Cell Rep Methods. 2024 Apr 5:100753. doi: 10.1016/j.crmeth.2024.100753. Online ahead of print.

ABSTRACT

Accurate characterization and comparison of T cell receptor (TCR) repertoires from small biological samples present significant challenges. The main challenge is the low material input, which compromises the quality of bulk sequencing and hinders the recovery of sufficient TCR sequences for robust analyses. We aimed to address this limitation by implementing a strategic approach to pool homologous biological samples. Our findings demonstrate that such pooling indeed enhances the TCR repertoire coverage, particularly for cell subsets of constrained sizes, and enables accurate comparisons of TCR repertoires at different levels of complexity across T cell subsets with different sizes. This methodology holds promise for advancing our understanding of T cell repertoires in scenarios where sample size constraints are a prevailing concern.

PMID:38614088 | DOI:10.1016/j.crmeth.2024.100753

Mol Plant. 2024 Apr 9:S1674-2052(24)00084-4. doi: 10.1016/j.molp.2024.03.011. Online ahead of print.

ABSTRACT

Macroalgae are multicellular, aquatic autotrophs that play vital roles in global climate maintenance and have diverse applications in biotechnology and eco-engineering, which are directly linked to their multicellularity phenotypes. However, their genomic diversity and the evolutionary mechanisms underlying multicellularity in these organisms remain uncharacterized. In this study, we sequenced 110 macroalgal genomes from diverse climates and phyla, and identified key genomic features that distinguish them from their microalgal relatives. Genes for cell adhesion, extracellular matrix formation, cell polarity, transport, and cell differentiation distinguish macroalgae from microalgae across all three major phyla, constituting conserved and unique gene sets supporting multicellular processes. Adhesome genes show phylum- and climate-specific expansions that may facilitate niche adaptation. Collectively, our study reveals genetic determinants of convergent and divergent evolutionary trajectories that have shaped morphological diversity in macroalgae and provides genome-wide frameworks to understand photosynthetic multicellular evolution in aquatic environments.

PMID:38614077 | DOI:10.1016/j.molp.2024.03.011

Food Chem. 2024 Apr 10;450:139301. doi: 10.1016/j.foodchem.2024.139301. Online ahead of print.

ABSTRACT

By-products from the potato processing industry, like potato trimmings, are sustainable sources of proteins. Here, a size-exclusion high performance liquid chromatography (SE-HPLC) method was applied to simultaneously determine the extractability and aggregation state of proteins from three batches of potato trimmings of different cultivars. Obtained SE-HPLC profiles allowed distinguishing between the patatin and protease inhibitor fractions of potato proteins. Moreover, only 75% of the crude proteins could be extracted in phosphate buffer containing sodium dodecyl sulfate and a reducing agent, indicating the presence of physical extraction barriers. Ball milling for 5 min significantly increased protein extractability, but prolonged treatment resulted in aggregation of native patatin and a reduced protein extractability. Microwave-dried trimmings had a lower protein extractability than freeze-dried trimmings. In future research, the SE-HPLC method can be used to examine changes in potato protein (fractions) as a result of processing.

PMID:38613966 | DOI:10.1016/j.foodchem.2024.139301

Int J Mol Sci. 2024 Mar 30;25(7):3887. doi: 10.3390/ijms25073887.

ABSTRACT

Tertiary lymphoid structures (TLSs) are organized aggregates of immune cells in non-lymphoid tissues and are associated with a favorable prognosis in tumors. However, TLS markers remain inconsistent, and the utilization of machine learning techniques for this purpose is limited. To tackle this challenge, we began by identifying TLS markers through bioinformatics analysis and machine learning techniques. Subsequently, we leveraged spatial transcriptomic data from Gene Expression Omnibus (GEO) and built two support vector classifier models for TLS prediction: one without feature selection and the other using the marker genes. The comparable performances of these two models confirm the efficacy of the selected markers. The majority of the markers are immunoglobulin genes, demonstrating their importance in the identification of TLSs. Our research has identified the markers of TLSs using machine learning methods and constructed a model to predict TLS location, contributing to the detection of TLS and holding the promising potential to impact cancer treatment strategies.

