VEGF-C prophylaxis favors lymphatic drainage and modulates neuroinflammation in a stroke model.

Meningeal lymphatic vessels (MLVs) promote tissue clearance and immune surveillance in the central nervous system (CNS). Vascular endothelial growth factor-C (VEGF-C) regulates MLV development and maintenance and has therapeutic potential for treating neurological disorders. Herein, we investigated the effects of VEGF-C overexpression on brain fluid drainage and ischemic stroke outcomes in mice. Intracerebrospinal administration of an adeno-associated virus expressing mouse full-length VEGF-C (AAV-mVEGF-C) increased CSF drainage to the deep cervical lymph nodes (dCLNs) by enhancing lymphatic growth and upregulated neuroprotective signaling pathways identified by single nuclei RNA sequencing of brain cells. In a mouse model of ischemic stroke, AAV-mVEGF-C pretreatment reduced stroke injury and ameliorated motor performances in the subacute stage, associated with mitigated microglia-mediated inflammation and increased BDNF signaling in brain cells. Neuroprotective effects of VEGF-C were lost upon cauterization of the dCLN afferent lymphatics and not mimicked by acute post-stroke VEGF-C injection. We conclude that VEGF-C prophylaxis promotes multiple vascular, immune, and neural responses that culminate in a protection against neurological damage in acute ischemic stroke.

Simulations of Sequence Evolution: How (Un)realistic They Are and Why.

MOTIVATION: Simulating multiple sequence alignments (MSAs) using probabilistic models of sequence evolution plays an important role in the evaluation of phylogenetic inference tools and is crucial to the development of novel learning-based approaches for phylogenetic reconstruction, for instance, neural networks. These models and the resulting simulated data need to be as realistic as possible to be indicative of the performance of the developed tools on empirical data and to ensure that neural networks trained on simulations perform well on empirical data. Over the years, numerous models of evolution have been published with the goal to represent as faithfully as possible the sequence evolution process and thus simulate empirical-like data. In this study, we simulated DNA and protein MSAs under increasingly complex models of evolution with and without insertion/deletion (indel) events using a state-of-the-art sequence simulator. We assessed their realism by quantifying how accurately supervised learning methods are able to predict whether a given MSA is simulated or empirical. RESULTS: Our results show that we can distinguish between empirical and simulated MSAs with high accuracy using two distinct and independently developed classification approaches across all tested models of sequence evolution. Our findings suggest that the current state-of-the-art models fail to accurately replicate several aspects of empirical MSAs, including site-wise rates as well as amino acid and nucleotide composition.

Correction: Impact of a Postintensive Care Unit Multidisciplinary Follow-up on the Quality of Life (SUIVI-REA): Protocol for a Multicenter Randomized Controlled Trial.

[This corrects the article DOI: 10.2196/30496.].

Mycobacterium tuberculosis genetic features associated with pulmonary tuberculosis severity.

OBJECTIVES: Mycobacterium tuberculosis (Mtb) infections result in a wide spectrum of clinical presentations but without proven Mtb genetic determinants. Herein, we hypothesized that the genetic features of Mtb clinical isolates, such as specific polymorphisms or microdiversity, may be linked to tuberculosis (TB) severity. METHODS: A total of 234 patients with pulmonary TB (including 193 drug-susceptible and 14 monoresistant cases diagnosed between 2017 and 2020 and 27 multidrug-resistant cases diagnosed between 2010 and 2020) were stratified according to TB disease severity, and Mtb genetic features were explored using whole genome sequencing, including heterologous single-nucleotide polymorphism (SNP), calling to explore microdiversity. Finally, we performed a structural equation modeling analysis to relate TB severity to Mtb genetic features. RESULTS: The clinical isolates from patients with mild TB carried mutations in genes associated with host-pathogen interaction, whereas those from patients with moderate/severe TB carried mutations associated with regulatory mechanisms. Genome-wide association study identified an SNP in the promoter of the gene coding for the virulence regulator espR, statistically associated with moderate/severe disease. Structural equation modeling and model comparisons indicated that TB severity was associated with the detection of Mtb microdiversity within clinical isolates and to the espR SNP. CONCLUSION: Taken together, these results provide a new insight to better understand TB pathophysiology and could provide a new prognosis tool for pulmonary TB severity.

