µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics.

Mass spectrometry has revolutionized cell signaling research by vastly simplifying the analysis of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to perturbations is crucial for further illuminating the functionality of the phosphoproteome. Here we describe µPhos ('microPhos'), an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture and small tissue amounts in <8 h total processing time. By greatly minimizing transfer steps and liquid volumes, we demonstrate increased sensitivity, >90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify ~17,000 Class I phosphosites in a human cancer cell line using 20 µg starting material, and confidently localize ~6200 phosphosites from 1 µg. This depth covers key signaling pathways, rendering sample-limited applications and perturbation experiments with hundreds of samples viable. We employ µPhos to study drug- and time-dependent response signatures in a leukemia cell line, and by quantifying 30,000 Class I phosphosites in the mouse brain we reveal distinct spatial kinase activities in subregions of the hippocampal formation.

The genetic and dietary landscape of the muscle insulin signalling network.

Metabolic disease is caused by a combination of genetic and environmental factors, yet few studies have examined how these factors influence signal transduction, a key mediator of metabolism. Using mass spectrometry-based phosphoproteomics, we quantified 23,126 phosphosites in skeletal muscle of five genetically distinct mouse strains in two dietary environments, with and without acute in vivo insulin stimulation. Almost half of the insulin-regulated phosphoproteome was modified by genetic background on an ordinary diet, and high-fat high-sugar feeding affected insulin signalling in a strain-dependent manner. Our data revealed coregulated subnetworks within the insulin signalling pathway, expanding our understanding of the pathway's organisation. Furthermore, associating diverse signalling responses with insulin-stimulated glucose uptake uncovered regulators of muscle insulin responsiveness, including the regulatory phosphosite S469 on Pfkfb2, a key activator of glycolysis. Finally, we confirmed the role of glycolysis in modulating insulin action in insulin resistance. Our results underscore the significance of genetics in shaping global signalling responses and their adaptability to environmental changes, emphasising the utility of studying biological diversity with phosphoproteomics to discover key regulatory mechanisms of complex traits.

When we eat, the pancreas releases a hormone called insulin, which helps our tissues absorb glucose. Insulin works by triggering a cascade of events in cells, which include adding chemical tags called phosphate groups at thousands of specific locations on proteins. This tag causes the changes needed to move glucose from the blood into cells and also regulates many other essential functions in the cell. If this process stops working and the body becomes resistant to the effects of insulin, it can lead to type 2 diabetes. This can result from a complex combination of genetic and lifestyle factors, which are difficult to study systematically in people. An alternative approach to understand these influences is to study mice, which are commonly used to investigate metabolic diseases and have contributed to our understanding of the mechanisms of type 2 diabetes. Using carefully bred mice allows precise control of their genetics and environment, revealing the independent and joint effects of these factors. Monitoring differences in the phosphate groups on proteins, van Gerwen et al. studied five distinct inbred mouse strains fed either an ordinary diet or one that was high in fat and sugar. Nearly half of the biochemical events triggered by insulin were altered by genetics on the ordinary diet. High-fat, high-sugar feeding also reshaped the pattern of phosphate tags depending on the mouse strain. By examining these cellular responses, van Gerwen et al. identified proteins that may regulate the insulin response in muscle cells. Increasing the activity of one of these enzymes reversed insulin resistance in skeletal muscle cells grown in the laboratory. This research underscores the importance of genetics in controlling insulin responses and shaping the impact of environmental challenges. It establishes a new opportunity in personalised medicine, which seeks to understand how an individual's genetics combine with their lifestyle to shape health. Furthermore, it identifies potential new targets for treating insulin resistance, paving the way for future research to develop more effective diabetes treatments.

Erratum: Proteomic pathways to metabolic disease and type 2 diabetes in the pancreatic islet.

[This corrects the article DOI: 10.1016/j.isci.2021.103099.].

SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data.

