Literature DB >> 21571072

One plate, two plates, a thousand plates. How crystallisation changes with large numbers of samples.

Janet Newman1.   

Abstract

Turning commercial lab automation into a high-throughput centre requires an underlying process, and implementing checks to ensure that the process is working as it should. At the Collaborative Crystallisation Centre (C3), protein samples from local, national and international groups are set up in crystallisation screening and optimisation experiments with two thousand 96 well plates being set up each year. During its five years of operation, the C3 has implemented a series of enabling protocols - from simple 'reality checks' to determine if a screen has evaporated during storage to more sophisticated systems such as a sample labelling and tracking system. The most important - and perhaps surprising - lesson has been how much effort is required to effectively communicate between the centre and its clients, as well as between the centre's staff members. It is easy to confuse the concept of 'high throughput' in any field with the idea of setting up an experiment quickly. Although automation can be used to set up a single experiment more rapidly than can be done by hand, the distinguishing feature of a high throughput technology is the sustainability of the increased rate.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21571072     DOI: 10.1016/j.ymeth.2011.04.004

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  5 in total

1.  The ESFRI Instruct Core Centre Frankfurt: automated high-throughput crystallization suited for membrane proteins and more.

Authors:  Yvonne Thielmann; Juergen Koepke; Hartmut Michel
Journal:  J Struct Funct Genomics       Date:  2011-11-19

2.  A strategy for selecting the pH of protein solutions to enhance crystallization.

Authors:  Chen Yan Zhang; Zi Qing Wu; Da Chuan Yin; Bo Ru Zhou; Yun Zhu Guo; Hui Meng Lu; Ren Bin Zhou; Peng Shang
Journal:  Acta Crystallogr Sect F Struct Biol Cryst Commun       Date:  2013-06-29

3.  Utilisation of adsorption and desorption for simultaneously improving protein crystallisation success rate and crystal quality.

Authors:  Yun-Zhu Guo; Li-Hua Sun; Dominik Oberthuer; Chen-Yan Zhang; Jian-Yu Shi; Jiang-Lei Di; Bao-Liang Zhang; Hui-Ling Cao; Yong-Ming Liu; Jian Li; Qian Wang; Huan-Huan Huang; Jun Liu; Jan-Mirco Schulz; Qiu-Yu Zhang; Jian-Lin Zhao; Christian Betzel; Jian-Hua He; Da-Chuan Yin
Journal:  Sci Rep       Date:  2014-12-04       Impact factor: 4.379

4.  An ignored variable: solution preparation temperature in protein crystallization.

Authors:  Rui-Qing Chen; Qin-Qin Lu; Qing-Di Cheng; Liang-Bo Ao; Chen-Yan Zhang; Hai Hou; Yong-Ming Liu; Da-Wei Li; Da-Chuan Yin
Journal:  Sci Rep       Date:  2015-01-19       Impact factor: 4.379

5.  Classification of crystallization outcomes using deep convolutional neural networks.

Authors:  Andrew E Bruno; Patrick Charbonneau; Janet Newman; Edward H Snell; David R So; Vincent Vanhoucke; Christopher J Watkins; Shawn Williams; Julie Wilson
Journal:  PLoS One       Date:  2018-06-20       Impact factor: 3.240

  5 in total

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