Conserved meningeal lymphatic drainage circuits in mice and humans.

Meningeal lymphatic vessels (MLVs) were identified in the dorsal and caudobasal regions of the dura mater, where they ensure waste product elimination and immune surveillance of brain tissues. Whether MLVs exist in the anterior part of the murine and human skull and how they connect with the glymphatic system and extracranial lymphatics remained unclear. Here, we used light-sheet fluorescence microscopy (LSFM) imaging of mouse whole-head preparations after OVA-A555 tracer injection into the cerebrospinal fluid (CSF) and performed real-time vessel-wall (VW) magnetic resonance imaging (VW-MRI) after systemic injection of gadobutrol in patients with neurological pathologies. We observed a conserved three-dimensional anatomy of MLVs in mice and humans that aligned with dural venous sinuses but not with nasal CSF outflow, and we discovered an extended anterior MLV network around the cavernous sinus, with exit routes through the foramina of emissary veins. VW-MRI may provide a diagnostic tool for patients with CSF drainage defects and neurological diseases.

CALDERA: finding all significant de Bruijn subgraphs for bacterial GWAS.

MOTIVATION: Genome-wide association studies (GWAS), aiming to find genetic variants associated with a trait, have widely been used on bacteria to identify genetic determinants of drug resistance or hypervirulence. Recent bacterial GWAS methods usually rely on k-mers, whose presence in a genome can denote variants ranging from single-nucleotide polymorphisms to mobile genetic elements. This approach does not require a reference genome, making it easier to account for accessory genes. However, a same gene can exist in slightly different versions across different strains, leading to diluted effects. RESULTS: Here, we overcome this issue by testing covariates built from closed connected subgraphs (CCSs) of the de Bruijn graph defined over genomic k-mers. These covariates capture polymorphic genes as a single entity, improving k-mer-based GWAS both in terms of power and interpretability. However, a method naively testing all possible subgraphs would be powerless due to multiple testing corrections, and the mere exploration of these subgraphs would quickly become computationally intractable. The concept of testable hypothesis has successfully been used to address both problems in similar contexts. We leverage this concept to test all CCSs by proposing a novel enumeration scheme for these objects which fully exploits the pruning opportunity offered by testability, resulting in drastic improvements in computational efficiency. Our method integrates with existing visual tools to facilitate interpretation. AVAILABILITY AND IMPLEMENTATION: We provide an implementation of our method, as well as code to reproduce all results at https://github.com/HectorRDB/Caldera_ISMB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Impact of a Postintensive Care Unit Multidisciplinary Follow-up on the Quality of Life (SUIVI-REA): Protocol for a Multicenter Randomized Controlled Trial.

