Structure of the Human Signal Peptidase Complex Reveals the Determinants for Signal Peptide Cleavage

The signal peptidase complex (SPC) is an essential membrane complex in the endoplasmic reticulum (ER), where it removes signal peptides (SPs) from a large variety of secretory pre-proteins with exquisite specificity. Although the determinants of this process have been established empirically, the molecular details of SP recognition and removal remain elusive. Here, we show that the human SPC exists in two functional paralogs with distinct proteolytic subunits. We determined the atomic structures of both paralogs using electron cryo-microscopy and structural proteomics. The active site is formed by a catalytic triad and abuts the ER membrane, where a transmembrane window collectively formed by all subunits locally thins the bilayer. This unique architecture generates specificity for thousands of SPs based on the length of their hydrophobic segments.

The importance of preexisting drug resistance due to overexpression of P-glycoprotein for the formation of resistance to bortezomib

Objective of the study. In our work we investigated the effect of pre-existing drug resistance by the mechanism of activation of ABC transporters – P-glycoprotein (Pgp) overexpression – on the development of resistance to the proteasome inhibitor bortezomib.Materials and methods. Cultures RPMI8226 and K562 / i-S9 (with Pgp overexpression) and their bortezomib-resistant sublines RPMI8226 / btz-6 and K562 / i-S9vlc were used as models. The methods used were MTT test, flow cytometry, Western blot and real-time polymerase chain reaction using the Human Signal Transduction Pathway Finder system.Results. The expression of the main PI3K-AKT and NF-κB signaling pathways did not change in RPMI8226 / btz-6 subline cells. However, AKT kinase expression was significantly increased and PTEN protein expression was reduced in K562 / i-S9vlc cells with Pgp-overexpression. Significant changes in gene expression (42 %) were found in RPMI8226 / btz-6 cells related to a number of main signaling pathways in the tumor cell, namely: activation of 3–4 genes in signaling pathways related to hypoxia, oxidative stress, PPAR and p53. The highest activation in these cells was found in the TGFβ signaling pathway. In resistant K562 / i-S9vlc cells, expression of only 5 genes (10 %) increased: Fas, HMOX1, CPT2, ICAM, and SOCS3. Three genes were also identified that changed in both resistant sublines: Fas, HMOX1 and CPT2. Further, we showed that in the RPMI8226 / btz-6 subline, along with changes in the expression of signal transduction genes, there is a large pool of CD138-negative cells, and in the K562 / i-S9vlc subline, the number of cells expressing CD34 increases and the number of CD13 decreases.Conclusion. We found that different signaling pathways are involved in the formation of resistance to bortezomib in the absence of Pgp expression and its overexpression. In addition, a cell line without activated resistance pathways requires more extensive rearrangements in the signal system to acquire resistance to bortezomib. However, in both cases, bortezomib leads to a change in the immunophenotype of the cells – to the appearance of dedifferentiated subpopulations.

The warm and extremely dry spring in 2015 in Tasmania contained the fingerprint of human influence on the climate

Tasmania saw a warm and very dry spring and summer in 2015–16, including a record dry October, which had significant, wide-ranging impacts. A previous study using two probabilistic event-attribution techniques found a small but statistically significant increase in the likelihood of the record dry October due to anthropogenic influence. Given the human signal was less clear amid natural variability for rainfall compared to temperature extremes, here we provided further evidence and context for this finding. An additional attribution method supported the October rainfall finding, and the median attributable risk to human influence in the three methods was ~25%, 48% and 75%. The results suggested that human influence on rainfall was partly through increased sea level pressure in the mid-latitudes associated with fewer rainbearing systems, a circulation driver that was consistent with recent trends that have been attributed to human influence. Dry conditions were also driven by a positive Indian Ocean Dipole and El Niño at the time, but this study could not reliably estimate the effect of human influence on these phenomena, as each model gave a different estimate of the ocean warming pattern. Along with rainfall, attribution modelling showed a role for human influence in higher temperature and evaporation through October 2015, as well as a high drought index throughout spring. Confidence in the attribution of a human signal on this extreme dry event increased as multiple attribution methods agreed, a plausible atmospheric circulation driver was identified, and temperature and evaporation also showed an anthropogenic signal.