Proximity Mapping of Desmosomes Reveals a Striking Shift in Their Molecular Neighborhood Associated With Maturation.

Desmosomes are multiprotein adhesion complexes that link intermediate filaments to the plasma membrane, ensuring the mechanical integrity of cells across tissues, but how they participate in the wider signaling network to exert their full function is unclear. To investigate this, we carried out protein proximity mapping using biotinylation (BioID). The combined interactomes of the essential desmosomal proteins desmocollin 2a, plakoglobin, and plakophilin 2a (Pkp2a) in Madin-Darby canine kidney epithelial cells were mapped and their differences and commonalities characterized as desmosome matured from Ca2+ dependence to the mature, Ca2+-independent, hyper-adhesive state, which predominates in tissues. Results suggest that individual desmosomal proteins have distinct roles in connecting to cellular signaling pathways and that these roles alter substantially when cells change their adhesion state. The data provide further support for a dualistic concept of desmosomes in which the properties of Pkp2a differ from those of the other, more stable proteins. This body of data provides an invaluable resource for the analysis of desmosome function.

Proximity labelling identifies pro-migratory endocytic recycling cargo and machinery of the Rab4 and Rab11 families.

Endocytic recycling controls the return of internalised cargoes to the plasma membrane to coordinate their positioning, availability and downstream signalling. The Rab4 and Rab11 small GTPase families regulate distinct recycling routes, broadly classified as fast recycling from early endosomes (Rab4) and slow recycling from perinuclear recycling endosomes (Rab11), and both routes handle a broad range of overlapping cargoes to regulate cell behaviour. We adopted a proximity labelling approach, BioID, to identify and compare the protein complexes recruited by Rab4a, Rab11a and Rab25 (a Rab11 family member implicated in cancer aggressiveness), revealing statistically robust protein-protein interaction networks of both new and well-characterised cargoes and trafficking machinery in migratory cancer cells. Gene ontological analysis of these interconnected networks revealed that these endocytic recycling pathways are intrinsically connected to cell motility and cell adhesion. Using a knock-sideways relocalisation approach, we were further able to confirm novel links between Rab11, Rab25 and the ESCPE-1 and retromer multiprotein sorting complexes, and identify new endocytic recycling machinery associated with Rab4, Rab11 and Rab25 that regulates cancer cell migration in the 3D matrix.

Mitochondrial antiviral-signalling protein is a client of the BAG6 protein quality control complex.

The heterotrimeric BAG6 complex coordinates the direct handover of newly synthesised tail-anchored (TA) membrane proteins from an SGTA-bound preloading complex to the endoplasmic reticulum (ER) delivery component TRC40. In contrast, defective precursors, including aberrant TA proteins, form a stable complex with this cytosolic protein quality control factor, enabling such clients to be either productively re-routed or selectively degraded. We identify the mitochondrial antiviral-signalling protein (MAVS) as an endogenous TA client of both SGTA and the BAG6 complex. Our data suggest that the BAG6 complex binds to a cytosolic pool of MAVS before its misinsertion into the ER membrane, from where it can subsequently be removed via ATP13A1-mediated dislocation. This BAG6-associated fraction of MAVS is dynamic and responds to the activation of an innate immune response, suggesting that BAG6 may modulate the pool of MAVS that is available for coordinating the cellular response to viral infection.

Modeling collagen fibril self-assembly from extracellular medium in embryonic tendon.

