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Park S, Kim M, Lee JW. Optimizing Nucleic Acid Delivery Systems through Barcode Technology. ACS Synth Biol 2024; 13:1006-1018. [PMID: 38526308 DOI: 10.1021/acssynbio.3c00602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
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.
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Affiliation(s)
- Soan Park
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
| | - Mibang Kim
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
| | - Jeong Wook Lee
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
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2
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Sun W, Perkins M, Huyghe M, Faraldo MM, Fre S, Perié L, Lyne AM. Extracting, filtering and simulating cellular barcodes using CellBarcode tools. NATURE COMPUTATIONAL SCIENCE 2024; 4:128-143. [PMID: 38374363 PMCID: PMC10899113 DOI: 10.1038/s43588-024-00595-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 01/16/2024] [Indexed: 02/21/2024]
Abstract
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.
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Affiliation(s)
- Wenjie Sun
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France.
| | - Meghan Perkins
- Institut Curie, Laboratory of Genetics and Developmental Biology, PSL Research University, INSERM U934, CNRS UMR3215, Paris, France
| | - Mathilde Huyghe
- Institut Curie, Laboratory of Genetics and Developmental Biology, PSL Research University, INSERM U934, CNRS UMR3215, Paris, France
| | - Marisa M Faraldo
- Institut Curie, Laboratory of Genetics and Developmental Biology, PSL Research University, INSERM U934, CNRS UMR3215, Paris, France
| | - Silvia Fre
- Institut Curie, Laboratory of Genetics and Developmental Biology, PSL Research University, INSERM U934, CNRS UMR3215, Paris, France
| | - Leïla Perié
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France.
| | - Anne-Marie Lyne
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France.
- INSERM U900, Paris, France.
- MINES ParisTech, CBIO-Centre for Computational Biology, PSL Research University, Paris, France.
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3
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Charlebois DA. Quantitative systems-based prediction of antimicrobial resistance evolution. NPJ Syst Biol Appl 2023; 9:40. [PMID: 37679446 PMCID: PMC10485028 DOI: 10.1038/s41540-023-00304-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 08/24/2023] [Indexed: 09/09/2023] Open
Abstract
Predicting evolution is a fundamental problem in biology with practical implications for treating antimicrobial resistance, which is a complex system-level phenomenon. In this perspective article, we explore the limits of predicting antimicrobial resistance evolution, quantitatively define the predictability and repeatability of microevolutionary processes, and speculate on how these quantities vary across temporal, biological, and complexity scales. The opportunities and challenges for predicting antimicrobial resistance in the context of systems biology are also discussed. Based on recent research, we conclude that the evolution of antimicrobial resistance can be predicted using a systems biology approach integrating quantitative models with multiscale data from microbial evolution experiments.
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Affiliation(s)
- Daniel A Charlebois
- Department of Physics, University of Alberta, Edmonton, AB, T6G-2E1, Canada.
- Department of Biological Sciences, University of Alberta, Edmonton, AB, T6G-2E9, Canada.
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4
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Stevenson ZC, Moerdyk-Schauwecker MJ, Banse SA, Patel DS, Lu H, Phillips PC. High-throughput library transgenesis in Caenorhabditis elegans via Transgenic Arrays Resulting in Diversity of Integrated Sequences (TARDIS). eLife 2023; 12:RP84831. [PMID: 37401921 PMCID: PMC10328503 DOI: 10.7554/elife.84831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2023] Open
Abstract
High-throughput transgenesis using synthetic DNA libraries is a powerful method for systematically exploring genetic function. Diverse synthesized libraries have been used for protein engineering, identification of protein-protein interactions, characterization of promoter libraries, developmental and evolutionary lineage tracking, and various other exploratory assays. However, the need for library transgenesis has effectively restricted these approaches to single-cell models. Here, we present Transgenic Arrays Resulting in Diversity of Integrated Sequences (TARDIS), a simple yet powerful approach to large-scale transgenesis that overcomes typical limitations encountered in multicellular systems. TARDIS splits the transgenesis process into a two-step process: creation of individuals carrying experimentally introduced sequence libraries, followed by inducible extraction and integration of individual sequences/library components from the larger library cassette into engineered genomic sites. Thus, transformation of a single individual, followed by lineage expansion and functional transgenesis, gives rise to thousands of genetically unique transgenic individuals. We demonstrate the power of this system using engineered, split selectable TARDIS sites in Caenorhabditis elegans to generate (1) a large set of individually barcoded lineages and (2) transcriptional reporter lines from predefined promoter libraries. We find that this approach increases transformation yields up to approximately 1000-fold over current single-step methods. While we demonstrate the utility of TARDIS using C. elegans, in principle the process is adaptable to any system where experimentally generated genomic loci landing pads and diverse, heritable DNA elements can be generated.
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Affiliation(s)
| | | | - Stephen A Banse
- Institute of Ecology and Evolution, University of OregonEugeneUnited States
| | - Dhaval S Patel
- School of Chemical & Biomolecular Engineering, Georgia Institute of TechnologyAtlantaUnited States
- Petit Institute for Bioengineering and Bioscience, Georgia Institute of TechnologyAtlantaUnited States
| | - Hang Lu
- School of Chemical & Biomolecular Engineering, Georgia Institute of TechnologyAtlantaUnited States
- Petit Institute for Bioengineering and Bioscience, Georgia Institute of TechnologyAtlantaUnited States
| | - Patrick C Phillips
- Institute of Ecology and Evolution, University of OregonEugeneUnited States
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5
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Rezenman S, Knafo M, Tsigalnitski I, Barad S, Jona G, Levi D, Dym O, Reich Z, Kapon R. gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution. PLoS One 2023; 18:e0286696. [PMID: 37285353 DOI: 10.1371/journal.pone.0286696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 05/19/2023] [Indexed: 06/09/2023] Open
Abstract
Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones' relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system's application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.
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Affiliation(s)
- Shahar Rezenman
- Department of Biomolecular Sciences, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Maor Knafo
- Department of Biomolecular Sciences, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Ivgeni Tsigalnitski
- Department of Biomolecular Sciences, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Shiri Barad
- Department of Biomolecular Sciences, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Ghil Jona
- Life Sciences Core Facilities, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Dikla Levi
- Life Sciences Core Facilities, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Orly Dym
- The Dana and Yossie Hollander Center for Structural Proteomics, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Ziv Reich
- Department of Biomolecular Sciences, Weizmann Institute of Science Rehovot, Rehovot, Israel
| | - Ruti Kapon
- Department of Biomolecular Sciences, Weizmann Institute of Science Rehovot, Rehovot, Israel
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6
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Theodosiou L, Farr AD, Rainey PB. Barcoding Populations of Pseudomonas fluorescens SBW25. J Mol Evol 2023; 91:254-262. [PMID: 37186220 PMCID: PMC10275814 DOI: 10.1007/s00239-023-10103-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 03/13/2023] [Indexed: 05/17/2023]
Abstract
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.
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Affiliation(s)
- Loukas Theodosiou
- Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany.
- Department of Comparative Development and Genetics, Max Planck Institute for Plant Breeding, Cologne, Germany.
| | - Andrew D Farr
- Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Paul B Rainey
- Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany
- Laboratory of Biophysics and Evolution, CBI, ESPCI Paris, Université PSL, CNRS, Paris, France
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7
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Johnson MS, Venkataram S, Kryazhimskiy S. Best Practices in Designing, Sequencing, and Identifying Random DNA Barcodes. J Mol Evol 2023; 91:263-280. [PMID: 36651964 PMCID: PMC10276077 DOI: 10.1007/s00239-022-10083-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 12/15/2022] [Indexed: 01/19/2023]
Abstract
Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.
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Affiliation(s)
- Milo S Johnson
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Sandeep Venkataram
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA, 92093, USA
| | - Sergey Kryazhimskiy
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA, 92093, USA.
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8
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Peng X, Dorman KS. Accurate estimation of molecular counts from amplicon sequence data with unique molecular identifiers. Bioinformatics 2023; 39:6971842. [PMID: 36610988 PMCID: PMC9891248 DOI: 10.1093/bioinformatics/btad002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 11/16/2022] [Accepted: 01/04/2023] [Indexed: 01/09/2023] Open
Abstract
MOTIVATION Amplicon sequencing is widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and quantifying their abundance is crucial for downstream analyses, but measured abundances are distorted by stochasticity and bias in amplification, plus errors during polymerase chain reaction (PCR) and sequencing. One solution attaches unique molecular identifiers (UMIs) to sample sequences before amplification. Counting UMIs instead of sequences provides unbiased estimates of abundance. While modern methods improve over naïve counting by UMI identity, most do not account for UMI reuse or collision, and they do not adequately model PCR and sequencing errors in the UMIs and sample sequences. RESULTS We introduce Deduplication and Abundance estimation with UMIs (DAUMI), a probabilistic framework to detect true biological amplicon sequences and accurately estimate their deduplicated abundance. DAUMI recognizes UMI collision, even on highly similar sequences, and detects and corrects most PCR and sequencing errors in the UMI and sampled sequences. DAUMI performs better on simulated and real data compared to other UMI-aware clustering methods. AVAILABILITY AND IMPLEMENTATION Source code is available at https://github.com/DormanLab/AmpliCI. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Xiyu Peng
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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9
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McMullen JG, Lennon JT. Mark-recapture of microorganisms. Environ Microbiol 2023; 25:150-157. [PMID: 36310117 DOI: 10.1111/1462-2920.16267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 10/27/2022] [Indexed: 01/21/2023]
Affiliation(s)
| | - Jay T Lennon
- Department of Biology, Indiana University, Bloomington, Indiana, USA
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10
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Koshy AA. Parasite potpourri: Toxoplasma gondii lineage tracing in vivo. Trends Parasitol 2022; 38:1026-1027. [PMID: 36302693 DOI: 10.1016/j.pt.2022.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 10/11/2022] [Indexed: 11/11/2022]
Abstract
Using a CRISPR/Cas9-based method, Wincott et al. generated a stable, complex Toxoplasma gondii population composed of 96 barcoded clonal lineages. By tracking the population structure in vivo, they determine that - contrary to expectations - the pathway to infecting the brain is widely permissive for T. gondii.
