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Abstract T cell receptors (TCR) are pivotal in mediating tumour cell cytolysis via recognition of mutation-derived tumour neoantigens (neoAgs) presented by major histocompatibility class-I (MHC-I). Understanding the factors governing the emergence of neoAg from somatic mutations is a major focus of current research. However, the structural and cellular determinants controlling TCR recognition of neoAgs remain poorly understood. This study describes the multi-level analysis of a model neoAg from the B16F10 murine melanoma, H2-Db/Hsf2 p.K72N68-76, as well as its cognate TCR 47BE7. Through cellular, molecular and structural studies we demonstrate that the p.K72N mutation enhances H2-Db binding, thereby improving cell surface presentation and stabilizing the TCR 47BE7 epitope. Furthermore, TCR 47BE7 exhibited high functional avidity and selectivity, attributable to a broad, stringent, binding interface enabling recognition of native B16F10 despite low antigen density. Our findings provide insight into the generation of anchor-residue modified neoAg, and emphasize the value of molecular and structural investigations of neoAg in diverse MHC-I contexts for advancing the understanding of neoAg immunogenicity.

ABSTRACT Serological correlates of protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection after vaccination (“vaccine breakthrough”) have been described. However, T cell correlates of protection against breakthrough are incompletely defined, especially the specific contributions of CD4+ and CD8+ T cells. Here, 279 volunteers in the Protective Immunity from T Cells in Healthcare Workers (PITCH) UK cohort study were enrolled in a nested case-control study. Cases were those who tested SARS-CoV-2 PCR or lateral flow device (LFD) positive after two vaccine doses during the Delta-predominant era (n = 32), while controls were those who did not report a positive test or undergo anti-nucleocapsid immunoglobulin G (IgG) seroconversion during this period (n = 247). Previous SARS-CoV-2 infection prior to vaccination was associated with reduced odds of vaccine breakthrough. Using samples from 28 d after the second vaccine dose, before all breakthroughs occurred, we observed future cases had lower ancestral spike (S)- and receptor binding domain-specific IgG titers and S1- and S2-specific T cell interferon gamma (IFNγ) responses compared with controls, although these differences did not persist when individuals were stratified according to previous infection status before vaccination. In a subset of matched infection-naïve cases and controls, vaccine breakthrough cases had lower CD4+ and CD8+ IFNγ and tumor necrosis factor (TNF) responses to Delta S peptides compared with controls. For CD8+ responses, this difference appeared to be driven by reduced responses to Delta compared with ancestral peptides among cases; this reduced response to Delta peptides was not observed in controls. Our findings support a protective role for T cells against Delta breakthrough infection. IMPORTANCE Defining correlates of protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine breakthrough infection informs vaccine policy for booster doses and future vaccine designs. Existing studies demonstrate humoral correlates of protection, but the role of T cells in protection is still unclear. In this study, we explore antibody and T cell immune responses associated with protection against Delta variant vaccine breakthrough infection in a well-characterized cohort of UK Healthcare Workers (HCWs). We demonstrate evidence to support a role for CD4+ and CD8+ T cells as well as antibodies against Delta vaccine breakthrough infection. In addition, our results suggest a potential role for cross-reactive T cells in vaccine breakthrough.

Summary: Extracellular signal-regulated kinases 1 and 2 (ERK1/2) are dysregulated in many pervasive diseases. Recently, we discovered that ERK1/2 is oxidized by signal-generated hydrogen peroxide in various cell types. Since the putative sites of oxidation lie within or near ERK1/2’s ligand-binding surfaces, we investigated how oxidation of ERK2 regulates interactions with the model substrates Sub-D and Sub-F. These studies revealed that ERK2 undergoes sulfenylation at C159 on its D-recruitment site surface and that this modification modulates ERK2 activity differentially between substrates. Integrated biochemical, computational, and mutational analyses suggest a plausible mechanism for peroxide-dependent changes in ERK2-substrate interactions. Interestingly, oxidation decreased ERK2’s affinity for some D-site ligands while increasing its affinity for others. Finally, oxidation by signal-generated peroxide enhanced ERK1/2’s ability to phosphorylate ribosomal S6 kinase A1 (RSK1) in HeLa cells. Together, these studies lay the foundation for examining crosstalk between redox- and phosphorylation-dependent signaling at the level of kinase-substrate selection.

