs/mRNAs. Then we crossed a list of differentially expressed mRNAs with a list of in silico predicted mRNA targets of the most and least abundant miRs to generate high probability miR-mRNA interaction networks.ResultsGene ontology and pathway analyses revealed several miR-mRNA pairs implicated in cellular processes and pathways suggesting perturbed neuroendocrine function (miR-7 and Reg family genes), cell adhesion (miR-216 family and NLGN1, NCAM1, and CNTN1; miR-670 and the claudins, CLDN1 and CLDN2), and metabolic processes (miR-670 and BCAT1/MPST; miR-129 and CTH).ConclusionThese novel miR-mRNA interaction networks identified dysregulated pathways not observed when assessing mRNA alone and provide a foundation for further investigation of their utility as diagnostic and predictive biomarkers.

Brain metastasis is a common and devastating complication of cancer that affects over 50% of HER2-positive (HER2+) breast cancer patients. The lack of effective long-term treatment options for brain metastasis significantly increases morbidity and mortality among these patients. Therefore, understanding the underlying mechanisms that drive brain metastasis is critically important for developing new strategies to treat it effectively. Genetically engineered mouse models (GEMMs) of HER2+ breast cancer have been instrumental in understanding the development and progression of HER2+ breast cancer. However, the GEMM models for HER2+ breast cancer do not develop brain metastasis and are not suitable for the study of brain metastasis. We therefore developed a fully immunocompetent mouse model of experimental brain metastasis in HER2+ breast cancer by injecting a murine HER2/neu-expressing mammary-tumor-cell line into the arterial circulation of syngeneic FVB/N mice followed by isolation of brain-metastatic derivatives through in-vivo selection. By this in-vivo serial passaging process, we selected highly brain-metastatic (BrM) derivatives known as neu-BrM. Notably, after intracardiac injection, neu-BrM cells generated brain metastasis in 100% of the mice, allowing us to study the later stages of metastatic progression, including cancer-cell extravasation and outgrowth in the brain. Analogous to human brain metastasis, we observed reactive gliosis and significant immune infiltration in the brain tissue of mice injected with neu-BrM cells. We further confirmed that brain-metastatic lesions in the neu-BrM model express HER2. Consistently, we found that the brain-metastatic burden in these mice can be significantly reduced but not eliminated with tucatinib, an FDA-approved, blood-brain-barrier-penetrant HER2 inhibitor. Therefore, the neu-BrM HER2+ breast cancer model can be used to investigate the roles of innate and adaptive immune-system components during brain-metastatic progression and the mechanisms of HER2-therapy response and resistance.