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Affiliation(s)
- Anita A Koshy
- Department of Neurology, Department of Immunobiology, BIO5 Institute, University of Arizona, Tucson, AZ, USA.
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11
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Wincott CJ, Sritharan G, Benns HJ, May D, Gilabert-Carbajo C, Bunyan M, Fairweather AR, Alves E, Andrew I, Game L, Frickel EM, Tiengwe C, Ewald SE, Child MA. Cellular barcoding of protozoan pathogens reveals the within-host population dynamics of Toxoplasma gondii host colonization. CELL REPORTS METHODS 2022; 2:100274. [PMID: 36046624 PMCID: PMC9421581 DOI: 10.1016/j.crmeth.2022.100274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 05/20/2022] [Accepted: 07/22/2022] [Indexed: 02/09/2023]
Abstract
Cellular barcoding techniques are powerful tools to understand microbial pathogenesis. However, barcoding strategies have not been broadly applied to protozoan parasites, which have unique genomic structures and virulence strategies compared with viral and bacterial pathogens. Here, we present a CRISPR-based method to barcode protozoa, which we successfully apply to Toxoplasma gondii and Trypanosoma brucei. Using libraries of barcoded T. gondii, we evaluate shifts in the population structure from acute to chronic infection of mice. Contrary to expectation, most barcodes were present in the brain one month post-intraperitoneal infection in both inbred CBA/J and outbred Swiss mice. Although parasite cyst number and barcode diversity declined over time, barcodes representing a minor fraction of the inoculum could become a dominant population in the brain by three months post-infection. These data establish a cellular barcoding approach for protozoa and evidence that the blood-brain barrier is not a major bottleneck to colonization by T. gondii.
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Affiliation(s)
- Ceire J. Wincott
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Gayathri Sritharan
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
- Department of Biological Sciences, Birkbeck, University of London, Mallet Street, Bloomsbury, London WC1E 7HX, UK
| | - Henry J. Benns
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
- Department of Chemistry, Imperial College London, White City Campus, London W12 0BZ, UK
| | - Dana May
- Department of Microbiology, Immunology and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Carla Gilabert-Carbajo
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Monique Bunyan
- Host-Toxoplasma Interaction Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1BF, UK
| | - Aisling R. Fairweather
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Eduardo Alves
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Ivan Andrew
- UKRI London Institute of Medical Sciences Genomics Laboratory, Shepherd’s Bush, London W12 0NN, UK
| | - Laurence Game
- UKRI London Institute of Medical Sciences Genomics Laboratory, Shepherd’s Bush, London W12 0NN, UK
| | - Eva-Maria Frickel
- Host-Toxoplasma Interaction Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1BF, UK
- Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Edgbaston B15 2TT, UK
| | - Calvin Tiengwe
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Sarah E. Ewald
- Department of Microbiology, Immunology and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Matthew A. Child
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
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12
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Tavakolian N, Frazão JG, Bendixsen D, Stelkens R, Li CB. Shepherd: Accurate Clustering for Correcting DNA Barcode Errors. Bioinformatics 2022; 38:3710-3716. [PMID: 35708611 PMCID: PMC9344852 DOI: 10.1093/bioinformatics/btac395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 03/26/2022] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
Motivation DNA barcodes are short, random nucleotide sequences introduced into cell populations to track the relative counts of hundreds of thousands of individual lineages over time. Lineage tracking is widely applied, e.g. to understand evolutionary dynamics in microbial populations and the progression of breast cancer in humans. Barcode sequences are unknown upon insertion and must be identified using next-generation sequencing technology, which is error prone. In this study, we frame the barcode error correction task as a clustering problem with the aim to identify true barcode sequences from noisy sequencing data. We present Shepherd, a novel clustering method that is based on an indexing system of barcode sequences using k-mers, and a Bayesian statistical test incorporating a substitution error rate to distinguish true from error sequences. Results When benchmarking with synthetic data, Shepherd provides barcode count estimates that are significantly more accurate than state-of-the-art methods, producing 10–150 times fewer spurious lineages. For empirical data, Shepherd produces results that are consistent with the improvements seen on synthetic data. These improvements enable higher resolution lineage tracking and more accurate estimates of biologically relevant quantities, e.g. the detection of small effect mutations. Availability and implementation A Python implementation of Shepherd is freely available at: https://www.github.com/Nik-Tavakolian/Shepherd. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Nik Tavakolian
- Department of Mathematics, Stockholm University, Stockholm, 10691, Sweden
| | | | - Devin Bendixsen
- Department of Zoology, Stockholm University, Stockholm, 10691, Sweden
| | - Rike Stelkens
- Department of Zoology, Stockholm University, Stockholm, 10691, Sweden
| | - Chun-Biu Li
- Department of Mathematics, Stockholm University, Stockholm, 10691, Sweden
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13
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A Cell Double-Barcoding System for Quantitative Evaluation of Primary Tumors and Metastasis in Animals That Uncovers Clonal-Specific Anti-Cancer Drug Effects. Cancers (Basel) 2022; 14:cancers14061381. [PMID: 35326533 PMCID: PMC8946264 DOI: 10.3390/cancers14061381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 02/23/2022] [Accepted: 03/01/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary The main problem in treating advanced cancers is a metastatic spread when individual cancer cells leave the primary tumor and colonize to distant organs. In drug development, it is important to quantitatively assess effects of novel drug candidates on both primary tumors and metastasis. Unfortunately, current methods of monitoring metastasis in mouse models have low sensitivity and are not quantitative. Here, we developed a methodology to monitor drug effects on metastasis that is quantitative and has a very high sensitivity and resolution. In fact, it allows monitoring effects of drugs on individual cancer cells in animals. Abstract Imaging in monitoring metastasis in mouse models has low sensitivity and is not quantitative. Cell DNA barcoding, demonstrating high sensitivity and resolution, allows monitoring effects of drugs on the number of tumor and metastatic clones. However, this technology is not suitable for comparison of sizes of metastatic clones in different animals, for example, drug treated and untreated, due to high biological and technical variability upon tumor and metastatic growth and isolation of barcodes from tissue DNA. However, both numbers of clones and their sizes are critical parameters for analysis of drug effects. Here we developed a modification of the barcoding approach for monitoring drug effects on tumors and metastasis that is quantitative, highly sensitive and highly reproducible. This novel cell double-barcoding system allows simultaneously following the fate of two or more cell variants or cell lines in xenograft models in vivo, and also following the fates of individual clones within each of these populations. This system allows comparing effects of drugs on different cell populations and thus normalizing drug effects by drug-resistant lines, which corrects for both biological and technical variabilities and significantly increases the reproducibility of results. Using this barcoding system, we uncovered that effects of a novel DYRK1B kinase inhibitor FX9847 on primary tumors and metastasis is clone-dependent, while a distinct drug osimertinib demonstrated clone-independent effects on cancer cell populations. Overall, a cell double-barcoding approach can significantly enrich our understanding of drug effects in basic research and preclinical studies.
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14
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Borer B, Or D. Bacterial age distribution in soil - Generational gaps in adjacent hot and cold spots. PLoS Comput Biol 2022; 18:e1009857. [PMID: 35213536 PMCID: PMC8906644 DOI: 10.1371/journal.pcbi.1009857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 03/09/2022] [Accepted: 01/23/2022] [Indexed: 11/25/2022] Open
Abstract
Resource patchiness and aqueous phase fragmentation in soil may induce large differences local growth conditions at submillimeter scales. These are translated to vast differences in bacterial age from cells dividing every thirty minutes in close proximity to plant roots to very old cells experiencing negligible growth in adjacent nutrient poor patches. In this study, we link bacterial population demographics with localized soil and hydration conditions to predict emerging generation time distributions and estimate mean bacterial cell ages using mechanistic and heuristic models of bacterial life in soil. Results show heavy-tailed distributions of generation times that resemble a power law for certain conditions, suggesting that we may find bacterial cells of vastly different ages living side by side within small soil volumes. Our results imply that individual bacteria may exist concurrently with all of their ancestors, resulting in an archive of bacterial cells with traits that have been gained (and lost) throughout time-a feature unique to microbial life. This reservoir of bacterial strains and the potential for the reemergence of rare strains with specific functions may be critical for ecosystem stability and function.
