Capturing the conversion of the pathogenic alpha-1-antitrypsin fold by ATF6 enhanced proteostasis

Phenylhydrazone-based Endoplasmic Reticulum Proteostasis Regulator Compounds with Enhanced Biological Activity

Pharmacological enhancement of endoplasmic reticulum (ER) proteostasis is an attractive strategy to mitigate pathology linked to etiologically-diverse protein misfolding diseases. However, despite this promise, few compounds have been identified that enhance ER proteostasis through defined mechanisms of action. We previously identified the phenylhydrazone-based compound AA263 as a compound that promotes adaptive ER proteostasis remodeling through mechanisms including activation of the ATF6 signaling arm of the unfolded protein response (UPR). However, the protein target(s) of AA263 and the potential for further development of this class of ER proteostasis regulators had not been previously explored. Here, we employ chemical proteomics to demonstrate that AA263 covalently targets a subset of ER protein disulfide isomerases, revealing a molecular mechanism for the activation of ATF6 afforded by this compound. We then use medicinal chemistry to establish next-generation AA263 analogs showing improved potency and efficacy for ATF6 activation, as compared to the parent compound. Finally, we show that treatment with these AA263 analogs enhances secretory pathway proteostasis to correct the pathologic protein misfolding and trafficking of both a destabilized, disease-associated α1-antitrypsin (A1AT) variant and an epilepsy-associated GABA A receptor variant. These results establish AA263 analogs with enhanced potential for correcting imbalanced ER proteostasis associated with etiologically-diverse protein misfolding disorders.

Metabolic dysfunction-associated steatotic liver disease (MASLD): Exploring systemic impacts and innovative therapies

Metabolic dysfunction-associated steatotic liver disease (MASLD), which includes the inflammatory subtype metabolic dysfunction-associated steatohepatitis, is a prominent cause of chronic liver disease with systemic effects. Insulin resistance, obesity, and dyslipidaemia produce MASLD in over 30 % of adults. It is a global health issue. From MASLD to MASH, hepatic inflammation and fibrosis grow, leading to cirrhosis, hepatocellular cancer, and extrahepatic complications such CVD, CKD, and sarcopenia. Effects of MASLD to MASH are mediated through mechanisms that include inflammation, oxidative stress, dysbiosis, and predisposition through genetic makeup. Advances in diagnostic nomenclature in the past few years have moved the emphasis away from NAFLD to MASLD, focusing on the metabolic etiology and away from the stigma of an alcoholic-related condition. Epidemiological data show a large geographical variability and increasing prevalence in younger populations, particularly in regions with high carbohydrate-rich diets and central adiposity. Lifestyle modification is considered as the main management of MASLD currently. This may include dietary intervention, exercise, and weight loss management. Pharmaceutical management is primarily aimed at metabolic dysfunction with promising findings for GLP-1 receptor agonists, pioglitazone and SGLT-2 inhibitors, which can correct both hepatic and systemic outcome. However, it still depends on well-integrated multidisciplinary care models by considering complex relationships between MASLD and its effects on extrahepatic organs. Determining complications at an early stage; developing precision medicine strategies; exploring new therapeutic targets will represent crucial factors in improving their outcomes. This review discuss the systemic nature of MASLD and calls for multiple collaborations to reduce its far-reaching health impacts and our quest for understanding its pathological mechanisms. Thus, collective efforts that are required to address MASLD are under the public health, clinical care, and research angles toward effectively containing its rapidly increasing burden.

Spatial covariance reveals isothiocyanate natural products adjust redox stress to restore function in alpha-1-antitrypsin deficiency

Alpha-1 antitrypsin (AAT) deficiency (AATD) is a monogenic disease caused by misfolding of AAT variants resulting in gain-of-toxic aggregation in the liver and loss of monomer activity in the lung leading to chronic obstructive pulmonary disease (COPD). Using high-throughput screening, we discovered a bioactive natural product, phenethyl isothiocyanate (PEITC), highly enriched in cruciferous vegetables, including watercress and broccoli, which improves the level of monomer secretion and neutrophil elastase (NE) inhibitory activity of AAT-Z through the endoplasmic reticulum (ER) redox sensor protein disulfide isomerase (PDI) A4 (PDIA4). The intracellular polymer burden of AAT-Z can be managed by combination treatment of PEITC and an autophagy activator. Using Gaussian process (GP)-based spatial covariance (SCV) (GP-SCV) machine learning to map on a residue-by-residue basis at atomic resolution all variants in the worldwide AATD clinical population, we reveal a global rescue of monomer secretion and NE inhibitory activity for most variants triggering disease. We present a proof of concept that GP-SCV mapping of restoration of AAT variant function serves as a standard model to discover natural products such as the anti-oxidant PEITC that could potentially impact the redox/inflammatory environment of the ER to provide a nutraceutical approach to help minimize disease in AATD patients.