BACKGROUND: Critically ill patients are at risk of developing a postintensive care syndrome (PICS), which is characterized by physical, psychological, and cognitive impairments and which dramatically impacts the patient's quality of life (QoL). No intervention has been shown to improve QoL. We hypothesized that a medical, psychological, and social follow-up would improve QoL by mitigating the PICS. OBJECTIVE: This multicenter, randomized controlled trial (SUIVI-REA) aims to compare a multidisciplinary follow-up with a standard postintensive care unit (ICU) follow-up. METHODS: Patients were randomized to the control or intervention arm. In the intervention arm, multidisciplinary follow-up involved medical, psychological, and social evaluation at ICU discharge and at 3, 6, and 12 months thereafter. In the placebo group, patients were seen only at 12 months by the multidisciplinary team. Baseline characteristics at ICU discharge were collected for all patients. The primary outcome was QoL at 1 year, assessed using the Euro Quality of Life-5 dimensions (EQ5D). Secondary outcomes were mortality, cognitive, psychological, and functional status; social and professional reintegration; and the rate of rehospitalization and outpatient consultations at 1 year. RESULTS: The study was funded by the Ministry of Health in June 2010. It was approved by the Ethics Committee on July 8, 2011. The first and last patient were randomized on December 20, 2012, and September 1, 2017, respectively. A total of 546 patients were enrolled across 11 ICUs. At present, data management is ongoing, and all parties involved in the trial remain blinded. CONCLUSIONS: The SUVI-REA multicenter randomized controlled trial aims to assess whether a post-ICU multidisciplinary follow-up improves QoL at 1 year. TRIAL REGISTRATION: Clinicaltrials.gov NCT01796509; https://clinicaltrials.gov/ct2/show/NCT01796509. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30496.

Endothelial Unc5B controls blood-brain barrier integrity.

Blood-brain barrier (BBB) integrity is critical for proper function of the central nervous system (CNS). Here, we show that the endothelial Unc5B receptor controls BBB integrity by maintaining Wnt/ß-catenin signaling. Inducible endothelial-specific deletion of Unc5B in adult mice leads to BBB leak from brain capillaries that convert to a barrier-incompetent state with reduced Claudin-5 and increased PLVAP expression. Loss of Unc5B decreases BBB Wnt/ß-catenin signaling, and ß-catenin overexpression rescues Unc5B mutant BBB defects. Mechanistically, the Unc5B ligand Netrin-1 enhances Unc5B interaction with the Wnt co-receptor LRP6, induces its phosphorylation and activates Wnt/ß-catenin downstream signaling. Intravenous delivery of antibodies blocking Netrin-1 binding to Unc5B causes a transient BBB breakdown and disruption of Wnt signaling, followed by neurovascular barrier resealing. These data identify Netrin-1-Unc5B signaling as a ligand-receptor pathway that regulates BBB integrity, with implications for CNS diseases.

SLIT2/ROBO signaling in tumor-associated microglia and macrophages drives glioblastoma immunosuppression and vascular dysmorphia.

SLIT2 is a secreted polypeptide that guides migration of cells expressing Roundabout 1 and 2 (ROBO1 and ROBO2) receptors. Herein, we investigated SLIT2/ROBO signaling effects in gliomas. In patients with glioblastoma (GBM), SLIT2 expression increased with malignant progression and correlated with poor survival and immunosuppression. Knockdown of SLIT2 in mouse glioma cells and patient-derived GBM xenografts reduced tumor growth and rendered tumors sensitive to immunotherapy. Tumor cell SLIT2 knockdown inhibited macrophage invasion and promoted a cytotoxic gene expression profile, which improved tumor vessel function and enhanced efficacy of chemotherapy and immunotherapy. Mechanistically, SLIT2 promoted microglia/macrophage chemotaxis and tumor-supportive polarization via ROBO1- and ROBO2-mediated PI3K-γ activation. Macrophage Robo1 and Robo2 deletion and systemic SLIT2 trap delivery mimicked SLIT2 knockdown effects on tumor growth and the tumor microenvironment (TME), revealing SLIT2 signaling through macrophage ROBOs as a potentially novel regulator of the GBM microenvironment and immunotherapeutic target for brain tumors.

Controlling technical variation amongst 6693 patient microarrays of the randomized MINDACT trial.

Gene expression data obtained in large studies hold great promises for discovering disease signatures or subtypes through data analysis. It is also prone to technical variation, whose removal is essential to avoid spurious discoveries. Because this variation is not always known and can be confounded with biological signals, its removal is a challenging task. Here we provide a step-wise procedure and comprehensive analysis of the MINDACT microarray dataset. The MINDACT trial enrolled 6693 breast cancer patients and prospectively validated the gene expression signature MammaPrint for outcome prediction. The study also yielded a full-transcriptome microarray for each tumor. We show for the first time in such a large dataset how technical variation can be removed while retaining expected biological signals. Because of its unprecedented size, we hope the resulting adjusted dataset will be an invaluable tool to discover or test gene expression signatures and to advance our understanding of breast cancer.

