Two regulatory T cell populations in the visceral adipose tissue shape systemic metabolism.

Visceral adipose tissue (VAT) is an energy store and endocrine organ critical for metabolic homeostasis. Regulatory T (Treg) cells restrain inflammation to preserve VAT homeostasis and glucose tolerance. Here, we show that the VAT harbors two distinct Treg cell populations: prototypical serum stimulation 2-positive (ST2+) Treg cells that are enriched in males and a previously uncharacterized population of C-X-C motif chemokine receptor 3-positive (CXCR3+) Treg cells that are enriched in females. We show that the transcription factors GATA-binding protein 3 and peroxisome proliferator-activated receptor-γ, together with the cytokine interleukin-33, promote the differentiation of ST2+ VAT Treg cells but repress CXCR3+ Treg cells. Conversely, the differentiation of CXCR3+ Treg cells is mediated by the cytokine interferon-γ and the transcription factor T-bet, which also antagonize ST2+ Treg cells. Finally, we demonstrate that ST2+ Treg cells preserve glucose homeostasis, whereas CXCR3+ Treg cells restrain inflammation in lean VAT and prevent glucose intolerance under high-fat diet conditions. Overall, this study defines two molecularly and developmentally distinct VAT Treg cell types with unique context- and sex-specific functions.

Blockade of the co-inhibitory molecule PD-1 unleashes ILC2-dependent antitumor immunity in melanoma.

Group 2 innate lymphoid cells (ILC2s) are essential to maintain tissue homeostasis. In cancer, ILC2s can harbor both pro-tumorigenic and anti-tumorigenic functions, but we know little about their underlying mechanisms or whether they could be clinically relevant or targeted to improve patient outcomes. Here, we found that high ILC2 infiltration in human melanoma was associated with a good clinical prognosis. ILC2s are critical producers of the cytokine granulocyte-macrophage colony-stimulating factor, which coordinates the recruitment and activation of eosinophils to enhance antitumor responses. Tumor-infiltrating ILC2s expressed programmed cell death protein-1, which limited their intratumoral accumulation, proliferation and antitumor effector functions. This inhibition could be overcome in vivo by combining interleukin-33-driven ILC2 activation with programmed cell death protein-1 blockade to significantly increase antitumor responses. Together, our results identified ILC2s as a critical immune cell type involved in melanoma immunity and revealed a potential synergistic approach to harness ILC2 function for antitumor immunotherapies.

c-Maf-dependent Treg cell control of intestinal TH17 cells and IgA establishes host-microbiota homeostasis.

Foxp3+ regulatory T cells (Treg cells) are crucial for the maintenance of immune homeostasis both in lymphoid tissues and in non-lymphoid tissues. Here we demonstrate that the ability of intestinal Treg cells to constrain microbiota-dependent interleukin (IL)-17-producing helper T cell (TH17 cell) and immunoglobulin A responses critically required expression of the transcription factor c-Maf. The terminal differentiation and function of several intestinal Treg cell populations, including RORγt+ Treg cells and follicular regulatory T cells, were c-Maf dependent. c-Maf controlled Treg cell-derived IL-10 production and prevented excessive signaling via the kinases PI(3)K (phosphatidylinositol-3-OH kinase) and Akt and the metabolic checkpoint kinase complex mTORC1 (mammalian target of rapamycin) and expression of inflammatory cytokines in intestinal Treg cells. c-Maf deficiency in Treg cells led to profound dysbiosis of the intestinal microbiota, which when transferred to germ-free mice was sufficient to induce exacerbated intestinal TH17 responses, even in a c-Maf-competent environment. Thus, c-Maf acts to preserve the identity and function of intestinal Treg cells, which is essential for the establishment of host-microbe symbiosis.

Blimp-1 controls plasma cell function through the regulation of immunoglobulin secretion and the unfolded protein response.

Plasma cell differentiation requires silencing of B cell transcription, while it establishes antibody-secretory function and long-term survival. The transcription factors Blimp-1 and IRF4 are essential for the generation of plasma cells; however, their function in mature plasma cells has remained elusive. We found that while IRF4 was essential for the survival of plasma cells, Blimp-1 was dispensable for this. Blimp-1-deficient plasma cells retained their transcriptional identity but lost the ability to secrete antibody. Blimp-1 regulated many components of the unfolded protein response (UPR), including XBP-1 and ATF6. The overlap in the functions of Blimp-1 and XBP-1 was restricted to that response, with Blimp-1 uniquely regulating activity of the kinase mTOR and the size of plasma cells. Thus, Blimp-1 was required for the unique physiological ability of plasma cells that enables the secretion of protective antibody.

