Interaction of Neisseria meningitidis carrier and disease isolates of MenB cc32 and MenW cc22 with epithelial cells of the nasopharyngeal barrier.

Neisseria meningitidis (Nm, the meningococcus) is considered an asymptomatic colonizer of the upper respiratory tract and a transient member of its microbiome. It is assumed that the spread of N. meningitidis into the bloodstream occurs via transcytosis of the nasopharyngeal epithelial barrier without destroying the barrier layer. Here, we used Calu-3 respiratory epithelial cells that were grown under air-liquid-interface conditions to induce formation of pseudostratified layers and mucus production. The number of bacterial localizations in the outer mucus, as well as cellular adhesion, invasion and transmigration of different carrier and disease N. meningitidis isolates belonging to MenB:cc32 and MenW:cc22 lineages was assessed. In addition, the effect on barrier integrity and cytokine release was determined. Our findings showed that all strains tested resided primarily in the outer mucus layer after 24 h of infection (>80%). Nonetheless, both MenB:cc32 and MenW:cc22 carrier and disease isolates reached the surface of the epithelial cells and overcame the barrier. Interestingly, we observed a significant difference in the number of bacteria transmigrating the epithelial cell barrier, with the representative disease isolates being more efficient to transmigrate compared to carrier isolates. This could be attributed to the capacity of the disease isolates to invade, however could not be assigned to expression of the outer membrane protein Opc. Moreover, we found that the representative meningococcal isolates tested in this study did not damage the epithelial barrier, as shown by TEER measurement, FITC-dextran permeability assays, and expression of cell-junction components.

Sphingosine kinase 1/S1P receptor signaling axis is essential for cellular uptake of Neisseria meningitidis in brain endothelial cells.

Invasion of brain endothelial cells (BECs) is central to the pathogenicity of Neisseria meningitidis infection. Here, we established a key role for the bioactive sphingolipid sphingosine-1-phosphate (S1P) and S1P receptor (S1PR) 2 in the uptake process. Quantitative sphingolipidome analyses of BECs infected with N. meningitidis revealed elevated S1P levels, which could be attributed to enhanced expression of the enzyme sphingosine kinase 1 and its activity. Increased activity was dependent on the interaction of meningococcal type IV pilus with the endothelial receptor CD147. Concurrently, infection led to increased expression of the S1PR2. Blocking S1PR2 signaling impaired epidermal growth factor receptor (EGFR) phosphorylation, which has been shown to be involved in cytoskeletal remodeling and bacterial endocytosis. Strikingly, targeting S1PR1 or S1PR3 also interfered with bacterial uptake. Collectively, our data support a critical role of the SphK/S1P/S1PR axis in the invasion of N. meningitidis into BECs, defining a potential target for adjuvant therapy.

A Comprehensive Review on the Interplay between Neisseria spp. and Host Sphingolipid Metabolites.

Sphingolipids represent a class of structural related lipids involved in membrane biology and various cellular processes including cell growth, apoptosis, inflammation and migration. Over the past decade, sphingolipids have become the focus of intensive studies regarding their involvement in infectious diseases. Pathogens can manipulate the sphingolipid metabolism resulting in cell membrane reorganization and receptor recruitment to facilitate their entry. They may recruit specific host sphingolipid metabolites to establish a favorable niche for intracellular survival and proliferation. In contrast, some sphingolipid metabolites can also act as a first line defense against bacteria based on their antimicrobial activity. In this review, we will focus on the strategies employed by pathogenic Neisseria spp. to modulate the sphingolipid metabolism and hijack the sphingolipid balance in the host to promote cellular colonization, invasion and intracellular survival. Novel techniques and innovative approaches will be highlighted that allow imaging of sphingolipid derivatives in the host cell as well as in the pathogen.

Click-correlative light and electron microscopy (click-AT-CLEM) for imaging and tracking azido-functionalized sphingolipids in bacteria.

Sphingolipids, including ceramides, are a diverse group of structurally related lipids composed of a sphingoid base backbone coupled to a fatty acid side chain and modified terminal hydroxyl group. Recently, it has been shown that sphingolipids show antimicrobial activity against a broad range of pathogenic microorganisms. The antimicrobial mechanism, however, remains so far elusive. Here, we introduce 'click-AT-CLEM', a labeling technique for correlated light and electron microscopy (CLEM) based on the super-resolution array tomography (srAT) approach and bio-orthogonal click chemistry for imaging of azido-tagged sphingolipids to directly visualize their interaction with the model Gram-negative bacterium Neisseria meningitidis at subcellular level. We observed ultrastructural damage of bacteria and disruption of the bacterial outer membrane induced by two azido-modified sphingolipids by scanning electron microscopy and transmission electron microscopy. Click-AT-CLEM imaging and mass spectrometry clearly revealed efficient incorporation of azido-tagged sphingolipids into the outer membrane of Gram-negative bacteria as underlying cause of their antimicrobial activity.

