iScience. 2024 Mar 29;27(5):109646. doi: 10.1016/j.isci.2024.109646. eCollection 2024 May 17.

ABSTRACT

Most advanced colorectal cancer (CRC) patients cannot benefit from targeted therapy due to lack of actionable targets. By mining data from the DepMap, we identified FAM126B as a specific vulnerability in CRC cell lines exhibiting low FAM126A expression. Employing a combination of genetic perturbation and inducible protein degradation techniques, we demonstrate that FAM126A and FAM126B function in a redundant manner to facilitate the recruitment of PI4KIIIα to the plasma membrane for PI4P synthesis. Examination of data from TCGA and GTEx revealed that over 7% of CRC tumor samples exhibited loss of FAM126A expression, contrasting with uniform FAM126A expression in normal tissues. In both CRC cell lines and tumor samples, promoter hypermethylation correlated with the loss of FAM126A expression, which could be reversed by DNA methylation inhibitors. In conclusion, our study reveals that loss of FAM126A expression results in FAM126B dependency, thus proposing FAM126B as a therapeutic target for CRC treatment.

PMID:38638566 | PMC:PMC11025007 | DOI:10.1016/j.isci.2024.109646

Front Bioeng Biotechnol. 2024 Apr 4;12:1356551. doi: 10.3389/fbioe.2024.1356551. eCollection 2024.

ABSTRACT

The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, and 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces.

PMID:38638323 | PMC:PMC11024372 | DOI:10.3389/fbioe.2024.1356551

Bioinform Adv. 2024 Mar 23;4(1):vbae048. doi: 10.1093/bioadv/vbae048. eCollection 2024.

ABSTRACT

MOTIVATION: Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods.

RESULTS: In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods.

AVAILABILITY AND IMPLEMENTATION: https://github.com/Papatheodorou-Group/CATD_snakemake.

PMID:38638280 | PMC:PMC11023940 | DOI:10.1093/bioadv/vbae048

F1000Res. 2024 Apr 8;12:745. doi: 10.12688/f1000research.133645.2. eCollection 2023.

ABSTRACT

A member of the RNA-binding protein family, T-cell intracellular antigen-1 (TIA1) regulates mRNA translation and splicing as well as cellular stress by promoting stress granule formation. Variants of the TIA1 gene have implications in neurogenerative disorders including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Reproducible research on TIA1 would be enhanced with the availability of high-quality anti-TIA1 antibodies. In this study, we characterized twelve TIA1 commercial antibodies for Western Blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. We identified many high-performing antibodies and encourage readers to use this report as a guide to select the most appropriate antibody for their specific needs.

PMID:38638178 | PMC:PMC11024596 | DOI:10.12688/f1000research.133645.2

Front Nephrol. 2024 Apr 4;4:1349859. doi: 10.3389/fneph.2024.1349859. eCollection 2024.

ABSTRACT

Renal cell carcinoma (RCC), particularly the clear cell subtype (ccRCC), poses a significant global health concern due to its increasing prevalence and resistance to conventional therapies. Early detection of ccRCC remains challenging, resulting in poor patient survival rates. In this study, we employed a bioinformatic approach to identify potential prognostic biomarkers for kidney renal clear cell carcinoma (KIRC). By analyzing RNA sequencing data from the TCGA-KIRC project, differentially expressed genes (DEGs) associated with ccRCC were identified. Pathway analysis utilizing the Qiagen Ingenuity Pathway Analysis (IPA) tool elucidated key pathways and genes involved in ccRCC dysregulation. Prognostic value assessment was conducted through survival analysis, including Cox univariate proportional hazards (PH) modeling and Kaplan-Meier plotting. This analysis unveiled several promising biomarkers, such as MMP9, PIK3R6, IFNG, and PGF, exhibiting significant associations with overall survival and relapse-free survival in ccRCC patients. Cox multivariate PH analysis, considering gene expression and age at diagnosis, further confirmed the prognostic potential of MMP9, IFNG, and PGF genes. These findings enhance our understanding of ccRCC and provide valuable insights into potential prognostic biomarkers that can aid healthcare professionals in risk stratification and treatment decision-making. The study also establishes a foundation for future research, validation, and clinical translation of the identified prognostic biomarkers, paving the way for personalized approaches in the management of KIRC.

