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Analysis of CNS autoimmunity in genetically diverse mice reveals unique phenotypes and mechanisms.
Get PDFMultiple sclerosis (MS) is a complex disease with significant heterogeneity in disease course and progression. Genetic studies have identified numerous loci associated with MS risk, but the genetic basis of disease progression remains elusive. To address this, we leveraged the Collaborative Cross (CC), a genetically diverse mouse strain panel, and experimental autoimmune encephalomyelitis (EAE). The 32 CC strains studied captured a wide spectrum of EAE severity, trajectory, and presentation, including severe-progressive, monophasic, relapsing remitting, and axial rotary-EAE (AR-EAE), accompanied by distinct immunopathology. Sex differences in EAE severity were observed in 6 strains. Quantitative trait locus analysis revealed distinct genetic linkage patterns for different EAE phenotypes, including EAE severity and incidence of AR-EAE. Machine learning-based approaches prioritized candidate genes for loci underlying EAE severity (Abcc4 and Gpc6) and AR-EAE (Yap1 and Dync2h1). This work expands the EAE phenotypic repertoire and identifies potentially novel loci controlling unique EAE phenotypes, supporting the hypothesis that heterogeneity in MS disease course is driven by genetic variation
Genomic sequencing of a pregnancy associated symptomatic meningioma of the diaphragma sellae: a case report.
No full textPregnancy-associated meningiomas have unique considerations and features regarding their pathophysiology, location, genetic profile, and neurosurgical management. These tumours have been reported to undergo rapid growth during gestation and regression post-partum, implicating a role for female sex hormones in tumour physiology. In addition, these tumours occur at a higher incidence in the skull base compared to sporadic meningiomas in the general population, often impinging neurovascular structures and requiring emergent resection. While the genomics of sporadic meningiomas have been described, there are no reports characterizing the genetic features of those associated with pregnancy. Here we describe a patient diagnosed with a diphragma sellae meningioma early in the third trimester after presenting with rapidly deteriorating vision. At 32 weeks gestation the baby was delivered by caesarean section and the tumour subsequently removed. Genomic profiling of the tumour sample revealed variants of unknown significant (VUS) in six genes, none of which were in canonical meningioma drivers. We describe our surgical approach and discuss the relevant pathology and genomics, as well as medical and surgical management considerations of meningiomas in pregnancy
Information-theory analysis of mouse string-pulling agrees with Fitts\u27s Law: Increasing task difficulty engages multiple sensorimotor modalities in a dual oscillator behavior.
No full textMouse string pulling, in which a mouse reels in a string with hand-over-hand movements, can provide insights into skilled motor behavior, neurological status, and cognitive function. The task involves two oscillatory movements connected by a string. The snout oscillates to track the pendulum movement of the string produced by hand-over-hand oscillations of pulling, and so the snout guides the hands to grasp the string. The present study examines the allocation of time required to pull strings of varying diameter. Movement is also described with end-point measures, string-pulling topography with 2D markerless pose estimates based on transfer learning with deep neural networks, and Mat-lab image-segmentation and heuristic algorithms for object tracking. With reduced string diameter, mice took longer to pull 60 cm long strings. They also made more pulling cycles, misses, and mouth engagements, and displayed changes in the amplitude and frequency of pull cycles. The time measures agree with Fitts\u27s law in showing that increased task difficulty slows behavior and engages multiple compensatory sensorimotor modalities. The analysis reveals that time is a valuable resource in skilled motor behavior and information-theory can serve as a measure of its effective use
Bioassay-Driven, Fractionation-Empowered, Focused Metabolomics for Discovering Bacterial Activators of Aryl Hydrocarbon Receptor.
No full textAryl hydrocarbon receptor (AhR) is a transcription factor that regulates gene expression upon ligand activation, enabling microbiota-dependent induction, training, and function of the host immune system. A spectrum of metabolites, encompassing indole and tryptophan derivatives, have been recognized as activators. This work introduces an integrated, mass spectrometry-centric workflow that employs a bioassay-guided, fractionation-based methodology for the identification of AhR activators derived from human bacterial isolates. By leveraging the workflow efficiency, the complexities inherent in metabolomics profiling are significantly reduced, paving the way for an in-depth and focused mass spectrometry analysis of bioactive fractions isolated from bacterial culture supernatants. Validation of AhR activator candidates used multiple criteria─MS/MS of the synthetic reference compound, bioassay of AhR activity, and elution time confirmation using a C-13 isotopic reference─and was demonstrated for N-formylkynurenine (NFK). The workflow reported provides a roadmap update for improved efficiency of identifying bioactive metabolites using mass spectrometry-based metabolomics. Mass spectrometry datasets are accessible at the National Metabolomics Data Repository (PR001479, Project DOI: 10.21228/M8JM7Q)
Assessing the potential relevance of CEACAM6 as a blood transcriptional biomarker.
