The Autophagy Receptor TAX1BP1 (T6BP) improves antigen presentation by MHC‐II molecules

CD4⁺ T lymphocytes play a major role in the establishment and maintenance of immunity. They are activated by antigenic peptides derived from extracellular or newly synthesized (endogenous) proteins presented by the MHC‐II molecules. The pathways leading to endogenous MHC‐II presentation remain poorly characterized. We demonstrate here that the autophagy receptor, T6BP, influences both autophagy‐dependent and ‐independent endogenous presentation of HIV‐ and HCMV‐derived peptides. By studying the immunopeptidome of MHC‐II molecules, we show that T6BP affects both the quantity and quality of peptides presented. T6BP silencing induces the mislocalization of the MHC‐II‐loading compartments and rapid degradation of the invariant chain (CD74) without altering the expression and internalization kinetics of MHC‐II molecules. Defining the interactome of T6BP, we identify calnexin as a T6BP partner. We show that the calnexin cytosolic tail is required for this interaction. Remarkably, calnexin silencing replicates the functional consequences of T6BP silencing: decreased CD4⁺ T cell activation and exacerbated CD74 degradation. Altogether, we unravel T6BP as a key player of the MHC‐II‐restricted endogenous presentation pathway, and we propose one potential mechanism of action.     

High‐throughput identification of conditional MHCI ligands and scaled‐up production of conditional MHCI complexes

Despite the need to monitor the impact of Cancer Immunotherapy (CI)/Immuno‐Oncology (IO) therapeutics on neoantigen‐specific T‐cell responses, very few clinical programs incorporate this aspect of immune monitoring due to the challenges in high‐throughput (HTP) generation of Major Histocompatibility Complex Class I (MHCI) tetramers across a wide range of HLA alleles. This limitation was recently addressed through the development of MHCI complexes with peptides containing a nonnatural UV cleavable amino acid (conditional MHCI ligands) that enabled HTP peptide exchange upon UV exposure. Despite this advancement, the number of alleles with known conditional MHCI ligands is limited. We developed a novel workflow to enable identification and validation of conditional MHCI ligands across a range of HLA alleles. First, known peptide binders were screened via an enzyme‐linked immunosorbent assay (ELISA) assay. Conditional MHCI ligands were designed using the highest‐performing peptides and evaluated in the same ELISA assay. The top performers were then selected for scale‐up production. Next‐generation analytical techniques (LC/MS, SEC‐MALS, and 2D LC/MS) were used to characterize the complex after refolding with the conditional MHCI ligands. Finally, we used 2D LC/MS to evaluate peptide exchange with these scaled‐up conditional MHCI complexes after UV exposure with validated peptide binders. Successful peptide exchange was observed for all conditional MHCI ligands upon UV exposure, validating our screening approach. This approach has the potential to be broadly applied and enable HTP generation of MHCI monomers and tetramers across a wider range of HLA alleles, which could be critical to enabling the use of MHCI tetramers to monitor neoantigen‐specific T‐cells in the clinic.     

The B domain of protein A retains residual structures in 6 M guanidinium chloride as revealed by hydrogen/deuterium‐exchange NMR spectroscopy

The characterization of residual structures persistent in unfolded proteins is an important issue in studies of protein folding, because the residual structures present, if any, may form a folding initiation site and guide the subsequent folding reactions. Here, we studied the residual structures of the isolated B domain (BDPA) of staphylococcal protein A in 6 M guanidinium chloride. BDPA is a small three‐helix‐bundle protein, and until recently its folding/unfolding reaction has been treated as a simple two‐state process between the native and the fully unfolded states. We employed a dimethylsulfoxide (DMSO)‐quenched hydrogen/deuterium (H/D)‐exchange 2D NMR techniques with the use of spin desalting columns, which allowed us to investigate the H/D‐exchange behavior of individually identified peptide amide (NH) protons. We obtained H/D‐exchange protection factors of the 21 NH protons that form an α‐helical hydrogen bond in the native structure, and the majority of these NH protons were significantly protected with a protection factor of 2.0–5.2 in 6 M guanidinium chloride, strongly suggesting that these weakly protected NH protons form much stronger hydrogen bonds under native folding conditions. The results can be used to deduce the structure of an early folding intermediate, when such an intermediate is shown by other methods. Among three native helical regions, the third helix in the C‐terminal side was highly protected and stabilized by side‐chain salt bridges, probably acting as the folding initiation site of BDPA. The present results are discussed in relation to previous experimental and computational findings on the folding mechanisms of BDPA.     