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Affiliation(s)
| | - Dani Or
- ETH Zurich, Zurich, Switzerland
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15
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Gardner A, Morgan D, Al'Khafaji A, Brock A. Functionalized Lineage Tracing for the Study and Manipulation of Heterogeneous Cell Populations. Methods Mol Biol 2022; 2394:109-131. [PMID: 35094325 DOI: 10.1007/978-1-0716-1811-0_8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The ability to track and isolate unique cell lineages from large heterogeneous populations increases the resolution at which cellular processes can be understood under normal and pathogenic states beyond snapshots obtained from single-cell RNA sequencing (scRNA-seq). Here, we describe the Control of Lineages by Barcode Enabled Recombinant Transcription (COLBERT) method in which unique single guide RNA (sgRNA) barcodes are used as functional tags to identify and recall specific lineages of interest. An sgRNA barcode is stably integrated and actively transcribed, such that all cellular progeny will contain the parental barcode and produce a functional sgRNA. The sgRNA barcode has all the benefits of a DNA barcode and added functionalities. Once a barcode pertaining to a lineage of interest is identified, the lineage of interest can be isolated using an activator variant of Cas9 (such as dCas9-VPR) and a barcode-matched sequence upstream of a fluorescent reporter gene. CRISPR activation of the fluorescent reporter will only occur in cells producing the matched sgRNA barcode, allowing precise identification and isolation of lineages of interest from heterogeneous populations.
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Affiliation(s)
- Andrea Gardner
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Daylin Morgan
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Aziz Al'Khafaji
- Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX, USA
| | - Amy Brock
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
- Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX, USA.
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16
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Kirby MB, Whitehead TA. Facile Assembly of Combinatorial Mutagenesis Libraries Using Nicking Mutagenesis. Methods Mol Biol 2022; 2461:85-109. [PMID: 35727445 PMCID: PMC9730894 DOI: 10.1007/978-1-0716-2152-3_6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Combinatorial mutagenesis is a method where multiple user-defined mutations are encoded at defined positions in a sequence. Combinatorial mutagenic libraries can be used in a variety of applications including evaluating fundamental questions about molecular evolution, directed evolution workflows for enzyme engineering, and in better understanding of biological processes like antibody affinity maturation. Here, we show a method of combinatorial mutagenesis utilizing the template-based nicking mutagenesis with several modifications. We show an example for generating a combinatorial library with 14 mutated positions, a total of 16,384 library variants, and a protocol for the generation of large, user-defined combinatorial libraries. The reader can use this protocol to create such libraries in 2 days.
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Affiliation(s)
- Monica B Kirby
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, USA
| | - Timothy A Whitehead
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, USA.
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17
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Gui P, Bivona TG. Evolution of metastasis: new tools and insights. Trends Cancer 2021; 8:98-109. [PMID: 34872888 DOI: 10.1016/j.trecan.2021.11.002] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 11/01/2021] [Accepted: 11/05/2021] [Indexed: 02/07/2023]
Abstract
Metastasis is an evolutionary process occurring across multiple organs and timescales. Due to its continuous and dynamic nature, this multifaceted process has been challenging to investigate and remains incompletely understood, in part due to the lack of tools capable of probing genomic evolution at high enough resolution. However, technological advances in genetic sequencing and editing have provided new and powerful methods to refine our understanding of the complex series of events that lead to metastatic dissemination. In this review, we summarize the latest genetic and lineage-tracing approaches developed to unravel the genetic evolution of metastasis. The findings that have emerged have enhanced our comprehension of the mechanistic trajectories and timescales of metastasis and could provide new strategies for therapy.
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Affiliation(s)
- Philippe Gui
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
| | - Trever G Bivona
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
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18
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Krasnov GS, Ghukasyan LG, Abramov IS, Nasedkina TV. Determination of the Subclonal Tumor Structure in Childhood Acute Myeloid Leukemia and Acral Melanoma by Next-Generation Sequencing. Mol Biol 2021. [DOI: 10.1134/s0026893321040051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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19
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Hullahalli K, Waldor MK. Pathogen clonal expansion underlies multiorgan dissemination and organ-specific outcomes during murine systemic infection. eLife 2021; 10:e70910. [PMID: 34636322 PMCID: PMC8545400 DOI: 10.7554/elife.70910] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 10/07/2021] [Indexed: 12/31/2022] Open
Abstract
The dissemination of pathogens through blood and their establishment within organs lead to severe clinical outcomes. However, the within-host dynamics that underlie pathogen spread to and clearance from systemic organs remain largely uncharacterized. In animal models of infection, the observed pathogen population results from the combined contributions of bacterial replication, persistence, death, and dissemination, each of which can vary across organs. Quantifying the contribution of each these processes is required to interpret and understand experimental phenotypes. Here, we leveraged STAMPR, a new barcoding framework, to investigate the population dynamics of extraintestinal pathogenic Escherichia coli, a common cause of bacteremia, during murine systemic infection. We show that while bacteria are largely cleared by most organs, organ-specific clearance failures are pervasive and result from dramatic expansions of clones representing less than 0.0001% of the inoculum. Clonal expansion underlies the variability in bacterial burden between animals, and stochastic dissemination of clones profoundly alters the pathogen population structure within organs. Despite variable pathogen expansion events, host bottlenecks are consistent yet highly sensitive to infection variables, including inoculum size and macrophage depletion. We adapted our barcoding methodology to facilitate multiplexed validation of bacterial fitness determinants identified with transposon mutagenesis and confirmed the importance of bacterial hexose metabolism and cell envelope homeostasis pathways for organ-specific pathogen survival. Collectively, our findings provide a comprehensive map of the population biology that underlies bacterial systemic infection and a framework for barcode-based high-resolution mapping of infection dynamics.
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Affiliation(s)
- Karthik Hullahalli
- Department of Microbiology, Harvard Medical SchoolBostonUnited States
- Division of Infectious Diseases, Brigham & Women’s HospitalBostonUnited States
| | - Matthew K Waldor
- Department of Microbiology, Harvard Medical SchoolBostonUnited States
- Division of Infectious Diseases, Brigham & Women’s HospitalBostonUnited States
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20
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Rana A, Patton D, Turner NT, Dillon MM, Cooper VS, Sung W. Precise measurement of the fitness effects of spontaneous mutations by droplet digital PCR in Burkholderia cenocepacia. Genetics 2021; 219:6325026. [PMID: 34849876 DOI: 10.1093/genetics/iyab117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 07/07/2021] [Accepted: 07/09/2021] [Indexed: 11/12/2022] Open
Abstract
Understanding how mutations affect survivability is a key component to knowing how organisms and complex traits evolve. However, most mutations have a minor effect on fitness and these effects are difficult to resolve using traditional molecular techniques. Therefore, there is a dire need for more accurate and precise fitness measurements methods. Here, we measured the fitness effects in Burkholderia cenocepacia HI2424 mutation accumulation (MA) lines using droplet-digital polymerase chain reaction (ddPCR). Overall, the fitness measurements from ddPCR-MA are correlated positively with fitness measurements derived from traditional phenotypic marker assays (r = 0.297, P = 0.05), but showed some differences. First, ddPCR had significantly lower measurement variance in fitness (F = 3.78, P < 2.6 × 10-13) in control experiments. Second, the mean fitness from ddPCR-MA measurements were significantly lower than phenotypic marker assays (-0.0041 vs -0.0071, P = 0.006). Consistent with phenotypic marker assays, ddPCR-MA measurements observed multiple (27/43) lineages that significantly deviated from mean fitness, suggesting that a majority of the mutations are neutral or slightly deleterious and intermixed with a few mutations that have extremely large effects. Of these mutations, we found a significant excess of mutations within DNA excinuclease and Lys R transcriptional regulators that have extreme deleterious and beneficial effects, indicating that modifications to transcription and replication may have a strong effect on organismal fitness. This study demonstrates the power of ddPCR as a ubiquitous method for high-throughput fitness measurements in both DNA- and RNA-based organisms regardless of cell type or physiology.
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Affiliation(s)
- Anita Rana
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - David Patton
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - Nathan T Turner
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - Marcus M Dillon
- Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario M5S3B2, Canada
| | - Vaughn S Cooper
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15219, USA
| | - Way Sung
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
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21
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Deatherage DE, Barrick JE. High-throughput characterization of mutations in genes that drive clonal evolution using multiplex adaptome capture sequencing. Cell Syst 2021; 12:1187-1200.e4. [PMID: 34536379 DOI: 10.1016/j.cels.2021.08.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 07/14/2021] [Accepted: 08/20/2021] [Indexed: 11/17/2022]
Abstract
Understanding how cells are likely to evolve can guide medical interventions and bioengineering efforts that must contend with unwanted mutations. The adaptome of a cell-the neighborhood of genetic changes that are most likely to drive adaptation in a given environment-can be mapped by tracking rare beneficial variants during the early stages of clonal evolution. We used multiplex adaptome capture sequencing (mAdCap-seq), a procedure that combines unique molecular identifiers and hybridization-based enrichment, to characterize mutations in eight Escherichia coli genes known to be under selection in a laboratory environment. We tracked 301 mutations at frequencies as low as 0.01% and inferred the fitness effects of 240 of these mutations. There were distinct molecular signatures of selection on protein structure and function for the three genes with the most beneficial mutations. Our results demonstrate how mAdCap-seq can be used to deeply profile a targeted portion of a cell's adaptome.
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Affiliation(s)
- Daniel E Deatherage
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712, USA
| | - Jeffrey E Barrick
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712, USA.
