Reverse aging to treat lupus.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with multifaceted pathogenetic processes, including abnormalities of T-cell subset distribution and function. Accumulation of senescent CD4+ T cells has been found to contribute to the development of the disease. In this issue, Jiang et al. provide compelling evidence that links an expanded pool of CD4+CD57+ senescent T cells in patients with SLE to disease activity favored by interleukin-15. Importantly, treatment of lupus-prone mice with a senolytic drug resulted in decreased autoimmune pathology. The findings of this study suggest possible novel therapeutics to treat patients with SLE.

FPLS-DC: functional partial least squares through distance covariance for imaging genetics.

MOTIVATION: Imaging genetics integrates imaging and genetic techniques to examine how genetic variations influence the function and structure of organs like the brain or heart, providing insights into their impact on behavior and disease phenotypes. The use of organ-wide imaging endophenotypes has increasingly been used to identify potential genes associated with complex disorders. However, analyzing organ-wide imaging data alongside genetic data presents two significant challenges: high dimensionality and complex relationships. To address these challenges, we propose a novel, nonlinear inference framework designed to partially mitigate these issues. RESULTS: We propose a functional partial least squares through distance covariance (FPLS-DC) framework for efficient genome wide analyses of imaging phenotypes. It consists of two components. The first component utilizes the FPLS-derived base functions to reduce image dimensionality while screening genetic markers. The second component maximizes the distance correlation between genetic markers and projected imaging data, which is a linear combination of the FPLS-basis functions, using simulated annealing algorithm. In addition, we proposed an iterative FPLS-DC method based on FPLS-DC framework, which effectively overcomes the influence of inter-gene correlation on inference analysis. We efficiently approximate the null distribution of test statistics using a gamma approximation. Compared to existing methods, FPLS-DC offers computational and statistical efficiency for handling large-scale imaging genetics. In real-world applications, our method successfully detected genetic variants associated with the hippocampus, demonstrating its value as a statistical toolbox for imaging genetic studies. AVAILABILITY AND IMPLEMENTATION: The FPLS-DC method we propose opens up new research avenues and offers valuable insights for analyzing functional and high-dimensional data. In addition, it serves as a useful tool for scientific analysis in practical applications within the field of imaging genetics research. The R package FPLS-DC is available in Github: https://github.com/BIG-S2/FPLSDC.

Viral RNA capping: Mechanisms and antiviral therapy.

RNA capping is an essential trigger for protein translation in eukaryotic cells. Many viruses have evolved various strategies for initiating the translation of viral genes and generating progeny virions in infected cells via synthesizing cap structure or stealing the RNA cap from nascent host messenger ribonucleotide acid (mRNA). In addition to protein translation, a new understanding of the role of the RNA cap in antiviral innate immunity has advanced the field of mRNA synthesis in vitro and therapeutic applications. Recent studies on these viral RNA capping systems have revealed startlingly diverse ways and molecular machinery. A comprehensive understanding of how viruses accomplish the RNA capping in infected cells is pivotal for designing effective broad-spectrum antiviral therapies. Here we systematically review the contemporary insights into the RNA-capping mechanisms employed by viruses causing human and animal infectious diseases, while also highlighting its impact on host antiviral innate immune response. The therapeutic applications of targeting RNA capping against viral infections and the development of RNA-capping inhibitors are also summarized.

PPP2R2D Suppresses Effector T Cell Exhaustion and Regulatory T Cell Expansion and Inhibits Tumor Growth in Melanoma.

