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The champions of drug development
doi : 10.1038/s41587-021-01095-z
Nature Biotechnology volume 39, page1167 (2021)
Drug hunters uncloak the non-coding ‘hidden’ genome
Michael Eisenstein
doi : 10.1038/s41587-021-01088-y
Nature Biotechnology volume 39, pages1169–1171 (2021)
Church to de-extinct woolly mammoths
Laura DeFrancesco
doi : 10.1038/s41587-021-01096-y
Nature Biotechnology volume 39, page1171 (2021)
Nanotechnology offers alternative ways to fight COVID-19 pandemic with antivirals
Mark Peplow
doi : 10.1038/s41587-021-01085-1
Nature Biotechnology volume 39, pages1172–1174 (2021)
Roche deal with RNA-editing spinout
doi : 10.1038/s41587-021-01097-x
Nature Biotechnology volume 39, page1173 (2021)
UK trials first CRISPR-edited wheat in Europe
doi : 10.1038/s41587-021-01098-w
Nature Biotechnology volume 39, page1174 (2021)
Biotech news from around the world
doi : 10.1038/s41587-021-01082-4
Nature Biotechnology volume 39, page1175 (2021)
Biotech patenting 2020
Brady Huggett & Kathryn Paisner
doi : 10.1038/s41587-021-01076-2
Nature Biotechnology volume 39, pages1176–1177 (2021)
Ready-to-use public infrastructure for global SARS-CoV-2 monitoring
Wolfgang Maier, Simon Bray, Marius van den Beek, Dave Bouvier, Nathan Coraor, Milad Miladi, Babita Singh, Jordi Rambla De Argila, Dannon Baker, Nathan Roach, Simon Gladman, Frederik Coppens, Darren P. Martin, Andrew Lonie, Björn Grüning, Sergei L. Kosakovsky Pond & Anton Nekrutenko
doi : 10.1038/s41587-021-01069-1
Nature Biotechnology volume 39, pages1178–1179 (2021)
Rapid delivery systems for future food security
Rajeev K. Varshney, Abhishek Bohra, Manish Roorkiwal, Rutwik Barmukh, Wallace Cowling, Annapurna Chitikineni, Hon-Ming Lam, Lee T. Hickey, Janine Croser, David Edwards, Muhammad Farooq, José Crossa, Wolfram Weckwerth, A. Harvey Millar, Arvind Kumar, Michael W. Bevan & Kadambot H. M. Siddique
doi : 10.1038/s41587-021-01079-z
Nature Biotechnology volume 39, pages1179–1181 (2021)
A public–private partnership model for COVID-19 diagnostics
Peter H. L. Krijger, Tim A. Hoek, Sanne Boersma, Lieke I. P. M. Donders, Maaike M. C. Broeders, Mark Pieterse, Pim W. Toonen, Ive Logister, Bram M. P. Verhagen, Marjon J. A. M. Verstegen, Thomas W. van Ravesteyn, Rene J. T. M. Roymans, Francesca Mattiroli, Jo Vandesompele, Monique Nijhuis, Stefan Meijer, Anton van Weert, Edwin Dekker, Fred J. Dom, Rob Ruijtenbeek, Lieven B. J. van der Velden, Jeroen H. B. van de Bovenkamp, Martijn Bosch, Wouter de Laat & Marvin E. Tanenbaum
doi : 10.1038/s41587-021-01080-6
Nature Biotechnology volume 39, pages1182–1184 (2021)
Synthetic virology: the experts speak
Laura DeFrancesco
doi : 10.1038/s41587-021-01078-0
Nature Biotechnology volume 39, pages1185–1193 (2021)
Patent landscape of brain–machine interface technology
Anastasia Greenberg, Alexis Cohen & Monica Grewal
doi : 10.1038/s41587-021-01071-7
Nature Biotechnology volume 39, pages1194–1199 (2021)
Hope Lies in Dreams
doi : 10.1038/s41587-021-01090-4
Nature Biotechnology volume 39, page1201 (2021)
Forum: Gene therapy roundtable with High and Kohn
doi : 10.1038/s41587-021-01083-3
Nature Biotechnology volume 39, page1201 (2021)
Computational principles and challenges in single-cell data integration
Ricard Argelaguet, Anna S. E. Cuomo, Oliver Stegle & John C. Marioni
doi : 10.1038/s41587-021-00895-7
Nature Biotechnology volume 39, pages1202–1215 (2021)
The development of single-cell multimodal assays provides a powerful tool for investigating multiple dimensions of cellular heterogeneity, enabling new insights into development, tissue homeostasis and disease. A key challenge in the analysis of single-cell multimodal data is to devise appropriate strategies for tying together data across different modalities. The term ‘data integration’ has been used to describe this task, encompassing a broad collection of approaches ranging from batch correction of individual omics datasets to association of chromatin accessibility and genetic variation with transcription. Although existing integration strategies exploit similar mathematical ideas, they typically have distinct goals and rely on different principles and assumptions. Consequently, new definitions and concepts are needed to contextualize existing methods and to enable development of new methods.