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22
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Abstract
Pathogen population dynamics during infection are critical determinants of infection susceptibility and define patterns of dissemination. However, deciphering these dynamics, particularly founding population sizes in host organs and patterns of dissemination between organs, is difficult because measuring bacterial burden alone is insufficient to observe these patterns. Introduction of allelic diversity into otherwise identical bacteria using DNA barcodes enables sequencing-based measurements of these parameters, in a method known as STAMP (Sequence Tag-based Analysis of Microbial Populations). However, bacteria often undergo unequal expansion within host organs, resulting in marked differences in the frequencies of barcodes in input and output libraries. Here, we show that these differences confound STAMP-based analyses of founding population sizes and dissemination patterns. We present STAMPR, a successor to STAMP, which accounts for such population expansions. Using data from systemic infection of barcoded extraintestinal pathogenic E. coli, we show that this new framework, along with the metrics it yields, enhances the fidelity of measurements of bottlenecks and dissemination patterns. STAMPR was also validated on an independent barcoded Pseudomonas aeruginosa data set, uncovering new patterns of dissemination within the data. This framework (available at https://github.com/hullahalli/stampr_rtisan), when coupled with barcoded data sets, enables a more complete assessment of within-host bacterial population dynamics. IMPORTANCE Barcoded bacteria are often employed to monitor pathogen population dynamics during infection. The accuracy of these measurements is diminished by unequal bacterial expansion rates. Here, we develop computational tools to circumvent this limitation and establish additional metrics that collectively enhance the fidelity of measuring within-host pathogen founding population sizes and dissemination patterns. These new tools will benefit future studies of the dynamics of pathogens and symbionts within their respective hosts and may have additional barcode-based applications beyond host-microbe interactions.
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23
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Farquhar KS, Rasouli Koohi S, Charlebois DA. Does transcriptional heterogeneity facilitate the development of genetic drug resistance? Bioessays 2021; 43:e2100043. [PMID: 34160842 DOI: 10.1002/bies.202100043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 05/30/2021] [Accepted: 06/07/2021] [Indexed: 12/24/2022]
Abstract
Non-genetic forms of antimicrobial (drug) resistance can result from cell-to-cell variability that is not encoded in the genetic material. Data from recent studies also suggest that non-genetic mechanisms can facilitate the development of genetic drug resistance. We speculate on how the interplay between non-genetic and genetic mechanisms may affect microbial adaptation and evolution during drug treatment. We argue that cellular heterogeneity arising from fluctuations in gene expression, epigenetic modifications, as well as genetic changes contribute to drug resistance at different timescales, and that the interplay between these mechanisms enhance pathogen resistance. Accordingly, developing a better understanding of the role of non-genetic mechanisms in drug resistance and how they interact with genetic mechanisms will enhance our ability to combat antimicrobial resistance. Also see the video abstract here: https://youtu.be/aefGpdh-bgU.
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Affiliation(s)
| | - Samira Rasouli Koohi
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G-2E1, Canada
| | - Daniel A Charlebois
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G-2E1, Canada.,Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
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24
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Kirby MB, Medina-Cucurella AV, Baumer ZT, Whitehead TA. Optimization of multi-site nicking mutagenesis for generation of large, user-defined combinatorial libraries. Protein Eng Des Sel 2021; 34:gzab017. [PMID: 34341824 PMCID: PMC8502461 DOI: 10.1093/protein/gzab017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 06/09/2021] [Accepted: 06/17/2021] [Indexed: 11/13/2022] Open
Abstract
Generating combinatorial libraries of specific sets of mutations are essential for addressing protein engineering questions involving contingency in molecular evolution, epistatic relationships between mutations, as well as functional antibody and enzyme engineering. Here we present optimization of a combinatorial mutagenesis method involving template-based nicking mutagenesis, which allows for the generation of libraries with >99% coverage for tens of thousands of user-defined variants. The non-optimized method resulted in low library coverage, which could be rationalized by a model of oligonucleotide annealing bias resulting from the nucleotide mismatch free-energy difference between mutagenic oligo and template. The optimized method mitigated this thermodynamic bias using longer primer sets and faster annealing conditions. Our updated method, applied to two antibody fragments, delivered between 99.0% (32451/32768 library members) to >99.9% coverage (32757/32768) for our desired libraries in 2 days and at an approximate 140-fold sequencing depth of coverage.
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Affiliation(s)
- Monica B Kirby
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80305, USA
| | - Angélica V Medina-Cucurella
- Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI 48824, USA
- GigaGen Inc., South San Francisco, CA 94080, USA
| | - Zachary T Baumer
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80305, USA
| | - Timothy A Whitehead
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80305, USA
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25
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Kasimatis KR, Sánchez-Ramírez S, Stevenson ZC. Sexual Dimorphism through the Lens of Genome Manipulation, Forward Genetics, and Spatiotemporal Sequencing. Genome Biol Evol 2021; 13:evaa243. [PMID: 33587127 PMCID: PMC7883666 DOI: 10.1093/gbe/evaa243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/15/2020] [Indexed: 11/14/2022] Open
Abstract
Sexual reproduction often leads to selection that favors the evolution of sex-limited traits or sex-specific variation for shared traits. These sexual dimorphisms manifest due to sex-specific genetic architectures and sex-biased gene expression across development, yet the molecular mechanisms underlying these patterns are largely unknown. The first step is to understand how sexual dimorphisms arise across the genotype-phenotype-fitness map. The emergence of "4D genome technologies" allows for efficient, high-throughput, and cost-effective manipulation and observations of this process. Studies of sexual dimorphism will benefit from combining these technological advances (e.g., precision genome editing, inducible transgenic systems, and single-cell RNA sequencing) with clever experiments inspired by classic designs (e.g., bulked segregant analysis, experimental evolution, and pedigree tracing). This perspective poses a synthetic view of how manipulative approaches coupled with cutting-edge observational methods and evolutionary theory are poised to uncover the molecular genetic basis of sexual dimorphism with unprecedented resolution. We outline hypothesis-driven experimental paradigms for identifying genetic mechanisms of sexual dimorphism among tissues, across development, and over evolutionary time.
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Affiliation(s)
- Katja R Kasimatis
- Department of Ecology and Evolutionary Biology, University of Toronto, Ontario, USA
| | | | - Zachary C Stevenson
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA
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26
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Multiplexed Competition in a Synthetic Squid Light Organ Microbiome Using Barcode-Tagged Gene Deletions. mSystems 2020; 5:5/6/e00846-20. [PMID: 33323415 PMCID: PMC7771539 DOI: 10.1128/msystems.00846-20] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Beneficial microbes play essential roles in the health and development of their hosts. However, the complexity of animal microbiomes and general genetic intractability of their symbionts have made it difficult to study the coevolved mechanisms for establishing and maintaining specificity at the microbe-animal host interface. Beneficial symbioses between microbes and their eukaryotic hosts are ubiquitous and have widespread impacts on host health and development. The binary symbiosis between the bioluminescent bacterium Vibrio fischeri and its squid host Euprymna scolopes serves as a model system to study molecular mechanisms at the microbe-animal interface. To identify colonization factors in this system, our lab previously conducted a global transposon insertion sequencing (INSeq) screen and identified over 300 putative novel squid colonization factors in V. fischeri. To pursue mechanistic studies on these candidate genes, we present an approach to quickly generate barcode-tagged gene deletions and perform high-throughput squid competition experiments with detection of the proportion of each strain in the mixture by barcode sequencing (BarSeq). Our deletion approach improves on previous techniques based on splicing by overlap extension PCR (SOE-PCR) and tfoX-based natural transformation by incorporating a randomized barcode that results in unique DNA sequences within each deletion scar. Amplicon sequencing of the pool of barcoded strains before and after colonization faithfully reports on known colonization factors and provides increased sensitivity over colony counting methods. BarSeq enables rapid and sensitive characterization of the molecular factors involved in establishing the Vibrio-squid symbiosis and provides a valuable tool to interrogate the molecular dialogue at microbe-animal host interfaces. IMPORTANCE Beneficial microbes play essential roles in the health and development of their hosts. However, the complexity of animal microbiomes and general genetic intractability of their symbionts have made it difficult to study the coevolved mechanisms for establishing and maintaining specificity at the microbe-animal host interface. Model symbioses are therefore invaluable for studying the mechanisms of beneficial microbe-host interactions. Here, we present a combined barcode-tagged deletion and BarSeq approach to interrogate the molecular dialogue that ensures specific and reproducible colonization of the Hawaiian bobtail squid by Vibrio fischeri. The ability to precisely manipulate the bacterial genome, combined with multiplex colonization assays, will accelerate the use of this valuable model system for mechanistic studies of how environmental microbes—both beneficial and pathogenic—colonize specific animal hosts.