Abstract Protein succinylation is an important post-translational modification (PTM) responsible for many vital metabolic activities in cells, including cellular respiration, regulation, and repair. Here, we present a novel approach that combines features from supervised word embedding with embedding from a protein language model called ProtT5-XL-UniRef50 (hereafter termed, ProtT5) in a deep learning framework to predict protein succinylation sites. To our knowledge, this is one of the first attempts to employ embedding from a pre-trained protein language model to predict protein succinylation sites. The proposed model, dubbed LMSuccSite, achieves state-of-the-art results compared to existing methods, with performance scores of 0.36, 0.79, 0.79 for MCC, sensitivity, and specificity, respectively. LMSuccSite is likely to serve as a valuable resource for exploration of succinylation and its role in cellular physiology and disease.

Background Immunotherapies are becoming front-line treatments for many advanced cancers, and combinations of two or more therapies are beginning to be investigated. Based on their individual antitumor capabilities, we sought to determine whether combination oncolytic virus (OV) and radiation therapy (RT) may improve cancer outcomes.Methods To investigate the activity of this combination therapy, we used in vitro mouse and human cancer cell lines as well as a mouse model of skin cancer. After initial results, we further included immune checkpoint blockade, whose addition constituted a triple combination immunotherapy.Results Our findings demonstrate that OV and RT reduce tumor growth via conversion of immunologically ‘cold’ tumors to ‘hot’, via a CD8+ T cell-dependent and IL-1α-dependent mechanism that is associated with increased PD-1/PD-L1 expression, and the triple combination of OV, RT, and PD-1 checkpoint inhibition impedes tumor growth and prolongs survival. Further, we describe the response of a PD-1-refractory patient with cutaneous squamous cell carcinoma who received the triple combination of OV, RT, and immune checkpoint inhibitor (ICI), and went on to experience unexpected, prolonged control and survival. He remains off-treatment and is without evidence of progression for >44 months since study entry.Conclusions Effective systemic antitumor immune response is rarely elicited by a single therapy. In a skin cancer mouse model, we demonstrate improved outcomes with combination OV, RT, and ICI treatment, which is associated with mechanisms involving augmented CD8+ T cell infiltration and IL-1α expression. We report tumor reduction and prolonged survival of a patient with skin cancer treated with combination OV, RT, and ICI. Overall, our data provide strong rationale for combining OV, RT, and ICI for treatment of patients with ICI-refractory skin and potentially other cancers.

Abstract Multicellular patterning of stem‐cell‐derived tissue models is commonly achieved via self‐organizing activities triggered by exogenous morphogenetic stimuli. However, such tissue models are prone to stochastic behavior, limiting the reproducibility of cellular composition and forming non‐physiological architectures. To enhance multicellular patterning in stem cell‐derived tissues, a method for creating complex tissue microenvironments endowed with programmable multimodal mechano‐chemical cues, including conjugated peptides, proteins, morphogens, and Young's moduli defined over a range of stiffnesses is developed. The ability of these cues to spatially guide tissue patterning processes, including mechanosensing and the biochemically driven differentiation of selected cell types, is demonstrated. By rationally designing niches, the authors engineered a bone‐fat assembly from stromal mesenchyme cells and regionalized germ layer tissues from pluripotent stem cells. Through defined niche‐material interactions, mechano‐chemically microstructured niches enable the spatial programming of tissue patterning processes. Mechano‐chemically microstructured cell niches thereby offer an entry point for enhancing the organization and composition of engineered tissues, potentiating structures that better recapitulate their native counterparts.

Summary: Whole-exome sequencing (WES) in the clinic has identified several rare monogenic developmental and epileptic encephalopathies (DEE) caused by ion channel variants. However, WES often fails to provide actionable insight for rare diseases, such as DEEs, due to the challenges of interpreting variants of unknown significance (VUS). Here, we describe a “personalized structural biology” (PSB) approach that leverages recent innovations in the analysis of protein 3D structures to address this challenge. We illustrate this approach in an Undiagnosed Diseases Network (UDN) individual with DEE symptoms and a de novo VUS in KCNC2 (p.V469L), the Kv3.2 voltage-gated potassium channel. A nearby KCNC2 variant (p.V471L) was recently suggested to cause DEE-like phenotypes. Computational structural modeling suggests that both affect protein function. However, despite their proximity, the p.V469L variant is likely to sterically block the channel pore, while the p.V471L variant is likely to stabilize the open state. Biochemical and electrophysiological analyses demonstrate heterogeneous loss-of-function and gain-of-function effects, as well as differential response to 4-aminopyridine treatment. Molecular dynamics simulations illustrate that the pore of the p.V469L variant is more constricted, increasing the energetic barrier for K+ permeation, whereas the p.V471L variant stabilizes the open conformation. Our results implicate variants in KCNC2 as causative for DEE and guide the interpretation of a UDN individual. They further delineate the molecular basis for the heterogeneous clinical phenotypes resulting from two proximal pathogenic variants. This demonstrates how the PSB approach can provide an analytical framework for individualized hypothesis-driven interpretation of protein-coding VUS.

