Human Intelectin-1 Promotes Cellular Attachment and Neutrophil Killing of Streptococcus pneumoniae in a Serotype-Dependent Manner

Andresen, Silke; Fantone, Kayla; Chapla, Digantkumar; Rada, Balázs; Moremen, Kelley W.; Pierce, Michael; Szymanski, Christine M.

doi:10.1128/iai.00682-21

Cited by 9 publications

(11 citation statements)

References 59 publications

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“…Previously, we found that hItln1 exhibits serotype-specific binding to isolates of Streptococcus pneumoniae ( 14 ). Others have noted binding to different bacterial species considered pathogenic, suggesting that hItln1 targets pathogens ( 17 , 18 ). Because hITLN1 is expressed in the small intestine ( 19 ), we assessed the binding of recombinant hItln1 to a collection of human gut microbial strains by flow cytometry.…”

Section: Resultsmentioning

confidence: 99%

Lectin-Seq: A method to profile lectin-microbe interactions in native communities

et al. 2023

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Soluble human lectins are critical components of innate immunity. Genetic models suggest that lectins influence host-resident microbiota, but their specificity for commensal and mutualist species is understudied. Elucidating lectins’ roles in regulating microbiota requires an understanding of which microbial species they bind within native communities. To profile human lectin recognition, we developed Lectin-Seq. We apply Lectin-Seq to human fecal microbiota using the soluble mannose-binding lectin (MBL) and intelectin-1 (hItln1). Although each lectin binds a substantial percentage of the samples (10 to 20%), the microbial interactomes of MBL and hItln1 differ markedly in composition and diversity. MBL binding is highly selective for a small subset of species commonly associated with humans. In contrast, hItln1’s interaction profile encompasses a broad range of lower-abundance species. Our data uncover stark differences in the commensal recognition properties of human lectins.

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Section: Resultsmentioning

confidence: 99%

Lectin-Seq: A method to profile lectin-microbe interactions in native communities

et al. 2023

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“…Previously, we found hItln1 exhibits serotype-specific binding to isolates of Streptococcus pneumoniae ( 14 ). Others have noted binding to different bacterial species considered pathogenic, suggesting hItln1 targets pathogens ( 17, 18 ). Since hItln1 is expressed in the small intestine ( 19 ), we assessed the binding of recombinant hItln1 to a collection of human gut microbial strains by flow cytometry.…”

Section: Resultsmentioning

confidence: 99%

“…The implications of hItln1 binding to these gut-resident species are unclear. The interaction of hItln1 with select pathogens activates macrophage- and neutrophil-mediated killing ( 17, 18, 42 ); however, hItln1-mediated neutrophil activation requires serum components suggesting the bactericidal functions of hItln1 may be limited to the blood. Unlike some intestinal lectins ( 11 ), hItln1 has no known microbial toxicity and, unlike MBL, lacks canonical domains for complement recruitment ( 14 ).…”

Section: Discussionmentioning

confidence: 99%

Lectin-Seq: a method to profile lectin-microbe interactions in native communities

McPherson

Isabella

Walker

et al. 2022

Preprint

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Soluble human lectins are critical components of innate immunity. Genetic models suggest lectins influence host-resident microbiota, but their specificity for commensal and mutualist species is understudied. Elucidating lectins roles in regulating microbiota requires an understanding of which microbial species they bind within native communities. To profile human lectin recognition, we developed Lectin-Seq. We apply Lectin-Seq to human fecal microbiota using the soluble mannose-binding lectin (MBL) and intelectin-1 (hItln1). The microbial interactomes of MBL and hItln1 differ in composition and diversity. MBL binding is highly selective for a small subset of species commonly associated with humans. In contrast, hItln1s interaction profile encompasses a broad range of lower-abundance species. Our data uncover stark differences in the commensal recognition properties of human lectins.

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“…In aneurysm pathogenesis, inflammatory cells migrate to the aneurysmal lesion, perpetuating the inflammatory response and destructive remodeling, including matrix degradation and internal elastic lamina disruption [ 31 ]. The DEG ITLN1 is associated with the innate immune system and defensins, which are predominantly found in neutrophils [ 37 ]. ITLN1 has been reported to be differentially expressed in aneurysm tissue compared to control superficial temporal artery tissue, indicating it may be related to IA-lesion specific signaling at the IA site [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

RNA Expression Signatures of Intracranial Aneurysm Growth Trajectory Identified in Circulating Whole Blood

Poppenberg

Chien

Santo

et al. 2023

JPM

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After detection, identifying which intracranial aneurysms (IAs) will rupture is imperative. We hypothesized that RNA expression in circulating blood reflects IA growth rate as a surrogate of instability and rupture risk. To this end, we performed RNA sequencing on 66 blood samples from IA patients, for which we also calculated the predicted aneurysm trajectory (PAT), a metric quantifying an IA’s future growth rate. We dichotomized dataset using the median PAT score into IAs that were either more stable and more likely to grow quickly. The dataset was then randomly divided into training (n = 46) and testing cohorts (n = 20). In training, differentially expressed protein-coding genes were identified as those with expression (TPM > 0.5) in at least 50% of the samples, a q-value < 0.05 (based on modified F-statistics with Benjamini-Hochberg correction), and an absolute fold-change ≥ 1.5. Ingenuity Pathway Analysis was used to construct networks of gene associations and to perform ontology term enrichment analysis. The MATLAB Classification Learner was then employed to assess modeling capability of the differentially expressed genes, using a 5-fold cross validation in training. Finally, the model was applied to the withheld, independent testing cohort (n = 20) to assess its predictive ability. In all, we examined transcriptomes of 66 IA patients, of which 33 IAs were “growing” (PAT ≥ 4.6) and 33 were more “stable”. After dividing dataset into training and testing, we identified 39 genes in training as differentially expressed (11 with decreased expression in “growing” and 28 with increased expression). Model genes largely reflected organismal injury and abnormalities and cell to cell signaling and interaction. Preliminary modeling using a subspace discriminant ensemble model achieved a training AUC of 0.85 and a testing AUC of 0.86. In conclusion, transcriptomic expression in circulating blood indeed can distinguish “growing” and “stable” IA cases. The predictive model constructed from these differentially expressed genes could be used to assess IA stability and rupture potential.

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Human Intelectin-1 Promotes Cellular Attachment and Neutrophil Killing of Streptococcus pneumoniae in a Serotype-Dependent Manner

Cited by 9 publications

References 59 publications

Lectin-Seq: A method to profile lectin-microbe interactions in native communities

Lectin-Seq: A method to profile lectin-microbe interactions in native communities

Lectin-Seq: a method to profile lectin-microbe interactions in native communities

RNA Expression Signatures of Intracranial Aneurysm Growth Trajectory Identified in Circulating Whole Blood

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