A major challenge in mass spectrometry-based phosphoproteomics lies in identifying the substrates of kinases, as currently only a small fraction of substrates identified can be confidently linked with a known kinase. Machine learning techniques are promising approaches for leveraging large-scale phosphoproteomics data to computationally predict substrates of kinases. However, the small number of experimentally validated kinase substrates (true positive) and the high data noise in many phosphoproteomics datasets together limit their applicability and utility. Here, we aim to develop advanced kinase-substrate prediction methods to address these challenges. Using a collection of seven large phosphoproteomics datasets, and both traditional and deep learning models, we first demonstrate that a 'pseudo-positive' learning strategy for alleviating small sample size is effective at improving model predictive performance. We next show that a data resampling-based ensemble learning strategy is useful for improving model stability while further enhancing prediction. Lastly, we introduce an ensemble deep learning model ('SnapKin') by incorporating the above two learning strategies into a 'snapshot' ensemble learning algorithm. We propose SnapKin, an ensemble deep learning method, for predicting substrates of kinases from large-scale phosphoproteomics data. We demonstrate that SnapKin consistently outperforms existing methods in kinase-substrate prediction. SnapKin is freely available at https://github.com/PYangLab/SnapKin.

Parallel use of human stem cell lung and heart models provide insights for SARS-CoV-2 treatment.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily infects the respiratory tract, but pulmonary and cardiac complications occur in severe coronavirus disease 2019 (COVID-19). To elucidate molecular mechanisms in the lung and heart, we conducted paired experiments in human stem cell-derived lung alveolar type II (AT2) epithelial cell and cardiac cultures infected with SARS-CoV-2. With CRISPR-Cas9-mediated knockout of ACE2, we demonstrated that angiotensin-converting enzyme 2 (ACE2) was essential for SARS-CoV-2 infection of both cell types but that further processing in lung cells required TMPRSS2, while cardiac cells required the endosomal pathway. Host responses were significantly different; transcriptome profiling and phosphoproteomics responses depended strongly on the cell type. We identified several antiviral compounds with distinct antiviral and toxicity profiles in lung AT2 and cardiac cells, highlighting the importance of using several relevant cell types for evaluation of antiviral drugs. Our data provide new insights into rational drug combinations for effective treatment of a virus that affects multiple organ systems.

Phosphoproteomics reveals rewiring of the insulin signaling network and multi-nodal defects in insulin resistance.

The failure of metabolic tissues to appropriately respond to insulin ("insulin resistance") is an early marker in the pathogenesis of type 2 diabetes. Protein phosphorylation is central to the adipocyte insulin response, but how adipocyte signaling networks are dysregulated upon insulin resistance is unknown. Here we employ phosphoproteomics to delineate insulin signal transduction in adipocyte cells and adipose tissue. Across a range of insults causing insulin resistance, we observe a marked rewiring of the insulin signaling network. This includes both attenuated insulin-responsive phosphorylation, and the emergence of phosphorylation uniquely insulin-regulated in insulin resistance. Identifying dysregulated phosphosites common to multiple insults reveals subnetworks containing non-canonical regulators of insulin action, such as MARK2/3, and causal drivers of insulin resistance. The presence of several bona fide GSK3 substrates among these phosphosites led us to establish a pipeline for identifying context-specific kinase substrates, revealing widespread dysregulation of GSK3 signaling. Pharmacological inhibition of GSK3 partially reverses insulin resistance in cells and tissue explants. These data highlight that insulin resistance is a multi-nodal signaling defect that includes dysregulated MARK2/3 and GSK3 activity.

Deep Proteome Profiling of White Adipose Tissue Reveals Marked Conservation and Distinct Features Between Different Anatomical Depots.