The cyclic AMP-dependent protein kinase (PKA) plays an essential role in the regulation of many important cellular processes and is dysregulated in several pervasive diseases, including diabetes, cardiovascular disease, and various neurodegenerative disorders. Previous studies suggest that the alpha isoform of the catalytic subunit of PKA (PKA-Cα) is oxidized on C199, both in vitro and in situ. However, the molecular consequences of these modifications on PKA-Cα’s substrate selection remain largely unexplored. C199 is located on the P + 1 loop within PKA-Cα’s active site, suggesting that redox modification may affect its kinase activity. Given the proximity of C199 to the substrate binding pocket, we hypothesized that oxidation could differentially alter PKA-Cα’s activity toward its substrates. To this end, we examined the effects of diamide- and H2O2-dependent oxidation on PKA-Cα’s activity toward select peptide and protein substrates using a combination of biochemical (i.e., trans-phosphorylation assays and steady-state kinetics analysis) and biophysical (i.e., surface plasmon resonance and fluorescence polarization assays) strategies. These studies suggest that redox modification of PKA-Cα differentially affects its activity toward different substrates. For instance, we found that diamide-mediated oxidation caused a marked decrease in PKA-Cα’s activity toward some substrates (e.g., Kemptide and CREBtide) while having little effect on others (e.g., Crosstide). In contrast, H2O2-dependent oxidation of PKA-Cα led to an increase in its activity toward each of the substrates at relatively low H2O2 concentrations, with differential effects at higher peroxide concentrations. Together, these studies offer novel insights into crosstalk between redox- and phosphorylation-dependent signaling pathways mediated by PKA. Likewise, since C199 is highly conserved among AGC kinase family members, they also lay the foundation for future studies designed to elucidate the role of redox-dependent modification of kinase substrate selection in physiological and pathological states.

Vilazodone (VLZ) is a drug for the treatment of major depressive disorders that targets the serotonin transporter (SERT). Here, the authors combine pharmacology measurements and cryo-EM structural analysis to characterize VLZ binding to SERT and observe that VLZ exhibits non-competitive inhibition of serotonin transport and binds with nanomolar affinity to an allosteric site in SERT.

Abstract Protein phosphorylation, which is one of the most important post-translational modifications (PTMs), is involved in regulating myriad cellular processes. Herein, we present a novel deep learning based approach for organism-specific protein phosphorylation site prediction in Chlamydomonas reinhardtii, a model algal phototroph. An ensemble model combining convolutional neural networks and long short-term memory (LSTM) achieves the best performance in predicting phosphorylation sites in C. reinhardtii. Deemed Chlamy-EnPhosSite, the measured best AUC and MCC are 0.90 and 0.64 respectively for a combined dataset of serine (S) and threonine (T) in independent testing higher than those measures for other predictors. When applied to the entire C. reinhardtii proteome (totaling 1,809,304 S and T sites), Chlamy-EnPhosSite yielded 499,411 phosphorylated sites with a cut-off value of 0.5 and 237,949 phosphorylated sites with a cut-off value of 0.7. These predictions were compared to an experimental dataset of phosphosites identified by liquid chromatography-tandem mass spectrometry (LC–MS/MS) in a blinded study and approximately 89.69% of 2,663 C. reinhardtii S and T phosphorylation sites were successfully predicted by Chlamy-EnPhosSite at a probability cut-off of 0.5 and 76.83% of sites were successfully identified at a more stringent 0.7 cut-off. Interestingly, Chlamy-EnPhosSite also successfully predicted experimentally confirmed phosphorylation sites in a protein sequence (e.g., RPS6 S245) which did not appear in the training dataset, highlighting prediction accuracy and the power of leveraging predictions to identify biologically relevant PTM sites. These results demonstrate that our method represents a robust and complementary technique for high-throughput phosphorylation site prediction in C. reinhardtii. It has potential to serve as a useful tool to the community. Chlamy-EnPhosSite will contribute to the understanding of how protein phosphorylation influences various biological processes in this important model microalga.

