Biology subjects

Cox, J.

Publications and source records attributed to Cox, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

CD200R1 promotes IL-17 production by ILC3s, by enhancing STAT3 activation

Psoriasis is a common chronic inflammatory skin disease with no cure. It is driven by the IL-23/IL-17A axis and TH17 cells but, recently group 3 innate lymphoid cells (ILC3s) have also been implicated. However, the development, and factors regulating the activity of ILC3s remain incompletely understood. Immune regulatory pathways are particularly important at barrier sites such as the skin, gut and lung, which are exposed to environmental substances and microbes. CD200R1 is an immune regulatory cell surface receptor which inhibits proinflammatory cytokine production in myeloid cells. CD200R1 is also highly expressed on ILCs, where its function remains largely unexplored. We previously observed reduced CD200R1 signalling in psoriasis skin, suggesting that dysregulation may promote disease. Here we show that contrary to this, psoriasis models are less severe in CD200R1-deficient mice due to reduced IL-17 production. Here we uncover a key cell-intrinsic role for CD200R1 in promoting IL-23-driven IL-17A production by ILC3s, by promoting STAT3 activation. CD200R1 is expressed on ILC precursors and is particularly high on neonatal ILC3s, suggesting CD200R1 may function during ILC development. Therefore, CD200R1 is required on ILC3s, potentially during their development, to promote IL-23-stimulated STAT3 activation triggering optimal IL-17 production.

immunology↗

bioRxiv2022

Prioritized single-cell proteomics reveals molecular and functional polarization across primary macrophages

Major aims of single-cell proteomics include increasing the consistency, sensitivity, and depth of protein quantification, especially for proteins and modifications of biological interest. To simultaneously advance all these aims, we developed prioritized Single Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while analyzing identifiable peptides at full duty-cycle, thus increasing proteome depth. These strategies increased the sensitivity, data completeness, and proteome coverage over 2-fold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport. This protein covariation within a treatment condition was similar across the treatment conditions and coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at: scp.slavovlab.net/pSCoPE O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/484655v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@c44f04org.highwire.dtl.DTLVardef@1fb3e8org.highwire.dtl.DTLVardef@15c456eorg.highwire.dtl.DTLVardef@d271e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2022

Trade-Offs Between Hepatic Host Defense and Metabolic Programs Underlie Sex-Biased Diseases

Current concepts in evolutionary medicine propose that trade-offs and mismatches with a shifting environment increase disease risk. While biological sex also impacts disease prevalence, contributions of environmental pressures to sex-biased diseases remain unexplored. Here, we show that sex-dependent hepatic programs confer a robust (~300%) survival advantage for male mice during lethal bacterial infection. The transcription factor BCL6, which masculinizes hepatic gene expression at puberty, is essential for this advantage. However, protection by BCL6 comes at a cost following dietary excess, resulting in overt fatty liver and glucose intolerance in males. Deleting hepatic BCL6 reverses these phenotypes but markedly lowers male fitness during infection, thus establishing a sex-dependent tradeoff between host defense and metabolic systems. We suggest that these tradeoffs, coupled with current environmental pressures, drive metabolic disease in males.

physiology↗

bioRxiv2021

Defining cellular complexity in human autosomal dominant polycystic kidney disease by multimodal single cell analysis

Autosomal dominant polycystic kidney disease (ADPKD) is the leading genetic cause of end stage renal disease and is characterized by the formation and progressive expansion of kidney cysts. Most ADPKD cases arise from mutations in either the PKD1 or PKD2 gene but the precise downstream signaling pathways driving cyst growth are not well understood, and relatively few studies investigate human cystic kidney due to sample scarcity. In order to better understand the cell types and states driving human ADPKD progression, we analyzed eight ADPKD and five healthy human kidney samples, generating a single cell multiomic atlas consisting of ~100,000 single nucleus transcriptomes and ~50,000 single nucleus epigenomes. The integrated datasets identified 11 primary cell clusters including most epithelial cell types as well as large endothelial and fibroblast cell clusters. Proximal tubular cells from ADPKD kidneys expressed a failed repair transcriptomic signature characterized by profibrotic and proinflammatory transcripts. We identified the G protein-coupled receptor GPRC5A as specifically upregulated in cyst lining cells derived from collecting duct. The principal cell subpopulation enriched for GPRC5A expression also exhibited increased transcription factor binding motif availability for NF-{kappa}B, TEAD, CREB and retinoic acid receptor families and we identified and validated a distal enhancer regulating GPRC5A expression containing these transcription factor binding motifs. This study establishes the single cell transcriptomic and epigenomic landscape of ADPKD, revealing previously unrecognized cellular heterogeneity.