No full textBACKGROUND: Changes in blood transcript abundance levels have been associated with pathogenesis in a wide range of diseases. While next generation sequencing technology can measure transcript abundance on a genome-wide scale, downstream clinical applications often require small sets of genes to be selected for inclusion in targeted panels. Here we set out to gather information from the literature and transcriptome datasets that would help researchers determine whether to include the gene CEACAM6 in such panels.
METHODS: We employed a workflow to systematically retrieve, structure, and aggregate information derived from both the literature and public transcriptome datasets. It consisted of profiling the CEACAM6 literature to identify major diseases associated with this candidate gene and establish its relevance as a biomarker. Accessing blood transcriptome datasets identified additional instances where CEACAM6 transcript levels differ in cases vs controls. Finally, the information retrieved throughout this process was captured in a structured format and aggregated in interactive circle packing plots.
RESULTS: Although it is not routinely used clinically, the relevance of CEACAM6 as a biomarker has already been well established in the cancer field, where it has invariably been found to be associated with poor prognosis. Focusing on the blood transcriptome literature, we found studies reporting elevated levels of CEACAM6 abundance across a wide range of pathologies, especially diseases where inflammation plays a dominant role, such as asthma, psoriasis, or Parkinson\u27s disease. The screening of public blood transcriptome datasets completed this picture, showing higher abundance levels in patients with infectious diseases caused by viral and bacterial pathogens.
CONCLUSIONS: Targeted assays measuring CEACAM6 transcript abundance in blood may be of potential utility for the management of patients with diseases presenting with systemic inflammation and for the management of patients with cancer, where the assay could potentially be run both on blood and tumor tissues
Mapping genetic effects of diverse mESC lines on cellular phenotypes with Census-seq
No full textPopulation-scale phenotyping of arrayed cell lines is currently expensive and complex; one solution is to combine cells from many individuals into a cell village. And while a number of groups have applied this approach to human cell populations, and have developed computational methods including Census-seq to estimate the relative proportion of cells from each individual, these approaches have not yet been validated in mouse cell models, despite their potential to increase genetic mapping power and enable validation of risk genes associated with complex disease. To implement Census-seq for mouse models, first a pipeline must be built to make it accessible to mESC data, then it needs to be thoroughly tested: focusing on Census-seq\u27s accuracy with varying sample sizes, sequencing depth, and genetic variation
Evidence of Renal Iron and FGF23 Signaling Interdependence on Vitamin D Homeostasis in Sickle Cell Disease
No full textHemolysis in sickle cell disease (SCD) leads to high circulating heme and kidney iron deposits. Kidney proximal tubular cells regulate vitamin D (VitD) synthesis enzymes. VitD deficiency is a common complication of SCD linked to poor disease outcomes. The bone-derived hormone, fibroblast growth factor 23 (FGF23), signals in the kidney to activate the VitD catabolite enzyme CYP24A1 and represses the anabolite enzyme CYP27B1, contributing to VitD regulation. Using SCD transgenic mouse model and in vitro methods, we tested the impact of proximal tubular iron loading and FGF23 signaling on VitD metabolism. In the bone compartment, FGF23 levels increased in SCD mice compared to wild-type mice, which is associated with renal iron loading as assessed by the iron deposition marker, FTH1. In SCD mice, the expression of CYP24A1 decreased by 80%, while CYP27B1 remained steady. To test whether VitD enzymes regulation is driven by iron, we fed C57BL/6J mice with iron overload diet to mimic renal iron loading. We found that iron represses CYP24A1 and increases CYP27B1 in the kidney. Using engineered Human Embryonic Kidney 293 cells, we found that iron overloading promotes FGF23 signaling as assessed by the biomarker, EGR1. Taken together, our results indicate that renal iron and FGF23 signaling effects on VitD regulation are interdependent and both may be required to adequately regulate VitD. Mechanistically, iron-mediated CYP24A1 down-regulation is a compensatory mechanism for FGF23-mediated CYP24A1 up-regulation. Understanding the implications of iron and FGF23 pathways on VitD metabolism could help in designing future therapies for managing SCD severity
Mapping the metabolic responses to oxaliplatin-based chemotherapy with