A molecular threshold for effector CD8(+) T cell differentiation controlled by transcription factors Blimp-1 and T-bet.

T cell responses are guided by cytokines that induce transcriptional regulators, which ultimately control differentiation of effector and memory T cells. However, it is unknown how the activities of these molecular regulators are coordinated and integrated during the differentiation process. Using genetic approaches and transcriptional profiling of antigen-specific CD8(+) T cells, we reveal a common program of effector differentiation that is regulated by IL-2 and IL-12 signaling and the combined activities of the transcriptional regulators Blimp-1 and T-bet. The loss of both T-bet and Blimp-1 leads to abrogated cytotoxic function and ectopic IL-17 production in CD8(+) T cells. Overall, our data reveal two major overlapping pathways of effector differentiation governed by the availability of Blimp-1 and T-bet and suggest a model for cytokine-induced transcriptional changes that combine, quantitatively and qualitatively, to promote robust effector CD8(+) T cell differentiation.

MYB orchestrates T cell exhaustion and response to checkpoint inhibition.

CD8+ T cells that respond to chronic viral infections or cancer are characterized by the expression of inhibitory receptors such as programmed cell death protein 1 (PD-1) and by the impaired production of cytokines. This state of restrained functionality-which is referred to as T cell exhaustion1,2-is maintained by precursors of exhausted T (TPEX) cells that express the transcription factor T cell factor 1 (TCF1), self-renew and give rise to TCF1- exhausted effector T cells3-6. Here we show that the long-term proliferative potential, multipotency and repopulation capacity of exhausted T cells during chronic infection are selectively preserved in a small population of transcriptionally distinct CD62L+ TPEX cells. The transcription factor MYB is not only essential for the development of CD62L+ TPEX cells and maintenance of the antiviral CD8+ T cell response, but also induces functional exhaustion and thereby prevents lethal immunopathology. Furthermore, the proliferative burst in response to PD-1 checkpoint inhibition originates exclusively from CD62L+ TPEX cells and depends on MYB. Our findings identify CD62L+ TPEX cells as a stem-like population that is central to the maintenance of long-term antiviral immunity and responsiveness to immunotherapy. Moreover, they show that MYB is a transcriptional orchestrator of two fundamental aspects of exhausted T cell responses: the downregulation of effector function and the long-term preservation of self-renewal capacity.

Transcriptional profiling of mouse B cell terminal differentiation defines a signature for antibody-secreting plasma cells.

When B cells encounter an antigen, they alter their physiological state and anatomical localization and initiate a differentiation process that ultimately produces antibody-secreting cells (ASCs). We have defined the transcriptomes of many mature B cell populations and stages of plasma cell differentiation in mice. We provide a molecular signature of ASCs that highlights the stark transcriptional divide between B cells and plasma cells and enables the demarcation of ASCs on the basis of location and maturity. Changes in gene expression correlated with cell-division history and the acquisition of permissive histone modifications, and they included many regulators that had not been previously implicated in B cell differentiation. These findings both highlight and expand the core program that guides B cell terminal differentiation and the production of antibodies.

The transcriptional regulators IRF4, BATF and IL-33 orchestrate development and maintenance of adipose tissue-resident regulatory T cells.

Foxp3(+) regulatory T (Treg) cells in visceral adipose tissue (VAT-Treg cells) are functionally specialized tissue-resident cells that prevent obesity-associated inflammation and preserve insulin sensitivity and glucose tolerance. Their development depends on the transcription factor PPAR-γ; however, the environmental cues required for their differentiation are unknown. Here we show that interleukin 33 (IL-33) signaling through the IL-33 receptor ST2 and myeloid differentiation factor MyD88 is essential for development and maintenance of VAT-Treg cells and sustains their transcriptional signature. Furthermore, the transcriptional regulators BATF and IRF4 were necessary for VAT-Treg differentiation through direct regulation of ST2 and PPAR-γ expression. IL-33 administration induced vigorous population expansion of VAT-Treg cells, which tightly correlated with improvements in metabolic parameters in obese mice. Human omental adipose tissue Treg cells also showed high ST2 expression, suggesting an evolutionarily conserved requirement for IL-33 in VAT-Treg cell homeostasis.

MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics.

