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      Capturing sequence diversity in metagenomes with comprehensive and scalable probe design

      research-article
      1 , 2 , § , 1 , 3 , § , 1 , 1 , 1 , 3 , 1 , 4 , 1 , 5 , 1 , 3 , 1 , 1 , 3 , 1 , 3 , 6 , 7 , 7 , 8 , 9 , 9 , 10 , 10 , 11 , 11 , 12 , 13 , 13 , 14 , 15 , Viral Hemorrhagic Fever Consortium 16 , 17 , 18 , 19 , 20 , 5 , 7 , 7 , 21 , 8 , 9 , 9 , 10 , 10 , 11 , 22 , 23 , 22 , 24 , 15 , 6 , 12 , 13 , 14 , 1 , 1 , 1 , 3 , 6 , 25 , 1
      Nature biotechnology

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          Abstract

          Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic-acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of and scale well with known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.

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          Counting absolute numbers of molecules using unique molecular identifiers.

          Counting individual RNA or DNA molecules is difficult because they are hard to copy quantitatively for detection. To overcome this limitation, we applied unique molecular identifiers (UMIs), which make each molecule in a population distinct, to genome-scale human karyotyping and mRNA sequencing in Drosophila melanogaster. Use of this method can improve accuracy of almost any next-generation sequencing method, including chromatin immunoprecipitation-sequencing, genome assembly, diagnostics and manufacturing-process control and monitoring.
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            A threshold of ln n for approximating set cover

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              The All-Species Living Tree project: a 16S rRNA-based phylogenetic tree of all sequenced type strains.

              The signing authors together with the journal Systematic and Applied Microbiology (SAM) have started an ambitious project that has been conceived to provide a useful tool especially for the scientific microbial taxonomist community. The aim of what we have called "The All-Species Living Tree" is to reconstruct a single 16S rRNA tree harboring all sequenced type strains of the hitherto classified species of Archaea and Bacteria. This tree is to be regularly updated by adding the species with validly published names that appear monthly in the Validation and Notification lists of the International Journal of Systematic and Evolutionary Microbiology. For this purpose, the SAM executive editors, together with the responsible teams of the ARB, SILVA, and LPSN projects (www.arb-home.de, www.arb-silva.de, and www.bacterio.cict.fr, respectively), have prepared a 16S rRNA database containing over 6700 sequences, each of which represents a single type strain of a classified species up to 31 December 2007. The selection of sequences had to be undertaken manually due to a high error rate in the names and information fields provided for the publicly deposited entries. In addition, from among the often occurring multiple entries for a single type strain, the best-quality sequence was selected for the project. The living tree database that SAM now provides contains corrected entries and the best-quality sequences with a manually checked alignment. The tree reconstruction has been performed by using the maximum likelihood algorithm RAxML. The tree provided in the first release is a result of the calculation of a single dataset containing 9975 single entries, 6728 corresponding to type strain gene sequences, as well as 3247 additional high-fquality sequences to give robustness to the reconstruction. Trees are dynamic structures that change on the basis of the quality and availability of the data used for their calculation. Therefore, the addition of new type strain sequences in further subsequent releases may help to resolve certain branching orders that appear ambiguous in this first release. On the web sites: www.elsevier.de/syapm and www.arb-silva.de/living-tree, the All-Species Living Tree team will release a regularly updated database compatible with the ARB software environment containing the whole 16S rRNA dataset used to reconstruct "The All-Species Living Tree". As a result, the latest reconstructed phylogeny will be provided. In addition to the ARB file, a readable multi-FASTA universal sequence editor file with the complete alignment will be provided for those not using ARB. There is also a complete set of supplementary tables and figures illustrating the selection procedure and its outcome. It is expected that the All-Species Living Tree will help to improve future classification efforts by simplifying the selection of the correct type strain sequences. For queries, information updates, remarks on the dataset or tree reconstructions shown, a contact email address has been created (living-tree@arb-silva.de). This provides an entry point for anyone from the scientific community to provide additional input for the construction and improvement of the first tree compiling all sequenced type strains of all prokaryotic species for which names had been validly published.
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                Author and article information

