A novel TPR-BEN domain interaction mediates PICH-BEND3 association

PICH is a DNA translocase required for the maintenance of chromosome stability in human cells. Recent data indicate that PICH co-operates with topoisomerase IIα to suppress pathological chromosome missegregation through promoting the resolution of ultra-fine anaphase bridges (UFBs). Here, we identify the BEN domain-containing protein 3 (BEND3) as an interaction partner of PICH in human cells in mitosis. We have purified full length PICH and BEND3 and shown that they exhibit a functional biochemical interaction in vitro. We demonstrate that the PICH-BEND3 interaction occurs via a novel interface between a TPR domain in PICH and a BEN domain in BEND3, and have determined the crystal structure of this TPR-BEN complex at 2.2 Å resolution. Based on the structure, we identified amino acids important for the TPR-BEN domain interaction, and for the functional interaction of the full-length proteins. Our data reveal a proposed new function for BEND3 in association with PICH, and the first example of a specific protein-protein interaction mediated by a BEN domain

The development of therapeutic proteins can be hindered by poor decision-making strategies in the early stage

In this study we address two major issues related to the current development process of therapeutic proteins and their characterization. First, due to limited samples amounts, the selection of lead molecules in the early stages is often based on the results from a limited physicochemical characterization. The latter can be based on measurements of only 2-3 parameters, e.g. protein melting temperature, protein aggregation temperature, and is usually performed in only one buffer, e.g. PBS. The hypothesis we present is that such approach can lead to the rejection of lead candidates that can still be manufacturable and can move on to clinical trials. The second matter we address are the often-reported correlations between protein physicochemical parameters in the literature. We propose that such correlations can be found only in a small sample population, e.g. one protein in different solution conditions or different proteins from the same class. However, we expect that such correlations would not be valid in a large population, including various protein structures and solution conditions. In order to address the above-mentioned issues, we created the PIPPI consortium (http://www.pippi.kemi.dtu.dk) and applied systematic approach to map the physicochemical properties of a wide range of proteins and extensively study their stability as a function of the solution conditions. We show that promising therapeutic protein lead candidate can appear as non-manufacturable when only limited physicochemical characterization is performed, e.g. a few methods are used and only a few solution conditions are tested. Therefore, the rejection rate during early-stage development can be improved by more thorough physicochemical characterization. Moreover, only weak linear correlations between biophysical properties of proteins are observed in a large populations. This suggests that the often-reported correlations between parameters describing the protein stability are not representative of a global population. Understanding the connections between various physiochemical parameters would require a systematic database which is currently in development by the PIPPI consortium

A Multilaboratory Comparison of Calibration Accuracy and the Performance of External References in Analytical Ultracentrifugation

Analytical ultracentrifugation (AUC) is a first principles based method to determine absolute sedimentation coefficients and buoyant molar masses of macromolecules and their complexes, reporting on their size and shape in free solution. The purpose of this multi-laboratory study was to establish the precision and accuracy of basic data dimensions in AUC and validate previously proposed calibration techniques. Three kits of AUC cell assemblies containing radial and temperature calibration tools and a bovine serum albumin (BSA) reference sample were shared among 67 laboratories, generating 129 comprehensive data sets. These allowed for an assessment of many parameters of instrument performance, including accuracy of the reported scan time after the start of centrifugation, the accuracy of the temperature calibration, and the accuracy of the radial magnification. The range of sedimentation coefficients obtained for BSA monomer in different instruments and using different optical systems was from 3.655 S to 4.949 S, with a mean and standard deviation of (4.304 ± 0.188) S (4.4%). After the combined application of correction factors derived from the external calibration references for elapsed time, scan velocity, temperature, and radial magnification, the range of s-values was reduced 7-fold with a mean of 4.325 S and a 6-fold reduced standard deviation of ± 0.030 S (0.7%). In addition, the large data set provided an opportunity to determine the instrument-to-instrument variation of the absolute radial positions reported in the scan files, the precision of photometric or refractometric signal magnitudes, and the precision of the calculated apparent molar mass of BSA monomer and the fraction of BSA dimers. These results highlight the necessity and effectiveness of independent calibration of basic AUC data dimensions for reliable quantitative studies

A multilaboratory comparison of calibration accuracy and the performance of external references in analytical ultracentrifugation.

Analytical ultracentrifugation (AUC) is a first principles based method to determine absolute sedimentation coefficients and buoyant molar masses of macromolecules and their complexes, reporting on their size and shape in free solution. The purpose of this multi-laboratory study was to establish the precision and accuracy of basic data dimensions in AUC and validate previously proposed calibration techniques. Three kits of AUC cell assemblies containing radial and temperature calibration tools and a bovine serum albumin (BSA) reference sample were shared among 67 laboratories, generating 129 comprehensive data sets. These allowed for an assessment of many parameters of instrument performance, including accuracy of the reported scan time after the start of centrifugation, the accuracy of the temperature calibration, and the accuracy of the radial magnification. The range of sedimentation coefficients obtained for BSA monomer in different instruments and using different optical systems was from 3.655 S to 4.949 S, with a mean and standard deviation of (4.304 ± 0.188) S (4.4%). After the combined application of correction factors derived from the external calibration references for elapsed time, scan velocity, temperature, and radial magnification, the range of s-values was reduced 7-fold with a mean of 4.325 S and a 6-fold reduced standard deviation of ± 0.030 S (0.7%). In addition, the large data set provided an opportunity to determine the instrument-to-instrument variation of the absolute radial positions reported in the scan files, the precision of photometric or refractometric signal magnitudes, and the precision of the calculated apparent molar mass of BSA monomer and the fraction of BSA dimers. These results highlight the necessity and effectiveness of independent calibration of basic AUC data dimensions for reliable quantitative studies

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016