PMID:38638111 | PMC:PMC11024385 | DOI:10.3389/fneph.2024.1349859

Curr Med Chem. 2024 Apr 17. doi: 10.2174/0109298673288774240406053607. Online ahead of print.

ABSTRACT

AIM: This study aimed to investigate the antioxidant properties, cytotoxic activity, and apoptotic effects of astaxanthin (ASX) on genes and pathways involved in breast cancer in Balb/c mice models injected with the 4T1 cell line.

BACKGROUND: ASX could inhibit some tumor progression by using in vivo and in vitro models.

OBJECTIVE: The effect of ASX on breast cancer was not fully understood till now.

METHOD: In an in vivo model, 4T1 cells-injected mice were administered with different concentrations of ASX (100 and 200 mg/kg), and histopathological evaluations were done using an optical microscope and the hematoxylin and eosin (H&E) staining. The real- time PCR investigated the expression levels of B-cell lymphoma 2-associated X (Bax), B-cell lymphoma 2 (Bcl-2), and Caspase 3 genes in mice treated with 100 and 200 mg/kg ASX. Also, the level of superoxide dismutase (SOD) and malondialdehyde (MDA) were examined in ASX-treated cancer mice.

RESULTS: ASX (200 mg/kg) caused a significant reduction in the mitotic cell count of tumor tissues compared to ASX (100 mg/kg). The antiproliferative effects of different concentrations of ASX were shown based on the MTT results. The treatment of breast tumor mice with both concentrations of ASX, especially 200 mg/kg, elevated the expression of Caspase 3, Bax, and SOD enzyme levels and decreased Bcl-2 expression and MDA enzyme levels.

CONCLUSION: ASX can be considered a promising alternative treatment for breast cancer.

PMID:38638038 | DOI:10.2174/0109298673288774240406053607

Nat Commun. 2024 Apr 18;15(1):3351. doi: 10.1038/s41467-024-47671-0.

ABSTRACT

While much prior work has explored the constraints on protein sequence and evolution induced by physical protein-protein interactions, the sequence-level constraints emerging from non-binding functional interactions in metabolism remain unclear. To quantify how variation in the activity of one enzyme constrains the biochemical parameters and sequence of another, we focus on dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), a pair of enzymes catalyzing consecutive reactions in folate metabolism. We use deep mutational scanning to quantify the growth rate effect of 2696 DHFR single mutations in 3 TYMS backgrounds under conditions selected to emphasize biochemical epistasis. Our data are well-described by a relatively simple enzyme velocity to growth rate model that quantifies how metabolic context tunes enzyme mutational tolerance. Together our results reveal the structural distribution of epistasis in a metabolic enzyme and establish a foundation for the design of multi-enzyme systems.

PMID:38637543 | DOI:10.1038/s41467-024-47671-0

Theor Appl Genet. 2024 Apr 18;137(5):108. doi: 10.1007/s00122-024-04613-0.