We present a case study of a 20-year-old male with an unknown neurodegenerative disease who was referred to the Undiagnosed Diseases Network Vanderbilt Medical Center site. A previous metabolic panel showed that the patient had a critical deficiency in nicotinamide intermediates that are generated during the biosynthesis of NAD(H). We followed up on these findings by evaluating the patient’s ability to metabolize nicotinamide. We performed a global metabolic profiling analysis of plasma samples that were collected: (1) under normal fed conditions (baseline), (2) after the patient had fasted, and (3) after he was challenged with a 500 mg nasogastric tube bolus of nicotinamide following the fast. Our findings showed that the patient’s nicotinamide N-methyltransferase (NNMT), a key enzyme in NAD(H) biosynthesis and methionine metabolism, was not functional under normal fed or fasting conditions but was restored in response to the nicotinamide challenge. Altered levels of metabolites situated downstream of NNMT and in neighboring biochemical pathways provided further evidence of a baseline defect in NNMT activity. To date, this is the only report of a critical defect in NNMT activity manifesting in adulthood and leading to neurodegenerative disease. Altogether, this study serves as an important reference in the rare disease literature and also demonstrates the utility of metabolomics as a diagnostic tool for uncharacterized metabolic diseases.

Abstract Background Protein succinylation has recently emerged as an important and common post-translation modification (PTM) that occurs on lysine residues. Succinylation is notable both in its size (e.g., at 100 Da, it is one of the larger chemical PTMs) and in its ability to modify the net charge of the modified lysine residue from + 1 to − 1 at physiological pH. The gross local changes that occur in proteins upon succinylation have been shown to correspond with changes in gene activity and to be perturbed by defects in the citric acid cycle. These observations, together with the fact that succinate is generated as a metabolic intermediate during cellular respiration, have led to suggestions that protein succinylation may play a role in the interaction between cellular metabolism and important cellular functions. For instance, succinylation likely represents an important aspect of genomic regulation and repair and may have important consequences in the etiology of a number of disease states. In this study, we developed DeepSuccinylSite, a novel prediction tool that uses deep learning methodology along with embedding to identify succinylation sites in proteins based on their primary structure. Results Using an independent test set of experimentally identified succinylation sites, our method achieved efficiency scores of 79%, 68.7% and 0.48 for sensitivity, specificity and MCC respectively, with an area under the receiver operator characteristic (ROC) curve of 0.8. In side-by-side comparisons with previously described succinylation predictors, DeepSuccinylSite represents a significant improvement in overall accuracy for prediction of succinylation sites. Conclusion Together, these results suggest that our method represents a robust and complementary technique for advanced exploration of protein succinylation.

Malonylation, which has recently emerged as an important lysine modification, regulates diverse biological activities and has been implicated in several pervasive disorders, including cardiovascular disease and cancer. However, conventional global proteomics analysis using tandem mass spectrometry can be time-consuming, expensive and technically challenging. Therefore, to complement and extend existing experimental methods for malonylation site identification, we developed two novel computational methods for malonylation site prediction based on random forest and deep learning machine learning algorithms, RF-MaloSite and DL-MaloSite, respectively. DL-MaloSite requires the primary amino acid sequence as an input and RF-MaloSite utilizes a diverse set of biochemical, physiochemical and sequence-based features. While systematic assessment of performance metrics suggests that both ‘RF-MaloSite’ and ‘DL-MaloSite’ perform well in all metrics tested, our methods perform particularly well in the areas of accuracy, sensitivity and overall method performance (assessed by the Matthew’s Correlation Coefficient). For instance, RF-MaloSite exhibited MCC scores of 0.42 and 0.40 using 10-fold cross-validation and an independent test set, respectively. Meanwhile, DL-MaloSite was characterized by MCC scores of 0.51 and 0.49 based on 10-fold cross-validation and an independent set, respectively. Importantly, both methods exhibited efficiency scores that were on par or better than those achieved by existing malonylation site prediction methods. The identification of these sites may also provide important insights into the mechanisms of crosstalk between malonylation and other lysine modifications, such as acetylation, glutarylation and succinylation. To facilitate their use, both methods have been made freely available to the research community at https://github.com/dukkakc/DL-MaloSite-and-RF-MaloSite.