White adipose tissue is deposited mainly as subcutaneous adipose tissue (SAT), often associated with metabolic protection, and abdominal/visceral adipose tissue, which contributes to metabolic disease. To investigate the molecular underpinnings of these differences, we conducted comprehensive proteomics profiling of whole tissue and isolated adipocytes from these two depots across two diets from C57Bl/6J mice. The adipocyte proteomes from lean mice were highly conserved between depots, with the major depot-specific differences encoded by just 3% of the proteome. Adipocytes from SAT (SAdi) were enriched in pathways related to mitochondrial complex I and beiging, whereas visceral adipocytes (VAdi) were enriched in structural proteins and positive regulators of mTOR presumably to promote nutrient storage and cellular expansion. This indicates that SAdi are geared toward higher catabolic activity, while VAdi are more suited for lipid storage. By comparing adipocytes from mice fed chow or Western diet (WD), we define a core adaptive proteomics signature consisting of increased extracellular matrix proteins and decreased fatty acid metabolism and mitochondrial Coenzyme Q biosynthesis. Relative to SAdi, VAdi displayed greater changes with WD including a pronounced decrease in mitochondrial proteins concomitant with upregulation of apoptotic signaling and decreased mitophagy, indicating pervasive mitochondrial stress. Furthermore, WD caused a reduction in lipid handling and glucose uptake pathways particularly in VAdi, consistent with adipocyte de-differentiation. By overlaying the proteomics changes with diet in whole adipose tissue and isolated adipocytes, we uncovered concordance between adipocytes and tissue only in the visceral adipose tissue, indicating a unique tissue-specific adaptation to sustained WD in SAT. Finally, an in-depth comparison of isolated adipocytes and 3T3-L1 proteomes revealed a high degree of overlap, supporting the utility of the 3T3-L1 adipocyte model. These deep proteomes provide an invaluable resource highlighting differences between white adipose depots that may fine-tune their unique functions and adaptation to an obesogenic environment.

Synergistic Targeting of DNA-PK and KIT Signaling Pathways in KIT Mutant Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is the most common and aggressive form of acute leukemia, with a 5-year survival rate of just 24%. Over a third of all AML patients harbor activating mutations in kinases, such as the receptor tyrosine kinases FLT3 (receptor-type tyrosine-protein kinase FLT3) and KIT (mast/stem cell growth factor receptor kit). FLT3 and KIT mutations are associated with poor clinical outcomes and lower remission rates in response to standard-of-care chemotherapy. We have recently identified that the core kinase of the non-homologous end joining DNA repair pathway, DNA-PK (DNA-dependent protein kinase), is activated downstream of FLT3; and targeting DNA-PK sensitized FLT3-mutant AML cells to standard-of-care therapies. Herein, we investigated DNA-PK as a possible therapeutic vulnerability in KIT mutant AML, using isogenic FDC-P1 mouse myeloid progenitor cell lines transduced with oncogenic mutant KIT (V560G and D816V) or vector control. Targeted quantitative phosphoproteomic profiling identified phosphorylation of DNA-PK in the T2599/T2605/S2608/S2610 cluster in KIT mutant cells, indicative of DNA-PK activation. Accordingly, proliferation assays revealed that KIT mutant FDC-P1 cells were more sensitive to the DNA-PK inhibitors M3814 or NU7441, compared with empty vector controls. DNA-PK inhibition combined with inhibition of KIT signaling using the kinase inhibitors dasatinib or ibrutinib, or the protein phosphatase 2A activators FTY720 or AAL(S), led to synergistic cell death. Global phosphoproteomic analysis of KIT-D816V cells revealed that dasatinib and M3814 single-agent treatments inhibited extracellular signal-regulated kinase and AKT (RAC-alpha serine/threonine-protein kinase)/MTOR (serine/threonine-protein kinase mTOR) activity, with greater inhibition of both pathways when used in combination. Combined dasatinib and M3814 treatment also synergistically inhibited phosphorylation of the transcriptional regulators MYC and MYB. This study provides insight into the oncogenic pathways regulated by DNA-PK beyond its canonical role in DNA repair and demonstrates that DNA-PK is a promising therapeutic target for KIT mutant cancers.

A high-content endogenous GLUT4 trafficking assay reveals new aspects of adipocyte biology.