Three-Dimensional Imaging of the Vertebral Lymphatic Vasculature and Drainage using iDISCO+ and Light Sheet Fluorescence Microscopy.

The lymphatic system associated with the central nervous system (CNS) includes the lymphatic vasculature that spins around the brain, the spinal cord, and its associated LNs. The CNS-associated lymphatic system is involved in the drainage of CSF macromolecules and meningeal immune cells toward CNS-draining LNs, thereby regulating waste clearance and immune surveillance within CNS tissues. Presented is a novel approach to obtain three-dimensional (3D) and cellular resolution images of CNS-associated lymphatics while preserving the integrity of their circuits within surrounding tissues. The iDISCO+ protocol is used to immunolabel lymphatic vessels in decalcified and cleared whole mount preparations of the vertebral column that are subsequently imaged with light sheet fluorescence microscopy (LSFM). The technique reveals the 3D structure of the lymphatic network connecting the meningeal and epidural spaces around the spinal cord to extravertebral lymphatic vessels. Provided are 3D images of the drainage circuits of molecular tracers previously injected into either the CSF via the cisterna magna or the thoracolumbar spinal parenchyma. The iDISCO+/LSFM approach brings unprecedented opportunities to explore the structure and function of the CNS-associated lymphatic system in neurovascular biology, neuroimmunology, brain and vertebral cancer, or vertebral bone and joint biology.

Niche specialization and spread of Staphylococcus capitis involved in neonatal sepsis.

The multidrug-resistant Staphylococcus capitis NRCS-A clone is responsible for sepsis in preterm infants in neonatal intensive care units (NICUs) worldwide. Here, to retrace the spread of this clone and to identify drivers of its specific success, we investigated a representative collection of 250 S. capitis isolates from adults and newborns. Bayesian analyses confirmed the spread of the NRCS-A clone and enabled us to date its emergence in the late 1960s and its expansion during the 1980s, coinciding with the establishment of NICUs and the increasing use of vancomycin in these units, respectively. This dynamic was accompanied by the acquisition of mutations in antimicrobial resistance- and bacteriocin-encoding genes. Furthermore, combined statistical tools and a genome-wide association study convergently point to vancomycin resistance as a major driver of NRCS-A success. We also identified another S. capitis subclade (alpha clade) that emerged independently, showing parallel evolution towards NICU specialization and non-susceptibility to vancomycin, indicating convergent evolution in NICU-associated pathogens. These findings illustrate how the broad use of antibiotics can repeatedly lead initially commensal drug-susceptible bacteria to evolve into multidrug-resistant clones that are able to successfully spread worldwide and become pathogenic for highly vulnerable patients.

Disruption of Sema3A/Plexin-A1 inhibitory signalling in oligodendrocytes as a therapeutic strategy to promote remyelination.

Current treatments in multiple sclerosis (MS) are modulating the inflammatory component of the disease, but no drugs are currently available to repair lesions. Our study identifies in MS patients the overexpression of Plexin-A1, the signalling receptor of the oligodendrocyte inhibitor Semaphorin 3A. Using a novel type of peptidic antagonist, we showed the possibility to counteract the Sema3A inhibitory effect on oligodendrocyte migration and differentiation in vitro when antagonizing Plexin-A1. The use of this compound in vivo demonstrated a myelin protective effect as shown with DTI-MRI and confirmed at the histological level in the mouse cuprizone model of induced demyelination/remyelination. This effect correlated with locomotor performances fully preserved in chronically treated animals. The administration of the peptide also showed protective effects, leading to a reduced severity of demyelination in the context of experimental autoimmune encephalitis (EAE). Hence, the disruption of the inhibitory microenvironmental molecular barriers allows normal myelinating cells to exert their spontaneous remyelinating capacity. This opens unprecedented therapeutic opportunity for patients suffering a disease for which no curative options are yet available.

