ESCRT machinery mediates selective microautophagy of endoplasmic reticulum in yeast

ER-phagy, the selective autophagy of endoplasmic reticulum (ER), safeguards organelle homeostasis by eliminating misfolded proteins and regulating ER size. ER-phagy can occur by macroautophagic and microautophagic mechanisms. While dedicated machinery for macro-ER-phagy has been discovered, the molecules and mechanisms mediating micro-ER-phagy remain unknown. Here, we first show that micro-ER-phagy in yeast involves the conversion of stacked cisternal ER into multilamellar ER whorls during microautophagic uptake into lysosomes. Second, we identify the conserved Nem1-Spo7 phosphatase complex and the ESCRT machinery as key components for micro-ER-phagy. Third, we demonstrate that macro- and micro-ER-phagy are parallel pathways with distinct molecular requirements. Finally, we provide evidence that the ESCRT machinery directly functions in scission of the lysosomal membrane to complete the microautophagic uptake of ER. These findings establish a framework for a mechanistic understanding of micro-ER-phagy and, thus, a comprehensive appreciation of the role of autophagy in ER homeostasis

HiCT: High Throughput Protocols For CPE Cloning And Transformation

The purpose of this RFC is to provide instructions for a rapid and cost efficient cloning and transformation method which allows for the manufacturing of multi-fragment plasmid constructs in a parallelized manner: High Throughput Circular Extension Cloning and Transformation (HiCT). Description of construct libraries generated by the HiCT method can be found at http://2013.igem.org/Team:Heidelberg/Indigoidine. This RFC also points out further optimization strategies with regard to construct stability, reduction of transformation background and the generation of competent cells

Standard for Synthesis of Customized Peptides by Non-Ribosomal Peptide Synthetases

The purpose of this RFC is to introduce a standardized framework for the engineering of customizable non-ribosomal peptide synthetases (NRPS) and their application for in vivo and in vitro synthesis of short non-ribosomal peptides (NRPs) of user-defined sequence and structure

Smoothing and slope calculation.

<p>The oxygen levels in the media of MCF-7 cells exposed to different Cisplatin concentrations (as depicted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131233#pone.0131233.g002" target="_blank">Fig 2G</a>) between day 2.2 and 5 (A) are smoothed (C) by replacing each time point by the average of an 11 time point-neighbourhood. The smoothing can be seen more precisely on a bigger scale as it is the case for 75–80% a.s. and day 3–3.5 by comparing the raw data (B) to the smoothed data (D). The slope of each time point (E) is then obtained by performing a linear fit of each point and 15 points on either side of it. The residual error of the fit is displayed as a grey shadow around each curve (very small in this case). The legend in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131233#pone.0131233.g003" target="_blank">Fig 3E</a> is valid for all the subfigures, microM stands for micromolar.</p

Time-Resolved Cell Culture Assay Analyser (TReCCA Analyser) for the Analysis of On-Line Data: Data Integration—Sensor Correction—Time-Resolved IC₅₀ Determination

<div><p>Time-resolved cell culture assays circumvent the need to set arbitrary end-points and reveal the dynamics of quality controlled experiments. However, they lead to the generation of large data sets, which can represent a complexity barrier to their use. We therefore developed the Time-Resolved Cell Culture Assay (TReCCA) Analyser program to perform standard cell assay analyses efficiently and make sophisticated in-depth analyses easily available. The functions of the program include data normalising and averaging, as well as smoothing and slope calculation, pin-pointing exact change time points. A time-resolved IC₅₀/EC₅₀ calculation provides a better understanding of drug toxicity over time and a more accurate drug to drug comparison. Finally the logarithmic sensor recalibration function, for sensors with an exponential calibration curve, homogenises the sensor output and enables the detection of low-scale changes. To illustrate the capabilities of the TReCCA Analyser, we performed on-line monitoring of dissolved oxygen in the culture media of the breast cancer cell line MCF-7 treated with different concentrations of the anti-cancer drug Cisplatin. The TReCCA Analyser is freely available at <a href="http://www.uni-heidelberg.de/fakultaeten/biowissenschaften/ipmb/biologie/woelfl/Research.html" target="_blank">www.uni-heidelberg.de/fakultaeten/biowissenschaften/ipmb/biologie/woelfl/Research.html</a>. By introducing the program, we hope to encourage more systematic use of time-resolved assays and lead researchers to fully exploit their data.</p></div

Medium oxygen level of MCF-7 cells when exposed to different concentrations of Cisplatin over time.

