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The replication of DNA in chromosomes is initiated at sequences called origins at which two replisome machines are assembled at replication forks that move in opposite directions. Interestingly, in vivo studies observe that the two replication forks remain fastened together, often referred to as a replication factory. Replication factories containing two replisomes are well documented in cellular studies of bacteria (Escherichia coli and Bacillus subtilis) and the eukaryote, Saccharomyces cerevisiae. This basic twin replisome factory architecture may also be preserved in higher eukaryotes. Despite many years of documenting the existence of replication factories, the molecular details of how the two replisome machines are tethered together has been completely unknown in any organism. Recent structural studies shed new light on the architecture of a eukaryote replisome factory, which brings with it a new twist on how a replication factory may function.

Hearing and balance rely on the capacity of mechanically sensitive hair bundles to transduce vibrations into electrical signals that are forwarded to the brain. Hair bundles possess tip links that interconnect the mechanosensitive stereocilia and convey force to the transduction channels. A dimer of dimers, each of these links comprises two molecules of protocadherin 15 (PCDH15) joined to two of cadherin 23 (CDH23). The "handshake" that conjoins the four molecules can be disrupted in vivo by intense stimulation and in vitro by exposure to Ca2+ chelators. Using hair bundles from the rat's cochlea and the bullfrog's sacculus, we observed that extensive recovery of mechanoelectrical transduction, hair bundle stiffness, and spontaneous bundle oscillation can occur within seconds after Ca2+ chelation, especially if hair bundles are deflected toward their short edges. Investigating the phenomenon in a two-compartment ionic environment that mimics natural conditions, we combined iontophoretic application of a Ca2+ chelator to selectively disrupt the tip links of individual frog hair bundles with displacement clamping to control hair bundle motion and measure forces. Our observations suggest that, after the normal Ca2+ concentration has been restored, mechanical stimulation facilitates the reconstitution of functional tip links.

Reduced nutrient intake is a widely conserved manifestation of sickness behavior with poorly characterized effects on adaptive immune responses. During infectious challenges, naive T cells encountering their cognate antigen become activated and differentiate into highly proliferative effector T cells. Despite their evident metabolic shift upon activation, it remains unclear how effector T cells respond to changes in nutrient availability in vivo. Here, we show that spontaneous or imposed feeding reduction during infection decreases the numbers of splenic lymphocytes. Effector T cells showed cell-intrinsic responses dependent on the nuclear receptor Farnesoid X Receptor (FXR). Deletion of FXR in T cells prevented starvation-induced loss of lymphocytes and increased effector T cell fitness in nutrient-limiting conditions, but imparted greater weight loss to the host. FXR deficiency increased the contribution of glutamine and fatty acids toward respiration and enhanced cell survival under low-glucose conditions. Provision of glucose during anorexia of infection rescued effector T cells, suggesting that this sugar is a limiting nutrient for activated lymphocytes and that alternative fuel usage may affect cell survival in starved animals. Altogether, we identified a mechanism by which the host scales immune responses according to food intake, featuring FXR as a T cell-intrinsic sensor.

The cognitive mechanisms underlying attention-deficit hyperactivity disorder (ADHD), a highly heritable disorder with an array of candidate genes and unclear genetic architecture, remain poorly understood. We previously demonstrated that mice overexpressing CK1 delta (CK1 delta OE) in the forebrain show hyperactivity and ADHD-like pharmacological responses to d-amphetamine. Here, we demonstrate that CK1 delta OE mice exhibit impaired visual attention and a lack of d-amphetamine-induced place preference, indicating a disruption of the dopamine-dependent reward pathway. We also demonstrate the presence of abnormalities in the frontostriatal circuitry, differences in synaptic ultra-structures by electron microscopy, as well as electrophysiological perturbations of both glutamatergic and GABAergic transmission, as observed by altered frequency and amplitude of mEPSCs and mIPSCs. Furthermore, gene expression profiling by next-generation sequencing alone, or in combination with bacTRAP technology to study specifically Drd1a versus Drd2 medium spiny neurons, revealed that developmental CK1 delta OE alters transcriptional homeostasis in the striatum, including specific alterations in Drd1a versus Drd2 neurons. These results led us to perform a fine molecular characterization of targeted gene networks and pathway analysis. Importantly, a large fraction of 92 genes identified by GWAS studies as associated with ADHD in humans are significantly altered in our mouse model. The multiple abnormalities described here might be responsible for synaptic alterations and lead to complex behavioral abnormalities. Collectively, CK1 delta OE mice share characteristics typically associated with ADHD and should represent a valuable model to investigate the disease in vivo.