We had shown previously that the protein phosphatase 2A regulatory subunit PPP2R2D suppresses IL-2 production, and PPP2R2D deficiency in T cells potentiates the suppressive function of regulatory T (Treg) cells and alleviates imiquimod-induced lupus-like pathology. In this study, in a melanoma xenograft model, we noted that the tumor grew in larger sizes in mice lacking PPP2R2D in T cells (LckCreR2Dfl/fl) compared with wild type (R2Dfl/fl) mice. The numbers of intratumoral T cells in LckCreR2Dfl/fl mice were reduced compared with R2Dfl/fl mice, and they expressed a PD-1+CD3+CD44+ exhaustion phenotype. In vitro experiments confirmed that the chromatin of exhaustion markers PD-1, LAG3, TIM3, and CTLA4 remained open in LckCreR2Dfl/fl CD4 T conventional compared with R2Dfl/fl T conventional cells. Moreover, the percentage of Treg cells (CD3+CD4+Foxp3+CD25hi) was significantly increased in the xenografted tumor of LckCreR2Dfl/fl mice compared with R2Dfl/fl mice probably because of the increase in the percentage of IL-2-producing LckCreR2Dfl/fl T cells. Moreover, using adoptive T cell transfer in mice xenografted with melanoma, we demonstrated that PPP2R2D deficiency in T cells enhanced the inhibitory effect of Treg cells in antitumor immunity. At the translational level, analysis of publicly available data from 418 patients with melanoma revealed that PPP2R2D expression levels correlated positively with tumor-infiltration level of CD4 and CD8 T cells. The data demonstrate that PPP2R2D is a negative regulator of immune checkpoint receptors, and its absence exacerbates effector T cell exhaustion and promotes Treg cell expansion. We conclude that PPP2R2D protects against melanoma growth, and PPP2R2D-promoting regimens can have therapeutic value in patients with melanoma.

Ultra-high dimensional variable selection for doubly robust causal inference.

Causal inference has been increasingly reliant on observational studies with rich covariate information. To build tractable causal procedures, such as the doubly robust estimators, it is imperative to first extract important features from high or even ultra-high dimensional data. In this paper, we propose causal ball screening for confounder selection from modern ultra-high dimensional data sets. Unlike the familiar task of variable selection for prediction modeling, our confounder selection procedure aims to control for confounding while improving efficiency in the resulting causal effect estimate. Previous empirical and theoretical studies suggest excluding causes of the treatment that are not confounders. Motivated by these results, our goal is to keep all the predictors of the outcome in both the propensity score and outcome regression models. A distinctive feature of our proposal is that we use an outcome model-free procedure for propensity score model selection, thereby maintaining double robustness in the resulting causal effect estimator. Our theoretical analyses show that the proposed procedure enjoys a number of properties, including model selection consistency and pointwise normality. Synthetic and real data analysis show that our proposal performs favorably with existing methods in a range of realistic settings. Data used in preparation of this paper were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

The Regulatory Subunit PPP2R2A of PP2A Enhances Th1 and Th17 Differentiation through Activation of the GEF-H1/RhoA/ROCK Signaling Pathway.

Protein phosphatase 2A (PP2A) composed of a scaffold subunit, a catalytic subunit, and multiple regulatory subunits is a ubiquitously expressed serine/threonine phosphatase. We have previously shown that the PP2A catalytic subunit is increased in T cells from patients with systemic lupus erythematosus and promotes IL-17 production by enhancing the activity of Rho-associated kinase (ROCK) in T cells. However, the molecular mechanism whereby PP2A regulates ROCK activity is unknown. In this study, we show that the PP2A regulatory subunit PPP2R2A is increased in T cells from people with systemic lupus erythematosus and binds to, dephosphorylates, and activates the guanine nucleotide exchange factor GEF-H1 at Ser885, which in turn increases the levels of RhoA-GTP and the activity of ROCK in T cells. Genetic PPP2R2A deficiency in murine T cells reduced Th1 and Th17, but not regulatory T cell differentiation and mice with T cell-specific PPP2R2A deficiency displayed less autoimmunity when immunized with myelin oligodendrocyte glycoprotein peptide. Our studies indicate that PPP2R2A is the regulatory subunit that dictates the PP2A-directed enhanced Th1 and Th17 differentiation, and therefore, it represents a therapeutic target for pathologies linked to Th1 and Th17 cell expansion.

Protein Tyrosine Phosphatase SHP2 Suppresses Host Innate Immunity against Influenza A Virus by Regulating EGFR-Mediated Signaling.