Field trial demonstrating phytoremediation of the military explosive RDX by XplA/XplB-expressing switchgrass
Timothy J. Cary, Elizabeth L. Rylott, Long Zhang, Ryan M. Routsong, Antonio J. Palazzo, Stuart E. Strand & Neil C. Bruce
doi : 10.1038/s41587-021-00909-4
Nature Biotechnology volume 39, pages1216–1219 (2021)
The explosive hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), a major component of munitions, is used extensively on military training ranges. As a result, widespread RDX pollution in groundwater and aquifers in the United States is now well documented. RDX is toxic, but its removal from training ranges is logistically challenging, lacking cost-effective and sustainable solutions. Previously, we have shown that thale cress (Arabidopsis thaliana) engineered to express two genes, xplA and xplB, encoding RDX-degrading enzymes from the soil bacterium Rhodococcus rhodochrous 11Y can break down this xenobiotic in laboratory studies. Here, we report the results of a 3-year field trial of XplA/XplB-expressing switchgrass (Panicum virgatum) conducted on three locations in a military site. Our data suggest that XplA/XplB switchgrass has in situ efficacy, with potential utility for detoxifying RDX on live-fire training ranges, munitions dumps and minefields.
Detection of low-frequency DNA variants by targeted sequencing of the Watson and Crick strands
Joshua D. Cohen, Christopher Douville, Jonathan C. Dudley, Brian J. Mog, Maria Popoli, Janine Ptak, Lisa Dobbyn, Natalie Silliman, Joy Schaefer, Jeanne Tie, Peter Gibbs, Cristian Tomasetti, Nickolas Papadopoulos, Kenneth W. Kinzler & Bert Vogelstein
doi : 10.1038/s41587-021-00900-z
Nature Biotechnology volume 39, pages1220–1227 (2021)
Identification and quantification of low-frequency mutations remain challenging despite improvements in the baseline error rate of next-generation sequencing technologies. Here, we describe a method, termed SaferSeqS, that addresses these challenges by (1) efficiently introducing identical molecular barcodes in the Watson and Crick strands of template molecules and (2) enriching target sequences with strand-specific PCR. The method achieves high sensitivity and specificity and detects variants at frequencies below 1 in 100,000 DNA template molecules with a background mutation rate of <5?×?10–7 mutants per base pair (bp). We demonstrate that it can evaluate mutations in a single amplicon or simultaneously in multiple amplicons, assess limited quantities of cell-free DNA with high recovery of both strands and reduce the error rate of existing PCR-based molecular barcoding approaches by >100-fold.
