Biology subjects

Liwang, A.

Publications and source records attributed to Liwang, A..

5 recordsLinked to original sources

bioRxiv2025

Proteome-wide identification of metamorphic protein candidates using mass spectrometry

How protein folds remodel at low temperature remains poorly mapped at the proteome scale. We combine brief, temperature-controlled proteolysis with LC-MS/MS to chart cold-dependent conformational changes in Escherichia coli lysate. Methodological validation with the metamorphic protein Sa1V90T--whose /{beta}-plait and 3 states interchange between 30 {degrees}C and 5 {degrees}C--showed that a high-protease, short-digestion regime detects temperature-dependent exposure at four peptides, whereas the temperature-insensitive variant Sa1V90TV52D is largely unchanged. Applied to lysate, the workflow identifies >750 proteolytic sites across >250 abundant proteins (>10% of the identified proteome) whose local susceptibility shifts as temperature decreases from 35 {degrees}C to 5 {degrees}C, including five Sa1V90T peptides recapitulating purified-protein behavior. A site-level scoring model yields 338 destabilized peptides (177 proteins) and 426 stabilized peptides (138 proteins). Cold stabilization prominently marks translation machinery (>15 ribosomal proteins), while cooling also exposes regions in chaperones and cell-division factors. Sequence analysis links temperature sensitivity to charge-enriched composition, consistent with thermodynamic expectations. These data provide a proteome-wide view of cold-sensitive folding, implicate translation and cytokinetic systems in low-temperature remodeling, and illuminate a new strategy for identifying metamorphic proteins on an unprecedented scale.

biophysics↗

bioRxiv2024

Insights into a clock's fidelity through vesicular encapsulation

The single-celled cyanobacterium, Synechococcus elongatus, generates circadian rhythms with exceptional fidelity and synchrony despite their femtoliter volumes. Here, we explore the mechanistic aspects of this fidelity, by reconstituting the KaiABC post-translational oscillator (PTO) in cell-mimetic giant vesicles (GUVs) under well-defined conditions in vitro. PTO proteins were encapsulated with a coefficient of variation that closely matched protein variations observed in live cells. Using fluorescently labeled KaiB and confocal microscopy, we were able to measure circadian rhythms generated by thousands of encapsulated PTOs at the single-vesicle level for several days as a function of protein concentration and GUV size. We find that PTO fidelity decreased with decreasing levels of encapsulated PTO proteins and in smaller GUVs. We also observed that in encapsulated PTOs, a significant fraction of KaiB localized to GUV membranes like it does in cyanobacteria. A mathematical model that uses empirical bulk concentration and stoichiometry limitations suggests that cyanobacteria overcome challenges to fidelity by expressing high levels of PTO proteins along with the CikA and SasA proteins, which buffer stochastic variations in the levels of KaiA and KaiB, respectively. Further, the model suggests that the transcription-translation feedback loop (TTFL) contributes at most a small percentage to the overall fidelity of the cyanobacterial circadian clock under constant conditions but is essential for maintaining phase synchrony. Our results are the first experimental demonstration of populations of synthetic cells that can autonomously keep circadian time. Additionally, the approach of using bulk relationships to understand complex phenomena in cell-like systems could be useful for understanding other collective behavior important in biology, such as liquid-liquid phase separation.

biophysics↗

bioRxiv2024

Temperature-Dependent Fold-Switching Mechanism of the Circadian Clock Protein KaiB

The oscillator of the cyanobacterial circadian clock relies on the ability of the KaiB protein to switch reversibly between a stable ground-state fold (gsKaiB) and an unstable fold-switched fold (fsKaiB). Rare fold-switching events by KaiB provide a critical delay in the negative feedback loop of this post-translational oscillator. In this study, we experimentally and computationally investigate the temperature dependence of fold switching and its mechanism. We demonstrate that the stability of gsKaiB increases with temperature compared to fsKaiB and that the Q10 value for the gsKaiB [->] fsKaiB transition is nearly three times smaller than that for the reverse transition. Simulations and native-state hydrogen-deuterium exchange NMR experiments suggest that fold switching can involve both subglobally and near-globally unfolded intermediates. The simulations predict that the transition state for fold switching coincides with isomerization of conserved prolines in the most rapidly exchanging region, and we confirm experimentally that proline isomerization is a rate-limiting step for fold switching. We explore the implications of our results for temperature compensation, a hallmark of circadian clocks, through a kinetic model.