genomics↗

bioRxiv2021

Spectrum graph-based de-novo sequencing algorithm MaxNovo achieves high peptide identification rates in collisional dissociation MS/MS spectra

We describe MaxNovo, a novel spectrum graph-based peptide de-novo sequencing algorithm integrated into the MaxQuant software. It identifies complete sequences of peptides as well as sequence tags that are incomplete at one or both of the peptide termini. MaxNovo searches for the highest-scoring path in a directed acyclic graph representing the MS/MS spectrum with peaks as nodes and edges as potential sequence constituents consisting of single amino acids or pairs. The raw score is a sum of node and edge weights, plus several reward scores, for instance, for complementary ions or protease compatibility. For search-engine identified peptides, it correlates well with the Andromeda search engine score. We use a particular score normalization and the score difference between the first and second-best solution to define a combined score that integrates all available information. To evaluate its performance, we use a human cell line dataset and take as ground truth all Andromeda-identified MS/MS spectra with an Andromeda score of at least 100. MaxNovo outperforms other software in particular in the high-sensitivity range of precision-coverage plots. We also identify incomplete sequence tags and study their statistical properties. Next, we apply MaxNovo to ion mobility-coupled time of flight data. Here we achieve excellent performance as well, except for potential swaps of the two amino acids closest to the C-terminus, which are not well resolved due to the low end of the mass range in MS/MS spectra in this dataset. We demonstrate the applicability of MaxNovo to palaeoproteomics samples with a Late Pleistocene hominin proteome dataset that was generated using three proteases. Interestingly, we did not use any machine learning in the construction of MaxNovo, but implemented expert domain knowledge directly in the definition of the score. Yet, it performs as good as or better than the leading deep learning-based algorithm.

bioinformatics↗

bioRxiv2021

Accurate and automated high-coverage identification of chemically cross-linked peptides with MaxLynx

Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the 3D structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to non-cleavable and MS-cleavable cross linkers. For both we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For non-cleavable peptides, we implemented a novel di-peptide Andromeda score, which is the basis for a computationally efficient N-squared search engine. Additionally, partial scores summarize the evidence for the two constituents of the di-peptide individually. A posterior error probability based on total and partial scores is used to control false discovery rates. For MS-cleavable cross linkers a scoring of signature peaks is combined with the conventional Andromeda score on the cleavage products. The MaxQuant 3D-peak detection was improved to ensure more accurate determination of the monoisotopic peak of isotope patterns for heavy molecules, which cross-linked peptides typically are. A wide selection of filtering parameters can replace manual filtering of identifications, which is often necessary when using other pipelines. On benchmark datasets of synthetic peptides, MaxLynx outperforms all other tested software on data for both types of cross linkers as well as on a proteome-wide dataset of cross-linked D. melanogaster cell lysate. The workflow also supports ion-mobility enhanced MS data. MaxLynx runs on Windows and Linux, contains an interactive viewer for displaying annotated cross-linked spectra and is freely available at https://www.maxquant.org/.

bioinformatics↗

bioRxiv2021

Strong and opponent contributions of dorsomedial striatal pathways to behavior depends on cognitive demands and task strategy

A classic view of the striatum holds that activity in direct and indirect pathways oppositely modulates motor output. Whether this involves direct control of movement, or reflects a cognitive process underlying movement, remains unresolved. Here we find that strong, opponent control of behavior by the two pathways of the dorsomedial striatum (DMS) depends on the cognitive requirements of a task. Furthermore, a latent state model (a hidden markov model with generalized linear model observations) reveals that--even within a single task--the contribution of the two pathways to behavior is state-dependent. Specifically, the two pathways have large contributions in one of two states associated with a strategy of evidence accumulation, compared to a state associated with a strategy of repeating previous choices. Thus, both the demands imposed by a task, as well as the internal state of mice when performing a task, determine whether DMS pathways provide strong and opponent control of behavior.

neuroscience↗

bioRxiv2021

Protein domain patterns reveal a functional diversity of the archaeal Cdv system and give insights into the origin of the eukaryotic ESCRT system