Aging influences the cardiac macrophage phenotype and function during steady state and during inflammation

Aging‐mediated immune dysregulation affects the normal cardiac immune cell phenotypes and functions, resulting in cardiac distress. During cardiac inflammation, immune activation is critical for mounting the regenerative responses to maintain normal heart function. We investigated the impact of aging on myeloid cell phenotype and function during cardiac inflammation induced by a sub‐lethal dose of LPS. Our data show that hearts of old mice contain more myeloid cells than the hearts of young mice. However, while the number of monocytic‐derived suppressor cells did not differ between young and old mice, monocytic‐derived suppressor cells from old mice were less able to suppress T‐cell proliferation. Since cardiac resident macrophages (CRMs) are important for immune surveillance, clearance of dead cells, and tissue repair, we focused our studies on CRMs phenotype and function during steady state and LPS treatment. In the steady state, we observed significantly more MHC‐II^low and MHC‐II^high CRMs in the hearts of old mice; however, these populations were decreased in both young and aged mice upon LPS treatment and the decrease in CRM populations correlated with defects in cardiac electrical activity. Notably, mice treated with a liver X receptor (LXR) agonist showed an increase in MerTK expression in CRMs of both young and old mice, which resulted in the reversal of cardiac electrical dysfunction caused by lipopolysaccharide (LPS). We conclude that aging alters the phenotype of CRMs, which contributes to the dysregulation of cardiac electrical dysfunction during infection in aged mice.     

Inhibition of IRGM establishes a robust antiviral immune state to restrict pathogenic viruses

The type I interferon (IFN) response is the major host arsenal against invading viruses. IRGM is a negative regulator of IFN responses under basal conditions. However, the role of human IRGM during viral infection has remained unclear. In this study, we show that IRGM expression is increased upon viral infection. IFN responses induced by viral PAMPs are negatively regulated by IRGM. Conversely, IRGM depletion results in a robust induction of key viral restriction factors including IFITMs, APOBECs, SAMHD1, tetherin, viperin, and HERC5/6. Additionally, antiviral processes such as MHC‐I antigen presentation and stress granule signaling are enhanced in IRGM‐deficient cells, indicating a robust cell‐intrinsic antiviral immune state. Consistently, IRGM‐depleted cells are resistant to the infection with seven viruses from five different families, including Togaviridae, Herpesviridae, Flaviviverdae, Rhabdoviridae, and Coronaviridae. Moreover, we show that Irgm1 knockout mice are highly resistant to chikungunya virus (CHIKV) infection. Altogether, our work highlights IRGM as a broad therapeutic target to promote defense against a large number of human viruses, including SARS‐CoV‐2, CHIKV, and Zika virus.     

Tertiary motifs as building blocks for the design of protein‐binding peptides

Despite advances in protein engineering, the de novo design of small proteins or peptides that bind to a desired target remains a difficult task. Most computational methods search for binder structures in a library of candidate scaffolds, which can lead to designs with poor target complementarity and low success rates. Instead of choosing from pre‐defined scaffolds, we propose that custom peptide structures can be constructed to complement a target surface. Our method mines tertiary motifs (TERMs) from known structures to identify surface‐complementing fragments or “seeds.” We combine seeds that satisfy geometric overlap criteria to generate peptide backbones and score the backbones to identify the most likely binding structures. We found that TERM‐based seeds can describe known binding structures with high resolution: the vast majority of peptide binders from 486 peptide‐protein complexes can be covered by seeds generated from single‐chain structures. Furthermore, we demonstrate that known peptide structures can be reconstructed with high accuracy from peptide‐covering seeds. As a proof of concept, we used our method to design 100 peptide binders of TRAF6, seven of which were predicted by Rosetta to form higher‐quality interfaces than a native binder. The designed peptides interact with distinct sites on TRAF6, including the native peptide‐binding site. These results demonstrate that known peptide‐binding structures can be constructed from TERMs in single‐chain structures and suggest that TERM information can be applied to efficiently design novel target‐complementing binders.     