PMID:38612697 | DOI:10.3390/ijms25073887

Int J Mol Sci. 2024 Mar 29;25(7):3837. doi: 10.3390/ijms25073837.

ABSTRACT

Impaired healing wounds do not proceed through the normal healing processes in a timely and orderly manner, and while they do eventually heal, their healing is not optimal. Chronic wounds, on the other hand, remain unhealed for weeks or months. In the US alone, chronic wounds impact ~8.5 million people and cost ~USD 28-90 billion per year, not accounting for the psychological and physical pain and emotional suffering that patients endure. These numbers are only expected to rise in the future as the elderly populations and the incidence of comorbidities such as diabetes, hypertension, and obesity increase. Over the last few decades, scientists have used a variety of approaches to treat chronic wounds, but unfortunately, to date, there is no effective treatment. Indeed, while there are thousands of drugs to combat cancer, there is only one single drug approved for the treatment of chronic wounds. This is in part because wound healing is a very complex process involving many phases that must occur sequentially and in a timely manner. Furthermore, models that fully mimic human chronic wounds have not been developed. In this review, we assess various models currently being used to study the biology of impaired healing and chronic non-healing wounds. Among them, this paper also highlights one model which shows significant promise; this model uses aged and obese db/db-/- mice and the chronic wounds that develop show characteristics of human chronic wounds that include increased oxidative stress, chronic inflammation, damaged microvasculature, abnormal collagen matrix deposition, a lack of re-epithelialization, and the spontaneous development of multi-bacterial biofilm. We also discuss how important it is that we continue to develop chronic wound models that more closely mimic those of humans and that can be used to test potential treatments to heal chronic wounds.

PMID:38612647 | DOI:10.3390/ijms25073837

Int J Mol Sci. 2024 Mar 25;25(7):3661. doi: 10.3390/ijms25073661.

ABSTRACT

Lung cancer is a global health challenge, hindered by delayed diagnosis and the disease's complex molecular landscape. Accurate patient survival prediction is critical, motivating the exploration of various -omics datasets using machine learning methods. Leveraging multi-omics data, this study seeks to enhance the accuracy of survival prediction by proposing new feature extraction techniques combined with unbiased feature selection. Two lung adenocarcinoma multi-omics datasets, originating from the TCGA and CPTAC-3 projects, were employed for this purpose, emphasizing gene expression, methylation, and mutations as the most relevant data sources that provide features for the survival prediction models. Additionally, gene set aggregation was shown to be the most effective feature extraction method for mutation and copy number variation data. Using the TCGA dataset, we identified 32 molecular features that allowed the construction of a 2-year survival prediction model with an AUC of 0.839. The selected features were additionally tested on an independent CPTAC-3 dataset, achieving an AUC of 0.815 in nested cross-validation, which confirmed the robustness of the identified features.

PMID:38612473 | DOI:10.3390/ijms25073661

Int J Mol Sci. 2024 Mar 23;25(7):3624. doi: 10.3390/ijms25073624.

ABSTRACT

Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

PMID:38612436 | DOI:10.3390/ijms25073624

Int J Mol Sci. 2024 Mar 23;25(7):3621. doi: 10.3390/ijms25073621.

ABSTRACT

Intravitreal aflibercept injection (IAI) is a treatment for diabetic macular edema (DME), but its mechanism of action (MoA) has not been completely elucidated. Here, we aimed to explore IAI's MoA and its multi-target nature in DME pathophysiology with an in silico (computer simulation) disease model. We used the Therapeutic Performance Mapping System (Anaxomics Biotech property) to generate mathematical models based on the available scientific knowledge at the time of the study, describing the relationship between the modulation of vascular endothelial growth factor receptors (VEGFRs) by IAI and DME pathophysiological processes. We also undertook an enrichment analysis to explore the processes modulated by IAI, visualized the effectors' predicted protein activity, and specifically evaluated the role of VEGFR1 pathway inhibition on DME treatment. The models simulated the potential pathophysiology of DME and the likely IAI's MoA by inhibiting VEGFR1 and VEGFR2 signaling. The action of IAI through both signaling pathways modulated the identified pathophysiological processes associated with DME, with the strongest effects in angiogenesis, blood-retinal barrier alteration and permeability, and inflammation. VEGFR1 inhibition was essential to modulate inflammatory protein effectors. Given the role of VEGFR1 signaling on the modulation of inflammatory-related pathways, IAI may offer therapeutic advantages for DME through sustained VEGFR1 pathway inhibition.