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27
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van Dijk B. Can mobile genetic elements rescue genes from extinction? Curr Genet 2020; 66:1069-1071. [PMID: 32880674 PMCID: PMC7599165 DOI: 10.1007/s00294-020-01104-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 08/19/2020] [Accepted: 08/24/2020] [Indexed: 01/04/2023]
Abstract
Bacteria and other prokaryotes evolve primarily through rapid changes in their gene content by quickly losing and gaining genes whenever an ecological opportunity emerges. As gene loss and horizontal gene transfer (HGT) appear to be the most common events across the prokaryotic tree of life, we need to think beyond gradual sequence evolution if we wish to understand the microbial world. Especially genes that reside on mobile genetic elements (MGEs) may spread much more rapidly through a microbial population than genes that reside on the bacterial chromosome. This raises the question: why are some genes associated with MGEs, while others are not? Here, I briefly review a recently proposed class of genes for which we have coined the term "rescuable genes". The fitness effect of carrying these genes is so small, either constantly or on average, that they are prone to be lost from a microbial population. I argue that HGT, even when costly to the individual cells, may play an important role in maintaining these rescuable genes in microbial communities.
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Affiliation(s)
- Bram van Dijk
- Max Planck Institute for Evolutionary Biology, Plön, Germany.
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28
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Fasanello VJ, Liu P, Botero CA, Fay JC. High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae. PeerJ 2020; 8:e10118. [PMID: 33088623 PMCID: PMC7571412 DOI: 10.7717/peerj.10118] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 09/16/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Experimental evolution of microbes can be used to empirically address a wide range of questions about evolution and is increasingly employed to study complex phenomena ranging from genetic evolution to evolutionary rescue. Regardless of experimental aims, fitness assays are a central component of this type of research, and low-throughput often limits the scope and complexity of experimental evolution studies. We created an experimental evolution system in Saccharomyces cerevisiae that utilizes genetic barcoding to overcome this challenge. RESULTS We first confirm that barcode insertions do not alter fitness and that barcode sequencing can be used to efficiently detect fitness differences via pooled competition-based fitness assays. Next, we examine the effects of ploidy, chemical stress, and population bottleneck size on the evolutionary dynamics and fitness gains (adaptation) in a total of 76 experimentally evolving, asexual populations by conducting 1,216 fitness assays and analyzing 532 longitudinal-evolutionary samples collected from the evolving populations. In our analysis of these data we describe the strengths of this experimental evolution system and explore sources of error in our measurements of fitness and evolutionary dynamics. CONCLUSIONS Our experimental treatments generated distinct fitness effects and evolutionary dynamics, respectively quantified via multiplexed fitness assays and barcode lineage tracking. These findings demonstrate the utility of this new resource for designing and improving high-throughput studies of experimental evolution. The approach described here provides a framework for future studies employing experimental designs that require high-throughput multiplexed fitness measurements.
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Affiliation(s)
- Vincent J. Fasanello
- Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, MO, United States of America
| | - Ping Liu
- Department of Genetics, Washington University in St. Louis, St. Louis, MO, United States of America
| | - Carlos A. Botero
- Department of Biology, Washington University in St. Louis, St. Louis, MO, United States of America
| | - Justin C. Fay
- Department of Genetics, Washington University in St. Louis, St. Louis, MO, United States of America
- Department of Biology, University of Rochester, Rochester, NY, United States of America
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29
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Meijer J, van Dijk B, Hogeweg P. Contingent evolution of alternative metabolic network topologies determines whether cross-feeding evolves. Commun Biol 2020; 3:401. [PMID: 32728180 PMCID: PMC7391776 DOI: 10.1038/s42003-020-1107-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 06/19/2020] [Indexed: 12/13/2022] Open
Abstract
Metabolic exchange is widespread in natural microbial communities and an important driver of ecosystem structure and diversity, yet it remains unclear what determines whether microbes evolve division of labor or maintain metabolic autonomy. Here we use a mechanistic model to study how metabolic strategies evolve in a constant, one resource environment, when metabolic networks are allowed to freely evolve. We find that initially identical ancestral communities of digital organisms follow different evolutionary trajectories, as some communities become dominated by a single, autonomous lineage, while others are formed by stably coexisting lineages that cross-feed on essential building blocks. Our results show how without presupposed cellular trade-offs or external drivers such as temporal niches, diverse metabolic strategies spontaneously emerge from the interplay between ecology, spatial structure, and metabolic constraints that arise during the evolution of metabolic networks. Thus, in the long term, whether microbes remain autonomous or evolve metabolic division of labour is an evolutionary contingency.
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Affiliation(s)
- Jeroen Meijer
- Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands.
| | - Bram van Dijk
- Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Paulien Hogeweg
- Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
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30
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van Dijk B, Hogeweg P, Doekes HM, Takeuchi N. Slightly beneficial genes are retained by bacteria evolving DNA uptake despite selfish elements. eLife 2020; 9:e56801. [PMID: 32432548 PMCID: PMC7316506 DOI: 10.7554/elife.56801] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 05/15/2020] [Indexed: 12/11/2022] Open
Abstract
Horizontal gene transfer (HGT) and gene loss result in rapid changes in the gene content of bacteria. While HGT aids bacteria to adapt to new environments, it also carries risks such as selfish genetic elements (SGEs). Here, we use modelling to study how HGT of slightly beneficial genes impacts growth rates of bacterial populations, and if bacterial collectives can evolve to take up DNA despite selfish elements. We find four classes of slightly beneficial genes: indispensable, enrichable, rescuable, and unrescuable genes. Rescuable genes - genes with small fitness benefits that are lost from the population without HGT - can be collectively retained by a community that engages in costly HGT. While this 'gene-sharing' cannot evolve in well-mixed cultures, it does evolve in a spatial population like a biofilm. Despite enabling infection by harmful SGEs, the uptake of foreign DNA is evolutionarily maintained by the hosts, explaining the coexistence of bacteria and SGEs.
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Affiliation(s)
- Bram van Dijk
- Utrecht University, Theoretical BiologyUtrechtNetherlands
| | | | - Hilje M Doekes
- Utrecht University, Theoretical BiologyUtrechtNetherlands
| | - Nobuto Takeuchi
- University of Auckland, Biological SciencesAucklandNew Zealand
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31
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Abstract
Diversity indices are useful single-number metrics for characterizing a complex distribution of a set of attributes across a population of interest. The utility of these different metrics or sets of metrics depends on the context and application, and whether a predictive mechanistic model exists. In this topical review, we first summarize the relevant mathematical principles underlying heterogeneity in a large population, before outlining the various definitions of 'diversity' and providing examples of scientific topics in which its quantification plays an important role. We then review how diversity has been a ubiquitous concept across multiple fields, including ecology, immunology, cellular barcoding experiments, and socioeconomic studies. Since many of these applications involve sampling of populations, we also review how diversity in small samples is related to the diversity in the entire population. Features that arise in each of these applications are highlighted.
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Affiliation(s)
- Song Xu
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, United States of America
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Chromosomal barcoding of E. coli populations reveals lineage diversity dynamics at high resolution. Nat Ecol Evol 2020; 4:437-452. [PMID: 32094541 DOI: 10.1038/s41559-020-1103-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 01/08/2020] [Indexed: 01/28/2023]
Abstract
Evolutionary dynamics in large asexual populations is strongly influenced by multiple competing beneficial lineages, most of which segregate at very low frequencies. However, technical barriers to tracking a large number of these rare lineages in bacterial populations have so far prevented a detailed elucidation of evolutionary dynamics. Here, we overcome this hurdle by developing a chromosomal-barcoding technique that allows simultaneous tracking of approximately 450,000 distinct lineages in Escherichia coli, which we use to test the effect of sub-inhibitory concentrations of common antibiotics on the evolutionary dynamics of low-frequency lineages. We find that populations lose lineage diversity at distinct rates that correspond to their antibiotic regimen. We also determine that some lineages have similar fates across independent experiments. By analysing the trajectory dynamics, we attribute the reproducible fates of these lineages to the presence of pre-existing beneficial mutations, and we demonstrate how the relative contribution of pre-existing and de novo mutations varies across drug regimens. Finally, we reproduce the observed lineage dynamics by simulations. Altogether, our results provide a valuable methodology for studying bacterial evolution as well as insights into evolution under sub-inhibitory antibiotic levels.
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Roh V, Abramowski P, Hiou-Feige A, Cornils K, Rivals JP, Zougman A, Aranyossy T, Thielecke L, Truan Z, Mermod M, Monnier Y, Prassolov V, Glauche I, Nowrouzi A, Abdollahi A, Fehse B, Simon C, Tolstonog GV. Cellular Barcoding Identifies Clonal Substitution as a Hallmark of Local Recurrence in a Surgical Model of Head and Neck Squamous Cell Carcinoma. Cell Rep 2019; 25:2208-2222.e7. [PMID: 30463016 DOI: 10.1016/j.celrep.2018.10.090] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Revised: 09/04/2018] [Accepted: 10/24/2018] [Indexed: 01/04/2023] Open
Abstract
Local recurrence after surgery for head and neck squamous cell carcinoma (HNSCC) remains a common event associated with a dismal prognosis. Improving this outcome requires a better understanding of cancer cell populations that expand from postsurgical minimal residual disease (MRD). Therefore, we assessed clonal dynamics in a surgical model of barcoded HNSCC growing in the submental region of immunodeficient mice. Clonal substitution and massive reduction of clonal heterogeneity emerged as hallmarks of local recurrence, as the clones dominating in less heterogeneous recurrences were scarce in their matched primary tumors. These lineages were selected by their ability to persist after surgery and competitively expand from MRD. Clones enriched in recurrences exhibited both private and shared genetic features and likely originated from ancestors shared with clones dominating in primary tumors. They demonstrated high invasiveness and epithelial-to-mesenchymal transition, eventually providing an attractive target for obtaining better local control for these tumors.