Pervasive mislocalization of pathogenic coding variants underlying human disorders

Widespread sequencing has yielded thousands of missense variants predicted or confirmed as disease causing. This creates a new bottleneck: determining the functional impact of each variant-typically a painstaking, customized process undertaken one or a few genes and variants at a time. Here, we established a high-throughput imaging platform to assay the impact of coding variation on protein localization, evaluating 3,448 missense variants of over 1,000 genes and phenotypes. We discovered that mislocalization is a common consequence of coding variation, affecting about one-sixth of all pathogenic missense variants, all cellular compartments, and recessive and dominant disorders alike. Mislocalization is primarily driven by effects on protein stability and membrane insertion rather than disruptions of trafficking signals or specific interactions. Furthermore, mislocalization patterns help explain pleiotropy and disease severity and provide insights on variants of uncertain significance. Our publicly available resource extends our understanding of coding variation in human diseases.

COPII cage assembly factor Sec13 integrates information flow regulating endomembrane function in response to human variation

How information flow is coordinated for managing transit of 1/3 of the genome through endomembrane pathways by the coat complex II (COPII) system in response to human variation remains an enigma. By examining the interactome of the COPII cage-assembly component Sec13, we show that it is simultaneously associated with multiple protein complexes that facilitate different features of a continuous program of chromatin organization, transcription, translation, trafficking, and degradation steps that are differentially sensitive to Sec13 levels. For the trafficking step, and unlike other COPII components, reduction of Sec13 expression decreased the ubiquitination and degradation of wild-type (WT) and F508del variant cargo protein cystic fibrosis transmembrane conductance regulator (CFTR) leading to a striking increase in fold stability suggesting that the events differentiating export from degradation are critically dependent on COPII cage assembly at the ER Golgi intermediate compartment (ERGIC) associated recycling and degradation step linked to COPI exchange. Given Sec13's multiple roles in protein complex assemblies that change in response to its expression, we suggest that Sec13 serves as an unanticipated master regulator coordinating information flow from the genome to the proteome to facilitate spatial covariant features initiating and maintaining design and function of membrane architecture in response to human variation.

Tracing genetic diversity captures the molecular basis of misfolding disease

Genetic variation in human populations can result in the misfolding and aggregation of proteins, giving rise to systemic and neurodegenerative diseases that require management by proteostasis. Here, we define the role of GRP94, the endoplasmic reticulum Hsp90 chaperone paralog, in managing alpha-1-antitrypsin deficiency on a residue-by-residue basis using Gaussian process regression-based machine learning to profile the spatial covariance relationships that dictate protein folding arising from sequence variants in the population. Covariance analysis suggests a role for the ATPase activity of GRP94 in controlling the N- to C-terminal cooperative folding of alpha-1-antitrypsin responsible for the correction of liver aggregation and lung-disease phenotypes of alpha-1-antitrypsin deficiency. Gaussian process-based spatial covariance profiling provides a standard model built on covariant principles to evaluate the role of proteostasis components in guiding information flow from genome to proteome in response to genetic variation, potentially allowing us to intervene in the onset and progression of complex multi-system human diseases.

Multiple Genes Core to ERAD, Macroautophagy and Lysosomal Degradation Pathways Participate in the Proteostasis Response in α1-Antitrypsin Deficiency

BACKGROUND & AIMS

In the classic form of α1-antitrypsin deficiency (ATD), the misfolded α1-antitrypsin Z (ATZ) variant accumulates in the endoplasmic reticulum (ER) of liver cells. A gain-of-function proteotoxic mechanism is responsible for chronic liver disease in a subgroup of homozygotes. Proteostatic response pathways, including conventional endoplasmic reticulum-associated degradation and autophagy, have been proposed as the mechanisms that allow cellular adaptation and presumably protection from the liver disease phenotype. Recent studies have concluded that a distinct lysosomal pathway called endoplasmic reticulum-to-lysosome completely supplants the role of the conventional macroautophagy pathway in degradation of ATZ. Here, we used several state-of-the-art approaches to characterize the proteostatic responses more fully in cellular systems that model ATD.

METHODS

We used clustered regularly interspaced short palindromic repeats (CRISPR)-mediated genome editing coupled to a cell selection step by fluorescence-activated cell sorter to perform screening for proteostasis genes that regulate ATZ accumulation and combined that with selective genome editing in 2 other model systems.