Collagen is a key structural component of multicellular organisms and is arranged in a highly organized manner. In structural tissues such as tendons, collagen forms bundles of parallel fibers between cells, which appear within a 24-h window between embryonic day 13.5 (E13.5) and E14.5 during mouse embryonic development. Current models assume that the organized structure of collagen requires direct cellular control, whereby cells actively lay down collagen fibrils from cell surfaces. However, such models appear incompatible with the time and length scales of fibril formation. We propose a phase-transition model to account for the rapid development of ordered fibrils in embryonic tendon, reducing reliance on active cellular processes. We develop phase-field crystal simulations of collagen fibrillogenesis in domains derived from electron micrographs of inter-cellular spaces in embryonic tendon and compare results qualitatively and quantitatively to observed patterns of fibril formation. To test the prediction of this phase-transition model that free protomeric collagen should exist in the inter-cellular spaces before the formation of observable fibrils, we use laser-capture microdissection, coupled with mass spectrometry, which demonstrates steadily increasing free collagen in inter-cellular spaces up to E13.5, followed by a rapid reduction of free collagen that coincides with the appearance of less-soluble collagen fibrils. The model and measurements together provide evidence for extracellular self-assembly of collagen fibrils in embryonic mouse tendon, supporting an additional mechanism for rapid collagen fibril formation during embryonic development.

Morphologically intact airways in lung fibrosis have an abnormal proteome.

Honeycombing is a histological pattern consistent with Usual Interstitial Pneumonia (UIP). Honeycombing refers to cystic airways located at sites of dense fibrosis with marked mucus accumulation. Utilizing laser capture microdissection coupled mass spectrometry (LCM-MS), we interrogated the fibrotic honeycomb airway cells and fibrotic uninvolved airway cells (distant from honeycomb airways and morphologically intact) in specimens from 10 patients with UIP. Non-fibrotic airway cell specimens from 6 patients served as controls. Furthermore, we performed LCM-MS on the mucus plugs found in 6 patients with UIP and 6 patients with mucinous adenocarcinoma. The mass spectrometry data were subject to both qualitative and quantitative analysis and validated by immunohistochemistry. Surprisingly, fibrotic uninvolved airway cells share a similar protein profile to honeycomb airway cells, showing deregulation of the slit and roundabout receptor (Slit and Robo) pathway as the strongest category. We find that (BPI) fold-containing family B member 1 (BPIFB1) is the most significantly increased secretome-associated protein in UIP, whereas Mucin-5AC (MUC5AC) is the most significantly increased in mucinous adenocarcinoma. We conclude that fibrotic uninvolved airway cells share pathological features with fibrotic honeycomb airway cells. In addition, fibrotic honeycomb airway cells are enriched in mucin biogenesis proteins with a marked derangement in proteins essential for ciliogenesis. This unbiased spatial proteomic approach generates novel and testable hypotheses to decipher fibrosis progression.

Collagen Sequence Analysis Reveals Evolutionary History of Extinct West Indies Nesophontes (Island-Shrews).

Ancient biomolecule analyses are proving increasingly useful in the study of evolutionary patterns, including extinct organisms. Proteomic sequencing techniques complement genomic approaches, having the potential to examine lineages further back in time than achievable using ancient DNA, given the less stringent preservation requirements. In this study, we demonstrate the ability to use collagen sequence analyses via proteomics to assist species delimitation as a foundation for informing evolutionary patterns. We uncover biogeographic information of an enigmatic and recently extinct lineage of Nesophontes across their range on the Caribbean islands. First, evolutionary relationships reconstructed from collagen sequences reaffirm the affinity of Nesophontes and Solenodon as sister taxa within Solenodonota. This relationship helps lay the foundation for testing geographical isolation hypotheses across islands within the Greater Antilles, including movement from Cuba toward Hispaniola. Second, our results are consistent with Cuba having just two species of Nesophontes (N. micrus and N. major) that exhibit intrapopulation morphological variation. Finally, analysis of the recently described species from the Cayman Islands (N. hemicingulus) indicates that it is a closer relative to N. major rather than N. micrus as previously speculated. This proteomic sequencing improves our understanding of the origin, evolution, and distribution of this extinct mammal lineage, particularly with respect to the approximate timing of speciation. Such knowledge is vital for this biodiversity hotspot, where the magnitude of recent extinctions may obscure true estimates of species richness in the past.

Laser capture microdissection coupled mass spectrometry (LCM-MS) for spatially resolved analysis of formalin-fixed and stained human lung tissues.