ABSTRACT

The integration of genomic prediction with crop growth models enabled the estimation of missing environmental variables which improved the prediction accuracy of grain yield. Since the invention of whole-genome prediction (WGP) more than two decades ago, breeding programmes have established extensive reference populations that are cultivated under diverse environmental conditions. The introduction of the CGM-WGP model, which integrates crop growth models (CGM) with WGP, has expanded the applications of WGP to the prediction of unphenotyped traits in untested environments, including future climates. However, CGMs require multiple seasonal environmental records, unlike WGP, which makes CGM-WGP less accurate when applied to historical reference populations that lack crucial environmental inputs. Here, we investigated the ability of CGM-WGP to approximate missing environmental variables to improve prediction accuracy. Two environmental variables in a wheat CGM, initial soil water content (InitlSoilWCont) and initial nitrate profile, were sampled from different normal distributions separately or jointly in each iteration within the CGM-WGP algorithm. Our results showed that sampling InitlSoilWCont alone gave the best results and improved the prediction accuracy of grain number by 0.07, yield by 0.06 and protein content by 0.03. When using the sampled InitlSoilWCont values as an input for the traditional CGM, the average narrow-sense heritability of the genotype-specific parameters (GSPs) improved by 0.05, with GNSlope, PreAnthRes, and VernSen showing the greatest improvements. Moreover, the root mean square of errors for grain number and yield was reduced by about 7% for CGM and 31% for CGM-WGP when using the sampled InitlSoilWCont values. Our results demonstrate the advantage of sampling missing environmental variables in CGM-WGP to improve prediction accuracy and increase the size of the reference population by enabling the utilisation of historical data that are missing environmental records.

PMID:38637355 | DOI:10.1007/s00122-024-04613-0

Semin Fetal Neonatal Med. 2024 Apr 9:101522. doi: 10.1016/j.siny.2024.101522. Online ahead of print.

ABSTRACT

Interdisciplinary fetal-neonatal neurology (FNN) training considers a woman's reproductive and pregnancy health histories when assessing the "four great neonatal neurological syndromes". This maternal-child dyad exemplifies the symptomatic neonatal minority, compared with the silent majority of healthy children who experience preclinical diseases with variable expressions over the first 1000 days. Healthy maternal reports with reassuring fetal surveillance testing preceded signs of fetal distress during parturition. An encephalopathic neonate with seizures later exhibited childhood autistic spectrum behaviors and intractable epilepsy correlated with identified genetic biomarkers. A systems biology approach to etiopathogenesis guides the diagnostic process to interpret phenotypic form and function. Evolving gene-environment interactions expressed by changing phenotypes reflect a dynamic neural exposome influenced by reproductive and pregnancy health. This strategy considers critical/sensitive periods of neuroplasticity beyond two years of life to encompass childhood and adolescence. Career-long FNN experiences reenforce earlier training to strengthen the cognitive process and minimize cognitive biases when assessing children or adults. Prioritizing social determinants of healthcare for persons with neurologic disorders will help mitigate the global burden of brain diseases for all women and children.

PMID:38637242 | DOI:10.1016/j.siny.2024.101522

Food Microbiol. 2024 Aug;121:104514. doi: 10.1016/j.fm.2024.104514. Epub 2024 Mar 2.

ABSTRACT

The enzymatic repertoire of starter cultures belonging to the Lactococcus genus determines various important characteristics of fermented dairy products but might change in response to the substantial environmental changes in the manufacturing process. Assessing bacterial proteome adaptation in dairy and other food environments is challenging due to the high matrix-protein concentration and is even further complicated in particularly cheese by the high fat concentrations, the semi-solid state of that matrix, and the non-growing state of the bacteria. Here, we present bacterial harvesting and processing procedures that enable reproducible, high-resolution proteome determination in lactococcal cultures harvested from laboratory media, milk, and miniature Gouda cheese. Comparative proteome analysis of Lactococcus cremoris NCDO712 grown in laboratory medium and milk revealed proteome adaptations that predominantly reflect the differential (micro-)nutrient availability in these two environments. Additionally, the drastic environmental changes during cheese manufacturing only elicited subtle changes in the L. cremoris NCDO712 proteome, including modified expression levels of enzymes involved in flavour formation. The technical advances we describe offer novel opportunities to evaluate bacterial proteomes in relation to their performance in complex, protein- and/or fat-rich food matrices and highlight the potential of steering starter culture performance by preculture condition adjustments.

PMID:38637076 | DOI:10.1016/j.fm.2024.104514

Metab Eng. 2024 Apr 16:S1096-7176(24)00058-2. doi: 10.1016/j.ymben.2024.04.004. Online ahead of print.

