MDM2 Influences ACE2 Stability and SARS-CoV-2 Uptake

Angiotensin-converting enzyme 2 (ACE2) is the central entry receptor for SARS-CoV-2. However, surprisingly little is known about the effects of host regulators on ACE2 localization, expression, and the associated influence on SARS-CoV-2 infection. Here we identify that ACE2 expression levels are regulated by the E3 ligase MDM2 and that MDM2 levels indirectly influence infection with SARS-CoV-2. Genetic depletion of MDM2 elevated ACE2 expression levels, which strongly promoted infection with all SARS-CoV-2 isolates tested. SARS-CoV-2 spike-pseudotyped viruses and the uptake of non-replication-competent virus-like particles showed that MDM2 affects the viral uptake process. MDM2 ubiquitinates Lysine 788 of ACE2 to induce proteasomal degradation, and degradation of this residue led to higher ACE2 expression levels and superior virus particle uptake. Our study illustrates that cellular regulators of ACE2 stability, such as MDM2, play an important role in defining the infection capabilities of SARS-CoV-2.

Evaluation of an E. coli Cell Extract Prepared by Lysozyme-Assisted Sonication via Gene Expression, Phage Assembly and Proteomics

Over the past decades, starting from crude cell extracts, a variety of successful preparation protocols and optimized reaction conditions have been established for the production of cell-free gene expression systems. One of the crucial steps during the preparation of cell extract-based expression systems is the cell lysis procedure itself, which largely determines the quality of the active components of the extract. Here we evaluate the utility of an E. coli cell extract, which was prepared using a combination of lysozyme incubation and a gentle sonication step. As quality measure, we demonstrate the cell-free expression of YFP at concentrations up to 0.6 mg/mL. In addition, we produced and assembled T7 bacteriophages up to a titer of 108  PFU/mL. State-of-the-art quantitative proteomics was used to compare the produced extracts with each other and with a commercial extract. The differences in protein composition were surprisingly small between lysozyme-assisted sonication (LAS) extracts, but we observed an increase in the release of DNA-binding proteins for increasing numbers of sonication cycles. Proteins taking part in carbohydrate metabolism, glycolysis, amino acid and nucleotide related pathways were found to be more abundant in the LAS extract, while proteins related to RNA modification and processing, DNA modification and replication, transcription regulation, initiation, termination and the TCA cycle were found enriched in the commercial extract.

SEQU-INTO: Early detection of impurities, contamination and off-targets (ICOs) in long read/MinION sequencing

The MinION sequencer by Oxford Nanopore Technologies turns DNA and RNA sequencing into a routine task in biology laboratories or in field research. For downstream analysis it is required to have a sufficient amount of target reads. Especially prokaryotic or bacteriophagic sequencing samples can contain a significant amount of off-target sequences in the processed sample, stemming from human DNA/RNA contamination, insufficient rRNA depletion, or remaining DNA/RNA from other organisms (e.g. host organism from bacteriophage cultivation). Such impurity, contamination and off-targets (ICOs) block read capacity, requiring to sequence deeper. In comparison to second-generation sequencing, MinION sequencing allows to reuse its chip after a (partial) run. This allows further usage of the same chip with more sample, even after adjusting the library preparation to reduce ICOs. The earlier a sample's ICOs are detected, the better the sequencing chip can be conserved for future use. Here we present sequ-into, a low-resource and user-friendly cross-platform tool to detect ICO sequences from a predefined ICO database in samples early during a MinION sequencing run. The data provided by sequ-into empowers the user to quickly take action to preserve sample material and chip capacity. sequ-into is available from https://github.com/mjoppich/sequ-into.