Ecker, N. | Search bioRxiv

bioRxiv2022

Mechanics of human embryo compaction

The shaping of the human embryo begins with compaction, during which cells come into close contact and form a tighter structure1,2. Assisted reproductive technology (ART) studies suggest that human embryos fail compaction primarily because of defective adhesion3,4. Based on our current understanding of animal morphogenesis5,6, other morphogenetic engines, such as cell contractility, could be involved in shaping the human embryo. However, the molecular, cellular and physical mechanisms driving human embryo morphogenesis remain uncharacterized. Using micropipette aspiration on human embryos donated to research, we have mapped cell surface tensions during compaction. This reveals a 4-fold increase of tension at the cellmedium interface while cell-cell contacts keep a steady tension. Comparison between human and mouse reveals qualitatively similar but quantitively different mechanical strategies, with human embryos being mechanically least efficient. Inhibition of cell contractility and cell-cell adhesion in human embryos reveal that only contractility controls the surface tension responsible for compaction. Interestingly, if both cellular processes are required for compaction, they exhibit distinct mechanical signatures when faulty. Analyzing the mechanical signature of naturally failing embryos, we find evidence that non-compacting embryos or partially compacting embryos with excluded cells have defective contractility. Together, our study reveals that an evolutionarily conserved increase in cell contractility is required to generate the forces driving the first morphogenetic movement shaping the human body.

developmental biology↗

bioRxiv2020

Harnessing machine learning to unravel protein degradation in Escherichia coli

Degradation of intracellular proteins in Gram-negative bacteria regulates various cellular processes and serves as a quality control mechanism by eliminating damaged proteins. To understand what causes the proteolytic machinery of the cell to degrade some proteins while sparing others, we employed a quantitative pulsed-SILAC (Stable Isotope Labeling with Amino acids in Cell culture) method followed by mass spectrometry analysis to determine the half-lives for the proteome of exponentially growing Escherichia coli, under standard conditions. We developed a likelihood-based statistical test to find actively degraded proteins, and identified dozens of novel proteins that are fast-degrading. Finally, we used structural, physicochemical and protein-protein interaction network descriptors to train a machine-learning classifier to discriminate fast-degrading proteins from the rest of the proteome. Our combined computational-experimental approach provides means for proteomic-based discovery of fast degrading proteins in bacteria and the elucidation of the factors determining protein half-lives and have implications for protein engineering. Moreover, as rapidly degraded proteins may play an important role in pathogenesis, our findings could identify new potential antibacterial drug targets.

microbiology↗