Deep mutational scanning of the plasminogen activator inhibitor-1 functional landscape

Variant effect predictor correlation with functional assays is reflective of clinical classification performance

BACKGROUND

Understanding the relationship between protein sequence and function is crucial for accurate classification of missense variants. Variant effect predictors (VEPs) play a vital role in deciphering this complex relationship, yet evaluating their performance remains challenging for several reasons, including data circularity, where the same or related data is used for training and assessment. High-throughput experimental strategies like deep mutational scanning (DMS) offer a promising solution.

RESULTS

In this study, we extend upon our previous benchmarking approach, assessing the performance of 97 VEPs using missense DMS measurements from 36 different human proteins. In addition, a new pairwise, VEP-centric approach mitigates the impact of missing predictions on overall performance comparison. We observe a strong correspondence between VEP performance in DMS-based benchmarks and clinical variant classification, especially for predictors that have not been directly trained on human clinical variants.

CONCLUSIONS

Our results suggest that comparing VEP performance against diverse functional assays represents a reliable strategy for assessing their relative performance in clinical variant classification. However, major challenges in clinical interpretation of VEP scores persist, highlighting the need for further research to fully leverage computational predictors for genetic diagnosis. We also address practical considerations for end users in terms of choice of methodology.

High-throughput amino acid-level characterization of the interactions of plasminogen activator inhibitor-1 with variably divergent proteases

While members of large paralogous protein families share structural features, their functional niches often diverge significantly. Serine protease inhibitors (SERPINs), whose members typically function as covalent inhibitors of serine proteases, are one such family. Plasminogen activator inhibitor-1 (PAI-1) is a prototypic SERPIN, which canonically inhibits tissue- and urokinase-type plasminogen activators (tPA and uPA) to regulate fibrinolysis. PAI-1 has been shown to also inhibit other serine proteases, including coagulation factor XIIa (FXIIa) and transmembrane serine protease 2 (TMPRSS2). The structural determinants of PAI-1 inhibitory function toward these non-canonical protease targets, and the biological significance of these functions, are unknown. We applied deep mutational scanning (DMS) to assess the effects of ~80% of all possible single-amino acid substitutions in PAI-1 on its ability to inhibit three putative serine protease targets (uPA, FXIIa, and TMPRSS2). Selection with each target protease generated a unique PAI-1 mutational landscape, with the determinants of protease specificity distributed throughout PAI-1's primary sequence. Next, we conducted a comparative analysis of extant orthologous sequences, demonstrating that key residues modulating PAI-1 inhibition of uPA and FXIIa, but not TMPRSS2, are maintained by purifying selection (also referred to as "negative selection"). PAI-1's activity toward FXIIa may reflect how protease evolutionary relationships predict SERPIN functional divergence, which we support via a cophylogenetic analysis of secreted SERPINs and their cognate serine proteases. This work provides insight into the functional diversification of SERPINs and lays the framework for extending these studies to other proteases and their regulators.

Immunomodulatory Significance of Mast Cell Exosomes (MC-EXOs) in Immune Response Coordination

Mast cells (MCs) communicate with other cells by direct cell-to-cell interaction, secreting mediators, and releasing exosomes (EXOs). MC-exosomes (MC-EXOs) contain proteins, lipids, mRNAs, and noncoding RNAs (ncRNAs), exhibit typical EXO markers such as heat shock proteins, tetraspanins, tumor susceptibility gene 101 protein (TSG101), and ALG-2-interacting protein X (ALIX), and are released constitutively or following MC degranulation. MC-EXOs also have signature MC markers like FcεRI and KIT (CD117), which allows for their identification and comparison with other EXO populations. Following their release, MC-EXOs may interact with the recipient cell(s) directly or be internalized and then release their protein and nucleic acid content. This may contribute to the regulation of immune responses and other biological processes and reprogramming of recipient cells. MC-EXO proteins may integrate and become a functional part of the recipient cell membrane. The mRNA transferred by MC-EXOs is functional and the transfer of exosomal RNA to other MCs results in the expression of donor MC proteins in the recipient MCs. Moreover, MCs may function as the recipients of EXOs that are released by other non-immune and immune cells, altering the secretome of MCs. In this review, we focus on how MC-EXOs modulate the biology of other cells and vice versa; and we highlight the role of MC-EXOs in the pathogenesis of allergic and non-allergic diseases.