Insulin-induced GLUT4 translocation to the plasma membrane in muscle and adipocytes is crucial for whole-body glucose homeostasis. Currently, GLUT4 trafficking assays rely on overexpression of tagged GLUT4. Here we describe a high-content imaging platform for studying endogenous GLUT4 translocation in intact adipocytes. This method enables high fidelity analysis of GLUT4 responses to specific perturbations, multiplexing of other trafficking proteins and other features including lipid droplet morphology. Using this multiplexed approach we showed that Vps45 and Rab14 are selective regulators of GLUT4, but Trarg1, Stx6, Stx16, Tbc1d4 and Rab10 knockdown affected both GLUT4 and TfR translocation. Thus, GLUT4 and TfR translocation machinery likely have some overlap upon insulin-stimulation. In addition, we identified Kif13A, a Rab10 binding molecular motor, as a novel regulator of GLUT4 traffic. Finally, comparison of endogenous to overexpressed GLUT4 highlights that the endogenous GLUT4 methodology has an enhanced sensitivity to genetic perturbations and emphasises the advantage of studying endogenous protein trafficking for drug discovery and genetic analysis of insulin action in relevant cell types.

Global profiling of the proteomic changes associated with the post-testicular maturation of mouse spermatozoa.

Spermatozoa acquire fertilization potential during passage through a highly specialized region of the extratesticular ductal system known as the epididymis. In the absence of de novo gene transcription or protein translation, this functional transformation is extrinsically driven via the exchange of varied macromolecular cargo between spermatozoa and the surrounding luminal plasma. Key among these changes is a substantive remodeling of the sperm proteomic architecture, the scale of which has yet to be fully resolved. Here, we have exploited quantitative mass spectrometry-based proteomics to define the extent of changes associated with the maturation of mouse spermatozoa; reporting the identity of >6,000 proteins, encompassing the selective loss and gain of several hundred proteins. Further, we demonstrate epididymal-driven activation of RHOA-mediated signaling pathways is an important component of sperm maturation. These data contribute molecular insights into the complexity of proteomic changes associated with epididymal sperm maturation.

Parallel use of pluripotent human stem cell lung and heart models provide new insights for treatment of SARS-CoV-2.

SARS-CoV-2 primarily infects the respiratory tract, but pulmonary and cardiac complications occur in severe COVID-19. To elucidate molecular mechanisms in the lung and heart, we conducted paired experiments in human stem cell-derived lung alveolar type II (AT2) epithelial cell and cardiac cultures infected with SARS-CoV-2. With CRISPR- Cas9 mediated knock-out of ACE2, we demonstrated that angiotensin converting enzyme 2 (ACE2) was essential for SARS-CoV-2 infection of both cell types but further processing in lung cells required TMPRSS2 while cardiac cells required the endosomal pathway. Host responses were significantly different; transcriptome profiling and phosphoproteomics responses depended strongly on the cell type. We identified several antiviral compounds with distinct antiviral and toxicity profiles in lung AT2 and cardiac cells, highlighting the importance of using several relevant cell types for evaluation of antiviral drugs. Our data provide new insights into rational drug combinations for effective treatment of a virus that affects multiple organ systems. One-sentence summary: Rational treatment strategies for SARS-CoV-2 derived from human PSC models.

Trafficking regulator of GLUT4-1 (TRARG1) is a GSK3 substrate.

Trafficking regulator of GLUT4-1, TRARG1, positively regulates insulin-stimulated GLUT4 trafficking and insulin sensitivity. However, the mechanism(s) by which this occurs remain(s) unclear. Using biochemical and mass spectrometry analyses we found that TRARG1 is dephosphorylated in response to insulin in a PI3K/Akt-dependent manner and is a novel substrate for GSK3. Priming phosphorylation of murine TRARG1 at serine 84 allows for GSK3-directed phosphorylation at serines 72, 76 and 80. A similar pattern of phosphorylation was observed in human TRARG1, suggesting that our findings are translatable to human TRARG1. Pharmacological inhibition of GSK3 increased cell surface GLUT4 in cells stimulated with a submaximal insulin dose, and this was impaired following Trarg1 knockdown, suggesting that TRARG1 acts as a GSK3-mediated regulator in GLUT4 trafficking. These data place TRARG1 within the insulin signaling network and provide insights into how GSK3 regulates GLUT4 trafficking in adipocytes.

Environmental control of Pub1 (NEDD4 family E3 ligase) in Schizosaccharomyces pombe is regulated by TORC2 and Gsk3.

