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Record W2595998300 · doi:10.1182/blood.v120.21.28.28

Time Course Studies of the Progeny of Barcoded CD34+ Human Cord Blood Cells Generated in Transplanted NOD/SCID-IL2Rγ−/− Mice Unveil the Clonal Dynamics of Short Term, Intermediate Term and Long Term Repopulating Cells

2012· article· en· W2595998300 on OpenAlexaff
Alice M.S. Cheung, Long Nguyen, Annaïck Carles, Paul H. Miller, Philip Beer, Pawan Pandoh, David J. H. F. Knapp, Kiran Dhillon, Kane Tse, Thomas Zeng, Yongjun Zhao, Martin Hirst, Connie J. Eaves

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsBiologyHaematopoiesisclone (Java method)Stem cellNodCord bloodCD34ImmunologyBone marrowTransplantationCell biologyMolecular biologyIn vivoAndrologyGeneticsGeneInternal medicineMedicine

Abstract

fetched live from OpenAlex

Abstract Abstract 28 Hematopoietic stem cells (HSC) exhibit heterogeneity in self-renewal and differentiation activity, but the extent to which this is intrinsically determined and extrinsically regulated is still poorly understood. In the mouse, purities of HSCs can now be achieved to allow such questions to be addressed directly. Interestingly, tracking the outputs of large numbers of serial transplantable clones produced from single-cell transplants, or the clonal progenies of vector-marked/barcoded cells indicate the existence in mice of 2 subsets of HSCs with durable self-renewal ability. These 2 subsets are characterized by distinct lineage output programs that are maintained through the many HSC self-renewal divisions required to serially propagate a clone in vivo. To begin to ask whether similar subsets of human HSCs exist, we have created a diverse lentiviral library encoding an estimated >105 different barcode sequences and GFP, and then used this library to track the in vivo clonal outputs of transduced human CD34+ cord blood cells in xenografted mice. For this experiment, CD34+ cells isolated immunomagnetically to a purity of >80% were exposed to virus for 6 hours in the presence of growth factors and then immediately injected intravenously into 2 sublethally irradiated NOD/SCID-IL2Rγ−/− mice (1.2 × 105 cells per mouse; 30% GFP+ cells after 3 days in vitro). Different subsets of human cells were then isolated by FACS from immunostained bone marrow cells aspirated sequentially from the femurs of the mice at intervals from 4–27 weeks post-transplant and the identity, number and size of clones in each established by next generation sequencing of barcoded amplicons derived from each sample. To identify barcodes arising from PCR and sequencing errors and calibrate clone sizes, we included 3 controls of 20, 100 and 500 cells with a known barcode at each datapoint. The data from these controls allowed a threshold of 20 cells per clone to be established with >95% confidence. We then compared the representation of clones among all samples from each mouse to derive the number and size of all clones detected, assuming a mouse contains 2×108 bone marrow cells. This analysis revealed a total of 154 uniquely barcoded clones containing up to 2×108 human hematopoietic cells in the 2 mice (8–30 × 106 in one and 4–165 × 106 in the other at any single time point). Analysis of the representation of each clone over time showed successive waves of repopulation from different clones with lineage output profiles consistent with those obtained by transplanting separate fractions of CD34+ cord blood cells distinguished by their surface phenotypes. Specifically, we detected 50 clones (32% of all clones) that were not sustained at detectable levels beyond 9 weeks post-transplantation and were characterized by robust myeloid differentiation with variable B cell outputs at 4 weeks. Another 30 clones (19%) showed significant but also transient outputs of either or both the myeloid and B cell lineage, disappearing between week 9 and 16 post-transplant. Mature cell output was detected from a total of 74 clones (48%) at the 27 week time point, among which 36 (23%) were not evident during the first 4 months post-transplant. These late-appearing clones were mostly small (contributing up to 3 × 105 total hematopoietic cells at week 27) and made a significantly higher contribution to the total human myeloid population than to the total human B cell population. Notably, the 12 long term clones that showed robust mature cell output detectable in all 3 sites sampled at week 27 when the mice were sacrificed (left leg vs right leg vs pelvis) contained both myeloid and lymphoid cells but with large (>100-fold) variations in their representation in the 3 different sites. This latter finding suggests less trafficking of human cells between sites than expected from parabiotic mouse experiments or substantial differences in the differentiation control exerted in different locations. Additionally, from one of the mice, we obtained the first direct evidence of a large output of human T cells (>9 × 106) that was part of a long term multi-lineage clone detectable at 27 weeks post-transplant. This first use of a barcoding strategy to analyze the clonal dynamics of normal human CD34+ cells with in vivo repopulating activity demonstrates the power of this approach to analyze their lineage outputs and sets the stage for novel applications to expanded and transformed populations. Disclosures: No relevant conflicts of interest to declare.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.037
GPT teacher head0.323
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations4
Published2012
Admission routes1
Has abstractyes

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