A novel platelets-related gene signature for predicting prognosis, immune features and drug sensitivity in gastric cancer

Background

Platelets can dynamically regulate tumor development and progression. Nevertheless, research on the predictive value and specific roles of platelets in gastric cancer (GC) is limited. This research aims to establish a predictive platelets-related gene signature in GC with prognostic and therapeutic implications.

Methods

We downloaded the transcriptome data and clinical materials of GC patients (n=378) from The Cancer Genome Atlas (TCGA) database. Prognostic platelets-related genes screened by univariate Cox regression were included in Least Absolute Shrinkage and Selection Operator (LASSO) analysis to construct a risk model. Kaplan-Meier curves and receiver operating characteristic curves (ROCs) were performed in the TCGA cohort and three independent validation cohorts. A nomogram integrating the risk score and clinicopathological features was constructed. Functional enrichment and tumor microenvironment (TME) analyses were performed. Drug sensitivity prediction was conducted through The Cancer Therapeutics Response Portal (CTRP) database. Finally, the expression of ten signature genes was validated by quantitative real-time PCR (qRT-PCR).

Results

A ten-gene (SERPINE1, ANXA5, DGKQ, PTPN6, F5, DGKB, PCDH7, GNG11, APOA1, and TF) predictive risk model was finally constructed. Patients were categorized as high- or low-risk using median risk score as the threshold. The area under the ROC curve (AUC) values for the 1-, 2-, and 3-year overall survival (OS) in the training cohort were 0.670, 0.695, and 0.707, respectively. Survival analysis showed a better OS in low-risk patients in the training and validation cohorts. The AUCs of the nomogram for predicting 1-, 2-, and 3-year OS were 0.708, 0.763, and 0.742, respectively. TME analyses revealed a higher M2 macrophage infiltration and an immunosuppressive TME in the high-risk group. Furthermore, High-risk patients tended to be more sensitive to thalidomide, MK-0752, and BRD-K17060750.

Conclusion

The novel platelets-related genes signature we identified could be used for prognosis and treatment prediction in GC.

High-throughput amino acid-level characterization of the interactions of plasminogen activator inhibitor-1 with variably divergent proteases

While members of large paralogous protein families share structural features, their functional niches often diverge significantly. Serine protease inhibitors (SERPINs), whose members typically function as covalent inhibitors of serine proteases, are one such family. Plasminogen activator inhibitor-1 (PAI-1) is a prototypic SERPIN, which canonically inhibits tissue-and urokinase-type plasminogen activators (tPA and uPA) to regulate fibrinolysis. PAI-1 has been shown to also inhibit other serine proteases, including coagulation factor XIIa (FXIIa) and transmembrane serine protease 2 (TMPRSS2). The structural determinants of PAI-1 inhibitory function toward these non-canonical protease targets, and the biological significance of these functions, are unknown. We applied deep mutational scanning (DMS) to assess the effects of ∼80% of all possible single amino acid substitutions in PAI-1 on its ability to inhibit three putative serine protease targets (uPA, FXIIa, and TMPRSS2). Selection with each target protease generated a unique PAI-1 mutational landscape, with the determinants of protease specificity distributed throughout PAI-1's primary sequence. Next, we conducted a comparative analysis of extant orthologous sequences, demonstrating that key residues modulating PAI-1 inhibition of uPA and FXIIa, but not TMPRSS2, are maintained by purifying selection. PAI-1's activity toward FXIIa may reflect how protease evolutionary relationships predict SERPIN functional divergence, which we support via a cophylogenetic analysis of all secreted SERPINs and their cognate serine proteases. This work provides insight into the functional diversification of SERPINs and lays the framework for extending these studies to other proteases and their regulators.