                Journal
                9604648
                20305
                Nat Biotechnol
                Nat. Biotechnol.
                Nature biotechnology
                1087-0156
                1546-1696
                9 January 2019
                04 February 2019
                February 2019
                04 August 2019
                : 37
                : 2
                : 160-168
                Affiliations
                [1 ]Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
                [2 ]Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
                [3 ]Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
                [4 ]Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts, USA
                [5 ]Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA
                [6 ]Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
                [7 ]The Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA
                [8 ]Massachusetts Department of Public Health, Boston, Massachusetts, USA
                [9 ]Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Rio de Janeiro, Brazil
                [10 ]Department of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, Florida, USA
                [11 ]Instituto de Investigacion en Microbiologia, Universidad Nacional Autónoma de Honduras, Tegucigalpa, Honduras
                [12 ]Institute of Lassa Fever Research and Control, Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria
                [13 ]African Center of Excellence for Genomics of Infectious Disease (ACEGID), Redeemer’s University, Ede, Osun State, Nigeria
                [14 ]Department of Biological Sciences, College of Natural Sciences, Redeemer’s University, Ede, Osun State, Nigeria
                [15 ]Lassa Fever Laboratory, Kenema Government Hospital, Kenema, Eastern Province, Sierra Leone
                [16 ]Tulane University, New Orleans, Louisiana, USA
                [17 ]Evolutionary genomics of RNA viruses, Virology Department, Institut Pasteur, Paris, France
                [18 ]Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, Maryland, USA
                [19 ]Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
                [20 ]Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, California, USA
                [21 ]Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, Massachusetts, USA
                [22 ]Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
                [23 ]Department of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA
                [24 ]Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA.
                [25 ]Howard Hughes Medical Institute, Chevy Chase, Maryland, USA.
                Author notes
                [*]

                These authors contributed equally to this work.

                [†]

                These authors jointly supervised this work.

                Author contributions

                H.C.M., D.J.P., A.Gn., P.C.S., and C.B.M. initiated the study of improved design and application of comprehensive probe sets.

                H.C.M. conceived of CATCH and implemented it with advice from D.J.P., A.Gn., and C.B.M.

                K.J.S. and C.B.M. conceived of experimental design for evaluating probe sets.

                C.B.M., J.Q., A.G.-Y., and K.J.S. developed enrichment protocols with help from A.Gol.

                K.J.S, A.G.-Y., J.Q., and P.B. prepared samples, performed enrichment, and sequenced samples.

                A.P., S.W., A.C., A.E.L., and K.G.B. helped with sample preparation and enrichment.

                D.C.T., B.C., S.H., G.B.-L., Y.R.V., L.M.P., A.L.T., K.F.G., L.A.P., A.B., E.H., D.S.K., T.M.A., J.A.R., S.S., F.A.B., T.M.L.S., S.I., S.F.M., I.L., L.G., and I.B. collected and shared samples with known viral content.

                E.S.-L. and L.H. shared viral seed stocks.

                G.E. shared uncharacterized mosquito pools.

                I.O., P.E., O.A.F., A.Gob., D.S.G., and C.T.H. collected human plasma samples from Nigeria and Sierra Leone.

                H.C.M. and K.J.S. formulated and performed data analyses with help from D.K.Y.

                H.C.M., K.J.S., and C.B.M. wrote the manuscript with input from other authors.

                [§ ] Correspondence should be addressed to: H.C.M. ( hayden@ 123456mit.edu ) and K.J.S. ( kjsiddle@ 123456broadinstitute.org ).
                Article
                NIHMS1516973
                10.1038/s41587-018-0006-x
                6587591
                30718881
                c6244d05-ff88-4901-bab7-a4fa88519caf

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