ABSTRACT

Microbes have inherent capacities for utilizing various carbon sources, however they often exhibit sub-par fitness due to low metabolic efficiency. To test whether a bacterial strain can optimally utilize multiple carbon sources, Escherichia coli was serially evolved in L-lactate and glycerol. This yielded two end-point strains that evolved first in L-lactate then in glycerol, and vice versa. The end-point strains displayed a universal growth advantage on single and a mixture of adaptive carbon sources, enabled by a concerted action of carbon source-specialists and generalist mutants. The combination of just four variants of glpK, ppsA, ydcI, and rph-pyrE, accounted for more than 80% of end-point strain fitness. In addition, machine learning analysis revealed a coordinated activity of transcriptional regulators imparting condition-specific regulation of gene expression. The effectiveness of the serial adaptive laboratory evolution (ALE) scheme in bioproduction applications was assessed under single and mixed-carbon culture conditions, in which serial ALE strain exhibited superior productivity of acetoin compared to ancestral strains. Together, systems-level analysis elucidated the molecular basis of serial evolution, which hold potential utility in bioproduction applications.

PMID:38636729 | DOI:10.1016/j.ymben.2024.04.004

Cell Syst. 2024 Apr 17;15(4):322-338.e5. doi: 10.1016/j.cels.2024.03.004.

ABSTRACT

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here, we integrated CODEX multiplexed tissue imaging with multiscale modeling software to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface. A record of this paper's transparent peer review process is included in the supplemental information.

PMID:38636457 | DOI:10.1016/j.cels.2024.03.004

Plant Cell. 2024 Apr 18:koae095. doi: 10.1093/plcell/koae095. Online ahead of print.

ABSTRACT

Cereal grains are an important source of food and feed. To provide comprehensive spatiotemporal information about biological processes in developing seeds of cultivated barley (Hordeum vulgare L. subsp. vulgare), we performed a transcriptomic study of the embryo, endosperm, and seed maternal tissues collected from grains 4-32 days after pollination. Weighted gene co-expression network and motif enrichment analyses identified specific groups of genes and transcription factors (TFs) potentially regulating barley seed tissue development. We defined a set of tissue-specific marker genes and families of TFs for functional studies of the pathways controlling barley grain development. Assessing selected groups of chromatin regulators revealed that epigenetic processes are highly dynamic and likely play a major role during barley endosperm development. The repressive H3K27me3 modification is globally reduced in endosperm tissues and at specific genes related to development and storage compounds. Altogether, this atlas uncovers the complexity of developmentally regulated gene expression in developing barley grains.

PMID:38635902 | DOI:10.1093/plcell/koae095

PLoS One. 2024 Apr 18;19(4):e0300524. doi: 10.1371/journal.pone.0300524. eCollection 2024.

ABSTRACT

To address the need for multivalent vaccines against Coronaviridae that can be rapidly developed and manufactured, we compared antibody responses against SARS-CoV, SARS-CoV-2, and several variants of concern in mice immunized with mRNA-lipid nanoparticle vaccines encoding homodimers or heterodimers of SARS-CoV/SARS-CoV-2 receptor-binding domains. All vaccine constructs induced robust anti-RBD antibody responses, and the heterodimeric vaccine elicited an IgG response capable of cross-neutralizing SARS-CoV, SARS-CoV-2 Wuhan-Hu-1, B.1.351 (beta), and B.1.617.2 (delta) variants.

PMID:38635805 | DOI:10.1371/journal.pone.0300524

Science. 2024 Apr 19;384(6693):eadl2016. doi: 10.1126/science.adl2016. Epub 2024 Apr 19.