Protein structure prediction is a longstanding issue crucial for identifying new drug targets and providing a mechanistic understanding of protein functions. To enhance the progress in this field, a spectrum of computational methodologies has been cultivated. AlphaFold2 has exhibited exceptional precision in predicting wild-type protein structures, with performance exceeding that of other methods. However, predicting the structures of missense mutant proteins using AlphaFold2 remains challenging due to the intricate and substantial structural alterations caused by minor sequence variations in the mutant proteins. Molecular dynamics (MD) has been validated for precisely capturing changes in amino acid interactions attributed to protein mutations. Therefore, for the first time, a strategy entitled 'MoDAFold' was proposed to improve the accuracy and reliability of missense mutant protein structure prediction by combining AlphaFold2 with MD. Multiple case studies have confirmed the superior performance of MoDAFold compared to other methods, particularly AlphaFold2.

Effector Regulatory T Cell Differentiation and Immune Homeostasis Depend on the Transcription Factor Myb.

FoxP3-expressing regulatory T (Treg) cells are essential for maintaining immune homeostasis. Activated Treg cells undergo further differentiation into an effector state that highly expresses genes critical for Treg cell function, although how this process is coordinated on a transcriptional level is poorly understood. Here, we demonstrate that mice lacking the transcription factor Myb in Treg cells succumbed to a multi-organ inflammatory disease. Myb was specifically expressed in, and required for the differentiation of, thymus-derived effector Treg cells. The combination of transcriptome and genomic footprint analyses revealed that Myb directly regulated a large proportion of the gene expression specific to effector Treg cells, identifying Myb as a critical component of the gene regulatory network controlling effector Treg cell differentiation and function.

Transcription Factor IRF4 Promotes CD8+ T Cell Exhaustion and Limits the Development of Memory-like T Cells during Chronic Infection.

During chronic stimulation, CD8+ T cells acquire an exhausted phenotype characterized by expression of inhibitory receptors, down-modulation of effector function, and metabolic impairments. T cell exhaustion protects from excessive immunopathology but limits clearance of virus-infected or tumor cells. We transcriptionally profiled antigen-specific T cells from mice infected with lymphocytic choriomeningitis virus strains that cause acute or chronic disease. T cell exhaustion during chronic infection was driven by high amounts of T cell receptor (TCR)-induced transcription factors IRF4, BATF, and NFATc1. These regulators promoted expression of inhibitory receptors, including PD-1, and mediated impaired cellular metabolism. Furthermore, they repressed the expression of TCF1, a transcription factor required for memory T cell differentiation. Reducing IRF4 expression restored the functional and metabolic properties of antigen-specific T cells and promoted memory-like T cell development. These findings indicate that IRF4 functions as a central node in a TCR-responsive transcriptional circuit that establishes and sustains T cell exhaustion during chronic infection.

Sex-specific adipose tissue imprinting of regulatory T cells.

Adipose tissue is an energy store and a dynamic endocrine organ1,2. In particular, visceral adipose tissue (VAT) is critical for the regulation of systemic metabolism3,4. Impaired VAT function-for example, in obesity-is associated with insulin resistance and type 2 diabetes5,6. Regulatory T (Treg) cells that express the transcription factor FOXP3 are critical for limiting immune responses and suppressing tissue inflammation, including in the VAT7-9. Here we uncover pronounced sexual dimorphism in Treg cells in the VAT. Male VAT was enriched for Treg cells compared with female VAT, and Treg cells from male VAT were markedly different from their female counterparts in phenotype, transcriptional landscape and chromatin accessibility. Heightened inflammation in the male VAT facilitated the recruitment of Treg cells via the CCL2-CCR2 axis. Androgen regulated the differentiation of a unique IL-33-producing stromal cell population specific to the male VAT, which paralleled the local expansion of Treg cells. Sex hormones also regulated VAT inflammation, which shaped the transcriptional landscape of VAT-resident Treg cells in a BLIMP1 transcription factor-dependent manner. Overall, we find that sex-specific differences in Treg cells from VAT are determined by the tissue niche in a sex-hormone-dependent manner to limit adipose tissue inflammation.

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

Dividing out quantification uncertainty allows efficient assessment of differential transcript expression with edgeR.