Dysfunctional dopaminergic neurotransmission is central to movement disorders and mental diseases. The dopamine transporter (DAT) regulates extracellular dopamine levels, but the genetic and mechanistic link between DAT function and dopamine-related pathologies is not clear. Particularly, the pathophysiological significance of monoallelic missense mutations in DAT is unknown. Here, we use clinical information, neuroimaging, and large-scale exome-sequencing data to uncover the occurrence and phenotypic spectrum of a DAT coding variant, DAT-K619N, which localizes to the critical C-terminal PSD-95/Discs-large/ZO-1 homology–binding motif of human DAT (hDAT). We identified the rare but recurrent hDAT-K619N variant in exome-sequenced samples of patients with neuropsychiatric diseases and a patient with early-onset neurodegenerative parkinsonism and comorbid neuropsychiatric disease. In cell cultures, hDAT-K619N displayed reduced uptake capacity, decreased surface expression, and accelerated turnover. Unilateral expression in mouse nigrostriatal neurons revealed differential effects of hDAT-K619N and hDAT-WT on dopamine-directed behaviors, and hDAT-K619N expression in Drosophila led to impairments in dopamine transmission with accompanying hyperlocomotion and age-dependent disturbances of the negative geotactic response. Moreover, cellular studies and viral expression of hDAT-K619N in mice demonstrated a dominant-negative effect of the hDAT-K619N mutant. Summarized, our results suggest that hDAT-K619N can effectuate dopamine dysfunction of pathological relevance in a dominant-negative manner.

Phosphorylation, which is mediated by protein kinases and opposed by protein phosphatases, is an important post-translational modification that regulates many cellular processes, including cellular metabolism, cell migration, and cell division. Due to its essential role in cellular physiology, a great deal of attention has been devoted to identifying sites of phosphorylation on cellular proteins and understanding how modification of these sites affects their cellular functions. This has led to the development of several computational methods designed to predict sites of phosphorylation based on a protein’s primary amino acid sequence. In contrast, much less attention has been paid to dephosphorylation and its role in regulating the phosphorylation status of proteins inside cells. Indeed, to date, dephosphorylation site prediction tools have been restricted to a few tyrosine phosphatases. To fill this knowledge gap, we have employed a transfer learning strategy to develop a deep learning-based model to predict sites that are likely to be dephosphorylated. Based on independent test results, our model, which we termed DTL-DephosSite, achieved efficiency scores for phosphoserine/phosphothreonine residues of 84%, 84% and 0.68 with respect to sensitivity (SN), specificity (SP) and Matthew’s correlation coefficient (MCC). Similarly, DTL-DephosSite exhibited efficiency scores of 75%, 88% and 0.64 for phosphotyrosine residues with respect to SN, SP, and MCC.

Abstract Levodopa-induced dyskinesias (LID) are a prevalent side effect of chronic treatment with levodopa (L-DOPA) for the motor symptoms of Parkinson’s disease (PD). It has long been hypothesized that serotonergic neurons of the dorsal raphe nucleus (DRN) are capable of L-DOPA uptake and dysregulated release of dopamine (DA), and that this “false neurotransmission” phenomenon is a main contributor to LID development. Indeed, many preclinical studies have demonstrated LID management with serotonin receptor agonist treatment, but unfortunately, promising preclinical data has not been translated in large-scale clinical trials. Importantly, while there is an abundance of convincing clinical and preclinical evidence supporting a role of maladaptive serotonergic neurotransmission in LID expression, there is no direct evidence that dysregulated DA release from serotonergic neurons impacts LID formation. In this study, we ectopically expressed the DA autoreceptor D2Rs (or GFP) in the DRN of 6-hydroxydopamine (6-OHDA) lesioned rats. No negative impact on the therapeutic efficacy of L-DOPA was seen with rAAV-D2Rs therapy. However, D2Rs treated animals, when subjected to a LID-inducing dose regimen of L-DOPA, remained completely resistant to LID, even at high doses. Moreover, the same subjects remained resistant to LID formation when treated with direct DA receptor agonists, suggesting D2Rs activity in the DRN blocked dyskinesogenic L-DOPA priming of striatal neurons. In vivo microdialysis confirmed that DA efflux in the striatum was reduced with rAAV-D2Rs treatment, providing explicit evidence that abnormal DA release from DRN neurons can affect LID. This is the first direct evidence of dopaminergic neurotransmission in DRN neurons and its modulation with rAAV-D2Rs gene therapy confirms the serotonin hypothesis in LID, demonstrating that regulation of serotonergic neurons achieved with a gene therapy approach offers a novel and potent antidyskinetic therapy.