Influenza A virus (IAV) is a highly contagious pathogen, causing acute respiratory illnesses in human beings and animals and frequently giving rise to epidemic outbreaks. Evasion by IAV of host immunity facilitates viral replication and spread, which can be initiated through various mechanisms, including epidermal growth factor receptor (EGFR) activation. However, how EGFR mediates the suppression of antiviral systems remains unclear. Here, we examined host innate immune responses and their relevant signaling to EGFR upon IAV infection. IAV was found to induce the phosphorylation of EGFR and extracellular signal-regulated kinase (ERK) at an early stage of infection. Inhibition of EGFR or ERK suppressed the viral replication but increased the expression of type I and type III interferons (IFNs) and interferon-stimulated genes (ISGs), supporting the idea that IAV escapes from antiviral innate immunity by activating EGFR/ERK signaling. Meanwhile, IAV infection also induced the activation of Src homology region 2-containing protein tyrosine phosphatase 2 (SHP2). Pharmacological inhibition or small interfering RNA (siRNA)-based silencing of SHP2 enhanced the IFN-dependent antiviral activity and reduced virion production. Furthermore, knockdown of SHP2 attenuated the EGFR-mediated ERK phosphorylation triggered by viral infection or EGF stimulation. Conversely, ectopic expression of constitutively active SHP2 noticeably promoted ERK activation and viral replication, concomitant with diminished immune function. Altogether, the results indicate that SHP2 is crucial for IAV-induced activation of the EGFR/ERK pathway to suppress host antiviral responses.IMPORTANCE Viral immune evasion is the most important strategy whereby viruses evolve for their survival. This work shows that influenza A virus (IAV) suppressed the antiviral innate immunity through downregulation of IFNs and ISGs by activating EGFR/ERK signaling. Meanwhile, IAV also induced the activation of protein tyrosine phosphatase SHP2, which was found to be responsible for modulating the EGFR-mediated ERK activity and subsequent antiviral effectiveness both in vitro and in vivo The results suggest that SHP2 is a key signal transducer between EGFR and ERK and plays a crucial role in suppressing host innate immunity during IAV infection. The finding enhances our understanding of influenza immune evasion and provides a new therapeutic approach to viral infection.

Co-sparse reduced-rank regression for association analysis between imaging phenotypes and genetic variants.

MOTIVATION: The association analysis between genetic variants and imaging phenotypes must be carried out to understand the inherited neuropsychiatric disorders via imaging genetic studies. Given the high dimensionality in imaging and genetic data, traditional methods based on massive univariate regression entail large computational cost and disregard many-to-many correlations between phenotypes and genetic variants. Several multivariate imaging genetic methods have been proposed to alleviate the above problems. However, most of these methods are based on the l1 penalty, which might cause the over-selection of variables and thus mislead scientists in analyzing data from the field of neuroimaging genetics. RESULTS: To address these challenges in both statistics and computation, we propose a novel co-sparse reduced-rank regression model that identifies complex correlations in a dimensional reduction manner. We developed an iterative algorithm based on a group primal dual-active set formulation to detect simultaneously important genetic variants and imaging phenotypes efficiently and precisely via non-convex penalty. The simulation studies showed that our method achieved accurate and stable performance in parameter estimation and variable selection. In real application, the proposed approach successfully detected several novel Alzheimer's disease-related genetic variants and regions of interest, which indicate that our method may be a valuable statistical toolbox for imaging genetic studies. AVAILABILITY AND IMPLEMENTATION: The R package csrrr, and the code for experiments in this article is available in Github: https://github.com/hailongba/csrrr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genome-wide association studies of brain imaging data via weighted distance correlation.