BACKGROUND: Haematoxylin and eosin (H&E)-which respectively stain nuclei blue and other cellular and stromal material pink-are routinely used for clinical diagnosis based on the identification of morphological features. A richer characterization can be achieved by laser capture microdissection coupled to mass spectrometry (LCM-MS), giving an unbiased assay of the proteins that make up the tissue. However, the process of fixing and H&E staining of tissues provides challenges with standard sample preparation methods for mass spectrometry, resulting in low protein yield. Here we describe a microproteomics technique to analyse H&E-stained, formalin-fixed paraffin-embedded (FFPE) tissues. METHODS: Herein, we utilize heat extraction, physical disruption, and in column digestion for the analysis of H&E stained FFPE tissues. Micro-dissected morphologically normal human lung alveoli (0.082 mm3) and human lung blood vessels (0.094 mm3) from FFPE-fixed H&E-stained sections from Idiopathic Pulmonary Fibrosis (IPF) specimens (n = 3 IPF specimens) were then subject to a qualitative and then quantitative proteomics approach using BayesENproteomics. In addition, we tested the sensitivity of this method by processing and analysing a range of micro-dissected human lung blood vessel tissue volumes. RESULTS: This approach yields 1252 uniquely expressed proteins (at a protein identification threshold of 3 unique peptides) with 892 differentially expressed proteins between these regions. In accord with prior knowledge, our methodology approach confirms that human lung blood vessels are enriched with smoothelin, CNN1, ITGA7, MYH11, TAGLN, and PTGIS; whereas morphologically normal human lung alveoli are enriched with cytokeratin-7, -8, -18, -19, 14, and -17. In addition, we identify a total of 137 extracellular matrix (ECM) proteins and immunohistologically validate that laminin subunit beta-1 localizes to morphologically normal human lung alveoli and tenascin localizes to human lung blood vessels. Lastly, we show that this micro-proteomics technique can be applied to tissue volumes as low as 0.0125 mm3. CONCLUSION: Herein we show that our multistep sample preparation methodology of LCM-MS can identify distinct, characteristic proteomic compositions of anatomical features within complex fixed and stained tissues.

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring.

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800Saccharomyces cerevisiaeproteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a "gold-standard" reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies.

Absolute protein quantification of the yeast chaperome under conditions of heat shock.

Chaperones are fundamental to regulating the heat shock response, mediating protein recovery from thermal-induced misfolding and aggregation. Using the QconCAT strategy and selected reaction monitoring (SRM) for absolute protein quantification, we have determined copy per cell values for 49 key chaperones in Saccharomyces cerevisiae under conditions of normal growth and heat shock. This work extends a previous chemostat quantification study by including up to five Q-peptides per protein to improve confidence in protein quantification. In contrast to the global proteome profile of S. cerevisiae in response to heat shock, which remains largely unchanged as determined by label-free quantification, many of the chaperones are upregulated with an average two-fold increase in protein abundance. Interestingly, eight of the significantly upregulated chaperones are direct gene targets of heat shock transcription factor-1. By performing absolute quantification of chaperones under heat stress for the first time, we were able to evaluate the individual protein-level response. Furthermore, this SRM data was used to calibrate label-free quantification values for the proteome in absolute terms, thus improving relative quantification between the two conditions. This study significantly enhances the largely transcriptomic data available in the field and illustrates a more nuanced response at the protein level.

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics.

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Representation of selected-reaction monitoring data in the mzQuantML data standard.

