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Coherent multidimensional spectroscopy provides experimental access to molecular structure and subpicosecond dynamics in solution. Dynamics are typically inferred from the evolution of lineshapes over a function of waiting time. Numerous spectral analysis methods, such as center/nodal line slope, have been developed to extract these dynamics. However, the extracted dynamics can depend heavily on subjective choices, such as the region selected for CLS analysis or the chosen models. In this study, we introduce a novel approach to extracting dynamics from ultrafast two-dimensional infrared (2D IR) spectra by using dynamic mode decomposition (DMD). As a data-driven method, DMD directly extracts spatiotemporal structures from the complex 2D IR spectra. We evaluated the performance of DMD in simulated and experimental spectra containing overlapped peaks. We show that DMD can retrieve the dynamics of overlapped transitions and cross peaks that are typically challenging to extract with traditional methods. In addition, we demonstrate that combining conditional generative adversarial neural networks with DMD can recover dynamics even at low signal-to-noise ratios. DMD methods do not require preliminary assumptions and can be readily extended to other multidimensional spectroscopies. 

BoxCARS and pump-probe geometries are common implementations of two-dimensional infrared (2D IR) spectroscopy. BoxCARS is background-free, generally offering greater signal-to-noise ratio, which enables measuring weak vibrational echo signals. Pulse shapers have been implemented in the pump-probe geometry to accelerate data collection and suppress scatter and other unwanted signals by precise control of the pump-pulse delay and carrier phase. Here, we introduce a 2D-IR optical setup in the BoxCARS geometry that implements a pulse shaper for rapid acquisition of background-free 2D IR spectra. We show a signal-to-noise improvement using this new fast-scan BoxCARS setup versus the pump-probe geometry within the same configuration.

 

Abstract The proteasome, the primary protease for ubiquitin-dependent proteolysis in eukaryotes, is usually found as a mixture of 30S, 26S, and 20S complexes. These complexes have common catalytic sites, which makes it challenging to determine their distinctive roles in intracellular proteolysis. Here, we chemically synthesize a panel of homogenous ubiquitinated proteins, and use them to compare 20S and 26S proteasomes with respect to substrate selection and peptide-product generation. We show that 20S proteasomes can degrade the ubiquitin tag along with the conjugated substrate. Ubiquitin remnants on branched peptide products identified by LC-MS/MS, and flexibility in the 20S gate observed by cryo-EM, reflect the ability of the 20S proteasome to proteolyze an isopeptide-linked ubiquitin-conjugate. Peptidomics identifies proteasome-trapped ubiquitin-derived peptides and peptides of potential 20S substrates in Hi20S cells, hypoxic cells, and human failing-heart. Moreover, elevated levels of 20S proteasomes appear to contribute to cell survival under stress associated with damaged proteins.