PMID:38612432 | DOI:10.3390/ijms25073621

Cancers (Basel). 2024 Mar 29;16(7):1337. doi: 10.3390/cancers16071337.

ABSTRACT

Inducing apoptosis in cancer cells is a primary goal in anti-cancer therapy, but curing cancer with a single drug is unattainable due to drug resistance. The complex molecular network in cancer cells causes heterogeneous responses to single-target drugs, thereby inducing an adaptive drug response. Here, we showed that targeted drug perturbations can trigger state conflicts between multi-stable motifs within a molecular regulatory network, resulting in heterogeneous drug responses. However, we revealed that properly regulating an interconnecting molecule between these motifs can synergistically minimize the heterogeneous responses and overcome drug resistance. We extracted the essential cellular response dynamics of the Boolean network driven by the target node perturbation and developed an algorithm to identify a synergistic combinatorial target that can reduce heterogeneous drug responses. We validated the proposed approach using exemplary network models and a gastric cancer model from a previous study by showing that the targets identified with our algorithm can better drive the networks to desired states than those with other control theories. Of note, our approach suggests a new synergistic pair of control targets that can increase cancer drug efficacy to overcome adaptive drug resistance.

PMID:38611015 | DOI:10.3390/cancers16071337

Exp Hematol Oncol. 2024 Apr 12;13(1):39. doi: 10.1186/s40164-024-00505-7.

ABSTRACT

Paradoxically, tumor development and progression can be inhibited and promoted by the immune system. After three stages of immune editing, namely, elimination, homeostasis and escape, tumor cells are no longer restricted by immune surveillance and thus develop into clinical tumors. The mechanisms of immune escape include abnormalities in antitumor-associated immune cells, selection for immune resistance to tumor cells, impaired transport of T cells, and the formation of an immunosuppressive tumor microenvironment. A population of distinct immature myeloid cells, myeloid-derived suppressor cells (MDSCs), mediate immune escape primarily by exerting immunosuppressive effects and participating in the constitution of an immunosuppressive microtumor environment. Clinical trials have found that the levels of MDSCs in the peripheral blood of cancer patients are strongly correlated with tumor stage, metastasis and prognosis. Moreover, animal experiments have confirmed that elimination of MDSCs inhibits tumor growth and metastasis to some extent. Therefore, MDSCs may become the target of immunotherapy for many cancers, and eliminating MDSCs can help improve the response rate to cancer treatment and patient survival. However, a clear definition of MDSCs and the specific mechanism involved in immune escape are lacking. In this paper, we review the role of the MDSCs population in tumor development and the mechanisms involved in immune escape in different tumor contexts. In addition, we discuss the use of these cells as targets for tumor immunotherapy. This review not only contributes to a systematic and comprehensive understanding of the essential role of MDSCs in immune system reactions against tumors but also provides information to guide the development of cancer therapies targeting MDSCs.

PMID:38609997 | DOI:10.1186/s40164-024-00505-7

Npj Ment Health Res. 2023 Nov 8;2(1):19. doi: 10.1038/s44184-023-00044-9.

NO ABSTRACT

PMID:38609480 | DOI:10.1038/s44184-023-00044-9

Nat Commun. 2024 Apr 12;15(1):3178. doi: 10.1038/s41467-024-47433-y.

ABSTRACT

Chemo-immunotherapy combinations have been regarded as one of the most practical ways to improve immunotherapy response in cancer patients. In this study, we integrate the transcriptomics data from anti-PD-1-treated tumors and compound-treated cancer cell lines to systematically screen for chemo-immunotherapy synergisms in silico. Through analyzing anti-PD-1 induced expression changes in patient tumors, we develop a shift ability score to measure if a chemotherapy or a small molecule inhibitor treatment can shift anti-PD-1 resistance in tumor cells. By applying shift ability analysis to 41,321 compounds and 16,853 shRNA treated cancer cell lines transcriptomic data, we characterize the landscape of chemo-immunotherapy synergism and experimentally validated a mitochondrial RNA-dependent mechanism for drug-induced immune activation in tumor. Our study represents an effort to mechanistically characterize chemo-immunotherapy synergism and will facilitate future pre-clinical and clinical studies.

