Transcriptional Features Research Articles

P0010 Characterization of proliferating memory CD4⁺ T cells reveals a distinct immune signature in anti-α4β7 integrin therapy non-responders Inflammatory Bowel Disease patients

Abstract Background Failure to respond to the anti-α4β7 integrin therapy, vedolizumab, is observed in a subset of inflammatory bowel disease (IBD) patients, potentially linked to distinct T cell activation profiles. This study aims to characterize the transcriptional and phenotypic features of circulating memory CD4⁺ T cells in vedolizumab non-responders and their association with treatment resistance. Methods We performed multidimensional flow cytometry and single-cell RNA sequencing to analyze IBD patients' circulating memory CD4⁺ T cell compartment, comparing pre- and post-treatment peripheral blood samples from vedolizumab responders and non-responders. Proteogenomic analysis and TCR repertoire profiling of CD4⁺ T cells were conducted using matched peripheral blood samples. Flow cytometry characterized T cell subsets based on surface markers, migration receptors, transcription factors, and cytokine expression, focusing on differences in activation and migration profiles. Results Ki67⁺ cells were enriched in the memory CD4⁺ T cell population of vedolizumab non-responders in both UC and CD, confirmed by two independent cohorts. TCR repertoire analysis showed increased diversity in memory CD4⁺ T cells post-treatment. Single-cell sequencing and proteomics revealed these Ki67⁺ cells had a high activation and proliferation profile (HLA-DR, CD40LG, MKI67) with reduced IL7R and SELL expression. They displayed elevated integrins (α4, β1, β7) and gut-homing receptors (CXCR3, CCR6). Upregulated T-bet, EOMES, and RORγt and increased IL-17A, indicated a pro-inflammatory Th1/Th17 phenotype in non-responders. Conclusion Ki67⁺ memory CD4⁺ T cells are significantly enriched in the peripheral blood of vedolizumab non-responders, displaying a distinct transcriptional and phenotypic profile characterized by Th1/Th17 polarization, high integrin α4β1 expression, and enhanced gut-homing capacity. These findings indicate that proliferating effector memory CD4⁺ T cells could contribute to therapy resistance in IBD, emphasizing the need for alternative therapeutic strategies targeting these cells in anti-α4β7 integrin therapy non-responders.

Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer

Recent evidence indicates that endocrine resistance in estrogen receptor-positive (ER+) breast cancer is closely correlated with phenotypic characteristics of epithelial-to-mesenchymal transition (EMT). Nonetheless, identifying tumor tissues with a mesenchymal phenotype remains challenging in clinical practice. In this study, we validated the correlation between EMT status and resistance to endocrine therapy in ER+ breast cancer from a transcriptomic perspective. To confirm the presence of morphological discrepancies in tumor tissues of ER+ breast cancer classified as epithelial- and mesenchymal-phenotypes according to EMT-related transcriptional features, we trained deep learning algorithms based on EfficientNetV2 architecture to assign the phenotypic status for each patient utilizing hematoxylin & eosin (H&E)-stained slides from The Cancer Genome Atlas database. Our classifier model accurately identified the precise phenotypic status, achieving an area under the curve (AUC) of 0.886 at the tile-level and an AUC of 0.910 at the slide-level. Furthermore, we evaluated the efficacy of the classifier in predicting endocrine response using data from an independent ER+ breast cancer patient cohort. Our classifier achieved a predicting accuracy of 81.25%, and 88.7% slides labeled as endocrine resistant were predicted as the mesenchymal-phenotype, while 75.6% slides labeled as sensitive were predicted as the epithelial-phenotype. Our work introduces an H&E-based framework capable of accurately predicting EMT phenotype and endocrine response for ER+ breast cancer, demonstrating its potential for clinical application and benefit.

Hormone Receptor-Positive HER2-Negative/MammaPrint High-2 Breast Cancers Closely Resemble Triple-Negative Breast Cancers.

The MammaPrint (MP) prognostic assay categorizes breast cancers into high- and low-risk subgroups, and the high-risk group can be further subdivided into high-1 (MP-H1), and very high-risk high-2 (MP-H2). The aim of this analysis was to assess clinical and molecular differences between the hormone receptor-positive (HR+)/HER2-negative MP-H1, -H2, and triple-negative (TN) MP-H1 and -H2 cancers. Pretreatment gene expression data from 742 HER2-negative breast cancers enrolled in the I-SPY2 neoadjuvant trial were used. Prognostic risk categories were assigned using the MP assay. Transcriptional similarities across the four receptor and prognostic groups were assessed using principal component analyses and by identifying differentially expressed genes. We also examined pathologic complete response rates and event-free survivals by risk group. Principal component analysis showed that HR+/MP-H2 tumors clustered with TN/MP-H2 cancers. Only 125 genes showed differential expression between the HR+/MP-H2 and TN/MP-H2 cancers, whereas 1,465 genes were differentially expressed between HR+/MP-H2 and -H1. Gene set analysis revealed similarly high expression of cell cycle, DNA repair, and immune infiltration-related pathways in HR+/MP-H2 and TN/MP-H2 cancers. HR+/MP-H2 cancers also showed low estrogen receptor-related gene expression. Pathologic complete response rates were similarly high in TN/MP-H2 and HR+/MP-H2 cancers (42% vs. 30.5%; P = 0.11), and MP-H2 cancers with residual cancer had similarly poor event-free survival regardless of estrogen receptor status. In conclusion, HR+/MP-H2 cancers closely resemble TN breast cancers in transcriptional and clinical features and benefit from similar treatment strategies.