The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across super-phyla suggests that a precursor ESCRT machinery existed already at an evolutionary early stage of life, making it a promising candidate for the (re)construction of a minimal cell division machinery. There are, however, only few experimental data about ESCRT machineries in Archaea, due to high technical challenges in cultivation and microscopy. Here, we analyse the proteins of archaeal ESCRT machineries bioinformatically on a domain level, to enable mechanistical comparison without such challenging experiments. First, we infer that there are at least three different cell division mechanisms utilizing ESCRT proteins in archaea, probably similar in their constriction mechanisms but different in membrane tethering. Second, we show that ESCRT proteins in Asgard archaea are highly similar to eukaryotic ESCRT proteins, strengthening the recently developed idea that all Eukaryotes descended from archaea. Third, we reconstruct a plausible evolutionary development of ESCRT machineries and suggest that a simple ESCRT-based constriction machinery existed in the last archaeal common ancestor. These findings not only give very interesting insights into the evolution of cell division in Archaea and Eukaryotes, but also reveal new research avenues by suggesting hypothesis-driven experiments for both, cell biology and bottom-up synthetic biology.

molecular biology↗

bioRxiv2020

Serine Palmitoyltransferase Controls Stemness of Intestinal Progenitors

Cancers of the gastrointestinal tract including esophageal adenocarcinomas, colorectal cancers, and cancers of the gastric cardia are common comorbidities of obesity. Excessive delivery of macronutrients to the cells lining the gut can increase ones risk for these cancer by inducing imbalances in the rate of intestinal stem cell proliferation vs. differentiation, which can produce polyps and other aberrant growths. We demonstrate that serine palmitoyltransferase (SPT), which diverts dietary fatty and amino acids into the sphingolipid biosynthesis pathway, is a critical modulator of intestinal stem cell homeostasis. SPT and other enzymes in the biosynthetic pathway are upregulated in human colon tumors. These enzymes produce sphingolipids that serve as pro-stemness signals that stimulate peroxisome-proliferator activated receptor alpha (PPAR)-mediated induction of fatty acid binding protein-1. This increases fatty acid uptake and oxidation and enhances the stemness program. Serine palmitoyltransferase thus serves as a critical link between dietary macronutrients, epithelial regeneration, and cancer risk.

cell biology↗

bioRxiv2020

Mitochondrial fatty acid synthesis coordinates mitochondrial oxidative metabolism

Cells harbor two systems for fatty acid synthesis, one in the cytoplasm (catalyzed by fatty acid synthase, FASN) and one in the mitochondria (mtFAS). In contrast to FASN, mtFAS is poorly characterized, especially in higher eukaryotes, with the major product(s), metabolic roles, and cellular function(s) being essentially unknown. Here we show that hypomorphic mtFAS mutants display a severe loss of electron transport chain (ETC) complexes and exhibit compensatory metabolic activities including reductive carboxylation. This effect on ETC complexes appears to be independent of protein lipoylation, the best characterized function of mtFAS, as mutants lacking lipoylation have an intact ETC. Finally, mtFAS impairment blocks the differentiation of skeletal myoblasts in vitro. Together, these data suggest that ETC activity in mammals is profoundly controlled by mtFAS function, thereby connecting anabolic fatty acid synthesis with the oxidation of carbon fuels.

biochemistry↗

bioRxiv2020

Isobaric matching between runs and novel PSM-level normalization in MaxQuant strongly improve reporter ion-based quantification

Isobaric labeling has the promise of combining high sample multiplexing with precise quantification. However, normalization issues and the missing value problem of complete n-plexes hamper quantification across more than one n-plex. Here we introduce two novel algorithms implemented in MaxQuant that substantially improve the data analysis with multiple n-plexes. First, isobaric matching between runs (IMBR) makes use of the three-dimensional MS1 features to transfer identifications from identified to unidentified MS/MS spectra between LC-MS runs in order to utilize reporter ion intensities in unidentified spectra for quantification. On typical datasets, we observe a significant gain in quantifiable n-plexes. Second, we introduce a novel PSM-level normalization, applicable to data with and without common reference channel. It is a weighted median-based method, in which the weights reflect the number of ions that were used for fragmentation. On a typical dataset, we observe complete removal of batch effects and dominance of the biological sample grouping after normalization. Furthermore, we provide many novel processing and normalization options in Perseus, the companion software for the downstream analysis of quantitative proteomics results. All novel tools and algorithms are available with the regular MaxQuant and Perseus releases, which are downloadable at http://maxquant.org.