<p>All the sensors are measured empty for sensor calibration between minutes 0 and 136 (A), then a sensor calibration is performed (B), followed by normalisation to the wells containing only medium (C). The whole time frame of the experiment is visible in the raw data (D): MCF-7 cell seeding at 136 min, medium change at day 1.09 and Cisplatin addition at different concentrations at day 2.1. The sensor correction and the normalisation to the conditions containing only medium are applied to all the data (E, F respectively). The time points used for sensor correction/normalisation (A, B, C) are depicted as black rectangles (D, E, F respectively). The triplicates of the sensor corrected and normalised data are averaged (G) and their standard deviation is displayed as a grey shadow around each curve. The legend at the bottom of the figure is valid for all the subfigures, microM stands for micromolar. These graphs are displayed as they are produced by the TReCCA Analyser.</p

Time-resolved IC₅₀ of MCF-7 cells exposed to Cisplatin.

<p>The oxygen level in the media of MCF-7 cells treated with different Cisplatin concentrations between days 2.2 and 5 (as depicted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131233#pone.0131233.g003" target="_blank">Fig 3A</a>) are fitted for each time point, as exemplified for day 2.50 (green), 2.89 (turquoise), 3.28 (blue), 3.66 (pink), 4.05 (red), 4.43 (yellow) (A). MicroM stands for micromolar. The IC_<b>50</b> over time (B) is then determined from the values of all the fits between days 2.5 and 4.7. The residual error of the fit is displayed as a grey shadow around each curve.</p

TReCCA Analyser user interface and analysis steps.

<p>Consecutive tabs are clicked through for data analysis and plotting. These include the “Analysis options” tab (A), where the analyses to be performed on the data are selected and their corresponding parameters entered, and the “Graph output” tab (B), where the graphs are visualised and can be further customised. These tabs can be seen at a higher resolution in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131233#pone.0131233.s001" target="_blank">S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131233#pone.0131233.s002" target="_blank">S2</a> Figs. All the analysis steps are summarised in the program flow chart (C). The black rectangle encloses a more precise representation of the available analysis options. The black arrows depict the succession of steps that are performed in our example of the analysis of the effect of Cisplatin on MCF-7 cells, the coloured arrows depict alternative analysis flows.</p

Accurate label-free quantification by directLFQ to compare unlimited numbers of proteomes

ABSTRACTRecent advances in mass spectrometry (MS)-based proteomics enable the acquisition of increasingly large datasets within relatively short times, which exposes bottlenecks in the bioinformatics pipeline. Whereas peptide identification is already scalable, most label-free quantification (LFQ) algorithms scale quadratic or cubic with the sample numbers, which may even preclude the analysis of large-scale data. Here we introduce directLFQ, a ratiobased approach for sample normalization and the calculation of protein intensities. It estimates quantities via aligning samples and ion traces by shifting them on top of each other in logarithmic space. Importantly, directLFQ scales linearly with the number of samples, allowing analyses of large studies to finish in minutes instead of days or months. We quantify 10,000 proteomes in 10 minutes and 100,000 proteomes in less than two hours - thousand-fold faster than some implementations of the popular LFQ algorithm MaxLFQ. In-depth characterization of directLFQ reveals excellent normalization properties and benchmark results, comparing favorably to MaxLFQ for both data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, directLFQ provides normalized peptide intensity estimates for peptide-level comparisons. It is available as an open-source Python package and as a GUI with a one-click installer and can be used in the AlphaPept ecosystem as well as downstream of most common computational proteomics pipelines.</jats:p