Quantifying the Number of Active Hematopoietic Precursors in Adult Mice Through Confetti Labeling

Conceitos essenciais

The number of active hematopoietic precursors contributing to native and perturbed hematopoiesis in adult mice can be quantified by leveraging the inverse correlation between the variance of Confetti fluorescent protein expression and the number of precursors.

Resumo

The study aimed to establish a method for quantifying a wide range of hematopoietic precursors in adult mice. The authors leveraged the random induction of Confetti fluorescent proteins in precursor cells, which follows a binomial distribution, to derive a mathematical relationship between the variance of Confetti expression and the number of precursors.
The authors first validated this relationship experimentally using a two-color HL-60 cell system, demonstrating a linear and inverse correlation between the standard deviation of the Confetti marker and the number of seeded cells. They then applied this approach to adult mice, using the HSC-Scl-CreERT driver to induce Confetti labeling in hematopoietic stem and progenitor cells.
The key findings are:

Thousands of hematopoietic precursors contribute to native adult hematopoiesis, with a moderate increase from the fetal to adult stage.
Precursor numbers dynamically respond to myeloablation by 5-fluorouracil treatment, with a reduction in progenitor precursors but not in long-term hematopoietic stem cell precursors.
In a mouse model of Fanconi Anemia (Fancc-/- mice), precursor numbers are normal at steady state but show a modest reduction in lymphoid precursors upon transplantation of aging donor cells.

The authors conclude that this approach provides a flexible and reliable method for quantifying hematopoietic precursors across a wide dynamic range, enabling the study of precursor contributions in both normal and genetically perturbed mouse models.

Estatísticas

The number of hematopoietic precursors contributing to native adult myelopoiesis is approximately 2,667.
The number of hematopoietic precursors in the bone marrow of Fancc-/- mice is similar to wild-type controls at steady state.
The number of lymphoid precursors in the peripheral blood of recipients transplanted with aging Fancc-/- donor cells is modestly reduced compared to recipients of wild-type donor cells.

Citações

"The number of HSPCs actively participating in white blood cell production was estimated to range from 20,000 to 200,000 in humans."
"We detected thousands of hematopoietic precursors contributing to adult hematopoiesis."
"Aging Fancc-/- mice showed a modest but consistent loss of active PB lymphoid precursors post-transplantation, implying decreased lymphoid precursors additionally contribute to reduced repopulation capacity as Fancc-/- mice age."

Principais Insights Extraídos De

Dynamic Tracking of Native Polyclonal Hematopoiesis in Adult Mice

by Liu,S., Adam... às www.biorxiv.org 04-03-2024

https://www.biorxiv.org/content/10.1101/2024.04.02.587737v1

Perguntas Mais Profundas

How might the non-uniform expansion of hematopoietic precursor clones impact the accuracy of the precursor number estimates derived from this approach?

The non-uniform expansion of hematopoietic precursor clones can introduce variability in the progeny, leading to inaccuracies in the estimation of precursor numbers. If certain clones expand more rapidly or to a greater extent than others, the distribution of fluorescence proteins (FPs) in the progeny may not accurately reflect the initial precursor numbers. This non-uniform expansion can skew the variance of FP% and potentially lead to overestimation or underestimation of precursor numbers. To address this, it is essential to consider the potential non-uniformity in clone expansion and its impact on the accuracy of the estimates. Additional validation methods may be needed to account for this variability and ensure the precision of the precursor number calculations.

What are the potential limitations or caveats of inferring precursor numbers from their differentiated progeny, and how could this be further validated?

Inferring precursor numbers from their differentiated progeny may have limitations and caveats that need to be considered. One limitation is the assumption of uniform and linear expansion from precursor to progeny, which may not always hold true in biological systems. Variability in the differentiation process, non-uniform proliferation rates, or selective advantages of certain clones can introduce biases in the estimation of precursor numbers. Additionally, the presence of non-clonal hematopoiesis or contributions from non-labeled precursors can further complicate the interpretation of precursor numbers from progeny analysis.
To validate the inferred precursor numbers, additional approaches can be employed. One method is to use complementary techniques such as single-cell sequencing or lineage tracing to directly track the fate of individual precursor cells and confirm the accuracy of the estimates. Functional assays, transplantation studies, or in vitro clonal assays can also provide validation by assessing the repopulation capacity and differentiation potential of the inferred precursor populations. By integrating multiple validation strategies, the reliability and robustness of the precursor number estimates can be enhanced.

Could this approach be adapted to quantify hematopoietic precursor numbers in human samples, and what would be the key considerations and challenges in doing so?

Adapting this approach to quantify hematopoietic precursor numbers in human samples is feasible but comes with several key considerations and challenges. One consideration is the availability of suitable genetic mouse models or humanized systems that mimic human hematopoiesis accurately. The choice of Cre drivers, labeling strategies, and experimental protocols would need to be optimized for human samples to ensure reliable and consistent results.
Challenges in applying this approach to human samples include the heterogeneity of human hematopoiesis, the limited availability of precursor-specific markers, and the ethical considerations associated with experimental manipulations in human subjects. Additionally, the scale and complexity of human hematopoietic systems may require adaptations in the analytical methods and computational models used to estimate precursor numbers accurately.
Validation of the approach in human samples would require extensive comparative studies with established methods, such as flow cytometry, single-cell sequencing, or functional assays. Collaborations with clinical researchers, access to patient samples, and adherence to ethical guidelines would be essential for conducting human studies. Overall, while challenging, adapting this approach to quantify hematopoietic precursor numbers in human samples holds great potential for advancing our understanding of hematopoiesis and hematological disorders in clinical settings.