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Affiliation(s)
- Vincent Roh
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pierre Abramowski
- Research Department Cell and Gene Therapy, Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Agnès Hiou-Feige
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland
| | - Kerstin Cornils
- Research Department Cell and Gene Therapy, Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Jean-Paul Rivals
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland
| | - Alexandre Zougman
- Clinical and Biomedical Proteomics Group, Cancer Research UK Centre, Leeds Institute of Cancer and Pathology, St. James's University Hospital, Leeds, UK
| | - Tim Aranyossy
- Research Department Cell and Gene Therapy, Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Lars Thielecke
- Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustave Carus, Technische Universität Dresden, Dresden, Germany
| | - Zinnia Truan
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland
| | - Maxime Mermod
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland
| | - Yan Monnier
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland
| | - Vladimir Prassolov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
| | - Ingmar Glauche
- Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustave Carus, Technische Universität Dresden, Dresden, Germany
| | - Ali Nowrouzi
- German Cancer Consortium (DKTK), Translational Radiation Oncology, German Cancer Research Center (DKFZ), Core Center Heidelberg, Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg University Hospital (UKHD) and DKFZ, Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
| | - Amir Abdollahi
- German Cancer Consortium (DKTK), Translational Radiation Oncology, German Cancer Research Center (DKFZ), Core Center Heidelberg, Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg University Hospital (UKHD) and DKFZ, Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
| | - Boris Fehse
- Research Department Cell and Gene Therapy, Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
| | - Christian Simon
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland.
| | - Genrich V Tolstonog
- Department of Otolaryngology - Head and Neck Surgery, University Hospital of Lausanne, Lausanne, Switzerland.
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Emerging Concepts and Tools in Cell Mechanomemory. Ann Biomed Eng 2019; 48:2103-2112. [DOI: 10.1007/s10439-019-02412-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Accepted: 11/11/2019] [Indexed: 12/25/2022]
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35
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Nguyen Ba AN, Cvijović I, Rojas Echenique JI, Lawrence KR, Rego-Costa A, Liu X, Levy SF, Desai MM. High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast. Nature 2019; 575:494-499. [PMID: 31723263 PMCID: PMC6938260 DOI: 10.1038/s41586-019-1749-3] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 10/04/2019] [Indexed: 11/09/2022]
Abstract
In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population1-5. These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. Previous studies have used whole-genome sequencing to follow molecular adaptation6-10; however, these methods have limited resolution in microbial populations. Here we introduce a renewable barcoding system to observe evolutionary dynamics at high resolution in laboratory budding yeast. We find nested patterns of interference and hitchhiking even at low frequencies. These events are driven by the continuous appearance of new mutations that modify the fates of existing lineages before they reach substantial frequencies. We observe how the distribution of fitness within the population changes over time, and find a travelling wave of adaptation that has been predicted by theory11-17. We show that clonal competition creates a dynamical 'rich-get-richer' effect: fitness advantages that are acquired early in evolution drive clonal expansions, which increase the chances of acquiring future mutations. However, less-fit lineages also routinely leapfrog over strains of higher fitness. Our results demonstrate that this combination of factors, which is not accounted for in existing models of evolutionary dynamics, is critical in determining the rate, predictability and molecular basis of adaptation.
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Affiliation(s)
- Alex N Nguyen Ba
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Ivana Cvijović
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.,Graduate Program in Systems Biology, Harvard University, Cambridge, MA, USA.,NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, MA, USA.,Quantitative Biology Initiative, Harvard University, Cambridge, MA, USA
| | - José I Rojas Echenique
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Katherine R Lawrence
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.,Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Artur Rego-Costa
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Xianan Liu
- Joint Initiative for Metrology in Biology, SLAC National Accelerator Laboratory, Stanford University, Stanford, CA, USA.,Laufer Center for Physical and Quantitative Biology, Department of Biochemistry, Stony Brook University, Stony Brook, NY, USA
| | - Sasha F Levy
- Joint Initiative for Metrology in Biology, SLAC National Accelerator Laboratory, Stanford University, Stanford, CA, USA.,Laufer Center for Physical and Quantitative Biology, Department of Biochemistry, Stony Brook University, Stony Brook, NY, USA
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA. .,NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, MA, USA. .,Quantitative Biology Initiative, Harvard University, Cambridge, MA, USA. .,Department of Physics, Harvard University, Cambridge, MA, USA.
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36
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van Dijk B, Meijer J, Cuypers TD, Hogeweg P. Trusting the hand that feeds: microbes evolve to anticipate a serial transfer protocol as individuals or collectives. BMC Evol Biol 2019; 19:201. [PMID: 31684861 PMCID: PMC6829849 DOI: 10.1186/s12862-019-1512-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 09/12/2019] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Experimental evolution of microbes often involves a serial transfer protocol, where microbes are repeatedly diluted by transfer to a fresh medium, starting a new growth cycle. This has revealed that evolution can be remarkably reproducible, where microbes show parallel adaptations both on the level of the phenotype as well as the genotype. However, these studies also reveal a strong potential for divergent evolution, leading to diversity both between and within replicate populations. We here study how in silico evolved Virtual Microbe "wild types" (WTs) adapt to a serial transfer protocol to investigate generic evolutionary adaptations, and how these adaptations can be manifested by a variety of different mechanisms. RESULTS We show that all WTs evolve to anticipate the regularity of the serial transfer protocol by adopting a fine-tuned balance of growth and survival. This anticipation is done by evolving either a high yield mode, or a high growth rate mode. We find that both modes of anticipation can be achieved by individual lineages and by collectives of microbes. Moreover, these different outcomes can be achieved with or without regulation, although the individual-based anticipation without regulation is less well adapted in the high growth rate mode. CONCLUSIONS All our in silico WTs evolve to trust the hand that feeds by evolving to anticipate the periodicity of a serial transfer protocol, but can do so by evolving two distinct growth strategies. Furthermore, both these growth strategies can be accomplished by gene regulation, a variety of different polymorphisms, and combinations thereof. Our work reveals that, even under controlled conditions like those in the lab, it may not be possible to predict individual evolutionary trajectories, but repeated experiments may well result in only a limited number of possible outcomes.
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Affiliation(s)
- Bram van Dijk
- Theoretical Biology, Utrecht University, Padualaan 8, Utrecht, The Netherlands
| | - Jeroen Meijer
- Theoretical Biology, Utrecht University, Padualaan 8, Utrecht, The Netherlands
| | - Thomas D. Cuypers
- Theoretical Biology, Utrecht University, Padualaan 8, Utrecht, The Netherlands
| | - Paulien Hogeweg
- Theoretical Biology, Utrecht University, Padualaan 8, Utrecht, The Netherlands
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37
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Macklin P. Key challenges facing data-driven multicellular systems biology. Gigascience 2019; 8:giz127. [PMID: 31648301 PMCID: PMC6812467 DOI: 10.1093/gigascience/giz127] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Revised: 09/27/2019] [Accepted: 09/30/2019] [Indexed: 12/17/2022] Open
Abstract
Increasingly sophisticated experiments, coupled with large-scale computational models, have the potential to systematically test biological hypotheses to drive our understanding of multicellular systems. In this short review, we explore key challenges that must be overcome to achieve robust, repeatable data-driven multicellular systems biology. If these challenges can be solved, we can grow beyond the current state of isolated tools and datasets to a community-driven ecosystem of interoperable data, software utilities, and computational modeling platforms. Progress is within our grasp, but it will take community (and financial) commitment.
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Affiliation(s)
- Paul Macklin
- Department of Intelligent Systems Engineering, Indiana University, 700 N Woodlawn Ave, Bloomington, IN 47408, USA
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38
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39
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Peitzsch C, Kurth I, Ebert N, Dubrovska A, Baumann M. Cancer stem cells in radiation response: current views and future perspectives in radiation oncology. Int J Radiat Biol 2019; 95:900-911. [PMID: 30897014 DOI: 10.1080/09553002.2019.1589023] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Purpose: Despite technological improvement and advances in biology-driven patient stratification, many patients still fail radiotherapy resulting in loco-regional and distant recurrence. Tumor heterogeneity remains a key challenge to effective cancer treatment, and reliable stratification of cancer patients for prediction of outcomes is highly important. Intratumoral heterogeneity is manifested at the different levels, including different tumorigenic properties of cancer cells. Since John Dick et al. isolated leukemia initiating cells in 1990, the populations of tumor initiating or cancer stem cells (CSCs) were identified and characterized also for a broad spectrum of solid tumor types. The properties of CSCs are of considerable clinical relevance: CSCs have self-renewal and tumor initiating potential, and the metastases are initiated by the CSC clones with the ability to disseminate from the primary tumor site. Conclusion: Evidence from both, experimental and clinical studies demonstrates that the probability of achieving local tumor control by radiation therapy depends on the complete eradication of CSC populations. The number, properties and molecular signature of CSCs are highly predictive for clinical outcome of radiotherapy, whereas targeted therapies against CSCs combined with conventional treatment are expected to provide an improved clinical response and prevent tumor relapse. In this review, we discuss the modern methods to study CSCs in radiation biology, the role of CSCs in personalized cancer therapy as well as future directions for CSC research in translational radiooncology.