HIV-SEQ REVEALS GLOBAL HOST GENE EXPRESSION DIFFERENCES BETWEEN HIV-TRANSCRIBING CELLS FROM VIREMIC AND SUPPRESSED PEOPLE WITH HIV.

"Active" reservoir cells transcribing HIV can perpetuate chronic inflammation in virally suppressed people with HIV (PWH) and likely contribute to viral rebound after antiretroviral therapy (ART) interruption, so they represent an important target for new therapies. These cells, however, are difficult to study using single-cell RNA-seq (scRNA-seq) due to their low frequency and low levels of HIV transcripts, which are usually not polyadenylated. Here, we developed "HIV-seq" to enable more efficient capture of HIV transcripts - including non-polyadenylated ones - for scRNA-seq analysis of cells from PWH. By spiking in a set of custom-designed capture sequences targeting conserved regions of the HIV genome during scRNA-seq, we increased our ability to find HIV RNA+ cells from PWH by up to 44%. Implementing HIV-seq in conjunction with surface phenotyping by CITE-seq on paired blood specimens from PWH before vs. after ART suppression, we found that HIV RNA+ cells were enriched among T effector memory (Tem) cells during both viremia and ART suppression, but exhibited a cytotoxic signature during viremia only. By contrast, HIV RNA+ cells from the ART-suppressed timepoints exhibited a distinct anti-inflammatory signature involving elevated TGF-β and diminished IFN signaling. Overall, these findings demonstrate that active reservoir cells exhibit transcriptional features distinct from HIV RNA+ cells during viremia, and underscore HIV-seq as a useful tool to better understand the mechanisms by which HIV-transcribing cells can persist during ART.

Single-cell analysis of cerebrospinal fluid reveals common features of neuroinflammation.

Neuroinflammation is often characterized by immune cell infiltrates in the cerebrospinal fluid (CSF). Here, we apply single-cell RNA sequencing to explore the functional characteristics of these cells in patients with various inflammatory, infectious, and non-inflammatory neurological disorders. We show that CSF is distinct from the peripheral blood in terms of both cellular composition and gene expression. We report that the cellular and transcriptional landscape of CSF is altered in neuroinflammation but is strikingly similar across different neuroinflammatory disorders. We find clonal expansion of CSF lymphocytes in all disorders but most pronounced in inflammatory diseases, and we functionally characterize the transcriptional features of these cells. Finally, we explore the genetic control of gene expression in CSF lymphocytes. Our results highlight the common features of immune cells in the CSF compartment across diverse neurological diseases and may help to identify new targets for drug development or repurposing in multiple sclerosis (MS).

Lung adenocarcinomas with mucinous histology: clinical, genomic, and immune microenvironment characterization and outcomes to immunotherapy-based treatments and KRASG12C inhibitors