MOTIVATION: Imaging genetics is mainly used to reveal the pathogenesis of neuropsychiatric risk genes and understand the relationship between human brain structure, functional and individual differences. Increasingly, the brain-wide imaging phenotypes in voxels are available to test the association with genetic markers. A challenge with analyzing such data is their high dimensionality and complex relationships. RESULTS: To tackle this challenge, we introduce a weighed distance correlation (wdCor) that can assess the association between genetic markers and voxel-based imaging data. Importantly, the wdCor test takes the voxel-based data as a whole multivariate phenotype, which preserves the spatial continuity and might enhance the power. Besides, an adaptive permutation procedure is introduced to determine the P-values of the wdCor test and also alleviate the computational burden in GWAS. In extensive simulation studies, wdCor achieves much better performances compared to the original distance correlation. We also successfully apply wdCor to conduct a large-scale analysis on data from the Alzheimer's disease neuroimaging project (ADNI). AVAILABILITY AND IMPLEMENTATION: Our wdCor method provides new research directions and ideas for multivariate analysis of high-dimensional data, it can also be used as a tool for scientific analysis of imaging genetics research in practical applications. The R package wdcor, and the code for reproducing all results in this article is available in Github: https://github.com/yangyuhui0129/wdcor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CSMD: a computational subtraction-based microbiome discovery pipeline for species-level characterization of clinical metagenomic samples.

MOTIVATION: Microbiome analyses of clinical samples with low microbial biomass are challenging because of the very small quantities of microbial DNA relative to the human host, ubiquitous contaminating DNA in sequencing experiments and the large and rapidly growing microbial reference databases. RESULTS: We present computational subtraction-based microbiome discovery (CSMD), a bioinformatics pipeline specifically developed to generate accurate species-level microbiome profiles for clinical samples with low microbial loads. CSMD applies strategies for the maximal elimination of host sequences with minimal loss of microbial signal and effectively detects microorganisms present in the sample with minimal false positives using a stepwise convergent solution. CSMD was benchmarked in a comparative evaluation with other classic tools on previously published well-characterized datasets. It showed higher sensitivity and specificity in host sequence removal and higher specificity in microbial identification, which led to more accurate abundance estimation. All these features are integrated into a free and easy-to-use tool. Additionally, CSMD applied to cell-free plasma DNA showed that microbial diversity within these samples is substantially broader than previously believed. AVAILABILITY AND IMPLEMENTATION: CSMD is freely available at https://github.com/liuyu8721/csmd. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pyruvate dehydrogenase phosphatase catalytic subunit 2 limits Th17 differentiation.

Th17 cells favor glycolytic metabolism, and pyruvate dehydrogenase (PDH) is the key bifurcation enzyme, which in its active dephosphorylated form advances the oxidative phosphorylation from glycolytic pathway. The transcriptional factor, inducible cAMP early repressor/cAMP response element modulator (ICER/CREM), has been shown to be induced in Th17 cells and to be overexpressed in CD4+ T cells from the patients with systemic lupus erythematosus (SLE). We found that glycolysis and lactate production in in vitro Th17-polarized T cells was reduced and that the expression of pyruvate dehydrogenase phosphatase catalytic subunit 2 (PDP2), an enzyme that converts the inactive PDH to its active form, and PDH enzyme activity were increased in Th17 cells from ICER/CREM-deficient animals. ICER was found to bind to the Pdp2 promoter and suppress its expression. Furthermore, forced expression of PDP2 in CD4+ cells reduced the in vitro Th17 differentiation, whereas shRNA-based suppression of PDP2 expression increased in vitro Th17 differentiation and augmented experimental autoimmune encephalomyelitis. At the translational level, PDP2 expression was decreased in memory Th17 cells from patients with SLE and forced expression of PDP2 in CD4+ T cells from lupus-prone MRL/lpr mice and patients with SLE suppressed Th17 differentiation. These data demonstrate the direct control of energy production during Th17 differentiation in health and disease by the transcription factor ICER/CREM at the PDH metabolism bifurcation level.

Temperature-dependent variations in toxicity of diamide insecticides against three lepidopteran insects.