ABSTRACT

Infectious diseases continue to claim many lives. Prevention of morbidity and mortality from these diseases would benefit not just from new medicines and vaccines but also from a better understanding of what constitutes protective immunity. Among the major immune signals that mobilize host defense against infection is interferon-γ (IFN-γ), a protein secreted by lymphocytes. Forty years ago, IFN-γ was identified as a macrophage-activating factor, and, in recent years, there has been a resurgent interest in IFN-γ biology and its role in human defense. Here we assess the current understanding of IFN-γ, revisit its designation as an "interferon," and weigh its prospects as a therapeutic against globally pervasive microbial pathogens.

PMID:38635718 | DOI:10.1126/science.adl2016

PLoS One. 2024 Apr 18;19(4):e0297847. doi: 10.1371/journal.pone.0297847. eCollection 2024.

ABSTRACT

The uterine muscular layer, or myometrium, undergoes profound changes in global gene expression during its progression from a quiescent state during pregnancy to a contractile state at the onset of labor. In this study, we investigate the role of SOX family transcription factors in myometrial cells and provide evidence for the role of SOX4 in regulating labor-associated genes. We show that Sox4 has elevated expression in the murine myometrium during a term laboring process and in two mouse models of preterm labor. Additionally, SOX4 differentially affects labor-associated gene promoter activity in cooperation with activator protein 1 (AP-1) dimers. SOX4 exerted no effect on the Gja1 promoter; a JUND-specific activation effect at the Fos promoter; a positive activation effect on the Mmp11 promoter with the AP-1 dimers; and surprisingly, we noted that the reporter expression of the Ptgs2 promoter in the presence of JUND and FOSL2 was repressed by the addition of SOX4. Our data indicate SOX4 may play a diverse role in regulating gene expression in the laboring myometrium in cooperation with AP-1 factors. This study enhances our current understanding of the regulatory network that governs the transcriptional changes associated with the onset of labor and highlights a new molecular player that may contribute to the labor transcriptional program.

PMID:38635533 | DOI:10.1371/journal.pone.0297847

Biochem Genet. 2024 Apr 18. doi: 10.1007/s10528-024-10799-1. Online ahead of print.

ABSTRACT

One of the trending fields in almost all areas of science and technology is artificial intelligence. Computational biology and artificial intelligence can help gene therapy in many steps including: gene identification, gene editing, vector design, development of new macromolecules and modeling of gene delivery. There are various tools used by computational biology and artificial intelligence in this field, such as genomics, transcriptomic and proteomics data analysis, machine learning algorithms and molecular interaction studies. These tools can introduce new gene targets, novel vectors, optimized experiment conditions, predict the outcomes and suggest the best solutions to avoid undesired immune responses following gene therapy treatment.

PMID:38635012 | DOI:10.1007/s10528-024-10799-1

Nucleic Acids Res. 2024 Apr 18:gkae287. doi: 10.1093/nar/gkae287. Online ahead of print.

ABSTRACT

Tackling climate change challenges requires replacing current chemical industrial processes through the rational and sustainable use of biodiversity resources. To that end, production routes to key bio-based chemicals for the bioeconomy have been identified. However, their production still remains inefficient in terms of titers, rates, and yields; because of the hurdles found when scaling up. In order to make production more efficient, strategies like automated screening and dynamic pathway regulation through biosensors have been applied as part of strain optimization. However, to date, no systematic way exists to design a genetic circuit that is responsive to concentrations of a given target compound. Here, the DetSpace web server provides a set of integrated tools that allows a user to select and design a biological circuit that performs the sensing of a molecule of interest by its enzymatic conversion to a detectable molecule through a transcription factor. In that way, the DetSpace web server allows synthetic biologists to easily design biosensing routes for the dynamic regulation of metabolic pathways in applications ranging from genetic circuits design, screening, production, and bioremediation of bio-based chemicals, to diagnostics and drug delivery.

PMID:38634809 | DOI:10.1093/nar/gkae287

mBio. 2024 Apr 18:e0001224. doi: 10.1128/mbio.00012-24. Online ahead of print.