Characterizing heterogeneity of non‐small cell lung tumour microenvironment to identify signature prognostic genes

Growing evidence has highlighted the immune response as an important feature of carcinogenesis and therapeutic efficacy in non‐small cell lung cancer (NSCLC). This study focused on the characterization of immune infiltration profiling in patients with NSCLC and its correlation with survival outcome. All TCGA samples were divided into three heterogeneous clusters based on immune cell profiles: cluster 1 (''low infiltration'' cluster), cluster 2 (''heterogeneous infiltration'' cluster) and cluster 3 (''high infiltration'' cluster). The immune cells were responsible for a significantly favourable prognosis for the ''high infiltration'' community. Cluster 1 had the lowest cytotoxic activity, tumour‐infiltrating lymphocytes and interferon‐gamma (IFN‐γ), as well as immune checkpoint molecules expressions. In addition, MHC‐I and immune co‐stimulator were also found to have lower cluster 1 expressions, indicating a possible immune escape mechanism. A total of 43 differentially expressed genes (DEGs) that overlapped among the groups were determined based on three clusters. Finally, based on a univariate Cox regression model, prognostic immune‐related genes were identified and combined to construct a risk score model able to predict overall survival (OS) rates in the validation datasets.     

Nicking and fragmentation are responsible for α‐lactalbumin amyloid fibril formation at acidic pH and elevated temperature

Amyloid fibrils are ordered aggregates that may be formed from disordered, partially unfolded, and fragments of proteins and peptides. There are several diseases, which are due to the formation and deposition of insoluble β‐sheet protein aggregates in various tissue, collectively known as amyloidosis. Here, we have used bovine α‐lactalbumin as a model protein to understand the mechanism of amyloid fibril formation at pH 1.6 and 65°C under non‐reducing conditions. Amyloid fibril formation is confirmed by Thioflavin T fluorescence and atomic force microscopy (AFM). Our finding demonstrates that hydrolysis of peptide bonds occurs under these conditions, which results in nicking and fragmentation. The nicking and fragmentation have been confirmed on non‐reducing and reducing gel. We have identified the fragments by matrix‐assisted laser desorption ionization‐time of flight (MALDI‐TOF) mass spectrometry. The fragmentation may initiate nucleation as it coincides with AFM images. Conformational changes associated with monomer resulting in fibrillation are shown by circular dichroism and Raman spectroscopy. The current study highlights the importance of nicking and fragmentation in amyloid fibril formation, which may help understand the role of acidic pH and proteolysis under in vivo conditions in the initiation of amyloid fibril formation.     

Influence of pH value and salts on the adsorption of lysozyme in mixed‐mode chromatography

Mixed‐mode chromatography (MMC) is an interesting technique for challenging protein separation processes which typically combines adsorption mechanisms of ion exchange (IEC) and hydrophobic interaction chromatography (HIC). Adsorption equilibria in MMC depend on multiple parameters but systematic studies on their influence are scarce. In the present work, the influence of the pH value and ionic strengths up to 3000 mM of four technically relevant salts (sodium chloride, sodium sulfate, ammonium chloride, and ammonium sulfate) on the lysozyme adsorption on the mixed‐mode resin Toyopearl MX‐Trp‐650M was studied systematically at 25℃. Equilibrium adsorption isotherms at pH 5.0 and 6.0 were measured and compared to experimental data at pH 7.0 from previous work. For all pH values, an exponential decay of the lysozyme loading with increasing ionic strength was observed. The influence of the pH value was found to depend significantly on the ionic strength with the strongest influence at low ionic strengths where increasing pH values lead to decreasing lysozyme loadings. Furthermore, a mathematical model that describes the influence of salts and the pH value on the adsorption of lysozyme in MMC is presented. The model enables predicting adsorption isotherms of lysozyme on Toyopearl MX‐Trp‐650M for a broad range of technically relevant conditions.     

The cellular modifier MOAG‐4/SERF drives amyloid formation through charge complementation

While aggregation‐prone proteins are known to accelerate aging and cause age‐related diseases, the cellular mechanisms that drive their cytotoxicity remain unresolved. The orthologous proteins MOAG‐4, SERF1A, and SERF2 have recently been identified as cellular modifiers of such proteotoxicity. Using a peptide array screening approach on human amyloidogenic proteins, we found that SERF2 interacted with protein segments enriched in negatively charged and hydrophobic, aromatic amino acids. The absence of such segments, or the neutralization of the positive charge in SERF2, prevented these interactions and abolished the amyloid‐promoting activity of SERF2. In protein aggregation models in the nematode worm Caenorhabditis elegans, protein aggregation and toxicity were suppressed by mutating the endogenous locus of MOAG‐4 to neutralize charge. Our data indicate that MOAG‐4 and SERF2 drive protein aggregation and toxicity by interactions with negatively charged segments in aggregation‐prone proteins. Such charge interactions might accelerate primary nucleation of amyloid by initiating structural changes and by decreasing colloidal stability. Our study points at charge interactions between cellular modifiers and amyloidogenic proteins as potential targets for interventions to reduce age‐related protein toxicity.     

