Single-molecule spectroscopy: investigations of protein folding to multi-laboratory consistencies on proteins

The investigation of complex biological processes has been challenging and require a variety of sophisticated tools to interpret the underlying processes. The study of the folding process in proteins is one of the focuses of this thesis work. To this end, both spontaneous and chaperone- assisted folding mechanisms were investigated. Single-molecule fluorescence spectroscopy has been extensively applied to the study of biomolecular bindings, conformational changes, and their dynamics due to its high sensitivity, time resolution, and its ability to differentiate between homogenous and heterogenous populations. Specifically, single-molecule Förster Resonance Energy Transfer (smFRET) studies on protein folding have elucidated the basic mechanisms of spontaneous protein folding, and properties of the chaperone-substrate interactions. The possibility to measure at low concentrations making it possible to avoid the aggregation, which is difficult to avoid in ensemble experiments. To investigate the spontaneous folding mechanisms in large multi-domain proteins, two-color smFRET studies were carried out on a slowly folding version of the two-domain Maltose- binding protein (MBP). Three-color smFRET, an extension of typical two-color smFRET to three-colors, was applied on specifically labeled MBP to visualize the co-ordination between the domains as they fold. Chaperone-substrate interactions are crucial to process the substrates and thus enable them to carry out their physiological function. Cavity confinement effect of GroEL/ES, a bacterial Hsp60 on MBP folding landscape was demonstrated. Another substrate protein, p53-DNA-binding domain was probed concerning the combined action of Hsp70 and Hsp90 chaperone on its folding. To conclude the thesis work, a smFRET comparison study on proteins involving 16 laboratories was undertaken to assess the accuracy and precision of smFRET measurements as well as to determine a detection limit for dynamic motions in proteins

Deep Convolutional Neural Network Classifier for Effective Knee Osteoarthritis Classification

Millions of people are affected by the disease Knee Osteoarthritis, and the prevalence of the condition is steadily increasing. Knee osteoarthritis has a significant impact on people's lives by generating increased worry, mental health disorders, and physical problems. Early detection of knee osteoarthritis is critical for decreasing disease consequences, and numerous studies are being conducted to classify knee osteoarthritis. In this study, the deep CNN classifier is used to classify knee osteoarthritis, which effectively extracts the features required for disease classification more efficiently. The preprocessing of the data, which is done in three processes such as Circular Fourier Transform, Multivariate Linear Function, and Histogram Equalization, is particularly important in this research since it aids in obtaining more efficient information about the image. The deep CNN classifier's weights and bias deliver better and desired classification results while spending less time and storage. The proposed deep CNN classifier attained the Accuracy of 94.244%, F1 measure of 94.059%, Precision of 94.059%, Recall of 93.586%

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology

Oxidative Homeostasis Regulates the Response to Reductive Endoplasmic Reticulum Stress through Translation Control

SummaryReductive stress leads to the loss of disulfide bond formation and induces the unfolded protein response of the endoplasmic reticulum (UPRER), necessary to regain proteostasis in the compartment. Here we show that peroxide accumulation during reductive stress attenuates UPRER amplitude by altering translation without any discernible effect on transcription. Through a comprehensive genetic screen in Saccharomyces cerevisiae, we identify modulators of reductive stress-induced UPRER and demonstrate that oxidative quality control (OQC) genes modulate this cellular response in the presence of chronic but not acute reductive stress. Using a combination of microarray and relative quantitative proteomics, we uncover a non-canonical translation attenuation mechanism that acts in a bipartite manner to selectively downregulate highly expressed proteins, decoupling the cell’s transcriptional and translational response during reductive ER stress. Finally, we demonstrate that PERK, a canonical translation attenuator in higher eukaryotes, helps in bypassing a ROS-dependent, non-canonical mode of translation attenuation

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins.

Funder: Ludwig Maximilians University Munich | Center for NanoScience, Ludwig-Maximilians-Universität Mnchen (CeNS, LMU); doi: https://doi.org/10.13039/501100007153Funder: Alexander von Humboldt-Stiftung (Alexander von Humboldt Foundation); doi: https://doi.org/10.13039/100005156Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins.

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology