ReviewMicroarrays (Basel, Switzerland)2015
Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays.
Review in Microarrays (Basel, Switzerland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Defined Glycan Ligands for Detecting Rare l-Sugar-Binding Proteins.Journal of the American Chemical Society · 2025Article
- A novel on-a-chip system with a 3D-bioinspired gut mucus suitable to investigate bacterial endotoxins dynamics.Materials today. Bio · 2024Article
- Glycomics Microarrays Reveal Differential In Situ Presentation of the Biofilm Polysaccharide Poly-International journal of molecular sciences · 2020Article
- Microarray Strategies for Exploring Bacterial Surface Glycans and Their Interactions With Glycan-Binding Proteins.Frontiers in microbiology · 2019Review
- The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human.Microorganisms · 2018Review
- Glycointeractions in bacterial pathogenesis.Nature reviews. Microbiology · 2018Review
- Structural basis of mammalian glycan targeting by Vibrio cholerae cytolysin and biofilm proteins.PLoS pathogens · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Carbohydrates play a crucial role in host-microorganism interactions and many host glycoconjugates are receptors or co-receptors for microbial binding. Host glycosylation varies with species and location in the body, and this contributes to species specificity and tropism of commensal and pathogenic bacteria. Additionally, bacterial glycosylation is often the first bacterial molecular species encountered and responded to by the host system. Accordingly, characterising and identifying the exact structures involved in these critical interactions is an important priority in deciphering microbial pathogenesis. Carbohydrate-based microarray platforms have been an underused tool for screening bacterial interactions with specific carbohydrate structures, but they are growing in popularity in recent years. In this review, we discuss carbohydrate-based microarrays that have been profiled with whole bacteria, recombinantly expressed adhesins or serum antibodies. Three main types of carbohydrate-based microarray platform are considered; (i) conventional carbohydrate or glycan microarrays; (ii) whole mucin microarrays; and (iii) microarrays constructed from bacterial polysaccharides or their components. Determining the nature of the interactions between bacteria and host can help clarify the molecular mechanisms of carbohydrate-mediated interactions in microbial pathogenesis, infectious disease and host immune response and may lead to new strategies to boost therapeutic treatments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.