ABSTRACT

The microbiome expresses a variety of functions that influence host biology. The range of functions depends on the microbiome's composition, which can change during the host's lifetime due to neutral assembly processes, host-mediated selection, and environmental conditions. To date, the exact dynamics of microbiome assembly, the underlying determinants, and the effects on host-associated functions remain poorly understood. Here, we used the nematode Caenorhabditis elegans and a defined community of fully sequenced, naturally associated bacteria to study microbiome dynamics and functions across a major part of the worm's lifetime of hosts under controlled experimental conditions. Bacterial community composition initially shows strongly declining levels of stochasticity, which increases during later time points, suggesting selective effects in younger animals as opposed to more random processes in older animals. The adult microbiome is enriched in genera Ochrobactrum and Enterobacter compared to the direct substrate and a host-free control environment. Using pathway analysis, metabolic, and ecological modeling, we further find that the lifetime assembly dynamics increase competitive strategies and gut-associated functions in the host-associated microbiome, indicating that the colonizing bacteria benefit the worm. Overall, our study introduces a framework for studying microbiome assembly dynamics based on stochastic, ecological, and metabolic models, yielding new insights into the processes that determine host-associated microbiome composition and function.

IMPORTANCE: The microbiome plays a crucial role in host biology. Its functions depend on the microbiome composition that can change during a host's lifetime. To date, the dynamics of microbiome assembly and the resulting functions still need to be better understood. This study introduces a new approach to characterize the functional consequences of microbiome assembly by modeling both the relevance of stochastic processes and metabolic characteristics of microbial community changes. The approach was applied to experimental time-series data obtained for the microbiome of the nematode Caenorhabditis elegans across the major part of its lifetime. Stochastic processes played a minor role, whereas beneficial bacteria as well as gut-associated functions enriched in hosts. This indicates that the host might actively shape the composition of its microbiome. Overall, this study provides a framework for studying microbiome assembly dynamics and yields new insights into C. elegans microbiome functions.

PMID:38634692 | DOI:10.1128/mbio.00012-24

Allergy. 2024 Apr 17. doi: 10.1111/all.16127. Online ahead of print.

ABSTRACT

BACKGROUND: Chronic spontaneous urticaria (CSU) is a common, debilitating skin disorder characterized by recurring episodes of raised, itchy and sometimes painful wheals lasting longer than 6 weeks. CSU is mediated by mast cells which are absent from peripheral blood. However, lineage-CD34hiCD117int/hiFcεRI+ cells in blood have previously been shown to represent a mast cell precursor.

METHODS: We enumerated FcεRI-, FcεRI+ and FcεRIhi lineage-CD34+CD117+ cells using flow cytometry in blood of patients with CSU (n = 55), including 12 patients receiving omalizumab and 43 not receiving omalizumab (n = 43). Twenty-two control samples were studied. Disease control and patient response to omalizumab was evaluated using the urticaria control test. We performed single-cell RNA sequencing (scRNA-Seq) on lineage-CD34hiCD117hi blood cells from a subset of patients with CSU (n = 8) and healthy controls (n = 4).

RESULTS: CSU patients had more lineage-CD34+CD117+FcεRI+ blood cells than controls. Lineage-CD34+CD117+FcεRI+ cells were significantly higher in patients with CSU who had an objective clinical response to omalizumab when compared to patients who had poor disease control 90 days after initiation of omalizumab. scRNA-Seq revealed that lineage-CD34+CD117+FcεRI+ cells contained both lymphoid and myeloid progenitor lineages, with omalizumab responsive patients having proportionally more myeloid progenitors. The myeloid progenitor lineage contained small numbers of true mast cell precursors along with more immature FcεRI- and FcεRI+ myeloid progenitors.

CONCLUSION: Increased blood CD34+CD117+FcεRI+ cells may reflect enhanced bone marrow egress in the setting of CSU. High expression of these cells strongly predicts better clinical responses to the anti-IgE therapy, omalizumab.

PMID:38634175 | DOI:10.1111/all.16127