bioinformatics↗

bioRxiv2019

Mitochondrial pyruvate carrier is required for optimal brown fat thermogenesis

Brown adipose tissue (BAT) is composed of thermogenic cells that convert chemical energy into heat to help maintain a constant body temperature and counteract metabolic disease in mammals. The metabolic adaptations required for thermogenesis are not fully understood. Here we explore how steady state levels of metabolic intermediates are altered in brown adipose tissue in response to cold exposure. Transcriptome and metabolome analysis revealed changes in pathways involved in amino acid, glucose, and TCA cycle metabolism. Using isotopic labeling experiments, we found that activated brown adipocytes increased labeling of pyruvate and TCA cycle intermediates from U13C-glucose. Although glucose oxidation has been implicated as being essential for thermogenesis, its requirement for efficient thermogenesis has not been directly tested. Here we show that mitochondrial pyruvate uptake is essential for optimal thermogenesis, as conditional deletion of Mpc1 in brown adipocytes leads to impaired cold adaptation. Isotopic labeling experiments using U13C-glucose showed that loss of MPC1 led to impaired labeling of TCA cycle intermediates, while labeling of glycolytic intermediates was unchanged. Loss of MPC1 in BAT increased 3-hydroxybutyrate levels in blood and BAT in response to the cold, suggesting that ketogenesis provides an alternative fuel source that partially compensates for impaired mitochondrial oxidation of cytosolic pyruvate. Collectively, these studies highlight that complete glucose oxidation is essential for optimal brown fat thermogenesis.

biochemistry↗

bioRxiv2019

A spatial genomic approach identifies time lags and historic barriers to gene flow in a rapidly fragmenting Appalachian landscape

The resolution offered by genomic data sets coupled with recently developed spatially informed analyses are allowing researchers to quantify population structure at increasingly fine temporal and spatial scales. However, uncertainties regarding data set size and quality thresholds and the time scale at which barriers to gene flow become detectable have limited both empirical research and conservation measures. Here, we used restriction site associated DNA sequencing to generate a large SNP data set for the copperhead snake (Agkistrodon contortrix) and address the population genomic impacts of recent and widespread landscape modification across an approximately 1000 km2 region of eastern Kentucky. Nonspatial population-based assignment and clustering methods supported little to no population structure. However, using individual-based spatial autocorrelation approaches we found evidence for genetic structuring which closely follows the path of a historic highway which experienced high traffic volumes from ca. 1920 to 1970. We found no similar spatial genomic signatures associated with more recently constructed highways or surface mining activity, though a time lag effect may be responsible for the lack of any emergent spatial genetic patterns. Subsampling of our SNP data set suggested that similar results could be obtained with as few as 250 SNPs, and thresholds for missing data exhibited limited impacts on the spatial patterns we detected outside of very strict or permissive extremes. Our findings highlight the importance of temporal factors in landscape genetics approaches, and suggest the potential advantages of large genomic data sets and fine-scale, spatially-informed approaches for quantifying subtle genetic patterns in temporally complex landscapes.

evolutionary biology↗

bioRxiv2019

LIN28B-PDZ Binding Kinase Signaling Promotes Neuroblastoma Metastasis

Neuroblastoma is an aggressive pediatric malignancy of the neural crest with suboptimal cure rates and a striking predilection for widespread metastases, underscoring the need to identify novel therapeutic vulnerabilities. We recently identified the RNA binding protein LIN28B as a driver in high-risk neuroblastoma and demonstrated it promotes oncogenic cell proliferation by coordinating a RAN-Aurora kinase A network. Here, we demonstrate that LIN28B influences another key hallmark of cancer, metastatic dissemination. Using a murine xenograft model of neuroblastoma dissemination, we show that LIN28B promotes metastasis. We demonstrate that this is in part due to the effects of LIN28B on self-renewal and migration, providing an understanding of how LIN28B shapes the metastatic phenotype. Our studies reveal that the let-7 family, which LIN28B inhibits, opposes the effects of LIN28B. Next, we identify PDZ Binding Kinase (PBK) as a novel LIN28B target. PBK is a serine/threonine kinase that promotes the proliferation and self-renewal of neural stem cells and serves as an oncogenic driver in multiple aggressive malignancies. We demonstrate that PBK is both a novel direct target of let-7 and that MYCN regulates PBK expression, thus elucidating two oncogenic drivers that converge on PBK. Functionally, PBK promotes self-renewal and migration, phenocopying LIN28B. Taken together, our findings define a role for LIN28B in neuroblastoma metastasis and define the targetable kinase PBK as a potential novel vulnerability in metastatic neuroblastoma.

cancer biology↗

bioRxiv2019

Local human movement patterns and land use impact exposure to zoonotic malaria in Malaysian Borneo