Cells respond to changing nutrient environments by adjusting the abundance of surface nutrient transporters and receptors. This can be achieved by modulating ubiquitin-dependent endocytosis, which in part is regulated by the NEDD4 family of E3 ligases. Here we report novel regulation of Pub1, a fission yeast Schizosaccharomyces pombe member of the NEDD4-family of E3 ligases. We show that nitrogen stress inhibits Pub1 function, thereby increasing the abundance of the amino acid transporter Aat1 at the plasma membrane and enhancing sensitivity to the toxic arginine analogue canavanine. We show that TOR complex 2 (TORC2) signalling negatively regulates Pub1, thus TORC2 mutants under nutrient stress have decreased Aat1 at the plasma membrane and are resistant to canavanine. Inhibition of TORC2 signalling increases Pub1 phosphorylation, and this is dependent on Gsk3 activity. Addition of the Tor inhibitor Torin1 increases phosphorylation of Pub1 at serine 199 (S199) by 2.5-fold, and Pub1 protein levels in S199A phospho-ablated mutants are reduced. S199 is conserved in NEDD4 and is located immediately upstream of a WW domain required for protein interaction. Together, we describe how the major TORC2 nutrient-sensing signalling network regulates environmental control of Pub1 to modulate the abundance of nutrient transporters.

Personalized phosphoproteomics identifies functional signaling.

Protein phosphorylation dynamically integrates environmental and cellular information to control biological processes. Identifying functional phosphorylation amongst the thousands of phosphosites regulated by a perturbation at a global scale is a major challenge. Here we introduce 'personalized phosphoproteomics', a combination of experimental and computational analyses to link signaling with biological function by utilizing human phenotypic variance. We measure individual subject phosphoproteome responses to interventions with corresponding phenotypes measured in parallel. Applying this approach to investigate how exercise potentiates insulin signaling in human skeletal muscle, we identify both known and previously unidentified phosphosites on proteins involved in glucose metabolism. This includes a cooperative relationship between mTOR and AMPK whereby the former directly phosphorylates the latter on S377, for which we find a role in metabolic regulation. These results establish personalized phosphoproteomics as a general approach for investigating the signal transduction underlying complex biology.

Proteomic pathways to metabolic disease and type 2 diabetes in the pancreatic islet.

Pancreatic islets are essential for maintaining physiological blood glucose levels, and declining islet function is a hallmark of type 2 diabetes. We employ mass spectrometry-based proteomics to systematically analyze islets from 9 genetic or diet-induced mouse models representing a broad cross-section of metabolic health. Quantifying the islet proteome to a depth of >11,500 proteins, this study represents the most detailed analysis of mouse islet proteins to date. Our data highlight that the majority of islet proteins are expressed in all strains and diets, but more than half of the proteins vary in expression levels, principally due to genetics. Associating these varied protein expression levels on an individual animal basis with individual phenotypic measures reveals islet mitochondrial function as a major positive indicator of metabolic health regardless of strain. This compendium of strain-specific and dietary changes to mouse islet proteomes represents a comprehensive resource for basic and translational islet cell biology.

MaxDIA enables library-based and library-free data-independent acquisition proteomics.

MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA-hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data, and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA's bootstrap DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies-BoxCar acquisition and trapped ion mobility spectrometry-both lead to deep and accurate proteome quantification.

Akt phosphorylates insulin receptor substrate to limit PI3K-mediated PIP3 synthesis.

The phosphoinositide 3-kinase (PI3K)-Akt network is tightly controlled by feedback mechanisms that regulate signal flow and ensure signal fidelity. A rapid overshoot in insulin-stimulated recruitment of Akt to the plasma membrane has previously been reported, which is indicative of negative feedback operating on acute timescales. Here, we show that Akt itself engages this negative feedback by phosphorylating insulin receptor substrate (IRS) 1 and 2 on a number of residues. Phosphorylation results in the depletion of plasma membrane-localised IRS1/2, reducing the pool available for interaction with the insulin receptor. Together these events limit plasma membrane-associated PI3K and phosphatidylinositol (3,4,5)-trisphosphate (PIP3) synthesis. We identified two Akt-dependent phosphorylation sites in IRS2 at S306 (S303 in mouse) and S577 (S573 in mouse) that are key drivers of this negative feedback. These findings establish a novel mechanism by which the kinase Akt acutely controls PIP3 abundance, through post-translational modification of the IRS scaffold.

