Best Practices in Designing, Sequencing, and Identifying Random DNA Barcodes

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.

Highly replicated experiments studying complex genotypes using nested DNA barcodes

Many biological experiments involve studying the differences caused by genetic modifications, including genotypes composed of modifications at more than one locus. However, as the number and complexity of the genotypes increases, independently generating and tracking the necessary number of biological replicate samples becomes a major challenge. We developed a barcode-based method to track large numbers of independent replicates of combinatorial genotypes in a pooled format, enabling robust detection of subtle phenotypic differences. To construct a plasmid library of combinatorial genotypes, we utilized a nested serial cloning process to combine gene variants of interest that have associated DNA barcodes. The final plasmids each contain variants of multiple genes of interest, and a combined barcode that specifies the genotype of all the genes while also encoding a random sequence for tracking individual replicates. Sequencing of the pool of barcodes by next-generation sequencing allows the whole population to be studied in a single flask, enabling a high degree of replication even for complex genotypes. Using this approach, we tested the functionality of combinations of yeast, human, and null orthologs of the nucleotide excision repair factor I (NEF-1) complex and found that cells expressing all three yeast NEF-1 subunits had superior growth in DNA-damaging conditions. We also assessed the sensitivity of our method by simulating downsampling of barcodes across different degrees of phenotypic differentiation. Our results demonstrate the utility of NICR barcodes for high-throughput combinatorial genetic screens and provide a scalable framework for exploring complex genotype-phenotype relationships.

Hierarchical Lineage Tracing Reveals Diverse Pathways of AML Treatment Resistance

Cancer cells adapt to treatment, leading to the emergence of clones that are more aggressive and resistant to anti-cancer therapies. We have a limited understanding of the development of treatment resistance as we lack technologies to map the evolution of cancer under the selective pressure of treatment. To address this, we developed a hierarchical, dynamic lineage tracing method called FLARE (Following Lineage Adaptation and Resistance Evolution). We use this technique to track the progression of acute myeloid leukemia (AML) cell lines through exposure to Cytarabine (AraC), a front-line treatment in AML, in vitro and in vivo. We map distinct cellular lineages in murine and human AML cell lines predisposed to AraC persistence and/or resistance via the upregulation of cell adhesion and motility pathways. Additionally, we highlight the heritable expression of immunoproteasome 11S regulatory cap subunits as a potential mechanism aiding AML cell survival, proliferation, and immune escape in vivo. Finally, we validate the clinical relevance of these signatures in the TARGET-AML cohort, with a bisected response in blood and bone marrow. Our findings reveal a broad spectrum of resistance signatures attributed to significant cell transcriptional changes. To our knowledge, this is the first application of dynamic lineage tracing to unravel treatment response and resistance in cancer, and we expect FLARE to be a valuable tool in dissecting the evolution of resistance in a wide range of tumor types.

Digital sequencing is improved by using structured unique molecular identifiers

Digital sequencing uses unique molecular identifiers (UMIs) to correct for polymerase induced errors and amplification biases. Here, we design 19 different structured UMIs to minimize the capacity of primers to form non-specific PCR products during library construction using SiMSen-Seq, a PCR-based digital sequencing approach with flexible multiplexing capabilities suitable for tumor-informed mutation analysis. All structured UMI designs demonstrate enhanced assay performance compared with an unstructured reference UMI. The best performing structured UMI design shows significant improvements in all tested aspects of assay and sequencing performance with the ability to reliable detect low variant allele frequencies.

NucBalancer: streamlining barcode sequence selection for optimal sample pooling for sequencing

Recent advancements in next-generation sequencing (NGS) technologies have brought to the forefront the necessity for versatile, cost-effective tools capable of adapting to a rapidly evolving landscape. The emergence of numerous new sequencing platforms, each with unique sample preparation and sequencing requirements, underscores the importance of efficient barcode balancing for successful pooling and accurate demultiplexing of samples. Recently launched new sequencing systems claiming better affordability comparable to more established platforms further exemplifies these challenges, especially when libraries originally prepared for one platform need conversion to another. In response to this dynamic environment, we introduce NucBalancer, a Shiny app developed for the optimal selection of barcode sequences. While initially tailored to meet the nucleotide, composition challenges specific to G400 and T7 series sequencers, NucBalancer's utility significantly broadens to accommodate the varied demands of these new sequencing technologies. Its application is particularly crucial in single-cell genomics, enabling the adaptation of libraries, such as those prepared for 10x technology, to various sequencers including G400 and T7 series sequencers. NucBalancer efficiently balances nucleotide composition and sample concentrations, reducing biases and enhancing the reliability of NGS data across platforms. Its adaptability makes it invaluable for addressing sequencing challenges, ensuring effective barcode balancing for sample pooling on any platform.

Availability and implementation

NucBalancer is implemented in R and is available at https://github.com/ersgupta/NucBalancer. Additionally, a shiny interface is available at https://ersgupta.shinyapps.io/NucBalancer/.

