Clonal Analysis of Cells with Cellular Barcoding: When Numbers and Sizes Matter

Barcodes based on nucleic acid sequences: Applications and challenges (Review)

Cells are the fundamental structural and functional units of living organisms and the study of these entities has remained a central focus throughout the history of biological sciences. Traditional cell research techniques, including fluorescent protein tagging and microscopy, have provided preliminary insights into the lineage history and clonal relationships between progenitor and descendant cells. However, these techniques exhibit inherent limitations in tracking the full developmental trajectory of cells and elucidating their heterogeneity, including sensitivity, stability and barcode drift. In developmental biology, nucleic acid barcode technology has introduced an innovative approach to cell lineage tracing. By assigning unique barcodes to individual cells, researchers can accurately identify and trace the origin and differentiation pathways of cells at various developmental stages, thereby illuminating the dynamic processes underlying tissue development and organogenesis. In cancer research, nucleic acid barcoding has played a pivotal role in analyzing the clonal architecture of tumor cells, exploring their heterogeneity and resistance mechanisms and enhancing our understanding of cancer evolution and inter‑clonal interactions. Furthermore, nucleic acid barcodes play a crucial role in stem cell research, enabling the tracking of stem cells from diverse origins and their derived progeny. This has offered novel perspectives on the mechanisms of stem cell self‑renewal and differentiation. The present review presented a comprehensive examination of the principles, applications and challenges associated with nucleic acid barcode technology.

Panhematopoietic RNA barcoding enables kinetic measurements of nucleate and anucleate lineages and the activation of myeloid clones following acute platelet depletion

BACKGROUND

Platelets and erythrocytes constitute over 95% of all hematopoietic stem cell output. However, the clonal dynamics of HSC contribution to these lineages remains largely unexplored.

RESULTS

We use lentiviral genetic labeling of mouse hematopoietic stem cells to quantify output from all lineages, nucleate, and anucleate, simultaneously linking these with stem and progenitor cell transcriptomic phenotypes using single-cell RNA-sequencing. We observe dynamic shifts of clonal behaviors through time in same-animal peripheral blood and demonstrate that acute platelet depletion shifts the output of multipotent hematopoietic stem cells to the exclusive production of platelets. Additionally, we observe the emergence of new myeloid-biased clones, which support short- and long-term production of blood cells.

CONCLUSIONS

Our approach enables kinetic studies of multi-lineage output in the peripheral blood and transcriptional heterogeneity of individual hematopoietic stem cells. Our results give a unique insight into hematopoietic stem cell reactivation upon platelet depletion and of clonal dynamics in both steady state and under stress.

In vitro clonal multilineage differentiation of distinct murine hematopoietic progenitor populations

Here we describe an in vitro co-culture system that can differentiate hematopoietic progenitor populations to all major hematopoietic lineages at clonal level. We present both a sensitive single-cell switch-culture system as well as a less laborious alternative barcoding protocol more convenient for larger cell numbers. Importantly, generation of all lineages from single long-term hematopoietic stem cells are described, following 21 days of culture. This protocol represents an efficient tool for validation experiments for single-cell genomics data. For complete details on the use and execution of this protocol, please refer to Safi et al. (2022).1.

DNA barcoding and gene expression recording reveal the presence of cancer cells with unique properties during tumor progression

Tumors comprise diverse cancer cell populations with specific capabilities for adaptation to the tumor microenvironment, resistance to anticancer treatments, and metastatic dissemination. However, whether these populations are pre-existing in cancer cells or stochastically appear during tumor growth remains unclear. Here, we show the heterogeneous behaviors of cancer cells regarding response to anticancer drug treatments, formation of lung metastases, and expression of transcription factors related to cancer stem-like cells using a DNA barcoding and gene expression recording system. B16F10 cells maintained clonal diversity after treatment with HVJ-E, a UV-irradiated Sendai virus, and the anticancer drug dacarbazine. PBS treatment of the primary tumor and intravenous injection of B16F10 cells resulted in metastases formed from clones of multiple cell lineages. Conversely, BL6 and 4T1 cells developed spontaneous lung metastases by a small number of clones. Notably, an identical clone of 4T1 cells developed lung metastases in different mice, suggesting the existence of cells with high metastatic potential. Cas9-based transcription recording analysis in a human prostate cancer cell line revealed that specific cells express POU5F1 in response to an anticancer drug and sphere formation. Our findings provide insights into the diversity of cancer cells during tumor progression.