PMID:38609378 | DOI:10.1038/s41467-024-47433-y

Nat Commun. 2024 Apr 12;15(1):3197. doi: 10.1038/s41467-024-47416-z.

ABSTRACT

Phages exert profound evolutionary pressure on bacteria by interacting with receptors on the cell surface to initiate infection. While the majority of phages use chromosomally encoded cell surface structures as receptors, plasmid-dependent phages exploit plasmid-encoded conjugation proteins, making their host range dependent on horizontal transfer of the plasmid. Despite their unique biology and biotechnological significance, only a small number of plasmid-dependent phages have been characterized. Here we systematically search for new plasmid-dependent phages targeting IncP and IncF plasmids using a targeted discovery platform, and find that they are common and abundant in wastewater, and largely unexplored in terms of their genetic diversity. Plasmid-dependent phages are enriched in non-canonical types of phages, and all but one of the 65 phages we isolated were non-tailed, and members of the lipid-containing tectiviruses, ssDNA filamentous phages or ssRNA phages. We show that plasmid-dependent tectiviruses exhibit profound differences in their host range which is associated with variation in the phage holin protein. Despite their relatively high abundance in wastewater, plasmid-dependent tectiviruses are missed by metaviromic analyses, underscoring the continued importance of culture-based phage discovery. Finally, we identify a tailed phage dependent on the IncF plasmid, and find related structural genes in phages that use the orthogonal type 4 pilus as a receptor, highlighting the evolutionarily promiscuous use of these distinct contractile structures by multiple groups of phages. Taken together, these results indicate plasmid-dependent phages play an under-appreciated evolutionary role in constraining horizontal gene transfer via conjugative plasmids.

PMID:38609370 | DOI:10.1038/s41467-024-47416-z

Nat Commun. 2024 Apr 12;15(1):3167. doi: 10.1038/s41467-024-47486-z.

ABSTRACT

Heme has a critical role in the chemical framework of the cell as an essential protein cofactor and signaling molecule that controls diverse processes and molecular interactions. Using a phylogenomics-based approach and complementary structural techniques, we identify a family of dimeric hemoproteins comprising a domain of unknown function DUF2470. The heme iron is axially coordinated by two zinc-bound histidine residues, forming a distinct two-fold symmetric zinc-histidine-iron-histidine-zinc site. Together with structure-guided in vitro and in vivo experiments, we further demonstrate the existence of a functional link between heme binding by Dri1 (Domain related to iron 1, formerly ssr1698) and post-translational regulation of succinate dehydrogenase in the cyanobacterium Synechocystis, suggesting an iron-dependent regulatory link between photosynthesis and respiration. Given the ubiquity of proteins containing homologous domains and connections to heme metabolism across eukaryotes and prokaryotes, we propose that DRI (Domain Related to Iron; formerly DUF2470) functions at the molecular level as a heme-dependent regulatory domain.

PMID:38609367 | DOI:10.1038/s41467-024-47486-z

Ann Rheum Dis. 2024 Apr 12:ard-2024-225664. doi: 10.1136/ard-2024-225664. Online ahead of print.

ABSTRACT

INTRODUCTION: Systemic lupus erythematosus with antiphospholipid syndrome (SLE-APS) represents a challenging SLE endotype whose molecular basis remains unknown.

METHODS: We analysed whole-blood RNA-sequencing data from 299 patients with SLE (108 SLE-antiphospholipid antibodies (aPL)-positive, including 67 SLE-APS; 191 SLE-aPL-negative) and 72 matched healthy controls (HC). Pathway enrichment analysis, unsupervised weighted gene coexpression network analysis and machine learning were applied to distinguish disease endotypes.