Differential expression analysis of RNA-seq is one of the most commonly performed bioinformatics analyses. Transcript-level quantifications are inherently more uncertain than gene-level read counts because of ambiguous assignment of sequence reads to transcripts. While sequence reads can usually be assigned unambiguously to a gene, reads are very often compatible with multiple transcripts for that gene, particularly for genes with many isoforms. Software tools designed for gene-level differential expression do not perform optimally on transcript counts because the read-to-transcript ambiguity (RTA) disrupts the mean-variance relationship normally observed for gene level RNA-seq data and interferes with the efficiency of the empirical Bayes dispersion estimation procedures. The pseudoaligners kallisto and Salmon provide bootstrap samples from which quantification uncertainty can be assessed. We show that the overdispersion arising from RTA can be elegantly estimated by fitting a quasi-Poisson model to the bootstrap counts for each transcript. The technical overdispersion arising from RTA can then be divided out of the transcript counts, leading to scaled counts that can be input for analysis by established gene-level software tools with full statistical efficiency. Comprehensive simulations and test data show that an edgeR analysis of the scaled counts is more powerful and efficient than previous differential transcript expression pipelines while providing correct control of the false discovery rate. Simulations explore a wide range of scenarios including the effects of paired vs single-end reads, different read lengths and different numbers of replicates.

PDCdb: the biological activity and pharmaceutical information of peptide-drug conjugate (PDC).

Peptide-drug conjugates (PDCs) have emerged as a promising class of targeted therapeutics with substantial pharmaceutical advantages and market potentials, which is a combination of a peptide (selective to the disease-relevant target), a linker (stable in circulation but cleavable at target site) and a cytotoxic/radioactive drug (efficacious/traceable for disease). Among existing PDCs, those based on radiopharmaceuticals (a.k.a. radioactive drugs) are valued due to their accurate imaging and targeted destruction of disease sites. It's demanded to accumulate the biological activity and pharmaceutical information of PDCs. Herein, a database PDCdb was thus constructed to systematically describe these valuable data. Particularly, biological activities for 2036 PDCs were retrieved from literatures, which resulted in 1684, 613 and 2753 activity data generated based on clinical trial, animal model and cell line, respectively. Furthermore, the pharmaceutical information for all 2036 PDCs was collected, which gave the diverse data of (a) ADME property, plasma half-life and administration approach of a PDC and (b) chemical modification, primary target, mode of action, conjugating feature of the constituent peptide/linker/drug. In sum, PDCdb systematically provided the biological activities and pharmaceutical information for the most comprehensive list of PDCs among the available databases, which was expected to attract broad interest from related communities and could be freely accessible at: https://idrblab.org/PDCdb/.

cellCounts: an R function for quantifying 10x Chromium single-cell RNA sequencing data.

SUMMARY: The 10x Genomics Chromium single-cell RNA sequencing technology is a powerful gene expression profiling platform, which is capable of profiling expression of thousands of genes in tens of thousands of cells simultaneously. This platform can produce hundreds of million reads in a single experiment, making it a very challenging task to quantify expression of genes in individual cells due to the massive data volume. Here, we present cellCounts, a new tool for efficient and accurate quantification of Chromium data. cellCounts employs the seed-and-vote strategy to align reads to a reference genome, collapses reads to Unique Molecular Identifiers (UMIs) and then assigns UMIs to genes based on the featureCounts program. Using both simulation and real datasets for evaluation, cellCounts was found to compare favourably to cellRanger and STARsolo. cellCounts is implemented in R, making it easily integrated with other R programs for analysing Chromium data. AVAILABILITY AND IMPLEMENTATION: cellCounts was implemented as a function in R package Rsubread that can be downloaded from http://bioconductor.org/packages/release/bioc/html/Rsubread.html. Data and analysis code used in this study can be freely accessed via La Trobe University's Institutional Repository at https://doi.org/10.26181/21588276.

Liver sinusoidal endothelial S1pr2 regulates experimental liver fibrosis through YAP/TGF-ß signaling pathway.

The hepatic vascular niche plays an important role in the pathological process of liver fibrosis. Liver sinusoidal endothelial cells (LSECs) predominantly compose hepatic vascular niches. Endothelial cell (EC)-expressing sphingosine 1-phosphate receptor 2 (S1pr2) plays an essential role in the regulation of vascular functions. Nevertheless, it remains unknown whether liver LSEC-S1pr2 might modulate pathological liver fibrosis. In this study, liver fibrosis was induced by hepatotoxin carbon tetrachloride (CCl4 ). The expression of S1pr2 is significantly downregulated in liver sinusoidal endothelial cells after CCl4 treatment. The loss of S1pr2 in LSECs significantly alleviated liver fibrosis after chronic insult, whereas the overexpression of S1pr2 in LSECs accentuated liver fibrogenesis. In vivo experiments further revealed that the deficiency of S1pr2 in LSECs dampened hepatic stellate cell (HSC) activation, while overexpression of S1pr2 in LSECs enhanced HSC activation with more extracellular matrix component production. Mechanistically, LSEC-S1pr2 activates the YAP signaling pathway to potentiate the transactivation of TGF-ß, which acts on HSCs in a paracrine manner, and thus aggravated liver fibrosis. Taken together, our results uncover a novel pathological mechanism of liver fibrosis in which LSEC-S1pr2 plays an important role in modulating the development of liver fibrosis, providing a future novel therapy target against liver fibrogenesis.