The mzQuantML data standard was designed to capture the output of quantitative software in proteomics, to support submissions to public repositories, development of visualization software and pipeline/modular approaches. The standard is designed around a common core that can be extended to support particular types of technique through the release of semantic rules that are checked by validation software. The first release of mzQuantML supported four quantitative proteomics techniques via four sets of semantic rules: (i) intensity-based (MS(1) ) label free, (ii) MS(1) label-based (such as SILAC or N(15) ), (iii) MS(2) tag-based (iTRAQ or tandem mass tags), and (iv) spectral counting. We present an update to mzQuantML for supporting SRM techniques. The update includes representing the quantitative measurements, and associated meta-data, for SRM transitions, the mechanism for inferring peptide-level or protein-level quantitative values, and support for both label-based or label-free SRM protocols, through the creation of semantic rules and controlled vocabulary terms. We have updated the specification document for mzQuantML (version 1.0.1) and the mzQuantML validator to ensure that consistent files are produced by different exporters. We also report the capabilities for production of mzQuantML files from popular SRM software packages, such as Skyline and Anubis.

Verification of a Parkinson's disease protein signature in T-lymphocytes by multiple reaction monitoring.

Diagnosis of Parkinson's disease, the second most common neurodegenerative disease, is based on the appearance of motor symptoms. A panel of protein biomarkers in the T-lymphocyte proteome was previously proposed as a Parkinson's disease signature. Here, we designed an LC-MS based method to quantitatively evaluate this protein signature by multiple reaction monitoring (MRM) in T-lymphocytes and peripheral blood mononuclear cells from a new cohort of nine patients with Parkinson's disease and nine unaffected subjects. Patients were classified using the discriminant function obtained from two-dimensional electrophoresis and protein amounts measured by MRM, thus assigning seven controls out of nine as true negatives and nine patients out of nine as true positives. A good discriminant power was obtained by selecting a subset of peptides from the protein signature, with an area under the receiver operating characteristic curve of 0.877. A similar result is achieved by evaluating all peptides of a selected panel of proteins (gelsolin, moesin, septin-6, twinfilin-2, lymphocyte-specific protein 1, vimentin, transaldolase), with an area under the curve of 0.840. Conversely, the signature was not able to classify the enrolled subjects when evaluated in whole mononuclear cells. Overall, this report shows the portability of the proposed method to a large-scale clinical validation study.

Optimising a self-assembling peptide hydrogel as a Matrigel alternative for 3-dimensional mammary epithelial cell culture.

Three-dimensional (3D) organoid models have been instrumental in understanding molecular mechanisms responsible for many cellular processes and diseases. However, established organic biomaterial scaffolds used for 3D hydrogel cultures, such as Matrigel, are biochemically complex and display significant batch variability, limiting reproducibility in experiments. Recently, there has been significant progress in the development of synthetic hydrogels for in vitro cell culture that are reproducible, mechanically tuneable, and biocompatible. Self-assembling peptide hydrogels (SAPHs) are synthetic biomaterials that can be engineered to be compatible with 3D cell culture. Here we investigate the ability of PeptiGel® SAPHs to model the mammary epithelial cell (MEC) microenvironment in vitro. The positively charged PeptiGel®Alpha4 supported MEC viability, but did not promote formation of polarised acini. Modifying the stiffness of PeptiGel® Alpha4 stimulated changes in MEC viability and changes in protein expression associated with altered MEC function, but did not fully recapitulate the morphologies of MECs grown in Matrigel. To supply the appropriate biochemical signals for MEC organoids, we supplemented PeptiGels® with laminin. Laminin was found to require negatively charged PeptiGel® Alpha7 for functionality, but was then able to provide appropriate signals for correct MEC polarisation and expression of characteristic proteins. Thus, optimisation of SAPH composition and mechanics allows tuning to support tissue-specific organoids.

Kidney resident macrophages have distinct subsets and multifunctional roles.