RESULTS: Patients with SLE-APS demonstrated upregulated type I and II interferon (IFN) pathways compared with HC. Using a 100-gene random forests model, we achieved a cross-validated accuracy of 75.6% in distinguishing these two states. Additionally, the comparison between SLE-APS and SLE-aPL-negative revealed 227 differentially expressed genes, indicating downregulation of IFN-α and IFN-γ signatures, coupled with dysregulation of the complement cascade, B-cell activation and neutrophil degranulation. Unsupervised analysis of SLE transcriptome identified 21 gene modules, with SLE-APS strongly linked to upregulation of the 'neutrophilic/myeloid' module. Within SLE-APS, venous thromboses positively correlated with 'neutrophilic/myeloid' and 'B cell' modules, while arterial thromboses were associated with dysregulation of 'DNA damage response (DDR)' and 'metabolism' modules. Anticardiolipin and anti-β2GPI positivity-irrespective of APS status-were associated with the 'neutrophilic/myeloid' and 'protein-binding' module, respectively.

CONCLUSIONS: There is a hierarchical upregulation and-likely-dependence on IFN in SLE with the highest IFN signature observed in SLE-aPL-negative patients. Venous thrombotic events are associated with neutrophils and B cells while arterial events with DDR and impaired metabolism. This may account for their differential requirements for anticoagulation and provide rationale for the potential use of mTOR inhibitors such as sirolimus and the direct fIIa inhibitor dabigatran in SLE-APS.

PMID:38609158 | DOI:10.1136/ard-2024-225664

Sci Total Environ. 2024 Apr 10:172352. doi: 10.1016/j.scitotenv.2024.172352. Online ahead of print.

ABSTRACT

Mulberry cultivation and silkworm rearing hold a prominent position in the agricultural industries of many Asian countries, contributing to economic growth, sustainable development, and cultural heritage preservation. Applying the soil-mulberry-silkworm system (SMSS) to heavy metal (HM)-contaminated areas is significant economically, environmentally, and socially. The ultimate goal of this paper is to review the main research progress of SMSS under HM stress, examining factors affecting its safe utilization and remediation potential for HM-contaminated soils. HM tolerance of mulberry and silkworms relates to their growth stages. Based on the standards for HM contaminants in various mulberry and silkworm products and the bioconcentration factor of HMs at different parts of SMSS, we calculated maximum safe Cd and Pb levels for SMSS application on contaminated lands. Several remediation practices demonstrated mulberry's ability to grow on barren lands, absorb various HMs, while silkworm excreta can adsorb HMs and improve soil fertility. Considering multiple factors influencing HM tolerance and accumulation, we propose a decision model to guide SMSS application in polluted areas. Finally, we discussed the potential of using molecular breeding techniques to screen or develop varieties better suited for HM-contaminated regions. However, actual pollution scenarios are often complex, requiring consideration of multiple factors. More large-scale applications are crucial to enhance the theoretical foundation for applying SMSS in HM pollution risk areas.

PMID:38608900 | DOI:10.1016/j.scitotenv.2024.172352

J Crit Care. 2024 Apr 11;82:154812. doi: 10.1016/j.jcrc.2024.154812. Online ahead of print.

ABSTRACT

PURPOSE: Identifying thresholds at which the ROX index would satisfactorily predict HFNC failure across heterogenous resourced contexts is necessary for clinical use.

METHODS: Patients ≥18 years admitted to 30 diverse ICUs across 10 states in India who required HFNC for respiratory support were retrospectively included in this study. Patient data and hourly ROX indices were then analyzed and contextualized to clinical outcomes as well as with ROX index thresholds in other regions of the world.

MEASUREMENTS AND MAIN RESULTS: Among the 614 patients included, 276 (44.9%) required respiratory escalation. Pneumonia was the most common diagnosis on admission. Receiver operating characteristic curve analysis revealed that a baseline ROX score of 7.86 was similar to 4.88 in other populations which was confirmed by Kaplan-Mier curves (hazard ratio,3.58 (2.72-4.69, p < 0.001)). ROX scores at 11.84 or 5.89 had roles in screening and confirming HFNC failure. The index performed poorly in a subset of patients who died without respiratory escalation. The ROX index was most predictive in the initial hours of ICU admission and a longer duration of HFNC was associated with more severe outcomes.

CONCLUSIONS: When optimally calibrated this index can using a method that can reliably predict the risk of HFNC failure among ICU patients from diverse settings.