Pathogenesis of cardiovascular diseases: effects of mitochondrial CF6 on endothelial cell function.

Cardiovascular disease (CVD) stands as a predominant global cause of morbidity and mortality, necessitating effective and cost-efficient therapies for cardiovascular risk reduction. Mitochondrial coupling factor 6 (CF6), identified as a novel proatherogenic peptide, emerges as a significant risk factor in endothelial dysfunction development, correlating with CVD severity. CF6 expression can be heightened by CVD risk factors like mechanical force, hypoxia, or high glucose stimuli through the NF-κB pathway. Many studies have explored the CF6-CVD relationship, revealing elevated plasma CF6 levels in essential hypertension, atherosclerotic cardiovascular disease (ASCVD), stroke, and preeclampsia patients. CF6 acts as a vasoactive and proatherogenic peptide in CVD, inducing intracellular acidosis in vascular endothelial cells, inhibiting nitric oxide (NO) and prostacyclin generation, increasing blood pressure, and producing proatherogenic molecules, significantly contributing to CVD development. CF6 induces an imbalance in endothelium-dependent factors, including NO, prostacyclin, and asymmetric dimethylarginine (ADMA), promoting vasoconstriction, vascular remodeling, thrombosis, and insulin resistance, possibly via C-src Ca2+ and PRMT-1/DDAH-2-ADMA-NO pathways. This review offers a comprehensive exploration of CF6 in the context of CVD, providing mechanistic insights into its role in processes impacting CVD, with a focus on CF6 functions, intracellular signaling, and regulatory mechanisms in vascular endothelial cells.

MRI-based assessment paraspinal extensor muscle fatty infiltration in acute cervical spinal cord injury patients - a retrospective study.

BACKGROUND: The effect of fat infiltration in the paraspinal muscles on cervical degenerative disease has been confirmed by multiple studies. However, little is known about fat infiltration in the paraspinal extensors in patients with acute cervical spinal cord injury (SCI). This study aimed to investigate the difference in paraspinal extensor fatty infiltration between patients with acute cervical SCI and healthy controls, and to further explore the protective role of the paravertebral extensor muscles in patients with cervical SCI. METHODS: A total of 50 patients with acute cervical SCI admitted to the emergency department from January 2019 to November 2023 were retrospectively analyzed, including 26 males and 24 females, with an average age of 59.60 ± 10.81 years. A control group of 50 healthy middle-aged and elderly individuals was also included, comprising 28 males and 22 females, with an average age of 55.00 ± 8.21 years. Cervical spine magnetic resonance imaging (MRI) was used to measure the cross-sectional areas of the superficial and deep cervical extensor muscles, the corresponding vertebral body cross-sectional areas, and the fat area within the superficial and deep extensor muscle groups using Image J software. Differences between the two groups were compared, and the cervical SCI patients were further analyzed based on the severity of the spinal cord injury and gender differences. RESULTS: The deep fatty infiltration ratio (DFIR) and superficial fatty infiltration ratio (SFIR) at C4-C7 in the cervical SCI group were significantly higher than those in the control group (P < 0.001). The cross-sectional area of the functional deep extensor area (FDEA) relative to the vertebral body area (VBA) and the cross-sectional area of the functional superficial extensor area (FSEA) relative to the VBA at the C5 and C6 levels in the cervical SCI group were significantly lower than those in the control group (P < 0.001, P < 0.001, P = 0.034, P = 0.004 respectively). Among the cervical SCI patients, the cross-sectional areas of the deep extensor area (DEA) and the superficial extensor area (SEA) in males were significantly higher than those in females (P < 0.001). At the C6 and C7 levels, the FDEA/VBA and FSEA/VBA ratios in the male group were higher than those in the female group (P = 0.009, P = 0.022, P = 0.019, P = 0.005, respectively). CONCLUSION: Patients with acute cervical SCI exhibit significantly higher fatty infiltration and a greater degree of paravertebral extensor muscle degeneration compared to healthy controls. This finding underscores the importance of the paravertebral extensor muscles in the context of cervical SCI and may guide future therapeutic strategies.