BACKGROUND: The kidney contains distinct glomerular and tubulointerstitial compartments with diverse cell types and extracellular matrix components. The role of immune cells in glomerular environment is crucial for dampening inflammation and maintaining homeostasis. Macrophages are innate immune cells that are influenced by their tissue microenvironment. However, the multifunctional role of kidney macrophages remains unclear. METHODS: Flow and imaging cytometry were used to determine the relative expression of CD81 and CX3CR1 (C-X3-C motif chemokine receptor 1) in kidney macrophages. Monocyte replenishment was assessed in Cx3cr1CreER X R26-yfp-reporter and shielded chimeric mice. Bulk RNA-sequencing and mass spectrometry-based proteomics were performed on isolated kidney macrophages from wild type and Col4a5-/- (Alport) mice. RNAscope was used to visualize transcripts and macrophage purity in bulk RNA assessed by CIBERSORTx analyses. RESULTS: In wild type mice we identified three distinct kidney macrophage subsets using CD81 and CX3CR1 and these subsets showed dependence on monocyte replenishment. In addition to their immune function, bulk RNA-sequencing of macrophages showed enrichment of biological processes associated with extracellular matrix. Proteomics identified collagen IV and laminins in kidney macrophages from wild type mice whilst other extracellular matrix proteins including cathepsins, ANXA2 and LAMP2 were enriched in Col4a5-/- (Alport) mice. A subset of kidney macrophages co-expressed matrix and macrophage transcripts. CONCLUSIONS: We identified CD81 and CX3CR1 positive kidney macrophage subsets with distinct dependence for monocyte replenishment. Multiomic analysis demonstrated that these cells have diverse functions that underscore the importance of macrophages in kidney health and disease.

Quantitative analysis of chaperone network throughput in budding yeast.

The network of molecular chaperones mediates the folding and translocation of the many proteins encoded in the genome of eukaryotic organisms, as well as a response to stress. It has been particularly well characterised in the budding yeast, Saccharomyces cerevisiae, where 63 known chaperones have been annotated and recent affinity purification and MS/MS experiments have helped characterise the attendant network of chaperone targets to a high degree. In this study, we apply our QconCAT methodology to directly quantify the set of yeast chaperones in absolute terms (copies per cell) via SRM MS. Firstly, we compare these to existing quantitative estimates of these yeast proteins, highlighting differences between approaches. Secondly, we cast the results into the context of the chaperone target network and show a distinct relationship between abundance of individual chaperones and their targets. This allows us to characterise the 'throughput' of protein molecules passing through individual chaperones and their groups on a proteome-wide scale in an unstressed model eukaryote for the first time. The results demonstrate specialisations of the chaperone classes, which display different overall workloads, efficiencies and preference for the sub-cellular localisation of their targets. The novel integration of the interactome data with quantification supports re-estimates of the level of protein throughout going through molecular chaperones. Additionally, although chaperones target fewer than 40% of annotated proteins we show that they mediate the folding of the majority of protein molecules (∼62% of the total protein flux in the cell), highlighting their importance.

CONSeQuence: prediction of reference peptides for absolute quantitative proteomics using consensus machine learning approaches.

Mass spectrometric based methods for absolute quantification of proteins, such as QconCAT, rely on internal standards of stable-isotope labeled reference peptides, or "Q-peptides," to act as surrogates. Key to the success of this and related methods for absolute protein quantification (such as AQUA) is selection of the Q-peptide. Here we describe a novel method, CONSeQuence (consensus predictor for Q-peptide sequence), based on four different machine learning approaches for Q-peptide selection. CONSeQuence demonstrates improved performance over existing methods for optimal Q-peptide selection in the absence of prior experimental information, as validated using two independent test sets derived from yeast. Furthermore, we examine the physicochemical parameters associated with good peptide surrogates, and demonstrate that in addition to charge and hydrophobicity, peptide secondary structure plays a significant role in determining peptide "detectability" in liquid chromatography-electrospray ionization experiments. We relate peptide properties to protein tertiary structure, demonstrating a counterintuitive preference for buried status for frequently detected peptides. Finally, we demonstrate the improved efficacy of the general approach by applying a predictor trained on yeast data to sets of proteotypic peptides from two additional species taken from an existing peptide identification repository.

Protocol to characterize basement membranes during kidney development using mass spectrometry-based label-free quantitative proteomics.