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Affiliation(s)
- Claudia Peitzsch
- a OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf , Dresden , Germany.,b National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and; Helmholtz-Zentrum Dresden - Rossendorf (HZDR) , Dresden , Germany.,c German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) , Heidelberg , Germany
| | - Ina Kurth
- d German Cancer Research Center (DKFZ) , Heidelberg , Germany
| | - Nadja Ebert
- d German Cancer Research Center (DKFZ) , Heidelberg , Germany.,f Department of Radiotherapy and Radiation Oncology , Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden , Dresden , Germany
| | - Anna Dubrovska
- a OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf , Dresden , Germany.,c German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) , Heidelberg , Germany.,e Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay , Dresden , Germany
| | - Michael Baumann
- d German Cancer Research Center (DKFZ) , Heidelberg , Germany.,f Department of Radiotherapy and Radiation Oncology , Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden , Dresden , Germany
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40
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Gauthier L, Di Franco R, Serohijos AWR. SodaPop: a forward simulation suite for the evolutionary dynamics of asexual populations on protein fitness landscapes. Bioinformatics 2019; 35:4053-4062. [DOI: 10.1093/bioinformatics/btz175] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 01/21/2019] [Accepted: 03/12/2019] [Indexed: 11/14/2022] Open
Abstract
Abstract
Motivation
Protein evolution is determined by forces at multiple levels of biological organization. Random mutations have an immediate effect on the biophysical properties, structure and function of proteins. These same mutations also affect the fitness of the organism. However, the evolutionary fate of mutations, whether they succeed to fixation or are purged, also depends on population size and dynamics. There is an emerging interest, both theoretically and experimentally, to integrate these two factors in protein evolution. Although there are several tools available for simulating protein evolution, most of them focus on either the biophysical or the population-level determinants, but not both. Hence, there is a need for a publicly available computational tool to explore both the effects of protein biophysics and population dynamics on protein evolution.
Results
To address this need, we developed SodaPop, a computational suite to simulate protein evolution in the context of the population dynamics of asexual populations. SodaPop accepts as input several fitness landscapes based on protein biochemistry or other user-defined fitness functions. The user can also provide as input experimental fitness landscapes derived from deep mutational scanning approaches or theoretical landscapes derived from physical force field estimates. Here, we demonstrate the broad utility of SodaPop with different applications describing the interplay of selection for protein properties and population dynamics. SodaPop is designed such that population geneticists can explore the influence of protein biochemistry on patterns of genetic variation, and that biochemists and biophysicists can explore the role of population size and demography on protein evolution.
Availability and implementation
Source code and binaries are freely available at https://github.com/louisgt/SodaPop under the GNU GPLv3 license. The software is implemented in C++ and supported on Linux, Mac OS/X and Windows.
Supplementary information
Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Louis Gauthier
- Département de Biochimie, Université de Montréal, Montréal, QC, Canada
- Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, Montréal, QC, Canada
| | - Rémicia Di Franco
- Département de Biochimie, Université de Montréal, Montréal, QC, Canada
- Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, Montréal, QC, Canada
- Enseirb-Matmeca, Bordeaux Institute of Technology, Talence, France
| | - Adrian W R Serohijos
- Département de Biochimie, Université de Montréal, Montréal, QC, Canada
- Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, Montréal, QC, Canada
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41
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Binan L, Drobetsky EA, Costantino S. Exploiting Molecular Barcodes in High-Throughput Cellular Assays. SLAS Technol 2019; 24:298-307. [PMID: 30707854 DOI: 10.1177/2472630318824337] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Multiplexing strategies, which greatly increase the number of simultaneously measured parameters in single experiments, are now being widely implemented by both the pharmaceutical industry and academic researchers. Color has long been used to identify biological signals and, when combined with molecular barcodes, has substantially enhanced the depth of multiplexed sample characterization. Moreover, the recent advent of DNA barcodes has led to an explosion of innovative cell sequencing approaches. Novel barcoding strategies also show great promise for encoding spatial information in transcriptomic studies, and for precise assessment of molecular abundance. Both color- and DNA-based barcodes can be conveniently analyzed with either a microscope or a cytometer, or via DNA sequencing. Here we review the basic principles of several technologies used to create barcodes and detail the type of samples that can be identified with such tags.
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Affiliation(s)
- Loïc Binan
- 1 Research Center of the Maisonneuve-Rosemont Hospital, Montreal, QC, Canada.,2 Department of Ophthalmology, Université de Montréal, Montreal, QC, Canada
| | - Elliot A Drobetsky
- 1 Research Center of the Maisonneuve-Rosemont Hospital, Montreal, QC, Canada.,3 Department of Medicine & Molecular Biology Program, University of Montreal, Montreal, QC, Canada
| | - Santiago Costantino
- 1 Research Center of the Maisonneuve-Rosemont Hospital, Montreal, QC, Canada.,2 Department of Ophthalmology, Université de Montréal, Montreal, QC, Canada
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42
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Swamy KBS, Zhou N. Experimental evolution: its principles and applications in developing stress-tolerant yeasts. Appl Microbiol Biotechnol 2019; 103:2067-2077. [PMID: 30659332 DOI: 10.1007/s00253-019-09616-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 01/03/2019] [Accepted: 01/03/2019] [Indexed: 10/27/2022]
Abstract
Stress tolerance and resistance in industrial yeast strains are important attributes for cost-effective bioprocessing. The source of stress-tolerant yeasts ranges from extremophilic environments to laboratory engineered strains. However, industrial stress-tolerant yeasts are very rare in nature as the natural environment forces them to evolve traits that optimize survival and reproduction and not the ability to withstand harsh habitat-irrelevant industrial conditions. Experimental evolution is a frequent method used to uncover the mechanisms of evolution and microbial adaption towards environmental stresses. It optimizes biological systems by means of adaptation to environmental stresses and thus has immense power of development of robust stress-tolerant yeasts. This mini-review briefly outlines the basics and implications of evolution experiments and their applications to industrial biotechnology. This work is meant to serve as an introduction to those new to the field of experimental evolution, and as a guide to biologists working in the field of yeast stress response. Future perspectives of experimental evolution for potential biotechnological applications have also been elucidated.
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Affiliation(s)
| | - Nerve Zhou
- Department of Biological Sciences and Biotechnology, Botswana International University of Science and Technology, P Bag 16, Palapye, Botswana
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43
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Zhao L, Liu Z, Levy SF, Wu S. Bartender: a fast and accurate clustering algorithm to count barcode reads. Bioinformatics 2018; 34:739-747. [PMID: 29069318 DOI: 10.1093/bioinformatics/btx655] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 10/18/2017] [Indexed: 11/14/2022] Open
Abstract
Motivation Barcode sequencing (bar-seq) is a high-throughput, and cost effective method to assay large numbers of cell lineages or genotypes in complex cell pools. Because of its advantages, applications for bar-seq are quickly growing-from using neutral random barcodes to study the evolution of microbes or cancer, to using pseudo-barcodes, such as shRNAs or sgRNAs to simultaneously screen large numbers of cell perturbations. However, the computational pipelines for bar-seq clustering are not well developed. Available methods often yield a high frequency of under-clustering artifacts that result in spurious barcodes, or over-clustering artifacts that group distinct barcodes together. Here, we developed Bartender, an accurate clustering algorithm to detect barcodes and their abundances from raw next-generation sequencing data. Results In contrast with existing methods that cluster based on sequence similarity alone, Bartender uses a modified two-sample proportion test that also considers cluster size. This modification results in higher accuracy and lower rates of under- and over-clustering artifacts. Additionally, Bartender includes unique molecular identifier handling and a 'multiple time point' mode that matches barcode clusters between different clustering runs for seamless handling of time course data. Bartender is a set of simple-to-use command line tools that can be performed on a laptop at comparable run times to existing methods. Availability and implementation Bartender is available at no charge for non-commercial use at https://github.com/LaoZZZZZ/bartender-1.1. Contact sasha.levy@stonybrook.edu or song.wu@stonybrook.edu. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Lu Zhao
- Department of Applied Mathematics and Statistics
| | - Zhimin Liu
- Laufer Center for Physical and Quantitative Biology.,Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Sasha F Levy
- Laufer Center for Physical and Quantitative Biology.,Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Song Wu
- Department of Applied Mathematics and Statistics
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44
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Al’Khafaji AM, Deatherage D, Brock A. Control of Lineage-Specific Gene Expression by Functionalized gRNA Barcodes. ACS Synth Biol 2018; 7:2468-2474. [PMID: 30169961 PMCID: PMC6661167 DOI: 10.1021/acssynbio.8b00105] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Lineage tracking delivers essential quantitative insight into dynamic, probabilistic cellular processes, such as somatic tumor evolution and differentiation. Methods for high diversity lineage quantitation rely on sequencing a population of DNA barcodes. However, manipulation of specific individual lineages is not possible with this approach. To address this challenge, we developed a functionalized lineage tracing tool, Control of Lineages by Barcode Enabled Recombinant Transcription (COLBERT), that enables high diversity lineage tracing and lineage-specific manipulation of gene expression. This modular platform utilizes expressed barcode gRNAs to both track cell lineages and direct lineage-specific gene expression.