Long-distance migrations influence the dynamics of hostpathogen interactions and understanding the role of migratory waterfowl in the spread of the highly pathogenic avian influenza viruses (HPAIV) is important. While wild geese have been associated with outbreak events, disease ecology of closely related species has not been studied to the same extent. The swan goose (Anser cygnoides) and the bar-headed goose (Anser indicus) are congeneric species with distinctly different HPAIV infection records; the former with few and the latter with numerous records. We compared movements of these species, as well as the more distantly related whooper swan (Cygnus cygnus) through their annual migratory cycle to better understand exposure to HPAIV events and how this compares within and between congeneric and noncongeneric species. In spite of their record of fewer infections, swan geese were more likely to come in contact with disease outbreaks than bar-headed geese. We propose two possible explanations: i) frequent prolonged contact with domestic ducks increases innate immunity in swan geese, and/or ii) the stress of high-elevation migration reduces immunity of bar-headed geese. Continued efforts to improve our understanding of species-level pathogen response is critical to assessing disease transmission risk.

The number of individuals affected by psychostimulant use disorder (PSUD) has increased rapidly over the last few decades resulting in economic, emotional, and physical burdens on our society. Further compounding this issue is the current lack of clinically approved medications to treat this disorder. The dopamine transporter (DAT) is a common target of psychostimulant actions related to their use and dependence, and the recent availability of atypical DAT inhibitors as a potential therapeutic option has garnered popularity in this research field. Modafinil (MOD), which is approved for clinical use for the treatment of narcolepsy and sleep disorders, blocks DAT just like commonly abused psychostimulants. However, preclinical and clinical studies have shown that it lacks the addictive properties (in both behavioral and neurochemical studies) associated with other abused DAT inhibitors. Clinical availability of MOD has facilitated its off-label use for several psychiatric disorders related to alteration of brain dopamine (DA) systems, including PSUD. In this review, we highlight clinical and preclinical research on MOD and its R-enantiomer, R-MOD, as potential medications for PSUD. Given the complexity of PSUD, we have also reported the effects of MOD on psychostimulant-induced appearance of several symptoms that could intensify the severity of the disease (i.e., sleep disorders and impairment of cognitive functions), besides the potential therapeutic effects of MOD on PSUD.

High-altitude pulmonary edema occurs most frequently in non-acclimatized low landers on exposure to altitude ≥2500 m. High-altitude pulmonary edema is a complex condition that involves perturbation of signaling pathways in vasoconstrictors, vasodilators, anti-diuretics, and vascular growth factors. Genetic variations are instrumental in regulating these pathways and evidence is accumulating for a role of epigenetic modification in hypoxic responses. This review focuses on the crosstalk between high-altitude pulmonary edema-associated genetic variants and transcription factors, comparing high-altitude adapted and high-altitude pulmonary edema-afflicted subjects. This approach might ultimately yield biomarker information both to understand and to design therapies for high-altitude adaptation.

Abstract Protein S-sulfenylation, which results from oxidation of free thiols on cysteine residues, has recently emerged as an important post-translational modification that regulates the structure and function of proteins involved in a variety of physiological and pathological processes. By altering the size and physiochemical properties of modified cysteine residues, sulfenylation can impact the cellular function of proteins in several different ways. Thus, the ability to rapidly and accurately identify putative sulfenylation sites in proteins will provide important insights into redox-dependent regulation of protein function in a variety of cellular contexts. Though bottom-up proteomic approaches, such as tandem mass spectrometry (MS/MS), provide a wealth of information about global changes in the sulfenylation state of proteins, MS/MS-based experiments are often labor-intensive, costly and technically challenging. Therefore, to complement existing proteomic approaches, researchers have developed a series of computational tools to identify putative sulfenylation sites on proteins. However, existing methods often suffer from low accuracy, specificity, and/or sensitivity. In this study, we developed SVM-SulfoSite, a novel sulfenylation prediction tool that uses support vector machines (SVM) to identify key determinants of sulfenylation among five feature classes: binary code, physiochemical properties, k-space amino acid pairs, amino acid composition and high-quality physiochemical indices. Using 10-fold cross-validation, SVM-SulfoSite achieved 95% sensitivity and 83% specificity, with an overall accuracy of 89% and Matthew’s correlation coefficient (MCC) of 0.79. Likewise, using an independent test set of experimentally identified sulfenylation sites, our method achieved scores of 74%, 62%, 80% and 0.42 for accuracy, sensitivity, specificity and MCC, with an area under the receiver operator characteristic (ROC) curve of 0.81. Moreover, in side-by-side comparisons, SVM-SulfoSite performed as well as or better than existing sulfenylation prediction tools. Together, these results suggest that our method represents a robust and complementary technique for advanced exploration of protein S-sulfenylation.

