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Record W4389231562 · doi:10.1182/blood-2023-187737

Investigation of CD83 As a Novel Human Hematopoietic Stem Cell Inflammatory Activation Marker

2023· article· en· W4389231562 on OpenAlexaff
Murtaza S. Nagree, Andy G.X. Zeng, Angelica Varesi, Isabel N.X. Lim, Sayyam Shah, Hyerin Kim, Liqing Jin, Mason Boulanger, John E. Dick, Stephanie Z. Xie

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersCelgene
KeywordsStem cellHaematopoiesisBiologyInflammationImmunologyImmune systemHematopoietic stem cellMyeloidCancer researchCell biology

Abstract

fetched live from OpenAlex

Hematopoietic stem cells (HSC) are responsible for life-long blood production and must balance homeostasis with sudden demand situations such as infections. However, the heterogeneity of molecular programs engaged by acute inflammatory stimuli to activate emergency hematopoiesis at the level of HSC are poorly understood. In a recent study linking human HSC heterogeneity to aging, recovery from severe COVID-19 infection, and clonal hematopoiesis (CH), we discovered two HSC subsets through multiomic analysis, denoted HSC-I and -II, in a xenograft model of inflammation-recovery. While HSC-I had few inflammation-driven molecular changes, HSC-II showed sustained epigenetic and transcriptional alterations in response to dual tumor necrosis factor α (TNFα) or lipopolysaccharide (LPS) challenges despite a 2.5-month recovery period. Importantly, a signature of long-term memory T cells (Akondy et al 2017) was enriched in HSC-II (Zeng, Nagree, et al, in submission). We interrogated the human HSC multiomic signatures uncovered from this human xenograft model to identify potential regulators associated with HSC response to and recovery from acute inflammation. We identified CD83 as a candidate that is differentially expressed between our HSC subsets. Similarly, we found CD83 expression to be enriched in a subset of adult-derived HSCs from patients where CH status was established and enrichment of an HSC-II signature observed (Jakobsen et al, submitted). CD83, first identified as a dendritic cell marker, is expressed on many immune cells, with linkage to controlling murine T regulatory (T-Reg) vs memory cell fate (Doebbeler et al, 2018), but has not previously been shown to be relevant for human HSC biology. Flow cytometry analysis of cord blood (CB) hematopoietic stem and progenitor cells (HSPC) showed CD83 to be low or absent in HSC (Figure A) and their downstream progeny at steady state. However, robust CD83 expression was observed in multiple HSPC subpopulations including long-term (LT-) and short-term (ST-) HSC within 16 hours of ex vivo culture, with highest expression in LT-HSC (Figure A). Importantly, CD83 surface expression on LT-HSC was enhanced following culture with TNFα (Figure A). Bystander effects were excluded by demonstrating similar findings after culture of purified HSC populations. Acute in vivo LPS treatment of mice xenografted with CB-derived HSC was sufficient to upregulate CD83 surface expression after 16 hours on LT-HSC/HSPC. To elucidate the potential function of CD83-expressing HSC/multipotent progenitors (MPP), CD19-CD34+CD38-CD45RA- cells were sorted from xenografts following acute inflammatory challenge for low and high CD83 expression and subjected to bulk RNA sequencing. We found enrichment of a gene expression signature specific to activated human HSCs (Garcia-Prat et al, 2021) within CD83-positive HSC/MPP (Figure B). Strikingly, enrichment of a signature of stimulated vs resting T cells (Galetti et al, 2020) and of effector T cells (Akondy et al 2017) was found in CD83-positive compared to CD83-negative HSC/MPP (Figure B). T cell effector function is in part dictated by metabolic reprogramming. We thus examined reactive oxygen species (ROS) levels in LT-HSC following ex vivo culture with TNFα and found lower ROS levels with CD83 expression. We therefore hypothesize that CD83 may be an ‘effector’ marker defining a distinct HSC subset during homeostatic or inflammatory activation that is subsequently fated to become memory-like HSC-II. We are undertaking studies to determine the mechanistic role of CD83 in HSC function and HSC-II formation via Cas9-sgRNA-mediated knockout or lentivirus-mediated overexpression of CD83. In summary, CD83 represents a long-sought marker of inflammatory activation at the HSC level. CD83 may have significant clinical potential as a biomarker of aberrant activation in gene therapy manufacturing protocols or for HSC transplantation. Future studies will shed light on whether CD83 can functionally regulate the molecular programs underlying human HSC heterogeneity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.238
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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