Semantic Deep Learning: Prior Knowledge and a Type of Four-Term Embedding Analogy to Acquire Treatments for Well-Known Diseases.

BACKGROUND: How to treat a disease remains to be the most common type of clinical question. Obtaining evidence-based answers from biomedical literature is difficult. Analogical reasoning with embeddings from deep learning (embedding analogies) may extract such biomedical facts, although the state-of-the-art focuses on pair-based proportional (pairwise) analogies such as man:woman::king:queen ("queen = -man +king +woman"). OBJECTIVE: This study aimed to systematically extract disease treatment statements with a Semantic Deep Learning (SemDeep) approach underpinned by prior knowledge and another type of 4-term analogy (other than pairwise). METHODS: As preliminaries, we investigated Continuous Bag-of-Words (CBOW) embedding analogies in a common-English corpus with five lines of text and observed a type of 4-term analogy (not pairwise) applying the 3CosAdd formula and relating the semantic fields person and death: "dagger = -Romeo +die +died" (search query: -Romeo +die +died). Our SemDeep approach worked with pre-existing items of knowledge (what is known) to make inferences sanctioned by a 4-term analogy (search query -x +z1 +z2) from CBOW and Skip-gram embeddings created with a PubMed systematic reviews subset (PMSB dataset). Stage1: Knowledge acquisition. Obtaining a set of terms, candidate y, from embeddings using vector arithmetic. Some n-gram pairs from the cosine and validated with evidence (prior knowledge) are the input for the 3cosAdd, seeking a type of 4-term analogy relating the semantic fields disease and treatment. Stage 2: Knowledge organization. Identification of candidates sanctioned by the analogy belonging to the semantic field treatment and mapping these candidates to unified medical language system Metathesaurus concepts with MetaMap. A concept pair is a brief disease treatment statement (biomedical fact). Stage 3: Knowledge validation. An evidence-based evaluation followed by human validation of biomedical facts potentially useful for clinicians. RESULTS: We obtained 5352 n-gram pairs from 446 search queries by applying the 3CosAdd. The microaveraging performance of MetaMap for candidate y belonging to the semantic field treatment was F-measure=80.00% (precision=77.00%, recall=83.25%). We developed an empirical heuristic with some predictive power for clinical winners, that is, search queries bringing candidate y with evidence of a therapeutic intent for target disease x. The search queries -asthma +inhaled_corticosteroids +inhaled_corticosteroid and -epilepsy +valproate +antiepileptic_drug were clinical winners, finding eight evidence-based beneficial treatments. CONCLUSIONS: Extracting treatments with therapeutic intent by analogical reasoning from embeddings (423K n-grams from the PMSB dataset) is an ambitious goal. Our SemDeep approach is knowledge-based, underpinned by embedding analogies that exploit prior knowledge. Biomedical facts from embedding analogies (4-term type, not pairwise) are potentially useful for clinicians. The heuristic offers a practical way to discover beneficial treatments for well-known diseases. Learning from deep learning models does not require a massive amount of data. Embedding analogies are not limited to pairwise analogies; hence, analogical reasoning with embeddings is underexploited.

Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.

BACKGROUND: Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and integration of this knowledge on a scale requires cross checking with ground truths (i.e. evidence-based resources) that are unavailable in an actionable or computable form. In this paper we explore how to turn information about diagnoses, prognoses, therapies and other clinical concepts into computable knowledge using free-text data about human and animal health. We used a Semantic Deep Learning approach that combines the Semantic Web technologies and Deep Learning to acquire and validate knowledge about 11 well-known medical conditions mined from two sets of unstructured free-text data: 300 K PubMed Systematic Review articles (the PMSB dataset) and 2.5 M veterinary clinical notes (the VetCN dataset). For each target condition we obtained 20 related clinical concepts using two deep learning methods applied separately on the two datasets, resulting in 880 term pairs (target term, candidate term). Each concept, represented by an n-gram, is mapped to UMLS using MetaMap; we also developed a bespoke method for mapping short forms (e.g. abbreviations and acronyms). Existing ontologies were used to formally represent associations. We also create ontological modules and illustrate how the extracted knowledge can be queried. The evaluation was performed using the content within BMJ Best Practice. RESULTS: MetaMap achieves an F measure of 88% (precision 85%, recall 91%) when applied directly to the total of 613 unique candidate terms for the 880 term pairs. When the processing of short forms is included, MetaMap achieves an F measure of 94% (precision 92%, recall 96%). Validation of the term pairs with BMJ Best Practice yields precision between 98 and 99%. CONCLUSIONS: The Semantic Deep Learning approach can transform neural embeddings built from unstructured free-text data into reliable and reusable One Health knowledge using ontologies and content from BMJ Best Practice.