Abstract Dopamine transporter (DAT) has been shown to accumulate in filopodia in neurons and non-neuronal cells. To examine the mechanisms of DAT filopodial targeting, we used quantitative live-cell fluorescence microscopy, and compared the effects of the DAT inhibitor cocaine and its fluorescent analog JHC1-64 on the plasma membrane distribution of wild-type DAT and two non-functional DAT mutants, R60A and W63A, that do not accumulate in filopodia. W63A did not bind JHC1-64, whereas R60A did, although less efficiently compared to the wild-type DAT. Molecular dynamics simulations predicted that R60A preferentially assumes an outward-facing (OF) conformation through compensatory intracellular salt bridge formation, which in turn favors binding of cocaine. Imaging analysis showed that JHC1-64-bound R60A mutant predominantly localized in filopodia, whereas free R60A molecules were evenly distributed within the plasma membrane. Cocaine binding significantly increased the density of R60A, but not that of W63A, in filopodia. Further, zinc binding, known to stabilize the OF state, also increased R60A concentration in filopodia. Finally, amphetamine, that is thought to disrupt DAT OF conformation, reduced the concentration of wild-type DAT in filopodia. Altogether, these data indicate that OF conformation is required for the efficient targeting of DAT to, and accumulation in, filopodia.

Abstract Background Family screening of a 48‐year‐old male with recently diagnosed IgG4‐related disease (IgG4‐RD) revealed unanticipated elevations in plasma IgG4 in his two healthy teenaged sons. Methods We performed gene sequencing, immune cell studies, HLA typing, and analyses of circulating cytotoxic CD4+ T lymphocytes and plasmablasts to seek clues to pathogenesis. DNA from a separate cohort of 99 patients with known IgG4‐RD was also sequenced for the presence of genetic variants in a specific gene, FGFBP2. Results The three share a previously unreported heterozygous single base deletion in fibroblast growth factor binding protein type 2 (FGFBP2), which causes a frameshift in the coding sequence. The FGFBP2 protein is secreted by cytotoxic T‐lymphocytes and binds fibroblast growth factor. The variant sequence in the FGFBP2 protein is predicted to form a disordered random coil rather than a helical‐turn‐helix structure, unable to adopt a stable conformation. The proband and the two sons had 5–10‐fold higher numbers of circulating cytotoxic CD4 + T cells and plasmablasts compared to matched controls. The three members also share a homozygous missense common variant in FGFBP2 found in heterozygous form in ~40% of the population. This common variant was found in 73% of an independent, well characterized IgG4‐RD cohort, showing enrichment in idiopathic IgG4‐RD. Conclusions The presence of a shared deleterious variant and homozygous common variant in FGFBP2 in the proband and sons strongly implicates this cytotoxic T cell product in the pathophysiology of IgG4‐RD. The high prevalence of a common FGFBP2 variant in sporadic IgG4‐RD supports the likelihood of participation in disease.

Avian influenza has advanced from a regional concern to a global health issue with significant economic, trade, and public health implications. Wild birds, particularly waterfowl (Anseriformes), are known reservoirs for low-pathogenic avian influenza viruses (AIV) and recent studies have shown their potential in the spread of highly pathogenic forms of virus. East Asia remains an epicenter for the emergence of novel strains of AIV, however, information on movement ecology of waterfowl, and subsequently a clearer understanding of disease transmission risks in this region has been greatly lacking. To address this, we marked two species of wild waterfowl, northern pintail (Anas acuta) and Eurasian wigeon (Anas penelope), with satellite transmitters on their wintering grounds in Hong Kong, China to study the northward spring migration in the East Asian-Australasian Flyway in relation to disease transmission factors. Northern pintail were found to initiate migration 42 days earlier, travel 2,150 km farther, and perform 4.4 more stopovers than Eurasian wigeon. We found both species used similar stopover locations including areas along the Yangtze River near Shanghai, Bohai Bay and Korea Bay in rapidly developing regions of the Yellow Sea, and the Sea of Okhotsk where the species appeared to funnel through a migratory bottleneck. Both species appeared to exhibit strong habitat selection for rice paddies during migration stopovers, a habitat preference which has the potential to influence risks of AIV outbreaks as rapid land use and land cover changes occur throughout China. Both species had greatest association with H5N1 outbreaks during the early stages of migration when they were at lower latitudes. While Eurasian wigeon were not associated with outbreaks after the mean date of wintering ground departures, northern pintail were associated with outbreaks until the majority of individuals departed from the Yellow Sea, a migratory stopover location. Our results show species-level differences in migration timing and behavior for these common and widespread species, demonstrating the need to consider their unique temporal and spatial movement ecology when incorporating wild birds into AIV risk modeling and management.