Basement membranes are specialized extracellular matrices formed by highly insoluble structural proteins and extracellular matrix (ECM)-bound components that provide structural and signaling support to tissues and are dynamic during development. Here, we present a mass spectrometry-based label-free quantitative proteomics protocol to investigate basement membranes and define their composition using samples from human kidney organoids and mouse fetal kidneys. This protocol facilitates the study of basement membrane and other ECM components during development to improve our understanding of matrix regulation and function. For complete details on the use and execution of this protocol, please refer to Morais et al.1.

Mechanical loading and hyperosmolarity as a daily resetting cue for skeletal circadian clocks.

Daily rhythms in mammalian behaviour and physiology are generated by a multi-oscillator circadian system entrained through environmental cues (e.g. light and feeding). The presence of tissue niche-dependent physiological time cues has been proposed, allowing tissues the ability of circadian phase adjustment based on local signals. However, to date, such stimuli have remained elusive. Here we show that daily patterns of mechanical loading and associated osmotic challenge within physiological ranges reset circadian clock phase and amplitude in cartilage and intervertebral disc tissues in vivo and in tissue explant cultures. Hyperosmolarity (but not hypo-osmolarity) resets clocks in young and ageing skeletal tissues and induce genome-wide expression of rhythmic genes in cells. Mechanistically, RNAseq and biochemical analysis revealed the PLD2-mTORC2-AKT-GSK3ß axis as a convergent pathway for both in vivo loading and hyperosmolarity-induced clock changes. These results reveal diurnal patterns of mechanical loading and consequent daily oscillations in osmolarity as a bona fide tissue niche-specific time cue to maintain skeletal circadian rhythms in sync.

Chemokines form complex signals during inflammation and disease that can be decoded by extracellular matrix proteoglycans.

Chemokine-driven leukocyte recruitment is a key component of the immune response and of various diseases. Therapeutically targeting the chemokine system in inflammatory disease has been unsuccessful, which has been attributed to redundancy. We investigated why chemokines instead have specific, specialized functions, as demonstrated by multiple studies. We analyzed the expression of genes encoding chemokines and their receptors across species, tissues, and diseases. This analysis revealed complex expression patterns such that genes encoding multiple chemokines that mediated recruitment of the same leukocyte type were expressed in the same context, such as the genes encoding the CXCR3 ligands CXCL9, CXCL10, and CXCL11. Through biophysical approaches, we showed that these chemokines differentially interacted with extracellular matrix glycosaminoglycans (ECM GAGs), which was enhanced by sulfation of specific GAGs. Last, in vivo approaches demonstrated that GAG binding was critical for the CXCL9-dependent recruitment of specific T cell subsets but not of others, irrespective of CXCR3 expression. Our data demonstrate that interactions with ECM GAGs regulated whether chemokines were presented on cell surfaces or remained more soluble, thereby affecting chemokine availability and ensuring specificity of chemokine action. Our findings provide a mechanistic understanding of chemokine-mediated immune cell recruitment and identify strategies to target specific chemokines during inflammatory disease.

Chemokine CXCL4 interactions with extracellular matrix proteoglycans mediate widespread immune cell recruitment independent of chemokine receptors.

Leukocyte recruitment from the vasculature into tissues is a crucial component of the immune system but is also key to inflammatory disease. Chemokines are central to this process but have yet to be therapeutically targeted during inflammation due to a lack of mechanistic understanding. Specifically, CXCL4 (Platelet Factor 4, PF4) has no established receptor that explains its function. Here, we use biophysical, in vitro, and in vivo techniques to determine the mechanism underlying CXCL4-mediated leukocyte recruitment. We demonstrate that CXCL4 binds to glycosaminoglycan (GAG) sugars on proteoglycans within the endothelial extracellular matrix, resulting in increased adhesion of leukocytes to the vasculature, increased vascular permeability, and non-specific recruitment of a range of leukocytes. Furthermore, GAG sulfation confers selectivity onto chemokine localization. These findings present mechanistic insights into chemokine biology and provide future therapeutic targets.