The diverse composition of mammalian tissues poses challenges for understanding the cell-cell interactions required for organ homeostasis and how spatial relationships are perturbed during disease. Existing methods such as single-cell genomics, lacking a spatial context, and traditional immunofluorescence, capturing only two to six molecular features, cannot resolve these issues. Imaging technologies have been developed to address these problems, but each possesses limitations that constrain widespread use. Here we report a method that overcomes major impediments to highly multiplex tissue imaging. "Iterative bleaching extends multiplexity" (IBEX) uses an iterative staining and chemical bleaching method to enable high-resolution imaging of >65 parameters in the same tissue section without physical degradation. IBEX can be employed with various types of conventional microscopes and permits use of both commercially available and user-generated antibodies in an "open" system to allow easy adjustment of staining panels based on ongoing marker discovery efforts. We show how IBEX can also be used with amplified staining methods for imaging strongly fixed tissues with limited epitope retention and with oligonucleotide-based staining, allowing potential cross-referencing between flow cytometry, cellular indexing of transcriptomes and epitopes by sequencing, and IBEX analysis of the same tissue. To facilitate data processing, we provide an open-source platform for automated registration of iterative images. IBEX thus represents a technology that can be rapidly integrated into most current laboratory workflows to achieve high-content imaging to reveal the complex cellular landscape of diverse organs and tissues.

Antibodies against viral pathogens represent promising therapeutic agents for the control of infection, and their antiviral efficacy has been shown torequire the coordinated function of both the Fab and Fc domains(1). The Fc domain engages a wide spectrum of receptors on discrete cells of the immune system to trigger the clearance of viruses and subsequent killing of infected cells(1-4). Here we report that Fc engineering of anti-influenza IgG monoclonal antibodies for selective binding to the activating Fc. receptor Fc.RIIa results in enhanced ability to prevent or treat lethal viral respiratory infection in mice, with increased maturation of dendritic cells and the induction of protective CD8(+) T cell responses. These findings highlight the capacity for IgG antibodies to induce protective adaptive immunity to viral infection when they selectively activate a dendritic cell and T cell pathway, with important implications for the development of therapeutic antibodies with improved antiviral efficacy against viral respiratory pathogens.

Susceptibility to herpes simplex virus type 1 (HSV-1) encephalitis (HSE-1) in otherwise healthy individuals, in the course of primary infection, can be caused by single-gene inborn errors of Toll-like receptor 3 (TLR3) dependent, interferon (IFN)-alpha/beta-mediated immunity,(1,2) or by single-gene inborn errors of snoRNA31.(3) These variations underlie infections of the forebrain, whereas mutations of DBR1 underlie infections of the brainstem.(3) HSV-2 encephalitis (HSE-2) is typically observed in neonates, albeit also rarely in older children and adults.(4) Its manifestations include altered level of consciousness, cranial neuropathies or more extensive brainstem encephalitis, hemiparesis, hemisensory loss, and permanent neurologic deficit.(4) MRI in HSE-2 may show normal findings, nonspecific white matter, orbitofrontal, mesial temporal lobe, or brainstem lesions. Inborn errors of immunity underlying HSE-2 have not been described.

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment(1). The origins of specific compounds are known, including metabolites that are highly heritable(2,3), or those that are influenced by the gut microbiome(4), by lifestyle choices such as smoking(5), or by diet(6). However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts(7,8) that were not available to us when we trained the algorithms. We used feature attribution analysis(9) to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites. The levels of 1,251 metabolites are measured in 475 phenotyped individuals, and machine-learning algorithms reveal that diet and the microbiome are the determinants with the strongest predictive power for the levels of these metabolites.