Mastering the use of cellular barcoding to explore cancer heterogeneity

Tumours are often composed of a multitude of malignant clones that are genomically unique, and only a few of them may have the ability to escape cancer therapy and grow as symptomatic lesions. As a result, tumours with a large degree of genomic diversity have a higher chance of leading to patient death. However, clonal fate can be driven by non-genomic features. In this context, new technologies are emerging not only to track the spatiotemporal fate of individual cells and their progeny but also to study their molecular features using various omics analysis. In particular, the recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in different microenvironments and in response to therapy. In this Review, we highlight the recent discoveries made using lentiviral-based cellular barcoding techniques, namely genetic and optical barcoding. We also emphasize the strengths and limitations of each of these technologies and discuss some of the key concepts that must be taken into consideration when one is designing barcoding experiments. Finally, we suggest new directions to further improve the use of these technologies in cancer research.

Connecting past and present: single-cell lineage tracing

Central to the core principle of cell theory, depicting cells' history, state and fate is a fundamental goal in modern biology. By leveraging clonal analysis and single-cell RNA-seq technologies, single-cell lineage tracing provides new opportunities to interrogate both cell states and lineage histories. During the past few years, many strategies to achieve lineage tracing at single-cell resolution have been developed, and three of them (integration barcodes, polylox barcodes, and CRISPR barcodes) are noteworthy as they are amenable in experimentally tractable systems. Although the above strategies have been demonstrated in animal development and stem cell research, much care and effort are still required to implement these methods. Here we review the development of single-cell lineage tracing, major characteristics of the cell barcoding strategies, applications, as well as technical considerations and limitations, providing a guide to choose or improve the single-cell barcoding lineage tracing.

CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data

Single-cell lineage tracing permits the labeling of individual cells with a heritable marker to follow the fate of each cell's progeny. Over the last twenty years, several single-cell lineage tracing methods have emerged, enabling major discoveries in developmental biology, oncology and gene therapies. Analytical tools are needed to draw meaningful conclusions from lineage tracing measurements, which are characterized by high variability, sparsity and technical noise. However, the single cell lineage tracing field lacks versatile and easy-to-use tools for standardized and reproducible analyses, in particular tools accessible to biologists. Here we present CellDestiny, a RShiny app and associated web application developed for experimentalists without coding skills to perform visualization and analysis of single cell lineage-tracing datasets through a graphical user interface. We demonstrate the functionality of CellDestiny through the analysis of (i) lentiviral barcoding datasets of murine hematopoietic progenitors; (ii) published integration site data from Wiskott-Aldrich Symdrome patients undergoing gene-therapy treatment; and (iii) simultaneous barcoding and transcriptomic analysis of murine hematopoietic progenitor differentiation in vitro. In summary, CellDestiny is an easy-to-use and versatile toolkit that enables biologists to visualize and analyze single-cell lineage tracing data.

The Reconstitution Dynamics of Cultivated Hematopoietic Stem Cells and Progenitors Is Independent of Age

Hematopoietic stem cell transplantation (HSCT) represents the only curative treatment option for numerous hematologic malignancies. While the influence of donor age and the composition of the graft have already been examined in clinical and preclinical studies, little information is available on the extent to which different hematological subpopulations contribute to the dynamics of the reconstitution process and on whether and how these contributions are altered with age. In a murine model of HSCT, we therefore simultaneously tracked different cultivated and transduced hematopoietic stem and progenitor cell (HSPC) populations using a multicolor-coded barcode system (BC32). We studied a series of age-matched and age-mismatched transplantations and compared the influence of age on the reconstitution dynamics. We show that reconstitution from these cultured and assembled grafts was substantially driven by hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) independent of age. The reconstitution patterns were polyclonal and stable in all age groups independently of the variability between individual animals, with higher output rates from MPPs than from HSCs. Our experiments suggest that the dynamics of reconstitution and the contribution of cultured and individually transduced HSPC subpopulations are largely independent of age. Our findings support ongoing efforts to expand the application of HSCT in older individuals as a promising strategy to combat hematological diseases, including gene therapy applications.