Environment-independent distribution of mutational effects emerges from microscopic epistasis

Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, in which the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.

Improving the Accuracy of Bulk Fitness Assays by Correcting Barcode Processing Biases

Measuring the fitnesses of genetic variants is a fundamental objective in evolutionary biology. A standard approach for measuring microbial fitnesses in bulk involves labeling a library of genetic variants with unique sequence barcodes, competing the labeled strains in batch culture, and using deep sequencing to track changes in the barcode abundances over time. However, idiosyncratic properties of barcodes can induce nonuniform amplification or uneven sequencing coverage that causes some barcodes to be over- or under-represented in samples. This systematic bias can result in erroneous read count trajectories and misestimates of fitness. Here, we develop a computational method, named REBAR (Removing the Effects of Bias through Analysis of Residuals), for inferring the effects of barcode processing bias by leveraging the structure of systematic deviations in the data. We illustrate this approach by applying it to two independent data sets, and demonstrate that this method estimates and corrects for bias more accurately than standard proxies, such as GC-based corrections. REBAR mitigates bias and improves fitness estimates in high-throughput assays without introducing additional complexity to the experimental protocols, with potential applications in a range of experimental evolution and mutation screening contexts.

Flexible parsing, interpretation, and editing of technical sequences with splitcode

MOTIVATION

Next-generation sequencing libraries are constructed with numerous synthetic constructs such as sequencing adapters, barcodes, and unique molecular identifiers. Such sequences can be essential for interpreting results of sequencing assays, and when they contain information pertinent to an experiment, they must be processed and analyzed.

RESULTS

We present a tool called splitcode, that enables flexible and efficient parsing, interpreting, and editing of sequencing reads. This versatile tool facilitates simple, reproducible preprocessing of reads from libraries constructed for a large array of single-cell and bulk sequencing assays.

AVAILABILITY AND IMPLEMENTATION

The splitcode program is available at http://github.com/pachterlab/splitcode.

ORBIT for E. coli: kilobase-scale oligonucleotide recombineering at high throughput and high efficiency

Microbiology and synthetic biology depend on reverse genetic approaches to manipulate bacterial genomes; however, existing methods require molecular biology to generate genomic homology, suffer from low efficiency, and are not easily scaled to high throughput. To overcome these limitations, we developed a system for creating kilobase-scale genomic modifications that uses DNA oligonucleotides to direct the integration of a non-replicating plasmid. This method, Oligonucleotide Recombineering followed by Bxb-1 Integrase Targeting (ORBIT) was pioneered in Mycobacteria, and here we adapt and expand it for Escherichia coli. Our redesigned plasmid toolkit for oligonucleotide recombineering achieved significantly higher efficiency than λ Red double-stranded DNA recombineering and enabled precise, stable knockouts (≤134 kb) and integrations (≤11 kb) of various sizes. Additionally, we constructed multi-mutants in a single transformation, using orthogonal attachment sites. At high throughput, we used pools of targeting oligonucleotides to knock out nearly all known transcription factor and small RNA genes, yielding accurate, genome-wide, single mutant libraries. By counting genomic barcodes, we also show ORBIT libraries can scale to thousands of unique members (>30k). This work demonstrates that ORBIT for E. coli is a flexible reverse genetic system that facilitates rapid construction of complex strains and readily scales to create sophisticated mutant libraries.

Optimizing Nucleic Acid Delivery Systems through Barcode Technology

Conventional biological experiments often focus on in vitro assays because of the inherent limitations when handling multiple variables in vivo, including labor-intensive and time-consuming procedures. Often only a subset of samples demonstrating significant efficacy in the in vitro assays can be evaluated in vivo. Nonetheless, because of the low correlation between the in vitro and in vivo tests, evaluation of the variables under examination in vivo and not solely in vitro is critical. An emerging approach to achieve high-throughput in vivo tests involves using a barcode system consisting of various nucleotide combinations. Unique barcodes for each variant enable the simultaneous testing of multiple entities, eliminating the need for separate individual tests. Subsequently, to identify crucial parameters, samples were collected and analyzed using barcode sequencing. This review explores the development of barcode design and its applications, including the evaluation of nucleic acid delivery systems and the optimization of gene expression in vivo.

Principles of digital sequencing using unique molecular identifiers

Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the principles of UMIs and how they are used in digital sequencing. We outline the properties of different UMI types and the consequences of various UMI approaches in relation to experimental protocols and bioinformatics. Finally, we describe how digital sequencing can be applied in specific research fields, focusing on cancer management where it can be used in screening of asymptomatic individuals, diagnosis, treatment prediction, prognostication, monitoring treatment efficacy and early detection of treatment resistance as well as relapse.