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Affiliation(s)
- Aziz M. Al’Khafaji
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Daniel Deatherage
- Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Amy Brock
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas 78712, United States
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45
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A decade of genome sequencing has revolutionized studies of experimental evolution. Curr Opin Microbiol 2018; 45:149-155. [DOI: 10.1016/j.mib.2018.03.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Revised: 03/02/2018] [Accepted: 03/07/2018] [Indexed: 11/20/2022]
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46
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Cvijović I, Nguyen Ba AN, Desai MM. Experimental Studies of Evolutionary Dynamics in Microbes. Trends Genet 2018; 34:693-703. [PMID: 30025666 PMCID: PMC6467257 DOI: 10.1016/j.tig.2018.06.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 06/18/2018] [Accepted: 06/22/2018] [Indexed: 11/16/2022]
Abstract
Evolutionary dynamics in laboratory microbial evolution experiments can be surprisingly complex. In the past two decades, observations of these dynamics have challenged simple models of adaptation and have shown that clonal interference, hitchhiking, ecological diversification, and contingency are widespread. In recent years, advances in high-throughput strain maintenance and phenotypic assays, the dramatically reduced cost of genome sequencing, and emerging methods for lineage barcoding have made it possible to observe evolutionary dynamics at unprecedented resolution. These new methods can now begin to provide detailed measurements of key aspects of fitness landscapes and of evolutionary outcomes across a range of systems. These measurements can highlight challenges to existing theoretical models and guide new theoretical work towards the complications that are most widely important.
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Affiliation(s)
- Ivana Cvijović
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA
| | - Alex N Nguyen Ba
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA.
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47
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Chromosomal barcoding as a tool for multiplexed phenotypic characterization of laboratory evolved lineages. Sci Rep 2018; 8:6961. [PMID: 29725068 PMCID: PMC5934437 DOI: 10.1038/s41598-018-25201-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Accepted: 04/04/2018] [Indexed: 11/15/2022] Open
Abstract
Adaptive laboratory evolution is an important tool to evolve organisms to increased tolerance towards different physical and chemical stress. It is applied to study the evolution of antibiotic resistance as well as genetic mechanisms underlying improvements in production strains. Adaptive evolution experiments can be automated in a high-throughput fashion. However, the characterization of the resulting lineages can become a time consuming task, when the performance of each lineage is evaluated individually. Here, we present a novel method for the markerless insertion of randomized genetic barcodes into the genome of Escherichia coli using a novel dual-auxotrophic selection approach. The barcoded E. coli library allows multiplexed phenotyping of evolved strains in pooled competition experiments. We use the barcoded library in an adaptive evolution experiment; evolving resistance towards three common antibiotics. Comparing this multiplexed phenotyping with conventional susceptibility testing and growth-rate measurements we can show a significant positive correlation between the two approaches. Use of barcoded bacterial strain libraries for individual adaptive evolution experiments drastically reduces the workload of characterizing the resulting phenotypes and enables prioritization of lineages for in-depth characterization. In addition, barcoded clones open up new ways to profile community dynamics or to track lineages in vivo or situ.
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48
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Hewett DR, Vandyke K, Lawrence DM, Friend N, Noll JE, Geoghegan JM, Croucher PI, Zannettino ACW. DNA Barcoding Reveals Habitual Clonal Dominance of Myeloma Plasma Cells in the Bone Marrow Microenvironment. Neoplasia 2017; 19:972-981. [PMID: 29091798 PMCID: PMC5678743 DOI: 10.1016/j.neo.2017.09.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 09/30/2017] [Indexed: 02/07/2023] Open
Abstract
Multiple myeloma (MM) is a hematological malignancy resulting from the uncontrolled proliferation of antibody-producing plasma cells in the bone marrow. At diagnosis, independent plasma cell tumors are found throughout the skeleton. The recirculation of mutant plasma cells from the initial lesion and their recolonization of distant marrow sites are thought to occur by a process similar to solid tumor metastasis. However, the efficiency of this bone marrow homing process and the proportion of disseminated cells that actively divide and contribute to new tumor growth in MM are both unknown. We used the C57BL/KaLwRij mouse model of myeloma, lentiviral-mediated DNA barcoding of 5TGM1 myeloma cells, and next-generation sequencing to investigate the relative efficiency of plasma cell migration to, and growth within, the bone marrow. This approach revealed three major findings: firstly, establishment of metastasis within the bone marrow was extremely inefficient, with approximately 0.01% of circulating myeloma cells becoming resident long term in the bone marrow of each long bone; secondly, the individual cells of each metastasis exhibited marked differences in their proliferative fates, with the majority of final tumor burden within a bone being attributable to the progeny of between 1 and 8 cells; and, thirdly, the proliferative fate of individual clonal plasma cells differed at each bone marrow site in which the cells “landed.” These findings suggest that individual myeloma plasma cells are subjected to vastly different selection pressures within the bone marrow microenvironment, highlighting the importance of niche-driven factors, which determine the disease course and outcome.
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Affiliation(s)
- Duncan R Hewett
- Myeloma Research Laboratory, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia, 5000, Australia.
| | - Kate Vandyke
- Myeloma Research Laboratory, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia, 5000, Australia
| | - David M Lawrence
- Centre for Cancer Biology, Australian Cancer Research Fund Cancer Genomics Facility, SA Pathology, Adelaide, Australia; School of Biological Sciences, Faculty of Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia
| | - Natasha Friend
- Myeloma Research Laboratory, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia, 5000, Australia
| | - Jacqueline E Noll
- Myeloma Research Laboratory, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia, 5000, Australia
| | - Joel M Geoghegan
- Centre for Cancer Biology, Australian Cancer Research Fund Cancer Genomics Facility, SA Pathology, Adelaide, Australia
| | - Peter I Croucher
- Garvan Institute of Medical Research, 384 Victoria Street, Sydney, New South Wales, 2010
| | - Andrew C W Zannettino
- Myeloma Research Laboratory, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia, 5000, Australia
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49
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Graves CJ, Weinreich DM. Variability in fitness effects can preclude selection of the fittest. ANNUAL REVIEW OF ECOLOGY EVOLUTION AND SYSTEMATICS 2017; 48:399-417. [PMID: 31572069 DOI: 10.1146/annurev-ecolsys-110316-022722] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Evolutionary biologists often predict the outcome of natural selection on an allele by measuring its effects on lifetime survival and reproduction of individual carriers. However, alleles affecting traits like sex, evolvability, and cooperation can cause fitness effects that depend heavily on differences in the environmental, social, and genetic context of individuals carrying the allele. This variability makes it difficult to summarize the evolutionary fate of an allele based solely on its effects on any one individual. Attempts to average over this variability can sometimes salvage the concept of fitness. In other cases evolutionary outcomes can only be predicted by considering the entire genealogy of an allele, thus limiting the utility of individual fitness altogether. We describe a number of intriguing new evolutionary phenomena that have emerged in studies that explicitly model long-term lineage dynamics and discuss implications for the evolution of infectious diseases.
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Affiliation(s)
- Christopher J Graves
- Brown University, Department of Ecology and Evolutionary Biology and Center for Computational and Molecular Biology. Providence, RI, USA
| | - Daniel M Weinreich
- Brown University, Department of Ecology and Evolutionary Biology and Center for Computational and Molecular Biology. Providence, RI, USA
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50
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Digitally Barcoding Mycobacterium tuberculosis Reveals In Vivo Infection Dynamics in the Macaque Model of Tuberculosis. mBio 2017; 8:mBio.00312-17. [PMID: 28487426 PMCID: PMC5424202 DOI: 10.1128/mbio.00312-17] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Infection with Mycobacterium tuberculosis causes a spectrum of outcomes; the majority of individuals contain but do not eliminate the infection, while a small subset present with primary active tuberculosis (TB) disease. This variability in infection outcomes is recapitulated at the granuloma level within each host, such that some sites of infection can be fully cleared while others progress. Understanding the spectrum of TB outcomes requires new tools to deconstruct the mechanisms underlying differences in granuloma fate. Here, we use novel genome-encoded barcodes to uniquely tag individual M. tuberculosis bacilli, enabling us to quantitatively track the trajectory of each infecting bacterium in a macaque model of TB. We also introduce a robust bioinformatics pipeline capable of identifying and counting barcode sequences within complex mixtures and at various read depths. By coupling this tagging strategy with serial positron emission tomography coregistered with computed tomography (PET/CT) imaging of lung pathology in macaques, we define a lesional map of M. tuberculosis infection dynamics. We find that there is no significant infection bottleneck, but there are significant constraints on productive bacterial trafficking out of primary granulomas. Our findings validate our barcoding approach and demonstrate its utility in probing lesion-specific biology and dissemination. This novel technology has the potential to greatly enhance our understanding of local dynamics in tuberculosis. Classically, M. tuberculosis infection was thought to result in either latent infection or active disease. More recently, the field has recognized that there is a spectrum of M. tuberculosis infection clinical outcomes. Within a single host, this spectrum is recapitulated at the granuloma level, where there can simultaneously be lesional sterilization and poorly contained disease. To better understand the lesional biology of TB infection, we digitally barcoded M. tuberculosis to quantitatively track the fate of each infecting bacterium. By combining this technology with serial PET-CT imaging, we can dynamically track both bacterial populations and granuloma trajectories. We demonstrate that there is little constraint on the bacterial population at the time of infection. However, the granuloma imposes a strong bottleneck on dissemination, and the subset of granulomas at risk of dissemination can be distinguished by physical features.
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