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      Insights into HIV-1 proviral transcription from integrative structure and dynamics of the Tat:AFF4:P-TEFb:TAR complex

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          Abstract

          HIV-1 Tat hijacks the human superelongation complex (SEC) to promote proviral transcription. Here we report the 5.9 Å structure of HIV-1 TAR in complex with HIV-1 Tat and human AFF4, CDK9, and CycT1. The TAR central loop contacts the CycT1 Tat-TAR recognition motif (TRM) and the second Tat Zn 2+-binding loop. Hydrogen-deuterium exchange (HDX) shows that AFF4 helix 2 is stabilized in the TAR complex despite not touching the RNA, explaining how it enhances TAR binding to the SEC 50-fold. RNA SHAPE and SAXS data were used to help model the extended (Tat Arginine-Rich Motif) ARM, which enters the TAR major groove between the bulge and the central loop. The structure and functional assays collectively support an integrative structure and a bipartite binding model, wherein the TAR central loop engages the CycT1 TRM and compact core of Tat, while the TAR major groove interacts with the extended Tat ARM.

          DOI: http://dx.doi.org/10.7554/eLife.15910.001

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          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Linking crystallographic model and data quality.

            In macromolecular x-ray crystallography, refinement R values measure the agreement between observed and calculated data. Analogously, R(merge) values reporting on the agreement between multiple measurements of a given reflection are used to assess data quality. Here, we show that despite their widespread use, R(merge) values are poorly suited for determining the high-resolution limit and that current standard protocols discard much useful data. We introduce a statistic that estimates the correlation of an observed data set with the underlying (not measurable) true signal; this quantity, CC*, provides a single statistically valid guide for deciding which data are useful. CC* also can be used to assess model and data quality on the same scale, and this reveals when data quality is limiting model improvement.
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              Getting up to speed with transcription elongation by RNA polymerase II.

              Recent advances in sequencing techniques that measure nascent transcripts and that reveal the positioning of RNA polymerase II (Pol II) have shown that the pausing of Pol II in promoter-proximal regions and its release to initiate a phase of productive elongation are key steps in transcription regulation. Moreover, after the release of Pol II from the promoter-proximal region, elongation rates are highly dynamic throughout the transcription of a gene, and vary on a gene-by-gene basis. Interestingly, Pol II elongation rates affect co-transcriptional processes such as splicing, termination and genome stability. Increasing numbers of factors and regulatory mechanisms have been associated with the steps of transcription elongation by Pol II, revealing that elongation is a highly complex process. Elongation is thus now recognized as a key phase in the regulation of transcription by Pol II.
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                Author and article information

                Contributors
                Role: Reviewing editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                12 October 2016
                2016
                : 5
                : e15910
                Affiliations
                [1 ]deptDepartment of Molecular and Cell Biology , University of California, Berkeley , Berkeley, United States
                [2 ]deptCalifornia Institute of Quantitative Biosciences , University of California, Berkeley , Berkeley, United States
                [3 ]deptDepartment of Bioengineering and Therapeutic Sciences , University of California, San Francisco , San Francisco, United States
                [4 ]deptDepartment of Pharmaceutical Chemistry , University of California, San Francisco , San Francisco, United States
                [5 ]deptCalifornia Institute of Quantitative Biosciences , University of California San, Francisco , San Francisco, United States
                [6 ]deptMolecular Biophysics and Integrated Bioimaging Division , Lawrence Berkeley National Laboratory , Berkeley, United States
                [7 ]deptHoward Hughes Medical Institute , University of California, Berkeley , Berkeley, United States
                [8 ]deptDepartment of Chemistry , University of California, Berkeley , Berkeley, United States
                [9]Stanford University Medical Center , United States
                [10]Stanford University Medical Center , United States
                Author notes
                Author information
                http://orcid.org/0000-0003-4717-1467
                http://orcid.org/0000-0002-4841-9949
                http://orcid.org/0000-0001-5054-5445
                Article
                15910
                10.7554/eLife.15910
                5072841
                27731797
                be3d52ad-9e4b-4f13-b31d-43b3daf43853
                © 2016, Schulze-Gahmen et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 09 March 2016
                : 07 October 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: P50GM082250
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R01AI041757
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R01AI095057
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Biochemistry
                Biophysics and Structural Biology
                Research Article
                Custom metadata
                2.5
                The crystal structure of the trans-activation response region (TAR) bound to HIV-1 Tat and an elongation factor, together with HDX, SHAPE, SAXS, and integrative modeling, shows how TAR binds this complex in two ways.

                Life sciences
                saxs,integrative modeling,hdx,shape,x-ray crystallography,virus
                Life sciences
                saxs, integrative modeling, hdx, shape, x-ray crystallography, virus

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