The effect of temperature on the toxicities of four diamide insecticides (chlorantraniliprole, cyantraniliprole, flubendiamide, tetraniliprole) against three lepidopteran insects (Helicoverpa armigera, Plutella xylostella, Athetis lepigone) were determined from 15 to 35 °C by exposing third-instar larvae to dip-treated cabbage leaf. The results indicated that increase in temperature led to an increase significantly and regularly in the toxicities of the four diamide insecticides against P. xylostella and H. armigera, but not for A. lepigone. The temperature coefficients (TCs) of the four diamide insecticides increased from 15 to 35 °C. Tetraniliprole for H. armigera (+825.83), chlorantraniliprole for P. xylostella (+315.65) and cyantraniliprole for H. armigera (+225.77) exhibited high positive TCs. For A. lepigone, temperature had a positively weak or no effect on the toxicities of most of the diamide insecticides from 20 to 30 °C, but a higher effect from 30 to 35 °C. In addition, the toxicities of chlorantraniliprole, cyantraniliprole and tetraniliprole all decreased from 15 to 20 °C. This study can guide pest managers in choosing suitable ambient field temperature when spraying diamide insecticides against lepidopteran insects.

Analysis of Differentially Expressed Transcripts in Apolygus lucorum (Meyer-Dür) Exposed to Different Temperature Coefficient Insecticides.

The existence of a temperature effect of insecticides frustrated the control of the green plant bug Apolygus lucorum (Meyer-Dür). Previous studies mostly focused on the application of insecticides, but the underlying mechanism remains incompletely understood. Here, we report a transcriptome profiling of A. lucorum treated by three kinds of temperature coefficient insecticides (TCIs) (positive TCI: imidacloprid, negative TCI: b-cypermethrin and non-effect TCI: phoxim) at 15 °C, 25 °C and 35 °C by using next- and third-generation RNA-Seq methods. A total of 34,739 transcripts were annotated from 277.74 Gb of clean data. There were more up-regulated transcripts than down-regulated transcripts in all three kinds of TCI treatments. Further Venn diagrams indicate the regulatory transcripts and regulatory modes were different at the three temperatures. The responses to imidacloprid involved more detox and stress response transcripts such as cytochrome P450 (CYP450), carboxylesterase (CarE) and catalase (CAT) at 35 °C, which was the case for beta-cypermethrin at 15 °C. UDP-glucuronyltransferase (UGT) and heat shock protein (HSP) transcripts were heavily involved, and thus deserve particular note in the temperature effect of insecticides. This high-confidence transcriptome atlas provides improved gene information for further study on the insecticide temperature effect related physiological and biochemical processes of A. lucorum.

BALL DIVERGENCE: NONPARAMETRIC TWO SAMPLE TEST.

In this paper, we first introduce Ball Divergence, a novel measure of the difference between two probability measures in separable Banach spaces, and show that the Ball Divergence of two probability measures is zero if and only if these two probability measures are identical without any moment assumption. Using Ball Divergence, we present a metric rank test procedure to detect the equality of distribution measures underlying independent samples. It is therefore robust to outliers or heavy-tail data. We show that this multivariate two sample test statistic is consistent with the Ball Divergence, and it converges to a mixture of χ2 distributions under the null hypothesis and a normal distribution under the alternative hypothesis. Importantly, we prove its consistency against a general alternative hypothesis. Moreover, this result does not depend on the ratio of the two imbalanced sample sizes, ensuring that can be applied to imbalanced data. Numerical studies confirm that our test is superior to several existing tests in terms of Type I error and power. We conclude our paper with two applications of our method: one is for virtual screening in drug development process and the other is for genome wide expression analysis in hormone replacement therapy.

Fungal proteinaceous compounds with multiple biological activities.

Fungi comprise organisms like molds, yeasts and mushrooms. They have been used as food or medicine for a long time. A large number of fungal proteins or peptides with diverse biological activities are considered as antibacterial, antifungal, antiviral and anticancer agents. They encompass proteases, ribosome inactivating proteins, defensins, hemolysins, lectins, laccases, ribonucleases, immunomodulatory proteins, and polysaccharopeptides. The target of the present review is to update the status of the various bioactivities of these fungal proteins and peptides and discuss their therapeutic potential.

Biological activities of ribosome-inactivating proteins and their possible applications as antimicrobial, anticancer, and anti-pest agents and in neuroscience research.