C‐terminal deletion‐induced condensation sequesters AID from IgH targets in immunodeficiency

In activated B cells, activation‐induced cytidine deaminase (AID) generates programmed DNA lesions required for antibody class switch recombination (CSR), which may also threaten genome integrity. AID dynamically shuttles between cytoplasm and nucleus, and the majority stays in the cytoplasm due to active nuclear export mediated by its C‐terminal peptide. In immunodeficient‐patient cells expressing mutant AID lacking its C‐terminus, a catalytically active AID‐delC protein accumulates in the nucleus but nevertheless fails to support CSR. To resolve this apparent paradox, we dissected the function of AID‐delC proteins in the CSR process and found that they cannot efficiently target antibody genes. We demonstrate that AID‐delC proteins form condensates both in vivo and in vitro, dependent on its N‐terminus and on a surface arginine‐rich patch. Co‐expression of AID‐delC and wild‐type AID leads to an unbalanced nuclear AID‐delC/AID ratio, with AID‐delC proteins able to trap wild‐type AID in condensates, resulting in a dominant‐negative phenotype that could contribute to immunodeficiency. The co‐condensation model of mutant and wild‐type proteins could be an alternative explanation for the dominant‐negative effect in genetic disorders.     

Fixed or random? On the reliability of mixed‐effects models for a small number of levels in grouping variables

Biological data are often intrinsically hierarchical (e.g., species from different genera, plants within different mountain regions), which made mixed‐effects models a common analysis tool in ecology and evolution because they can account for the non‐independence. Many questions around their practical applications are solved but one is still debated: Should we treat a grouping variable with a low number of levels as a random or fixed effect? In such situations, the variance estimate of the random effect can be imprecise, but it is unknown if this affects statistical power and type I error rates of the fixed effects of interest. Here, we analyzed the consequences of treating a grouping variable with 2–8 levels as fixed or random effect in correctly specified and alternative models (under‐ or overparametrized models). We calculated type I error rates and statistical power for all‐model specifications and quantified the influences of study design on these quantities. We found no influence of model choice on type I error rate and power on the population‐level effect (slope) for random intercept‐only models. However, with varying intercepts and slopes in the data‐generating process, using a random slope and intercept model, and switching to a fixed‐effects model, in case of a singular fit, avoids overconfidence in the results. Additionally, the number and difference between levels strongly influences power and type I error. We conclude that inferring the correct random‐effect structure is of great importance to obtain correct type I error rates. We encourage to start with a mixed‐effects model independent of the number of levels in the grouping variable and switch to a fixed‐effects model only in case of a singular fit. With these recommendations, we allow for more informative choices about study design and data analysis and make ecological inference with mixed‐effects models more robust for small number of levels.     

Plasticity and artificial selection for developmental mode in a poecilogonous sea slug

The contribution of phenotypically plastic traits to evolution depends on the degree of environmental influence on the target of selection (the phenotype) as well as the underlying genetic structure of the trait and plastic response. Likewise, maternal effects can help or hinder evolution through affects to the response to selection. The sacoglossan sea slug Alderia willowi exhibits intraspecific variation for developmental mode (= poecilogony) that is environmentally modulated with populations producing more yolk‐feeding (lecithotrophic) larvae during the summer, and more planktonic‐feeding (planktotrophic) larvae in the winter. I found significant family‐level variation in the reaction norms between 17 maternal families of A. willowi when reared in a split‐brood design in low (16 ppt) versus high (32 ppt) salinity, conditions which mimic seasonal variation in salinity of natural populations. I documented a significant response to selection for lecithotrophic larvae in high and low salinity. The slope of the reaction norm was maintained following one generation of selection for lecithotrophy. When the maternal environment was controlled in the laboratory, I found significant maternal effects, which reduced the response to selection. These results suggest there is standing genetic variation for egg‐mass type in A. willowi, but the ability of selection to act on that variation may depend on the environment in which the phenotype is expressed in preceding generations.     