Anatomy and function of the vertebral column lymphatic network in mice.

Cranial lymphatic vessels (LVs) are involved in the transport of fluids, macromolecules and central nervous system (CNS) immune responses. Little information about spinal LVs is available, because these delicate structures are embedded within vertebral tissues and difficult to visualize using traditional histology. Here we show an extended vertebral column LV network using three-dimensional imaging of decalcified iDISCO+-clarified spine segments. Vertebral LVs connect to peripheral sensory and sympathetic ganglia and form metameric vertebral circuits connecting to lymph nodes and the thoracic duct. They drain the epidural space and the dura mater around the spinal cord and associate with leukocytes. Vertebral LVs remodel extensively after spinal cord injury and VEGF-C-induced vertebral lymphangiogenesis exacerbates the inflammatory responses, T cell infiltration and demyelination following focal spinal cord lesion. Therefore, vertebral LVs add to skull meningeal LVs as gatekeepers of CNS immunity and may be potential targets to improve the maintenance and repair of spinal tissues.

An IgG-induced neutrophil activation pathway contributes to human drug-induced anaphylaxis.

Anaphylaxis is a systemic acute hypersensitivity reaction that is considered to depend on allergen-specific immunoglobulin E (IgE) antibodies and histamine release by mast cells and basophils. Nevertheless, allergen-specific IgG antibodies have been proposed to contribute when the allergen is an abundant circulating large molecule, e.g., after infusions of therapeutic antibodies or dextran. Data from animal models demonstrate a pathway involving platelet-activating factor (PAF) release by monocytes/macrophages and neutrophils activated via their Fc gamma receptors (FcγRs). We hypothesized that such a pathway may also apply to small drugs and could be responsible for non-IgE-mediated anaphylaxis and influence anaphylaxis severity in humans. We prospectively conducted a multicentric study of 86 patients with suspected anaphylaxis to neuromuscular-blocking agents (NMBAs) during general anesthesia and 86 matched controls. We found that concentrations of anti-NMBA IgG and markers of FcγR activation, PAF release, and neutrophil activation correlated with anaphylaxis severity. Neutrophils underwent degranulation and NETosis early after anaphylaxis onset, and plasma-purified anti-NMBA IgG triggered neutrophil activation ex vivo in the presence of NMBA. Neutrophil activation could also be observed in patients lacking evidence of classical IgE-dependent anaphylaxis. This study supports the existence of an IgG-neutrophil pathway in human NMBA-induced anaphylaxis, which may aggravate anaphylaxis in combination with the IgE pathway or underlie anaphylaxis in the absence of specific IgE. These results reconcile clinical and experimental data on the role of antibody classes in anaphylaxis and could inform diagnostic approaches to NMBA-induced acute hypersensitivity reactions.

RNA Profiling of the Human and Mouse Spinal Cord Stem Cell Niches Reveals an Embryonic-like Regionalization with MSX1+ Roof-Plate-Derived Cells.

Anamniotes, rodents, and young humans maintain neural stem cells in the ependymal zone (EZ) around the central canal of the spinal cord, representing a possible endogenous source for repair in mammalian lesions. Cell diversity and genes specific for this region are ill defined. A cellular and molecular resource is provided here for the mouse and human EZ based on RNA profiling, immunostaining, and fluorescent transgenic mice. This uncovered the conserved expression of 1,200 genes including 120 transcription factors. Unexpectedly the EZ maintains an embryonic-like dorsal-ventral pattern of expression of spinal cord developmental transcription factors (ARX, FOXA2, MSX1, and PAX6). In mice, dorsal and ventral EZ cells express Vegfr3 and are derived from the embryonic roof and floor plates. The dorsal EZ expresses a high level of Bmp6 and Gdf10 genes and harbors a subpopulation of radial quiescent cells expressing MSX1 and ID4 transcription factors.