BAR-Seq clonal tracking of gene-edited cells

Gene editing by engineered nucleases has revolutionized the field of gene therapy by enabling targeted and precise modification of the genome. However, the limited availability of methods for clonal tracking of edited cells has resulted in a paucity of information on the diversity, abundance and behavior of engineered clones. Here we detail the wet laboratory and bioinformatic BAR-Seq pipeline, a strategy for clonal tracking of cells harboring homology-directed targeted integration of a barcoding cassette. We present the BAR-Seq web application, an online, freely available and easy-to-use software that allows performing clonal tracking analyses on raw sequencing data without any computational resources or advanced bioinformatic skills. BAR-Seq can be applied to most editing strategies, and we describe its use to investigate the clonal dynamics of human edited hematopoietic stem/progenitor cells in xenotransplanted hosts. Notably, BAR-Seq may be applied in both basic and translational research contexts to investigate the biology of edited cells and stringently compare editing protocols at a clonal level. Our BAR-Seq pipeline allows library preparation and validation in a few days and clonal analyses of edited cell populations in 1 week.

The clonal repopulation of HSPC gene modified with anti-HIV-1 RNAi is not affected by preexisting HIV-1 infection

Despite advances in hematopoietic stem/progenitor cell (HSPC) transplant for HIV-1-infected patients, the impact of a preexisting HIV-1 infection on the engraftment and clonal repopulation of HSPCs remains poorly understood. We have developed a long terminal repeat indexing-mediated integration site sequencing (LTRi-Seq) method that provides a multiplexed clonal quantitation of both anti-HIV-1 RNAi (RNA interference) gene-modified and control vector-modified cell populations, together with HIV-1-infected cells-all within the same animal. In our HIV-1-preinfected humanized mice, both therapeutic and control HSPCs repopulated efficiently without abnormalities. Although the HIV-1-mediated selection of anti-HIV-1 RNAi-modified clones was evident in HIV-1-infected mice, the organ-to-organ and intra-organ clonal distributions in infected mice were indistinguishable from those in uninfected mice. HIV-1-infected cells showed clonal patterns distinct from those of HSPCs. Our data demonstrate that, despite the substantial impact of HIV-1 infection on CD4+ T cells, HSPC repopulation remains polyclonal, thus supporting the use of HSPC transplant for anti-HIV treatment.

Clonal tracking using embedded viral barcoding and high-throughput sequencing

Embedded viral barcoding in combination with high-throughput sequencing is a powerful technology with which to track single-cell clones. It can provide clonal-level insights into cellular proliferation, development, differentiation, migration, and treatment efficacy. Here, we present a detailed protocol for a viral barcoding procedure that includes the creation of barcode libraries, the viral delivery of barcodes, the recovery of barcodes, and the computational analysis of barcode sequencing data. The entire procedure can be completed within a few weeks. This barcoding method requires cells to be susceptible to viral transduction. It provides high sensitivity and throughput, and enables precise quantification of cellular progeny. It is cost efficient and does not require any advanced skills. It can also be easily adapted to many types of applications, including both in vitro and in vivo experiments.

Patient-derived cancer modeling for precision medicine in colorectal cancer: beyond the cancer cell line

Since effective immunotherapeutic agents such as immune checkpoint blockade to treat cancer have emerged, the need for reliable preclinical cancer models that can evaluate and discover such drugs became stronger than ever before. The traditional preclinical cancer model using a cancer cell line has several limitations to recapitulate intra-tumor heterogeneity and in-vivo tumor activity including interactions between tumor-microenvironment. In this review, we will go over various preclinical cancer models recently discovered including patient-derived xenografts, humanized mice, organoids, organotypic-tumor spheroids, and organ-on-a-chip models. Moreover, we will discuss the future directions of preclinical cancer research.