PMID:38608348 | DOI:10.1016/j.jcrc.2024.154812

Comput Biol Med. 2024 Apr 3;174:108398. doi: 10.1016/j.compbiomed.2024.108398. Online ahead of print.

ABSTRACT

The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models, despite their potential, lack comprehensive genetic data. This inadequacy fuels our research focus-integrating specific genetic information, such as pathway scores, into clinical data. Our aim is to refine machine learning models for more precise relapse prediction in early-stage non-small cell lung cancer. To address the scarcity of genetic data, we employ imputation techniques, leveraging publicly available datasets such as The Cancer Genome Atlas (TCGA), integrating pathway scores into our patient cohort from the Cancer Long Survivor Artificial Intelligence Follow-up (CLARIFY) project. Through the integration of imputed pathway scores from the TCGA dataset with clinical data, our approach achieves notable strides in predicting relapse among a held-out test set of 200 patients. By training machine learning models on enriched knowledge graph data, inclusive of triples derived from pathway score imputation, we achieve a promising precision of 82% and specificity of 91%. These outcomes highlight the potential of our models as supplementary tools within tumour, node, and metastasis (TNM) classification systems, offering improved prognostic capabilities for lung cancer patients. In summary, our research underscores the significance of refining machine learning models for relapse prediction in early-stage non-small cell lung cancer. Our approach, centered on imputing pathway scores and integrating them with clinical data, not only enhances predictive performance but also demonstrates the promising role of machine learning in anticipating relapse and ultimately elevating patient outcomes.

PMID:38608322 | DOI:10.1016/j.compbiomed.2024.108398

Environ Sci Technol. 2024 Apr 12. doi: 10.1021/acs.est.3c07972. Online ahead of print.

ABSTRACT

The sources and sinks of nitrous oxide, as control emissions to the atmosphere, are generally poorly constrained for most environmental systems. Initial depth-resolved analysis of nitrous oxide flux from observation wells and the proximal surface within a nitrate contaminated aquifer system revealed high subsurface production but little escape from the surface. To better understand the environmental controls of production and emission at this site, we used a combination of isotopic, geochemical, and molecular analyses to show that chemodenitrification and bacterial denitrification are major sources of nitrous oxide in this subsurface, where low DO, low pH, and high nitrate are correlated with significant nitrous oxide production. Depth-resolved metagenomes showed that consumption of nitrous oxide near the surface was correlated with an enrichment of Clade II nitrous oxide reducers, consistent with a growing appreciation of their importance in controlling release of nitrous oxide to the atmosphere. Our work also provides evidence for the reduction of nitrous oxide at a pH of 4, well below the generally accepted limit of pH 5.

PMID:38608141 | DOI:10.1021/acs.est.3c07972

Sci Immunol. 2024 Apr 12;9(94):eadi1023. doi: 10.1126/sciimmunol.adi1023. Epub 2024 Apr 12.

ABSTRACT

The development of dendritic cells (DCs), including antigen-presenting conventional DCs (cDCs) and cytokine-producing plasmacytoid DCs (pDCs), is controlled by the growth factor Flt3 ligand (Flt3L) and its receptor Flt3. We genetically dissected Flt3L-driven DC differentiation using CRISPR-Cas9-based screening. Genome-wide screening identified multiple regulators of DC differentiation including subunits of TSC and GATOR1 complexes, which restricted progenitor growth but enabled DC differentiation by inhibiting mTOR signaling. An orthogonal screen identified the transcriptional repressor Trim33 (TIF-1γ) as a regulator of DC differentiation. Conditional targeting in vivo revealed an essential role of Trim33 in the development of all DCs, but not of monocytes or granulocytes. In particular, deletion of Trim33 caused rapid loss of DC progenitors, pDCs, and the cross-presenting cDC1 subset. Trim33-deficient Flt3+ progenitors up-regulated pro-inflammatory and macrophage-specific genes but failed to induce the DC differentiation program. Collectively, these data elucidate mechanisms that control Flt3L-driven differentiation of the entire DC lineage and identify Trim33 as its essential regulator.

PMID:38608038 | DOI:10.1126/sciimmunol.adi1023