High‐resolution analysis of the conformational transition of pro‐apoptotic Bak at the lipid membrane

Permeabilization of the outer mitochondrial membrane by pore‐forming Bcl2 proteins is a crucial step for the induction of apoptosis. Despite a large set of data suggesting global conformational changes within pro‐apoptotic Bak during pore formation, high‐resolution structural details in a membrane environment remain sparse. Here, we used NMR and HDX‐MS (Hydrogen deuterium exchange mass spectrometry) in lipid nanodiscs to gain important high‐resolution structural insights into the conformational changes of Bak at the membrane that are dependent on a direct activation by BH3‐only proteins. Furthermore, we determined the first high‐resolution structure of the Bak transmembrane helix. Upon activation, α‐helix 1 in the soluble domain of Bak dissociates from the protein and adopts an unfolded and dynamic potentially membrane‐bound state. In line with this finding, comparative protein folding experiments with Bak and anti‐apoptotic BclxL suggest that α‐helix 1 in Bak is a metastable structural element contributing to its pro‐apoptotic features. Consequently, mutagenesis experiments aimed at stabilizing α‐helix 1 yielded Bak variants with delayed pore‐forming activity. These insights will contribute to a better mechanistic understanding of Bak‐mediated membrane permeabilization.     

Depicting the proton relay network in human aromatase: New insights into the role of the alcohol‐acid pair

Human aromatase is the cytochrome P450 catalyzing the conversion of androgens into estrogens in a three steps reaction essential to maintain steroid hormones balance. Here we report the capture and spectroscopic characterization of its compound I (Cpd I), the main reactive species in cytochromes P450. The typical spectroscopic transitions indicating the formation of Cpd I are detected within 0.8 s when mixing aromatase with meta‐chloroperoxybenzoic acid. The estrogen product is obtained from the same reaction mixture, demonstrating the involvement of Cpd I in aromatization reaction. Site‐directed mutagenesis is applied to the acid‐alcohol pair D309 and T310 and to R192, predicted to be part of the proton relay network. Mutants D309N and R192Q do not lead to Cpd I with an associated loss of activity, confirming that these residues are involved in proton delivery for Cpd I generation. Cpd I is captured for T310A mutant and shows 2.9‐ and 4.4‐fold faster rates of formation and decay, respectively, compared to wild‐type (WT). However, its activity is lower than the WT and a larger amount of H₂O₂ is produced during catalysis, indicating that T310 has an essential role in proton gating for generation of Cpd 0 and Cpd I and for their stabilization. The data provide new evidences on the role of threonine belonging to the conserved “acid‐alcohol” pair and known to be crucial for oxygen activation in cytochromes P450.     

Large‐scale survey and database of high affinity ligands for peptide recognition modules

Many proteins involved in signal transduction contain peptide recognition modules (PRMs) that recognize short linear motifs (SLiMs) within their interaction partners. Here, we used large‐scale peptide‐phage display methods to derive optimal ligands for 163 unique PRMs representing 79 distinct structural families. We combined the new data with previous data that we collected for the large SH3, PDZ, and WW domain families to assemble a database containing 7,984 unique peptide ligands for 500 PRMs representing 82 structural families. For 74 PRMs, we acquired enough new data to map the specificity profiles in detail and derived position weight matrices and binding specificity logos based on multiple peptide ligands. These analyses showed that optimal peptide ligands resembled peptides observed in existing structures of PRM‐ligand complexes, indicating that a large majority of the phage‐derived peptides are likely to target natural peptide‐binding sites and could thus act as inhibitors of natural protein–protein interactions. The complete dataset has been assembled in an online database (http://www.prm‐db.org) that will enable many structural, functional, and biological studies of PRMs and SLiMs.     

Neural network‐derived Potts models for structure‐based protein design using backbone atomic coordinates and tertiary motifs

Designing novel proteins to perform desired functions, such as binding or catalysis, is a major goal in synthetic biology. A variety of computational approaches can aid in this task. An energy‐based framework rooted in the sequence‐structure statistics of tertiary motifs (TERMs) can be used for sequence design on predefined backbones. Neural network models that use backbone coordinate‐derived features provide another way to design new proteins. In this work, we combine the two methods to make neural structure‐based models more suitable for protein design. Specifically, we supplement backbone‐coordinate features with TERM‐derived data, as inputs, and we generate energy functions as outputs. We present two architectures that generate Potts models over the sequence space: TERMinator, which uses both TERM‐based and coordinate‐based information, and COORDinator, which uses only coordinate‐based information. Using these two models, we demonstrate that TERMs can be utilized to improve native sequence recovery performance of neural models. Furthermore, we demonstrate that sequences designed by TERMinator are predicted to fold to their target structures by AlphaFold. Finally, we show that both TERMinator and COORDinator learn notions of energetics, and these methods can be fine‐tuned on experimental data to improve predictions. Our results suggest that using TERM‐based and coordinate‐based features together may be beneficial for protein design and that structure‐based neural models that produce Potts energy tables have utility for flexible applications in protein science.