biochemistry↗

bioRxiv2020

A Novel Regulatory Role for the Circadian Clock Protein TOC1 via RNA binding

The circadian clock enables plants to predict daily changes of external signals and synchronize them with internal processes, conferring enhanced fitness and growth vigor. The first described Arabidopsis circadian clock protein is TIMING OF CAB EXPRESSION 1 (TOC1), which functions in a transcriptional feedback loop with two myb transcription factors, CIRCADIAN CLOCK-ASSOCIATED 1 (CCA1) and LATE ELONGATED HYPOCOTYL (LHY). Previous studies have shown that TOC1 is a DNA-binding transcriptional repressor of CCA1 and LHY. However, the DNA motifs enriched amongst TOC1 targets share weak sequence similarity and lack consensus, suggesting that TOC1 regulates the expression of its targets through a novel mechanism. Here we show that the TOC1 protein binds directly to RNA via its conserved CCT domain. Using in vitro RNA selection, we identified an RNA motif that is recognized by the TOC1-CCT domain. The TOC1-CCT domain binds to this RNA sequence with nanomolar affinity determined by quantitative electrophoretic mobility shift assays (EMSAs) and isothermal titration calorimetry (ITC). NMR experiments showed that two CCT fragments, CCT533-547 and CCT550-565, use basic residues to bind the RNA motif. Mutational analysis confirmed that lysyl and arginyl residues bind to RNA in a cooperative manner. Furthermore, transiently expressed wildtype and mutant TOC1 in protoplasts demonstrated that RNA binding activity of TOC1 is required for its function as a transcriptional repressor in vivo. Our results reveal a novel regulatory mechanism for TOC1 through RNA binding, suggesting that TOC1 might play key roles as a multi-function protein.

plant biology↗

bioRxiv2020

Sequence-based Prediction of Metamorphic Behavior in Proteins

An increasing number of proteins have been demonstrated in recent years to adopt multiple three-dimensional folds with different functions. These metamorphic proteins are characterized by having two or more folds with significant differences in their secondary structure, where each fold is stabilized by a distinct local environment. So far, about 90 metamorphic proteins have been identified in the Protein Databank (PDB), but we and others hypothesize that a far greater number of metamorphic proteins remain undiscovered. In this work, we introduce a computational model to predict metamorphic behavior in proteins using only knowledge of the sequence. In this model, secondary structure prediction programs are used to calculate diversity indices, which are measures of uncertainty in predicted secondary structure at each position in the sequence; these are then used to assign protein sequences as likely to be metamorphic vs. monomorphic (i.e. having just one-fold). We constructed a reference dataset to train our classification method, which includes a novel compilation of 140 likely-monomorphic proteins, and a set of 201 metamorphic proteins taken from the literature. Our model is able to classify proteins as metamorphic vs. monomorphic with a Matthews correlation coefficient of [~]0.4 and true positive / true negative rates of [~]65% / 80%, suggesting that it is possible to predict metamorphic behavior in proteins using only sequence information. Statement of SignificanceThis paper introduces the diversity index as a descriptor to distinguish metamorphic proteins, which possess multiple stable folds, from monomorphic proteins that possess only one fold. The diversity index is designed to measure uncertainty in computationally predicted secondary structure, which we hypothesize is elevated for metamorphic proteins. We tested our hypothesis by training a binary classifier using the diversity index and an annotated dataset of metamorphic and monomorphic proteins, and found an optimal Matthews correlation coefficient of 0.4, supporting the hypothesis and demonstrating for the first time that it is possible to predict metamorphic behavior in proteins using only sequence information. The sequence-based classifier has broader applicability compared to methods that rely on making comparison to experimentally measured structures.

biophysics↗