Donor-to-Donor Heterogeneity in the Clonal Dynamics of Transplanted Human Cord Blood Stem Cells in Murine Xenografts

Umbilical cord blood (UCB) provides an alternative source of hematopoietic stem cells (HSCs) for allogeneic transplantation. Administration of sufficient donor HSCs is critical to restore recipient hematopoiesis and to maintain long-term polyclonal blood formation. However, due to lack of unique markers, the frequency of HSCs among UCB CD34⁺ cells is the subject of ongoing debate, urging for reproducible strategies for their counting. Here, we used cellular barcoding to determine the frequency and clonal dynamics of human UCB HSCs and to determine how data analysis methods affect these parameters. We transplanted lentivirally barcoded CD34⁺ cells from 20 UCB donors into Nod/Scid/IL2Ry^-/- (NSG) mice (n = 30). Twelve recipients (of 8 UCB donors) engrafted with >1% GFP⁺ cells, allowing for clonal analysis by multiplexed barcode deep sequencing. Using multiple definitions of clonal diversity and strategies for data filtering, we demonstrate that differences in data analysis can change clonal counts by several orders of magnitude and propose methods to improve their consistency. Using these methods, we show that the frequency of NSG-repopulating cells was low (median ∼1 HSC/10⁴ CD34⁺ UCB cells) and could vary up to 10-fold between donors. Clonal patterns in blood became increasingly consistent over time, likely reflecting initial output of transient progenitors, followed by long-term HSCs with stable hierarchies. The majority of long-term clones displayed multilineage output, yet clones with lymphoid- or myeloid-biased output were also observed. Altogether, this study uncovers substantial interdonor and analysis-induced variability in the frequency of UCB CD34⁺ clones that contribute to post-transplant hematopoiesis. As clone tracing is increasingly relevant, we urge for universal and transparent methods to count HSC clones during normal aging and upon transplantation.

Clonal Composition of Human Multipotent Mesenchymal Stromal Cells: Application of Genetic Barcodes in Research

Clonal composition of human multipotent mesenchymal stromal cells (MMSCs) labeled with lentiviral vectors carrying genetic barcodes was studied. MMSCs were transduced with a cloned library of self-inactivating lentiviral vectors carrying 667 unique barcodes. At each cell culture passage, 120 cells were plated one cell per well in 96-well plates. The efficiency of cloning and labeling of the clonogenic cells was determined. DNA was extracted from the cell-derived colonies, and the barcodes were identified by Sanger sequencing. Also, DNA was extracted from the total MMSC population at each passage to analyze the diversity and representation of barcodes by deep sequencing using the Illumina platform. It was shown that the portion of MMSCs labeled with the lentiviral vectors remained stable in the passaged cells. Because of the high multiplicity of infection, the labeling procedure could decrease the proliferative potential of MMSCs. Identification of barcodes in individual cell clones confirmed the polyclonal character of the MMSC population. Clonal composition of MMSCs changed significantly with the passages due to the depletion of proliferative potential of most cells. Large clones were found at the first passage; at later passages, many small clones with a limited proliferative potential were detected in the population. The results of deep sequencing confirmed changes in the clonal composition of MMSCs. The polyclonal MMSC population contained only a small number of cells with a high proliferative potential, some of which could be stem cells. MMSCs with a high proliferative potential were detected more often in the earliest passages. In this regard, we would recommend to use MMSCs of early passages for regenerative medicine applications based on cell proliferation.

Assays for functionally defined normal and malignant mammary stem cells

The discovery of rare, heterogeneous self-renewing stem cells with shared developmental and molecular features within epithelial components of mammary gland and breast cancers has provided a conceptual framework to understand cellular composition of these tissues and mechanisms that control their number. These normal mammary epithelial stem cells (MaSCs) and breast cancer stem cells (BCSCs) were identified and analyzed using transplant assays (namely mammary repopulating unit (MRU) assay, mammary tumor-initiating cell (TIC) assay), which reveal their latent ability to regenerate respective normal and malignant epithelial tissues with self-renewing units displaying hierarchical cellular differentiation over multiple generations in recipient mice. "Next-generation" methods using "barcoded" normal and malignant mammary cells, with the help of next-generation sequencing (NGS) technology, have revealed hidden complexity and heterogeneous growth potential of MaSCs and BCSCs. Several single markers or combinations of markers have been reported to prospectively enrich MaSCs and BCSCs. Such markers and the extent to which they enrich for MaSCs and BCSCs activity require a critical appraisal. Also, knowledge of the functional assays and their limitations and harmonious reporting of results is a prerequisite to improve our understanding of MaSCs and BCSCs. This chapter describes evolution of the concept of MaSCs and BCSCs, and specific methodologies to investigate them.