Get PDFAdjuvant chemotherapy improves the survival outlook for patients undergoing operations for lung metastases caused by colorectal cancer (CRC). However, a multidisciplinary approach that evaluates several factors related to patient and tumor characteristics is necessary for managing chemotherapy treatment in metastatic CRC patients with lung disease, as such factors dictate the timing and drug regimen, which may affect treatment response and prognosis. In this study, we explore the potential of spatial metabolomics for evaluating metabolic phenotypes and therapy outcomes during the local delivery of the anticancer drug, oxaliplatin, to the lung. 12 male Yorkshire pigs underwent a 3 h left lung in vivo lung perfusion (IVLP) with various doses of oxaliplatin (7.5, 10, 20, 40, and 80 mg/L), which were administered to the perfusion circuit reservoir as a bolus. Biocompatible solid-phase microextraction (SPME) microprobes were combined with global metabolite profiling to obtain spatiotemporal information about the activity of the drug, determine toxic doses that exceed therapeutic efficacy, and conduct a mechanistic exploration of associated lung injury. Mild and subclinical lung injury was observed at 40 mg/L of oxaliplatin, and significant compromise of the hemodynamic lung function was found at 80 mg/L. This result was associated with massive alterations in metabolic patterns of lung tissue and perfusate, resulting in a total of 139 discriminant compounds. Uncontrolled inflammatory response, abnormalities in energy metabolism, and mitochondrial dysfunction next to accelerated kynurenine and aldosterone production were recognized as distinct features of dysregulated metabolipidome. Spatial pharmacometabolomics may be a promising tool for identifying pathological responses to chemotherapy
Targeting mitochondrial dysfunction using methylene blue or mitoquinone to improve skeletal aging.
Get PDFMethylene blue (MB) is a well-established antioxidant that has been shown to improve mitochondrial function in both in vitro and in vivo settings. Mitoquinone (MitoQ) is a selective antioxidant that specifically targets mitochondria and effectively reduces the accumulation of reactive oxygen species. To investigate the effect of long-term administration of MB on skeletal morphology, we administered MB to aged (18 months old) female C57BL/J6 mice, as well as to adult male and female mice with a genetically diverse background (UM-HET3). Additionally, we used MitoQ as an alternative approach to target mitochondrial oxidative stress during aging in adult female and male UM-HET3 mice. Although we observed some beneficial effects of MB and MitoQ in vitro, the administration of these compounds in vivo did not alter the progression of age-induced bone loss. Specifically, treating 18-month-old female mice with MB for 6 or 12 months did not have an effect on age-related bone loss. Similarly, long-term treatment with MB from 7 to 22 months or with MitoQ from 4 to 22 months of age did not affect the morphology of cortical bone at the mid-diaphysis of the femur, trabecular bone at the distal-metaphysis of the femur, or trabecular bone at the lumbar vertebra-5 in UM-HET3 mice. Based on our findings, it appears that long-term treatment with MB or MitoQ alone, as a means to reduce skeletal oxidative stress, is insufficient to inhibit age-associated bone loss. This supports the notion that interventions solely with antioxidants may not provide adequate protection against skeletal aging
A host-microbiota interactome reveals extensive transkingdom connectivity.
No full textThe myriad microorganisms that live in close association with humans have diverse effects on physiology, yet the molecular bases for these impacts remain mostly unknown 1–3 . Classical pathogens often invade host tissues and modulate immune responses through interactions with human extracellular and secreted proteins (the ‘exoproteome’). Commensal microorganisms may also facilitate niche colonization and shape host biology by engaging host exoproteins; however, direct exoproteome–microbiota interactions remain largely unexplored. Here we developed and validated a novel technology, BASEHIT, that enables proteome-scale assessment of human exoproteome–microbiome interactions. Using BASEHIT, we interrogated more than 1.7 million potential interactions between 519 human- associated bacterial strains from diverse phylogenies and tissues of origin and 3,324 human exoproteins. The resulting interactome revealed an extensive network of transkingdom connectivity consisting of thousands of previously undescribed host–microorganism interactions involving 383 strains and 651 host proteins. Specific binding patterns within this network implied underlying biological logic; for example, conspecific strains exhibited shared exoprotein-binding patterns, and individual tissue isolates uniquely bound tissue-specific exoproteins. Furthermore, we observed dozens of unique and often strain-specific interactions with potential roles in niche colonization, tissue remodelling and immunomodulation, and found that strains with differing host interaction profiles had divergent interactions with host cells in vitro and effects on the host immune system in vivo. Overall, these studies expose a previously unexplored landscape of molecular-level host–microbiota interactions that may underlie causal effects of indigenous microorganisms on human health and disease