Venous thromboembolic disease genetics: from variants to function

Venous thromboembolic disease (VTE) is a prevalent and potentially life-threatening vascular disease, including both deep vein thrombosis and pulmonary embolism. This review will focus on recent insights into the heritable factors that influence an individual's risk for VTE. Here, we will explore not only the discovery of new genetic risk variants but also the importance of functional characterization of these variants. These genome-wide studies should lead to a better understanding of the biological role of genes inside and outside of the canonical coagulation system in thrombus formation and lead to an improved ability to predict an individual's risk of VTE. Further understanding of the molecular mechanisms altered by genetic variation in VTE risk will be accelerated by further human genome sequencing efforts and the use of functional genetic screens.

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.

Administration of spermidine attenuates concanavalin A-induced liver injury

A previous study revealed that treatment with the anticoagulant heparin attenuated concanavalin A (ConA)-induced liver injury. The administration of spermidine (SPD) increased urokinase-type plasminogen activator (uPA) levels in the serum. uPA is clinically used for the treatment of some thrombotic diseases such as cerebral infarction. Therefore, SPD may attenuate ConA-induced liver injury that is exacerbated by blood coagulation. The present study investigated the effect of SPD on liver injury in mice with autoimmune hepatopathy induced by ConA. A model of liver injury was created by intravenous injection of ConA into mice. SPD was administered in free drinking water and was biochemically and pathologically examined over time. The administration of SPD to ConA-treated mice significantly reduced liver injury. However, SPD treatment upregulated the mRNA expression of TNF-α and IFN-ϒ in the livers of ConA-treated mice. In contrast, the mRNA expression of tissue factor in the livers of SPD-treated mice was decreased after ConA injection. The frequency of lymphocytes and lymphocyte activation were not affected by SPD administration in ConA-treated mice. SPD treatment increased uPA levels in the serum and decreased the level of D-dimer in ConA-treated mice. Moreover, SPD decreased fibrin in the livers of ConA-treated mice. These results indicated that SPD treatment increased anticoagulant ability by increasing of uPA and attenuated ConA-induced liver injury.

Deep mutational scanning and massively parallel kinetics of plasminogen activator inhibitor-1 functional stability to probe its latency transition

Plasminogen activator inhibitor-1 (PAI-1), a member of the serine protease inhibitor superfamily of proteins, is unique among serine protease inhibitors for exhibiting a spontaneous conformational change to a latent or inactive state. The functional half-life for this transition at physiologic temperature and pH is ∼1 to 2 h. To better understand the molecular mechanisms underlying this transition, we now report on the analysis of a comprehensive PAI-1 variant library expressed on filamentous phage and selected for functional stability after 48 h at 37 °C. Of the 7201 possible single amino acid substitutions in PAI-1, we identified 439 that increased the functional stability of PAI-1 beyond that of the WT protein. We also found 1549 single amino acid substitutions that retained inhibitory activity toward the canonical target protease of PAI-1 (urokinase-like plasminogen activator), whereas exhibiting functional stability less than or equal to that of WT PAI-1. Missense mutations that increase PAI-1 functional stability are concentrated in highly flexible regions within the PAI-1 structure. Finally, we developed a method for simultaneously measuring the functional half-lives of hundreds of PAI-1 variants in a multiplexed, massively parallel manner, quantifying the functional half-lives for 697 single missense variants of PAI-1 by this approach. Overall, these findings provide novel insight into the mechanisms underlying the latency transition of PAI-1 and provide a database for interpreting human PAI-1 genetic variants.

Current and Future Approaches to Classify VUSs in LGMD-Related Genes

Next-generation sequencing (NGS) has revealed large numbers of genetic variants in LGMD-related genes, with most of them classified as variants of uncertain significance (VUSs). VUSs are genetic changes with unknown pathological impact and present a major challenge in genetic test interpretation and disease diagnosis. Understanding the phenotypic consequences of VUSs can provide clinical guidance regarding LGMD risk and therapy. In this review, we provide a brief overview of the subtypes of LGMD, disease diagnosis, current classification systems for investigating VUSs, and a potential deep mutational scanning approach to classify VUSs in LGMD-related genes.