For the body to work properly, cells must constantly 'talk' to each other using signalling molecules. Receiving a chemical signal triggers a series of molecular events in a cell, a so-called 'signal transduction pathway' that connects a signal with a precise outcome. Disturbing cell signalling can trigger disease, and strict control mechanisms are therefore in place to ensure that communication does not break down or become erratic. For instance, just as a thermostat turns off the heater once the right temperature is reached, negative feedback mechanisms in cells switch off signal transduction pathways when the desired outcome has been achieved. The hormone insulin is a signal for growth that increases in the body following a meal to promote the storage of excess blood glucose (sugar) in muscle and fat cells. The hormone binds to insulin receptors at the cell surface and switches on a signal transduction pathway that makes the cell take up glucose from the bloodstream. If the signal is not engaged diseases such as diabetes develop. Conversely, if the signal cannot be adequately switched of cancer can develop. Determining exactly how insulin works would help to understand these diseases better and to develop new treatments. Kearney et al. therefore set out to examine the biochemical 'fail-safes' that control insulin signalling. Experiments using computer simulations of the insulin signalling pathway revealed a potential new mechanism for negative feedback, which centred on a molecule known as Akt. The models predicted that if the negative feedback were removed, then Akt would become hyperactive and accumulate at the cell's surface after stimulation with insulin. Further manipulation of the 'virtual' insulin signalling pathway and studies of live cells in culture confirmed that this was indeed the case. The cell biology experiments also showed how Akt, once at the cell surface, was able to engage the negative feedback and shut down further insulin signalling. Akt did this by inactivating a protein required to pass the signal from the insulin receptor to the rest of the cell. Overall, this work helps to understand cell communication by revealing a previously unknown, and critical component of the insulin signalling pathway.

A Two-Dimensional Metallacycle Cross-Linked Switchable Polymer for Fast and Highly Efficient Phosphorylated Peptide Enrichment.

The selective and efficient capture of phosphopeptides is critical for comprehensive and in-depth phosphoproteome analysis. Here we report a new switchable two-dimensional (2D) supramolecular polymer that serves as an ideal platform for the enrichment of phosphopeptides. A well-defined, positively charged metallacycle incorporated into the polymer endows the resultant polymer with a high affinity for phosphopeptides. Importantly, the stimuli-responsive nature of the polymer facilitates switchable binding affinity of phosphopeptides, thus resulting in an excellent performance in phosphopeptide enrichment and separation from model proteins. The polymer has a high enrichment capacity (165 mg/g) and detection sensitivity (2 fmol), high enrichment recovery (88%), excellent specificity, and rapid enrichment and separation properties. Additionally, we have demonstrated the capture of phosphopeptides from the tryptic digest of real biosamples, thus illustrating the potential of this polymeric material in phosphoproteomic studies.

BET inhibition blocks inflammation-induced cardiac dysfunction and SARS-CoV-2 infection.

Cardiac injury and dysfunction occur in COVID-19 patients and increase the risk of mortality. Causes are ill defined but could be through direct cardiac infection and/or inflammation-induced dysfunction. To identify mechanisms and cardio-protective drugs, we use a state-of-the-art pipeline combining human cardiac organoids with phosphoproteomics and single nuclei RNA sequencing. We identify an inflammatory "cytokine-storm", a cocktail of interferon gamma, interleukin 1ß, and poly(I:C), induced diastolic dysfunction. Bromodomain-containing protein 4 is activated along with a viral response that is consistent in both human cardiac organoids (hCOs) and hearts of SARS-CoV-2-infected K18-hACE2 mice. Bromodomain and extraterminal family inhibitors (BETi) recover dysfunction in hCOs and completely prevent cardiac dysfunction and death in a mouse cytokine-storm model. Additionally, BETi decreases transcription of genes in the viral response, decreases ACE2 expression, and reduces SARS-CoV-2 infection of cardiomyocytes. Together, BETi, including the Food and Drug Administration (FDA) breakthrough designated drug, apabetalone, are promising candidates to prevent COVID-19 mediated cardiac damage.