Ribosome-inactivating proteins (RIPs) are enzymes which depurinate ribosomal RNA (rRNA), thus impeding the process of translation resulting in inhibition of protein synthesis. They are produced by various organisms including plants, fungi and bacteria. RIPs from plants are linked to plant defense due to their antiviral, antifungal, antibacterial, and insecticidal activities in which they can be applied in agriculture to combat microbial pathogens and pests. Their anticancer, antiviral, embryotoxic, and abortifacient properties may find medicinal applications. Besides, conjugation of RIPs with antibodies or other carriers to form immunotoxins has been found useful to research in neuroscience and anticancer therapy.

Marine lectins and their medicinal applications.

Marine organisms have been extensively explored for the last several decades as potential sources of novel biologically active compounds, and extensive research has been conducted on lectins. Lectins derived from marine organisms are structurally diverse and also differ from those identified from terrestrial organisms. Marine lectins appear to be particularly useful in some biological applications. They seem to induce negligible immunogenicity because they have a relatively small size, are more stable due to extensive disulfide bridge formation, and have high specificity for complex glyco-conjugates and carbohydrates instead of simple sugars. It is clear that many of them have not yet been extensively studied when compared with their terrestrial counterparts. Marine lectins can be used to design and develop new potentially useful therapeutic agents. This review encompasses recent research on the isolation and identification of marine lectins with potential value in medicinal applications.

Lectins with anti-HIV activity: a review.

Lectins including flowering plant lectins, algal lectins, cyanobacterial lectins, actinomycete lectin, worm lectins, and the nonpeptidic lectin mimics pradimicins and benanomicins, exhibit anti-HIV activity. The anti-HIV plant lectins include Artocarpus heterophyllus (jacalin) lectin, concanavalin A, Galanthus nivalis (snowdrop) agglutinin-related lectins, Musa acuminata (banana) lectin, Myrianthus holstii lectin, Narcissus pseudonarcissus lectin, and Urtica diocia agglutinin. The anti-HIV algal lectins comprise Boodlea coacta lectin, Griffithsin, Oscillatoria agardhii agglutinin. The anti-HIV cyanobacterial lectins are cyanovirin-N, scytovirin, Microcystis viridis lectin, and microvirin. Actinohivin is an anti-HIV actinomycete lectin. The anti-HIV worm lectins include Chaetopterus variopedatus polychaete marine worm lectin, Serpula vermicularis sea worm lectin, and C-type lectin Mermaid from nematode (Laxus oneistus). The anti-HIV nonpeptidic lectin mimics comprise pradimicins and benanomicins. Their anti-HIV mechanisms are discussed.

Lectins from edible mushrooms.

Mushrooms are famous for their nutritional and medicinal values and also for the diversity of bioactive compounds they contain including lectins. The present review is an attempt to summarize and discuss data available on molecular weights, structures, biological properties, N-terminal sequences and possible applications of lectins from edible mushrooms. It further aims to update and discuss/examine the recent advancements in the study of these lectins regarding their structures, functions, and exploitable properties. A detailed tabling of all the available data for N-terminal sequences of these lectins is also presented here.

The PP2A regulatory subunit PPP2R2A controls NAD+ biosynthesis to regulate T cell subset differentiation in systemic autoimmunity.

The protein phosphatase 2A (PP2A) regulatory subunit PPP2R2A is involved in the regulation of immune response. We report that lupus-prone mice with T cells deficient in PPP2R2A display less autoimmunity and nephritis. PPP2R2A deficiency promotes NAD+ biosynthesis through the nicotinamide riboside (NR)-directed salvage pathway in T cells. NR inhibits murine Th17 and promotes Treg cell differentiation, in vitro, by PΑRylating histone H1.2 and causing its reduced occupancy in the Foxp3 loci and increased occupancy in the Il17a loci, leading to increased Foxp3 and decreased Il17a transcription. NR treatment suppresses disease in MRL.lpr mice and restores NAD+-dependent poly [ADP-ribose] polymerase 1 (PARP1) activity in CD4 T cells from patients with systemic lupus erythematosus (SLE), while reducing interferon (IFN)-γ and interleukin (IL)-17 production. We conclude that PPP2R2A controls the level of NAD+ through the NR-directed salvage pathway and promotes systemic autoimmunity. Translationally, NR suppresses lupus nephritis in mice and limits the production of proinflammatory cytokines by SLE T cells.