Fully implantable and bioresorbable cardiac pacemakers without leads or batteries
Yeon Sik Choi, Rose T. Yin, Anna Pfenniger, Jahyun Koo, Raudel Avila, K. Benjamin Lee, Sheena W. Chen, Geumbee Lee, Gang Li, Yun Qiao, Alejandro Murillo-Berlioz, Alexi Kiss, Shuling Han, Seung Min Lee, Chenhang Li, Zhaoqian Xie, Yu-Yu Chen, Amy Burrell, Beth Geist, Hyoyoung Jeong, Joohee Kim, Hong-Joon Yoon, Anthony Banks, Seung-Kyun Kang, Zheng Jenny Zhang, Chad R. Haney, Alan Varteres Sahakian, David Johnson, Tatiana Efimova, Yonggang Huang, Gregory D. Trachiotis, Bradley P. Knight, Rishi K. Arora, Igor R. Efimov & John A. Rogers
doi : 10.1038/s41587-021-00948-x
Nature Biotechnology volume 39, pages1228–1238 (2021)
Temporary cardiac pacemakers used in periods of need during surgical recovery involve percutaneous leads and externalized hardware that carry risks of infection, constrain patient mobility and may damage the heart during lead removal. Here we report a leadless, battery-free, fully implantable cardiac pacemaker for postoperative control of cardiac rate and rhythm that undergoes complete dissolution and clearance by natural biological processes after a defined operating timeframe. We show that these devices provide effective pacing of hearts of various sizes in mouse, rat, rabbit, canine and human cardiac models, with tailored geometries and operation timescales, powered by wireless energy transfer. This approach overcomes key disadvantages of traditional temporary pacing devices and may serve as the basis for the next generation of postoperative temporary pacing technology.
Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D
Ravian L. van Ineveld, Michiel Kleinnijenhuis, Maria Alieva, Sam de Blank, Mario Barrera Roman, Esmée J. van Vliet, Clara Martínez Mir, Hannah R. Johnson, Frank L. Bos, Raimond Heukers, Susana M. Chuva de Sousa Lopes, Jarno Drost, Johanna F. Dekkers, Ellen J. Wehrens & Anne C. Rios
doi : 10.1038/s41587-021-00926-3
Nature Biotechnology volume 39, pages1239–1245 (2021)
Despite advances in three-dimensional (3D) imaging, it remains challenging to profile all the cells within a large 3D tissue, including the morphology and organization of the many cell types present. Here, we introduce eight-color, multispectral, large-scale single-cell resolution 3D (mLSR-3D) imaging and image analysis software for the parallelized, deep learning–based segmentation of large numbers of single cells in tissues, called segmentation analysis by parallelization of 3D datasets (STAPL-3D). Applying the method to pediatric Wilms tumor, we extract molecular, spatial and morphological features of millions of cells and reconstruct the tumor’s spatio-phenotypic patterning. In situ population profiling and pseudotime ordering reveals a highly disorganized spatial pattern in Wilms tumor compared to healthy fetal kidney, yet cellular profiles closely resembling human fetal kidney cells could be observed. In addition, we identify previously unreported tumor-specific populations, uniquely characterized by their spatial embedding or morphological attributes. Our results demonstrate the use of combining mLSR-3D and STAPL-3D to generate a comprehensive cellular map of human tumors.
Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells
Eleni P. Mimitou, Caleb A. Lareau, Kelvin Y. Chen, Andre L. Zorzetto-Fernandes, Yuhan Hao, Yusuke Takeshima, Wendy Luo, Tse-Shun Huang, Bertrand Z. Yeung, Efthymia Papalexi, Pratiksha I. Thakore, Tatsuya Kibayashi, James Badger Wing, Mayu Hata, Rahul Satija, Kristopher L. Nazor, Shimon Sakaguchi, Leif S. Ludwig, Vijay G. Sankaran, Aviv Regev & Peter Smibert
doi : 10.1038/s41587-021-00927-2
Nature Biotechnology volume 39, pages1246–1258 (2021)
Recent technological advances have enabled massively parallel chromatin profiling with scATAC-seq (single-cell assay for transposase accessible chromatin by sequencing). Here we present ATAC with select antigen profiling by sequencing (ASAP-seq), a tool to simultaneously profile accessible chromatin and protein levels. Our approach pairs sparse scATAC-seq data with robust detection of hundreds of cell surface and intracellular protein markers and optional capture of mitochondrial DNA for clonal tracking, capturing three distinct modalities in single cells. ASAP-seq uses a bridging approach that repurposes antibody:oligonucleotide conjugates designed for existing technologies that pair protein measurements with single-cell RNA sequencing. Together with DOGMA-seq, an adaptation of CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) for measuring gene activity across the central dogma of gene regulation, we demonstrate the utility of systematic multi-omic profiling by revealing coordinated and distinct changes in chromatin, RNA and surface proteins during native hematopoietic differentiation and peripheral blood mononuclear cell stimulation and as a combinatorial decoder and reporter of multiplexed perturbations in primary T cells.