Evolution of Relapse-Proficient Subclones Constrained by Collateral Sensitivity to Oncogene Overdose in Wnt-Driven Mammary Cancer

Targeted cancer therapeutics select for drug-resistant rescue subclones (RSCs), which typically carry rescue mutations that restore oncogenic signaling. Whereas mutations underlying antibiotic resistance frequently burden drug-naive microbes with a fitness cost, it remains unknown whether and how rescue mutations underlying cancer relapse encounter negative selection prior to targeted therapy. Here, using mouse models of reversible, Wnt-driven mam-mary cancer, we uncovered stringent counter-selection against Wnt signaling overdose during the clonal evolution of RSCs. Analyzing recurrent tumors emerging during simulated targeted therapy (Wnt withdrawal) by multi-region DNA sequencing revealed polyclonal relapses comprised of multiple RSCs, which bear distinct but functionally equivalent rescue mutations that converge on sub-maximal Wnt pathway activation. When superimposed on native (i.e., undrugged) signaling, these rescue mutations faced negative selection, indicating that they burden RSCs with a fitness cost before Wnt withdrawal unmasks their selective advantage. Exploiting collateral sensitivity to oncogene overdose may help eliminate RSCs and prevent cancer relapse.

Keller and Gunther show that Wnt-driven mammary cancers challenged with simulated targeted therapy (Wnt withdrawal) undergo clonal evolution, which stringently selects for mutations that restore a “just right” level of oncogenic signaling. Therefore, cancer relapses emerge from rare subclones that are encumbered by an untapped vulnerability to oncogene overdose.

Heritable tumor cell division rate heterogeneity induces clonal dominance

Tumors consist of a hierarchical population of cells that differ in their phenotype and genotype. This hierarchical organization of cells means that a few clones (i.e., cells and several generations of offspring) are abundant while most are rare, which is called clonal dominance. Such dominance also occurred in published in vitro iterated growth and passage experiments with tumor cells in which genetic barcodes were used for lineage tracing. A potential source for such heterogeneity is that dominant clones derive from cancer stem cells with an unlimited self-renewal capacity. Furthermore, ongoing evolution and selection within the growing population may also induce clonal dominance. To understand how clonal dominance developed in the iterated growth and passage experiments, we built a computational model that accurately simulates these experiments. The model simulations reproduced the clonal dominance that developed in in vitro iterated growth and passage experiments when the division rates vary between cells, due to a combination of initial variation and of ongoing mutational processes. In contrast, the experimental results can neither be reproduced with a model that considers random growth and passage, nor with a model based on cancer stem cells. Altogether, our model suggests that in vitro clonal dominance develops due to selection of fast-dividing clones.

Tumors consist of numerous cell populations, i.e., clones, that differ with respect to genotype, and potentially with respect to phenotype, and these populations strongly differ in their size. A limited number of clones tend to dominate tumors, but it remains unclear how this clonal dominance arises. Potential driving mechanisms are the presence of cancer stem cells, which either divide indefinitely of differentiate into cells with a limited division potential, and ongoing evolutionary processes within the tumor. Here we use a computational model to understand how clonal dominance developed during in vitro growth and passage experiments with cancer cells. Incorporating cancer stem cells in this model did not result in a match between simulations and in vitro data. In contrast, by considering all cells to divide indefinitely and division rates to evolve due to the combination of division rate variability and selection by passage, our model closely matches the in vitro data.

Left or right? Directions to stem cell engraftment

In this issue of JEM, Wu et al. (https://doi.org/10.1084/jem.20171341) use genetic barcoding of macaque hematopoietic stem cells to demonstrate that, after transplantation, HSCs are very asymmetrically distributed and uncover a thymus-independent pathway for mature T cell production in the bone marrow.

