Hidden information on protein function in censuses of proteome foldedness

PERCEPT: Replacing binary p-value thresholding with scaling for more nuanced identification of sample differences

Key to a biologists' capacity to understand data is the ability to make meaningful conclusions about differences in experimental observations. Typically, data are noisy, and conventional methods rely on replicates to average out noise and enable univariate statistical tests to assign p-values. Yet thresholding p-values to determine significance is controversial and often misleading, especially for omics datasets with few replicates. This study introduces PERCEPT, an alternative that transforms data using an ad-hoc scaling factor derived from p-values. By applying this method, low confidence effects are suppressed compared to high confidence ones, enabling clearer patterns to emerge from noisy datasets. The effectiveness of PERCEPT scaling is demonstrated using simulated datasets and published omics studies. The approach reduces the exclusion of datapoints, enhances accuracy, and enables nuanced interpretation of data. PERCEPT is easy to apply for the non-expert in statistics and provides researchers a straightforward way to improve data-driven analyses.

Systematic Investigation of Dose-Dependent Protein Thermal Stability Changes to Uncover the Mechanisms of the Pleiotropic Effects of Metformin

Metformin is a widely used drug to treat type II diabetes. Beyond lowering blood sugar, it has been reported to have pleiotropic effects such as suppressing cancer growth and attenuating cell oxidative stress and inflammation. However, the underlying mechanisms of these effects remain to be explored. Here, we systematically study the thermal stability changes of proteins in liver cells (HepG2) induced by a wide dosage range of metformin by using the proteome integral solubility alteration (PISA) assay. The current results demonstrate that, besides the most accepted target of metformin (complex I), low concentrations of metformin (such as 0.2 μM) stabilize the complex IV subunits, suggesting its important role in the sugar-lowering effect. Low-dose metformin also results in stability alterations of ribosomal proteins, correlating with its inhibitive effect on cell proliferation. We further find that low-concentration metformin impacts mitochondrial cargo and vesicle transport, while high-concentration metformin affects cell redox responses and cell membrane protein sorting. This study provides mechanistic insights into the molecular mechanisms of lowering blood sugar and the pleiotropic effects of metformin.

Cellular Exposure to Chloroacetanilide Herbicides Induces Distinct Protein Destabilization Profiles

Herbicides in the widely used chloroacetanilide class harbor a potent electrophilic moiety, which can damage proteins through nucleophilic substitution. In general, damaged proteins are subject to misfolding. Accumulation of misfolded proteins compromises cellular integrity by disrupting cellular proteostasis networks, which can further destabilize the cellular proteome. While direct conjugation targets can be discovered through affinity-based protein profiling, there are few approaches to probe how cellular exposure to toxicants impacts the stability of the proteome. We apply a quantitative proteomics methodology to identify chloroacetanilide-destabilized proteins in HEK293T cells based on their binding to the H31Q mutant of the human Hsp40 chaperone DNAJB8. We find that a brief cellular exposure to the chloroacetanilides acetochlor, alachlor, and propachlor induces misfolding of dozens of cellular proteins. These herbicides feature distinct but overlapping profiles of protein destabilization, highly concentrated in proteins with reactive cysteine residues. Consistent with the recent literature from the pharmacology field, reactivity is driven by neither inherent nucleophilic nor electrophilic reactivity but is idiosyncratic. We discover that propachlor induces a general increase in protein aggregation and selectively targets GAPDH and PARK7, leading to a decrease in their cellular activities. Hsp40 affinity profiling identifies a majority of propachlor targets identified by competitive activity-based protein profiling (ABPP), but ABPP can only identify about 10% of protein targets identified by Hsp40 affinity profiling. GAPDH is primarily modified by the direct conjugation of propachlor at a catalytic cysteine residue, leading to global destabilization of the protein. The Hsp40 affinity strategy is an effective technique to profile cellular proteins that are destabilized by cellular toxin exposure. Raw proteomics data is available through the PRIDE Archive at PXD030635.

Profiling protein targets of cellular toxicant exposure

Environmental agents of exposure can damage proteins, affecting protein function and cellular protein homeostasis. Specific residues are inherently chemically susceptible to damage from individual types of exposure. Amino acid content is not completely predictive of protein susceptibility, as secondary, tertiary, and quaternary structures of proteins strongly influence the reactivity of the proteome to individual exposures. Because we cannot readily predict which proteins will be affected by which chemical exposures, mass spectrometry-based proteomic strategies are necessary to determine the protein targets of environmental toxins and toxicants. This review describes the mechanisms by which environmental exposure to toxins and toxicants can damage proteins and affect their function, and emerging omic methodologies that can be used to identify the protein targets of a given agent. These methods include target identification strategies that have recently revolutionized the drug discovery field, such as activity-based protein profiling, protein footprinting, and protein stability profiling technologies. In particular, we highlight the necessity of multiple, complementary approaches to fully interrogate how protein integrity is challenged by individual exposures.

Protein painting reveals pervasive remodeling of conserved proteostasis machinery in response to pharmacological stimuli

The correct spatio-temporal organization of the proteome is essential for cellular homeostasis. However, a detailed mechanistic understanding of this organization and how it is altered in response to external stimuli in the intact cellular environment is as-yet unrealized. ‘Protein painting methods provide a means to address this gap in knowledge by monitoring the conformational status of proteins within cells at the proteome-wide scale. Here, we demonstrate the ability of a protein painting method employing tetraphenylethene maleimide (TPE-MI) to reveal proteome network remodeling in whole cells in response to a cohort of commonly used pharmacological stimuli of varying specificity. We report specific, albeit heterogeneous, responses to individual stimuli that coalesce on a conserved set of core cellular machineries. This work expands our understanding of proteome conformational remodeling in response to cellular stimuli, and provides a blueprint for assessing how these conformational changes may contribute to disorders characterized by proteostasis imbalance.

Sequence grammar underlying the unfolding and phase separation of globular proteins

Aberrant phase separation of globular proteins is associated with many diseases. Here, we use a model protein system to understand how the unfolded states of globular proteins drive phase separation and the formation of unfolded protein deposits (UPODs). We find that for UPODs to form, the concentrations of unfolded molecules must be above a threshold value. Additionally, unfolded molecules must possess appropriate sequence grammars to drive phase separation. While UPODs recruit molecular chaperones, their compositional profiles are also influenced by synergistic physicochemical interactions governed by the sequence grammars of unfolded proteins and cellular proteins. Overall, the driving forces for phase separation and the compositional profiles of UPODs are governed by the sequence grammars of unfolded proteins. Our studies highlight the need for uncovering the sequence grammars of unfolded proteins that drive UPOD formation and cause gain-of-function interactions whereby proteins are aberrantly recruited into UPODs.