Integrative single-cell analysis of allele-specific copy number alterations and chromatin accessibility in cancer
Chi-Yun Wu, Billy T. Lau, Heon Seok Kim, Anuja Sathe, Susan M. Grimes, Hanlee P. Ji & Nancy R. Zhang
doi : 10.1038/s41587-021-00911-w
Nature Biotechnology volume 39, pages1259–1269 (2021)
Cancer progression is driven by both somatic copy number aberrations (CNAs) and chromatin remodeling, yet little is known about the interplay between these two classes of events in shaping the clonal diversity of cancers. We present Alleloscope, a method for allele-specific copy number estimation that can be applied to single-cell DNA- and/or transposase-accessible chromatin-sequencing (scDNA-seq, ATAC-seq) data, enabling combined analysis of allele-specific copy number and chromatin accessibility. On scDNA-seq data from gastric, colorectal and breast cancer samples, with validation using matched linked-read sequencing, Alleloscope finds pervasive occurrence of highly complex, multiallelic CNAs, in which cells that carry varying allelic configurations adding to the same total copy number coevolve within a tumor. On scATAC-seq from two basal cell carcinoma samples and a gastric cancer cell line, Alleloscope detected multiallelic copy number events and copy-neutral loss-of-heterozygosity, enabling dissection of the contributions of chromosomal instability and chromatin remodeling to tumor evolution.
Profiling the genetic determinants of chromatin accessibility with scalable single-cell CRISPR screens
Noa Liscovitch-Brauer, Antonino Montalbano, Jiale Deng, Alejandro Méndez-Mancilla, Hans-Hermann Wessels, Nicholas G. Moss, Chia-Yu Kung, Akash Sookdeo, Xinyi Guo, Evan Geller, Suma Jaini, Peter Smibert & Neville E. Sanjana
doi : 10.1038/s41587-021-00902-x
Nature Biotechnology volume 39, pages1270–1277 (2021)
CRISPR screens have been used to connect genetic perturbations with changes in gene expression and phenotypes. Here we describe a CRISPR-based, single-cell combinatorial indexing assay for transposase-accessible chromatin (CRISPR–sciATAC) to link genetic perturbations to genome-wide chromatin accessibility in a large number of cells. In human myelogenous leukemia cells, we apply CRISPR–sciATAC to target 105?chromatin-related genes, generating chromatin accessibility data for ~30,000?single cells. We correlate the loss of specific chromatin remodelers with changes in accessibility globally and at the binding sites of individual transcription factors (TFs). For example, we show that loss of the H3K27 methyltransferase EZH2 increases accessibility at heterochromatic regions involved in embryonic development and triggers expression of genes in the HOXA and HOXD clusters. At a subset of regulatory sites, we also analyze changes in nucleosome spacing following the loss of chromatin remodelers. CRISPR–sciATAC is a high-throughput, single-cell method for studying the effect of genetic perturbations on chromatin in normal and disease states.