Human movement into insect vector and wildlife reservoir habitats determines zoonotic disease risks; however, few data are available to quantify the impact of land use on pathogen transmission. Here, we utilise GPS tracking devices and novel applications of ecological methods to develop fine-scale models of human space use relative to land cover to assess exposure to the zoonotic malaria Plasmodium knowlesi in Malaysian Borneo. Combining data with spatially explicit models of mosquito biting rates, we demonstrate the role of individual heterogeneities in local space use in disease exposure. At a community level, our data indicate that areas close to both secondary forest and houses have the highest probability of human P. knowlesi exposure, providing quantitative evidence for the importance of ecotones. Despite higher biting rates in forests, incorporating human movement space use into exposure estimates illustrates the importance of intensified interactions between pathogens, insect vectors and people around habitat edges.

ecology↗

bioRxiv2019

MaxQuant software for ion mobility enhanced shotgun proteomics

Ion mobility can add a dimension to LC-MS based shotgun proteomics which has the potential to boost proteome coverage, quantification accuracy and dynamic range. Required for this is suitable software that extracts the information contained in the four-dimensional (4D) data space spanned by m/z, retention time, ion mobility and signal intensity. Here we describe the ion mobility enhanced MaxQuant software, which utilizes the added data dimension. It offers an end to end computational workflow for the identification and quantification of peptides, proteins and posttranslational modification sites in LC-IMS-MS/MS shotgun proteomics data. We apply it to trapped ion mobility spectrometry (TIMS) coupled to a quadrupole time-of-flight (QTOF) analyzer. A highly parallelizable 4D feature detection algorithm extracts peaks which are assembled to isotope patterns. Masses are recalibrated with a non-linear m/z, retention time, ion mobility and signal intensity dependent model, based on peptides from the sample. A new matching between runs (MBR) algorithm that utilizes collisional cross section (CCS) values of MS1 features in the matching process significantly gains specificity from the extra dimension. Prerequisite for using CCS values in MBR is a relative alignment of the ion mobility values between the runs. The missing value problem in protein quantification over many samples is greatly reduced by CCS aware MBR.MS1 level label-free quantification is also implemented which proves to be highly precise and accurate on a benchmark dataset with known ground truth. MaxQuant for LC-IMS-MS/MS is part of the basic MaxQuant release and can be downloaded from http://maxquant.org.

bioinformatics↗

bioRxiv2019

Sensory neuron-derived Nav1.7 contributes to dorsal horn neuron excitability

Expression of the voltage-gated sodium channel Nav1.7 in sensory neurons is required for pain sensation. We examined the role of Nav1.7 in the dorsal horn of the spinal cord using an epitope-tagged knock-in mouse. Immuno-electron microscopy showed the presence of Nav1.7 in dendrites of lamina II neurons, despite the absence of mRNA. Peripheral nervous system-specific Nav1.7 KO mice showed central deficits with lamina II dorsal horn tonic firing neurons more than halved and single spiking neurons more than doubled. Nav1.7 blocker PF05089771 diminished excitability in dorsal horn neurons, but had no effect on Nav1.7 KO mice. These data demonstrate an unsuspected functional role of peripherally generated Nav1.7 in dorsal horn neurons and an expression pattern that would not be predicted by transcriptomic analysis.

neuroscience↗

bioRxiv2018

Specialized and spatially organized coding of sensory, motor, and cognitive variables in midbrain dopamine neurons

There is increased appreciation that dopamine (DA) neurons in the midbrain respond not only to reward 1,2 and reward-predicting cues 1,3,4, but also to other variables such as distance to reward 5, movements 6-11 and behavioral choices 12-15. Based on these findings, a major open question is how the responses to these diverse variables are organized across the population of DA neurons. In other words, do individual DA neurons multiplex multiple variables, or are subsets of neurons specialized in encoding specific behavioral variables? The reason that this fundamental question has been difficult to resolve is that recordings from large populations of individual DA neurons have not been performed in a behavioral task with sufficient complexity to examine these diverse variables simultaneously. To address this gap, we used 2-photon calcium imaging through an implanted lens to record activity of >300 midbrain DA neurons in the VTA during a complex decision-making task. As mice navigated in a virtual reality (VR) environment, DA neurons encoded an array of sensory, motor, and cognitive variables. These responses were functionally clustered, such that subpopulations of neurons transmitted information about a subset of behavioral variables, in addition to encoding reward. These functional clusters were spatially organized, such that neighboring neurons were more likely to be part of the same cluster. Taken together with the topography between DA neurons and their projections, this specialization and anatomical organization may aid downstream circuits in correctly interpreting the wide range of signals transmitted by DA neurons.

neuroscience↗