Super-Resolution Microscopy Reveals Local Accumulation of Plasma Membrane Gangliosides at Neisseria meningitidis Invasion Sites.

Neisseria meningitidis (meningococcus) is a Gram-negative bacterium responsible for epidemic meningitis and sepsis worldwide. A critical step in the development of meningitis is the interaction of bacteria with cells forming the blood-cerebrospinal fluid barrier, which requires tight adhesion of the pathogen to highly specialized brain endothelial cells. Two endothelial receptors, CD147 and the ß2-adrenergic receptor, have been found to be sequentially recruited by meningococci involving the interaction with type IV pilus. Despite the identification of cellular key players in bacterial adhesion the detailed mechanism of invasion is still poorly understood. Here, we investigated cellular dynamics and mobility of the type IV pilus receptor CD147 upon treatment with pili enriched fractions and specific antibodies directed against two extracellular Ig-like domains in living human brain microvascular endothelial cells. Modulation of CD147 mobility after ligand binding revealed by single-molecule tracking experiments demonstrates receptor activation and indicates plasma membrane rearrangements. Exploiting the binding of Shiga (STxB) and Cholera toxin B (CTxB) subunits to the two native plasma membrane sphingolipids globotriaosylceramide (Gb3) and raft-associated monosialotetrahexosylganglioside GM1, respectively, we investigated their involvement in bacterial invasion by super-resolution microscopy. Structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM) unraveled accumulation and coating of meningococci with GM1 upon cellular uptake. Blocking of CTxB binding sites did not impair bacterial adhesion but dramatically reduced bacterial invasion efficiency. In addition, cell cycle arrest in G1 phase induced by serum starvation led to an overall increase of GM1 molecules in the plasma membrane and consequently also in bacterial invasion efficiency. Our results will help to understand downstream signaling events after initial type IV pilus-host cell interactions and thus have general impact on the development of new therapeutics targeting key molecules involved in infection.

Neisseria meningitidis Type IV Pili Trigger Ca2+-Dependent Lysosomal Trafficking of the Acid Sphingomyelinase To Enhance Surface Ceramide Levels.

Acid sphingomyelinase (ASM) is a lipid hydrolase that converts sphingomyelin to ceramide and that can be activated by various cellular stress mechanisms, including bacterial pathogens. Vesicle transportation or trafficking of ASM from the lysosomal compartment to the cell membrane is a prerequisite for its activation in response to bacterial infections; however, the effectors and mechanisms of ASM translocation and activation are poorly defined. Our recent work documented the key importance of ASM for Neisseria meningitidis uptake into human brain microvascular endothelial cells (HBMEC). We clearly identified OpcA to be one bacterial effector promoting ASM translocation and activity, though it became clear that additional bacterial components were involved, as up to 80% of ASM activity and ceramide generation was retained in cells infected with an opcA-deficient mutant. We hypothesized that N. meningitidis might use pilus components to promote the translocation of ASM into HBMEC. Indeed, we found that both live, piliated N. meningitidis and pilus-enriched fractions trigger transient ASM surface display, followed by the formation of ceramide-rich platforms (CRPs). By using indirect immunocytochemistry and direct stochastic optical reconstruction microscopy, we show that the overall number of CRPs with a size of ∼80 nm in the plasma membrane is significantly increased after exposure to pilus-enriched fractions. Infection with live bacteria as well as exposure to pilus-enriched fractions transiently increased cytosolic Ca2+ levels in HBMEC, and this was found to be important for ASM surface display mediated by lysosomal exocytosis, as depletion of cytosolic Ca2+ resulted in a significant decrease in ASM surface levels, ASM activity, and CRP formation.