The dopamine D2/D3 receptor (D2R/D3R) agonists are used as therapeutics for Parkinson’s disease (PD) and other motor disorders. Selective targeting of D3R over D2R is attractive because of D3R’s restricted tissue distribution with potentially fewer side-effects and its putative neuroprotective effect. However, the high sequence homology between the D2R and D3R poses a challenge in the development of D3R selective agonists. To address the ligand selectivity, bitopic ligands were designed and synthesized previously based on a potent D3R-preferential agonist PF592,379 as the primary pharmacophore (PP). This PP was attached to various secondary pharmacophores (SPs) using chemically different linkers. Here, we characterize some of these novel bitopic ligands at both D3R and D2R using BRET-based functional assays. The bitopic ligands showed varying differences in potencies and efficacies. In addition, the chirality of the PP was key to conferring improved D3R potency, selectivity, and G protein signaling bias. In particular, compound AB04-88 exhibited significant D3R over D2R selectivity, and G protein bias at D3R. This bias was consistently observed at various time-points ranging from 8 to 46 min. Together, the structure-activity relationships derived from these functional studies reveal unique pharmacology at D3R and support further evaluation of functionally biased D3R agonists for their therapeutic potential.

In light of increased cancer prevalence and cancer-specific deaths in patients with infections, we investigated whether infections alter anti-tumor immune responses. We report that acute influenza infection of the lung promotes distal melanoma growth in the dermis and leads to accelerated cancer-specific host death. Furthermore, we show that during influenza infection, anti-melanoma CD8+ T cells are shunted from the tumor to the infection site, where they express high levels of the inhibitory receptor programmed cell death protein 1 (PD-1). Immunotherapy to block PD-1 reverses this loss of anti-tumor CD8+ T cells from the tumor and decreases infection-induced tumor growth. Our findings show that acute non-oncogenic infection can promote cancer growth, raising concerns regarding acute viral illness sequelae. They also suggest an unexpected role for PD-1 blockade in cancer immunotherapy and provide insight into the immune response when faced with concomitant challenges.

Agro-ecological conditions associated with the spread and persistence of highly pathogenic avian influenza (HPAI) are not well understood, but the trade of live poultry is suspected to be a major pathway. Although market chains of live bird trade have been studied through indirect means including interviews and questionnaires, direct methods have not been used to identify movements of individual poultry. To bridge the knowledge gap on quantitative movement and transportation of poultry, we introduced a novel approach for applying telemetry to document domestic duck movements from source farms at Poyang Lake, China. We deployed recently developed transmitters that record Global Positioning System (GPS) locations and send them through the Groupe Spécial Mobile (GSM) cellular telephone system. For the first time, we were able to track individually marked ducks from 3 to 396 km from their origin to other farms, distribution facilities, or live bird markets. Our proof of concept test showed that the use of GPS-GSM transmitters may provide direct, quantitative information to document the movement of poultry and reveal their market chains. Our findings provide an initial indication of the complexity of source-market network connectivity and highlight the great potential for future telemetry studies in poultry network analyses.

Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north–south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches.

Diabetes is the leading cause of chronic kidney disease. African Americans are disproportionately burdened by diabetic kidney disease (DKD) and end stage renal disease (ESRD). Disparities in DKD have genetic and socioeconomic components, yet its prevalence in African Americans is not adequately studied. The current study used multiple biomarkers of DKD to evaluate undiagnosed DKD in uninsured and underinsured African American men in Greensboro, North Carolina. Participants consisted of three groups: nondiabetic controls, diabetic patients without known kidney disease, and diabetic patients with diagnosed DKD. Our data reveal undiagnosed kidney injury in a significant proportion of the diabetic patients, based on levels of both plasma and urinary biomarkers of kidney injury, namely, urinary albumin to creatinine ratio, kidney injury molecule-1, cystatin C, and neutrophil gelatinase-associated lipocalin. We also found that the urinary levels of meprin A, meprin B, and two kidney meprin targets (nidogen-1 and monocytes chemoattractant protein-1) increased with severity of kidney injury, suggesting a potential role for meprin metalloproteases in the pathophysiology of DKD in this subpopulation. The study also demonstrates a need for more aggressive tests to assess kidney injury in uninsured diabetic patients to facilitate early diagnosis and targeted interventions that could slow progression to ESRD.