Biological sequence modeling with convolutional kernel networks.

MOTIVATION: The growing number of annotated biological sequences available makes it possible to learn genotype-phenotype relationships from data with increasingly high accuracy. When large quantities of labeled samples are available for training a model, convolutional neural networks can be used to predict the phenotype of unannotated sequences with good accuracy. Unfortunately, their performance with medium- or small-scale datasets is mitigated, which requires inventing new data-efficient approaches. RESULTS: We introduce a hybrid approach between convolutional neural networks and kernel methods to model biological sequences. Our method enjoys the ability of convolutional neural networks to learn data representations that are adapted to a specific task, while the kernel point of view yields algorithms that perform significantly better when the amount of training data is small. We illustrate these advantages for transcription factor binding prediction and protein homology detection, and we demonstrate that our model is also simple to interpret, which is crucial for discovering predictive motifs in sequences. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://gitlab.inria.fr/dchen/CKN-seq. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hormonal pleiotropy and the evolution of allocation trade-offs.

Recent empirical evidence suggests that trade-off relationships can evolve, challenging the classical image of their high entrenchment. For energy reliant traits, this relationship should depend on the endocrine system that regulates resource allocation. Here, we model changes in this system by mutating the expression and conformation of its constitutive hormones and receptors. We show that the shape of trade-offs can indeed evolve in this model through the combined action of genetic drift and selection, such that their evolutionarily expected curvature and length depend on context. In particular, the shape of a trade-off should depend on the cost associated with resource storage, itself depending on the traded resource and on the ecological context. Despite this convergence at the phenotypic level, we show that a variety of physiological mechanisms may evolve in similar simulations, suggesting redundancy at the genetic level. This model should provide a useful framework to interpret and unify the overly complex observations of evolutionary endocrinology and evolutionary ecology.

[Lymphatic system in central nervous system]. / Système lymphatique et cerveau.

The considerable metabolic activity of the central nervous system (CNS) requires an efficient system of tissue drainage and detoxification. The CNS is however devoid of lymphatic vessels, a vasculature ensuring interstitial fluid drainage and immune survey in other organs. A unique system of drainage has recently been identified between the cerebrospinal fluid (CSF), brain interstitial fluids and meningeal lymphatic vessels. This system is coupling a cerebral "glymphatic" flow with a meningeal lymphatic vasculature. The "glymphatic" system includes perivascular spaces and astrocytes, and drains interstitial fluids, from and towards the CSF. Meningeal lymphatic vessels are functionally linked to the cerebral "glymphatic" efflux by clearing intracerebral macromolecules and antigens towards the peripheral lymphatic system. The "glymphatic"-"meningeal lymphatics" system is potentially offering new therapeutic targets to improve cerebral drainage and immune survey in human CNS diseases.

PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides.

We propose a new hypothesis test for the differential abundance of proteins in mass-spectrometry based relative quantification. An important feature of this type of high-throughput analyses is that it involves an enzymatic digestion of the sample proteins into peptides prior to identification and quantification. Due to numerous homology sequences, different proteins can lead to peptides with identical amino acid chains, so that their parent protein is ambiguous. These so-called shared peptides make the protein-level statistical analysis a challenge and are often not accounted for. In this article, we use a linear model describing peptide-protein relationships to build a likelihood ratio test of differential abundance for proteins. We show that the likelihood ratio statistic can be computed in linear time with the number of peptides. We also provide the asymptotic null distribution of a regularized version of our statistic. Experiments on both real and simulated datasets show that our procedures outperforms state-of-the-art methods. The procedures are available via the pepa.test function of the DAPAR Bioconductor R package.