Quantitative profiling of pseudouridylation dynamics in native RNAs with nanopore sequencing
Oguzhan Begik, Morghan C. Lucas, Leszek P. Pryszcz, Jose Miguel Ramirez, Rebeca Medina, Ivan Milenkovic, Sonia Cruciani, Huanle Liu, Helaine Graziele Santos Vieira, Aldema Sas-Chen, John S. Mattick, Schraga Schwartz & Eva Maria Novoa
doi : 10.1038/s41587-021-00915-6
Nature Biotechnology volume 39, pages1278–1291 (2021)
Nanopore RNA sequencing shows promise as a method for discriminating and identifying different RNA modifications in native RNA. Expanding on the ability of nanopore sequencing to detect N6-methyladenosine, we show that other modifications, in particular pseudouridine (?) and 2?-O-methylation (Nm), also result in characteristic base-calling ‘error’ signatures in the nanopore data. Focusing on ? modification sites, we detected known and uncovered previously unreported ? sites in mRNAs, non-coding RNAs and rRNAs, including a Pus4-dependent ? modification in yeast mitochondrial rRNA. To explore the dynamics of pseudouridylation, we treated yeast cells with oxidative, cold and heat stresses and detected heat-sensitive ?-modified sites in small nuclear RNAs, small nucleolar RNAs and mRNAs. Finally, we developed a software, nanoRMS, that estimates per-site modification stoichiometries by identifying single-molecule reads with altered current intensity and trace profiles. This work demonstrates that Nm and ? RNA modifications can be detected in cellular RNAs and that their modification stoichiometry can be quantified by nanopore sequencing of native RNA.
Genome-wide specificity of prime editors in plants
Shuai Jin, Qiupeng Lin, Yingfeng Luo, Zixu Zhu, Guanwen Liu, Yunjia Li, Kunling Chen, Jin-Long Qiu & Caixia Gao
doi : 10.1038/s41587-021-00891-x
Nature Biotechnology volume 39, pages1292–1299 (2021)
Although prime editors (PEs) have the potential to facilitate precise genome editing in therapeutic, agricultural and research applications, their specificity has not been comprehensively evaluated. To provide a systematic assessment in plants, we first examined the mismatch tolerance of PEs in plant cells and found that the editing frequency was influenced by the number and location of mismatches in the primer binding site and spacer of the prime editing guide RNA (pegRNA). Assessing the activity of 12 pegRNAs at 179 predicted off-target sites, we detected only low frequencies of off-target edits (0.00~0.23%). Whole-genome sequencing of 29 PE-treated rice plants confirmed that PEs do not induce genome-wide pegRNA-independent off-target single-nucleotide variants or small insertions/deletions. We also show that ectopic expression of the Moloney murine leukemia virus reverse transcriptase as part of the PE does not change retrotransposon copy number or telomere structure or cause insertion of pegRNA or messenger RNA sequences into the genome.
Learning on knowledge graph dynamics provides an early warning of impactful research
James W. Weis & Joseph M. Jacobson
doi : 10.1038/s41587-021-00907-6
Nature Biotechnology volume 39, pages1300–1307 (2021)
The scientific ecosystem relies on citation-based metrics that provide only imperfect, inconsistent and easily manipulated measures of research quality. Here we describe DELPHI (Dynamic Early-warning by Learning to Predict High Impact), a framework that provides an early-warning signal for ‘impactful’ research by autonomously learning high-dimensional relationships among features calculated across time from the scientific literature. We prototype this framework and deduce its performance and scaling properties on time-structured publication graphs from 1980 to 2019 drawn from 42 biotechnology-related journals, including over 7.8 million individual nodes, 201 million relationships and 3.8 billion calculated metrics. We demonstrate the framework’s performance by correctly identifying 19/20 seminal biotechnologies from 1980 to 2014 via a blinded retrospective study and provide 50 research papers from 2018 that DELPHI predicts will be in the top 5% of time-rescaled node centrality in the future. We propose DELPHI as a tool to aid in the construction of diversified, impact-optimized funding portfolios.
Publisher Correction: Send in the senolytics
Elie Dolgin
doi : 10.1038/s41587-021-01073-5
Nature Biotechnology volume 39, page1308 (2021)
Improving scientific communication with service, education and career development
Amanda Dicks, Himanshi Bhatia, Adam W. Clemens, Marissa C. Locke, Elizabeth A. Mueller, Daniel Murphy, Nathan Pomper, Anne E. Robinson & Kathleen M. Schoch
doi : 10.1038/s41587-021-01077-1
Nature Biotechnology volume 39, pages1309–1313 (2021)
