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Cellular barcoding enables the dissection of clonal dynamics in heterogeneous cell populations through single cell lineage tracing. The labeling of hematopoietic stem and progenitor cells (HSPCs) with unique and heritable DNA barcodes, makes it possible to resolve donor cell heterogeneity in terms of differentiation potential and lineage bias at the single cell level, through subsequent transplantation and high-throughput sequencing. Furthermore, cellular barcoding allows for bona fide hematopoietic stem cells (HSCs) to be defined based on functional rather than immunophenotypic parameters. This protocol describes the work flow of lentiviral cellular barcoding, tracking 14.5 days post coitum (d.p.c.) fetal liver (FL) Lineage-Sca+cKit+ (LSK) HSPCs following long-term reconstitution (Figure 1) (Kristiansen et al., 2016), but can be adapted to the cell type or time frame of choice.Figure 1. Summary of experimental workflow (Naik et al., 2013)
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[Abstract] Cellular barcoding enables the dissection of clonal dynamics in heterogeneous cell populations through single cell lineage tracing. The labeling of hematopoietic stem and progenitor cells (HSPCs) with unique and heritable DNA barcodes, makes it possible to resolve donor cell heterogeneity in terms of differentiation potential and lineage bias at the single cell level, through subsequent transplantation and high-throughput sequencing. Furthermore, cellular barcoding allows for bona fide hematopoietic stem cells (HSCs) to be defined based on functional rather than immunophenotypic parameters. This protocol describes the work flow of lentiviral cellular barcoding, tracking 14.5 days post coitum (d.p.c.) fetal liver (FL) Lineage-Sca+cKit+ (LSK) HSPCs following long-term reconstitution (Figure 1) (Kristiansen et al., 2016), but can be adapted to the cell type or time frame of choice.Figure 1. Summary of experimental workflow (Naik et al., 2013)
Keywords: Cellular barcoding, Lentiviral transduction, Fetal liver, Hematopoietic stem and progenitor cells, Single cell lineage tracing, Transplantation
[Background] The cellular barcoding technique was initially established to resolve single cell dynamics upon transplantation of hematopoietic cells in vivo and has in recent years contributed significantly to our appreciation of the functional heterogeneity within blood cell populations in a transplantation setting (Schepers et al., 2008; Gerrits et al., 2010; Lu et al., 2011; Naik et al., 2013; Verovskaya et al., 2013; Kristiansen et al., 2016). The generation and characterization of lentiviral barcode libraries, the importance of library complexity as well as the associated analytical challenges have been carefully reviewed (Bystrykh et al., 2014; Naik et al., 2014; Bystrykh and Belderbosv, 2016) and need to be considered before starting this protocol to ensure proper experimental design. The current protocol pertains our adaptation of the technology as seen in our recent article (Kristiansen et al., 2016), to trace the long-term reconstitution capacity of FL derived HSPCs.
Materials and Reagents
Equipment
Procedure
Data analysis
The initial steps of cellular barcode analysis aims at generating a list of reliable barcodes for each sorted sample coupled with the barcode read frequency reflecting the abundance of each clone within the population. The most crucial part of this analysis is filtering out barcodes introduced by e.g., sequencing errors, which would otherwise bias the results. The filtering steps are customized for the barcode library of choice and experimental design. For example, if a reference library exists for the barcode library of choice, the sequenced barcodes can be mapped back to the reference and the filtering step can be streamlined. Here, we briefly provide an example for the analysis of randomly generated barcode libraries lacking a known reference (Figure 1; Kristiansen et al., 2016). For in depth recommendations, we have provided a number relevant references.
Notes
Recipes
Acknowledgments
This protocol was originally described in and adapted from Kristiansen et al. (2016). This work was supported by grants from the Swedish Cancer Foundation, the Swedish Research Council, StemTherapy, and The Knut and Alice Wallenberg Foundation.
References
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