Trends in Surgical Research in Head and Neck Cancer

OPINION STATEMENT

The task of surgical research is to improve the efficacy of available surgical therapeutic modalities, develop new ones, and balance this well with favorable functional outcome. Therefore, surgical research is composed of a translational and a clinical component. In translational surgical research, animal models are used to better understand the biology of head and neck cancers, but even more importantly, the biology of changes to the disease and the microenvironment created by surgical interventions. Animal models additionally allow for the development of image-guided surgery systems, novel strategies of intraoperative adjuvant treatment, and patient "avatars" to test innovative anticancer drug combinations. In clinical surgical research, surgical techniques are validated in clinical trials for effectiveness of tumor control and improvement of functional recovery of the patient. In conclusion, surgical research for head and neck cancer is an active field spanning across the entire breadth of basic and clinical science devoted to a better understanding of what surgery does to the disease and to the patient.

Modeling the process of human tumorigenesis

Modelling the genesis of human cancers is at a scientific turning point. Starting from primary sources of normal human cells, it is now possible to reproducibly generate several types of malignant cell populations. Powerful methods for clonally tracking and manipulating their appearance and progression in serially transplanted immunodeficient mice are also in place. These developments circumvent historic drawbacks inherent in analyses of cancers produced in model organisms, established human malignant cell lines, or highly heterogeneous patient samples. In this review, we survey the advantages, contributions and limitations of current de novo human tumorigenesis strategies and note several exciting prospects on the horizon.

A better understanding of the earliest stages of human cancer formation can enable future improvements in early detection, diagnosis and treatment. In this review, the authors summarize the methods enabling de novo tumorigenesis protocols to be applied to human cells and the insights derived from them to date, as well as the exciting and relevant technical developments anticipated to extend even further the utility of these strategies.

Lentiviral Barcode Labeling and Transplantation of Fetal Liver Hematopoietic Stem and Progenitor Cells

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 ).

Clonal selection and asymmetric distribution of human leukemia in murine xenografts revealed by cellular barcoding

Genetic and phenotypic heterogeneity of human leukemia is thought to drive leukemia progression through a Darwinian process of selection and evolution of increasingly malignant clones. However, the lack of markers that uniquely identify individual leukemia clones precludes high-resolution tracing of their clonal dynamics. Here, we use cellular barcoding to analyze the clonal behavior of patient-derived leukemia-propagating cells (LPCs) in murine xenografts. Using a leukemic cell line and diagnostic bone marrow cells from 6 patients with B-progenitor cell acute lymphoblastic leukemia, we demonstrate that patient-derived xenografts were highly polyclonal, consisting of tens to hundreds of LPC clones. The number of clones was stable within xenografts but strongly reduced upon serial transplantation. In contrast to primary recipients, in which clonal composition was highly diverse, clonal composition in serial xenografts was highly similar between recipients of the same donor and reflected donor clonality, supporting a deterministic, clone-size-based model for clonal selection. Quantitative analysis of clonal abundance in several anatomic sites identified 2 types of anatomic asymmetry. First, clones were asymmetrically distributed between different bones. Second, clonal composition in the skeleton significantly differed from extramedullary sites, showing similar numbers but different clone sizes. Altogether, this study shows that cellular barcoding and xenotransplantation providea useful model to study the behavior of patient-derived LPC clones, which provides insights relevant for experimental studies on cancer stem cells and for clinical protocols for the diagnosis and treatment of leukemia.

Limitations and challenges of genetic barcode quantification

Genetic barcodes are increasingly used to track individual cells and to quantitatively assess their clonal contributions over time. Although barcode quantification relies entirely on counting sequencing reads, detailed studies about the method’s accuracy are still limited. We report on a systematic investigation of the relation between barcode abundance and resulting read counts after amplification and sequencing using cell-mixtures that contain barcodes with known frequencies (“miniBulks”). We evaluated the influence of protocol modifications to identify potential sources of error and elucidate possible limitations of the quantification approach. Based on these findings we designed an advanced barcode construct (BC32) to improved barcode calling and quantification, and to ensure a sensitive detection of even highly diluted barcodes. Our results emphasize the importance of using curated barcode libraries to obtain interpretable quantitative data and underline the need for rigorous analyses of any utilized barcode library in terms of reliability and reproducibility.