RESULTS

Endoplasmic reticulum-associated degradation genes are key early regulators and multiple autophagy genes, from classic as well as from ER-to-lysosome and other newly described ER-phagy pathways, participate in degradation of ATZ in a manner that is temporally regulated and evolves as ATZ accumulation persists. Time-dependent changes in gene expression are accompanied by specific ultrastructural changes including dilation of the ER, formation of globular inclusions, budding of autophagic vesicles, and alterations in the overall shape and component parts of mitochondria.

CONCLUSIONS

Macroautophagy is a critical component of the proteostasis response to cellular ATZ accumulation and it becomes more important over time as ATZ synthesis continues unabated. Multiple subtypes of macroautophagy and nonautophagic lysosomal degradative pathways are needed to respond to the high concentrations of misfolded protein that characterizes ATD and these pathways are attractive candidates for genetic variants that predispose to the hepatic phenotype.

Pervasive mislocalization of pathogenic coding variants underlying human disorders

Widespread sequencing has yielded thousands of missense variants predicted or confirmed as disease-causing. This creates a new bottleneck: determining the functional impact of each variant - largely a painstaking, customized process undertaken one or a few genes or variants at a time. Here, we established a high-throughput imaging platform to assay the impact of coding variation on protein localization, evaluating 3,547 missense variants of over 1,000 genes and phenotypes. We discovered that mislocalization is a common consequence of coding variation, affecting about one-sixth of all pathogenic missense variants, all cellular compartments, and recessive and dominant disorders alike. Mislocalization is primarily driven by effects on protein stability and membrane insertion rather than disruptions of trafficking signals or specific interactions. Furthermore, mislocalization patterns help explain pleiotropy and disease severity and provide insights on variants of unknown significance. Our publicly available resource will likely accelerate the understanding of coding variation in human diseases.

Divergent Proteome Reactivity Influences Arm-Selective Activation of the Unfolded Protein Response by Pharmacological Endoplasmic Reticulum Proteostasis Regulators

Pharmacological activation of the activating transcription factor 6 (ATF6) arm of the unfolded protein response (UPR) has proven useful for ameliorating proteostasis deficiencies in cellular and mouse models of numerous etiologically diverse diseases. Previous high-throughput screening efforts identified the small molecule AA147 as a potent and selective ATF6 activating compound that operates through a mechanism involving metabolic activation of its 2-amino-p-cresol substructure affording a quinone methide, which then covalently modifies a subset of endoplasmic reticulum (ER) protein disulfide isomerases (PDIs). Another compound identified in this screen, AA132, also contains a 2-amino-p-cresol moiety; however, this compound showed less transcriptional selectivity, instead globally activating all three arms of the UPR. Here, we show that AA132 activates global UPR signaling through a mechanism analogous to that of AA147, involving metabolic activation and covalent modification of proteins including multiple PDIs. Chemoproteomic-enabled analyses show that AA132 covalently modifies PDIs to a greater extent than AA147. However, the extent of PDI labeling by AA147 approaches a plateau more rapidly than PDI labeling by AA132. These observations together suggest that AA132 can access a larger pool of proteins for covalent modification, possibly because its activated form is less susceptible to quenching than activated AA147. In other words, the lower reactivity of activated AA132 allows it to persist longer and modify more PDIs in the cellular environment. Collectively, these results suggest that AA132 globally activates the UPR through increased engagement of ER PDIs. Consistent with this, reducing the cellular concentration of AA132 decreases PDI modifications and enables selective ATF6 activation. Our results highlight the relationship between metabolically activatable-electrophile stability, ER proteome reactivity, and the transcriptional response observed with the enaminone chemotype of ER proteostasis regulators, enabling continued development of next-generation ATF6 activating compounds.

Understanding the host-pathogen evolutionary balance through Gaussian process modeling of SARS-CoV-2

We have developed a machine learning (ML) approach using Gaussian process (GP)-based spatial covariance (SCV) to track the impact of spatial-temporal mutational events driving host-pathogen balance in biology. We show how SCV can be applied to understanding the response of evolving covariant relationships linking the variant pattern of virus spread to pathology for the entire SARS-CoV-2 genome on a daily basis. We show that GP-based SCV relationships in conjunction with genome-wide co-occurrence analysis provides an early warning anomaly detection (EWAD) system for the emergence of variants of concern (VOCs). EWAD can anticipate changes in the pattern of performance of spread and pathology weeks in advance, identifying signatures destined to become VOCs. GP-based analyses of variation across entire viral genomes can be used to monitor micro and macro features responsible for host-pathogen balance. The versatility of GP-based SCV defines starting point for understanding nature's evolutionary path to complexity through natural selection.