Assessing microbiome population dynamics using wild-type isogenic standardized hybrid (WISH)-tags

Microbiomes feature recurrent compositional structures under given environmental conditions. However, these patterns may conceal diverse underlying population dynamics that require intrastrain resolution. Here we developed a genomic tagging system, termed wild-type isogenic standardized hybrid (WISH)-tags, that can be combined with quantitative polymerase chain reaction and next-generation sequencing for microbial strain enumeration. We experimentally validated the performance of 62 tags and showed that they can be differentiated with high precision. WISH-tags were introduced into model and non-model bacterial members of the mouse and plant microbiota. Intrastrain priority effects were tested using one species of isogenic barcoded bacteria in the murine gut and the Arabidopsis phyllosphere, both with and without microbiota context. We observed colonization resistance against late-arriving strains of Salmonella Typhimurium in the mouse gut, whereas the phyllosphere accommodated Sphingomonas latecomers in a manner proportional to their presence at the late inoculation timepoint. This demonstrates that WISH-tags are a resource for deciphering population dynamics underlying microbiome assembly across biological systems.

Extracting, filtering and simulating cellular barcodes using CellBarcode tools

Identifying true DNA cellular barcodes among polymerase chain reaction and sequencing errors is challenging. Current tools are restricted in the diversity of barcode types supported or the analysis strategies implemented. As such, there is a need for more versatile and efficient tools for barcode extraction, as well as for tools to investigate which factors impact barcode detection and which filtering strategies to best apply. Here we introduce the package CellBarcode and its barcode simulation kit, CellBarcodeSim, that allows efficient and versatile barcode extraction and filtering for a range of barcode types from bulk or single-cell sequencing data using a variety of filtering strategies. Using the barcode simulation kit and biological data, we explore the technical and biological factors influencing barcode identification and provide a decision tree on how to optimize barcode identification for different barcode settings. We believe that CellBarcode and CellBarcodeSim have the capability to enhance the reproducibility and interpretation of barcode results across studies.

Flexible parsing, interpretation, and editing of technical sequences with splitcode

Next-generation sequencing libraries are constructed with numerous synthetic constructs such as sequencing adapters, barcodes, and unique molecular identifiers. Such sequences can be essential for interpreting results of sequencing assays, and when they contain information pertinent to an experiment, they must be processed and analyzed. We present a tool called splitcode, that enables flexible and efficient parsing, interpreting, and editing of sequencing reads. This versatile tool facilitates simple, reproducible preprocessing of reads from libraries constructed for a large array of single-cell and bulk sequencing assays.

Barcoding Populations of Pseudomonas fluorescens SBW25

In recent years, evolutionary biologists have developed an increasing interest in the use of barcoding strategies to study eco-evolutionary dynamics of lineages within evolving populations and communities. Although barcoded populations can deliver unprecedented insight into evolutionary change, barcoding microbes presents specific technical challenges. Here, strategies are described for barcoding populations of the model bacterium Pseudomonas fluorescens SBW25, including the design and cloning of barcoded regions, preparation of libraries for amplicon sequencing, and quantification of resulting barcoded lineages. In so doing, we hope to aid the design and implementation of barcoding methodologies in a broad range of model and non-model organisms.

Extreme Sensitivity of Fitness to Environmental Conditions: Lessons from #1BigBatch

The phrase "survival of the fittest" has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcodes, all methods are limited in their precision to differentiate strains with small fitness differences. In this study, we rule out some major sources of imprecision, but still find that fitness measurements vary substantially from replicate to replicate. Our data suggest that very subtle and difficult to avoid environmental differences between replicates create systematic variation across fitness measurements. We conclude by discussing how fitness measurements should be interpreted given their extreme environment dependence. This work was inspired by the scientific community who followed us and gave us tips as we live tweeted a high-replicate fitness measurement experiment at #1BigBatch.

Best Practices in Microbial Experimental Evolution: Using Reporters and Long-Read Sequencing to Identify Copy Number Variation in Experimental Evolution

Copy number variants (CNVs), comprising gene amplifications and deletions, are a pervasive class of heritable variation. CNVs play a key role in rapid adaptation in both natural, and experimental, evolution. However, despite the advent of new DNA sequencing technologies, detection and quantification of CNVs in heterogeneous populations has remained challenging. Here, we summarize recent advances in the use of CNV reporters that provide a facile means of quantifying de novo CNVs at a specific locus in the genome, and nanopore sequencing, for resolving the often complex structures of CNVs. We provide guidance for the engineering and analysis of CNV reporters and practical guidelines for single-cell analysis of CNVs using flow cytometry. We summarize recent advances in nanopore sequencing, discuss the utility of this technology, and provide guidance for the bioinformatic analysis of these data to define the molecular structure of CNVs. The combination of reporter systems for tracking and isolating CNV lineages and long-read DNA sequencing for characterizing CNV structures enables unprecedented resolution of the mechanisms by which CNVs are generated and their evolutionary dynamics.