BackgroundApproximately 10% of lung adenocarcinomas (LUAD) have mucinous histology (LUADMuc), which is associated to a light/absent smoking history and a high prevalence of KRAS mutations. We sought to characterize LUADMuc by comparing it to LUAD without mucinous histology (LUADnon-muc) and determine the relative benefit of current treatments. Patients and MethodsPatients with LUAD from five institutions and TCGA PanCancer Atlas classified as LUADMuc or LUADnon-muc were included. Clinicopathologic, genomic, immunophenotypic, transcriptional features, and treatment outcomes were compared between LUADMuc and LUADnon-muc. ResultsOf 4,082 patients with LUAD, 9.9% had LUADMuc. Compared to LUADnon-muc, patients with LUADMuc had a lighter smoking history (median: 15 vs 20 pack-years, P=0.008), lower PD-L1 TPS (median: 0% vs 5%, P<0.0001), and lower tumor mutation burden (median: 6.8 vs 8.5 mutations/megabase, P<0.0001). Mutations in KRAS, NKX2-1 (TTF-1), STK11, SMARCA4, GNAS, and ALK rearrangements were enriched in LUADMuc, while TP53, EGFR, BRAF, and MET mutations were enriched in LUADnon-muc. At stage IV diagnosis, LUADMuc was more likely to have contralateral lung metastasis (55.2% vs 36.9%, P<0.0001) and less likely to have brain metastases (23.3% vs 41.9%, P<0.0001). Compared to LUADnon-muc, LUADMuc cases showed lower intratumor CD8+, PD-1+, CD8+PD-1+, and FOXP3+ cells. Among metastatic cases receiving ICIs, compared to LUADnon-muc (N=1,511), LUADMuc (N=112) had lower objective response rate (ORR, 8.4% vs 25.9%, P<0.0001), and shorter median progression-free survival (mPFS, 2.6 vs 3.9 months, P<0.0001) and overall survival (mOS, 9.9 vs 17.2 months, P<0.0001). Similarly, patients with LUADMuc had worse outcomes to chemo-immunotherapy. LUADMuc (N=18) and LUADnon-muc (N=150) had similar ORR (16.7% vs 34.9%, P=0.12) and mPFS (4.6 vs 5.6 months, P=0.17) to treatment with KRASG12C inhibitors, but LUADMuc had shorter mOS (6.8 vs 10.8 months, P=0.018). ConclusionLUADMuc represents a distinct LUAD subpopulation with unique clinicopathologic, genomic, immunophenotypic, and transcriptional features, achieving worse outcomes to standard immunotherapy-based treatments.

Systemic inflammation and lymphocyte activation precede rheumatoid arthritis.

Some autoimmune diseases, including rheumatoid arthritis (RA), are preceded by a critical subclinical phase of disease activity. Proactive clinical management is hampered by a lack of biological understanding of this subclinical at-risk state and the changes underlying disease development. In a cross-sectional and longitudinal multi-omics study of peripheral immunity in the autoantibody-positive at-risk for RA period, we identified systemic inflammation, proinflammatory-skewed B cells, expanded Tfh17-like cells, epigenetic bias in naive T cells, TNF+IL1B+ monocytes resembling a synovial macrophage population, and CD4 T cell transcriptional features resembling those suppressed by abatacept (CTLA4-Ig) in RA patients. Our findings characterize pathogenesis prior to clinical diagnosis and suggest the at-risk state exhibits substantial immune alterations that could potentially be targeted for early intervention to delay or prevent autoimmunity. We provide a suite of tools at https://apps.allenimmunology.org/aifi/insights/ra-progression/ to facilitate exploration and enhance accessibility of this extensive dataset.

A promising drug repurposing approach for Alzheimer's treatment: Givinostat improves cognitive behavior and pathological features in APP/PS1 mice

Alzheimer's disease (AD) is the most common neurodegenerative disease, characterized by memory loss, speech and motor defects, personality changes, and psychological disorders. The exact cause of AD remains unclear. Current treatments focus on maintaining neurotransmitter levels or targeting β-amyloid (Aβ) protein, but these only alleviate symptoms and do not reverse the disease. Developing new drugs is time-consuming, costly, and has a high failure rate. Utilizing multi-omics for drug repositioning has emerged as a new strategy. Based on transcriptomic perturbation data of over 40,000 drugs in human cells from the LINCS-L1000 database, our study employed the Jaccard index and hypergeometric distribution test for reverse transcriptional feature matching analysis, identifying Givinostat as a potential treatment for AD. Our research found that Givinostat improved cognitive behavior and brain pathology in models and enhanced hippocampal synaptic plasticity. Transcriptome sequencing revealed increased expression of mitochondrial respiratory chain complex proteins in the brains of APP/PS1 mice after Givinostat treatment. Functionally, Givinostat restored mitochondrial membrane potential, reduced reactive oxygen species, and increased ATP content in Aβ-induced HT22 cells. Additionally, it improved mitochondrial morphology and quantity in the hippocampus of APP/PS1 mice and enhanced brain glucose metabolic activity. These effects are linked to Givinostat promoting mitochondrial biogenesis and improving mitochondrial function. In summary, Givinostat offers a promising new strategy for AD treatment by targeting mitochondrial dysfunction.

Senolytic treatment diminishes microglia and decreases severity of experimental autoimmune encephalomyelitis

BackgroundThe role of senescence in disease contexts is complex, however there is considerable evidence that depletion of senescent cells improves outcomes in a variety of contexts particularly related to aging, cognition, and neurodegeneration. Much research has shown previously that inflammation can promote cellular senescence. Microglia are a central nervous system innate immune cell that undergo senescence with aging and during neurodegeneration. The contribution of senescent microglia to multiple sclerosis, an inflammatory neurodegenerative disease, is not clear, but microglia are strongly implicated in chronic active lesion pathology, tissue injury, and disease progression. Drugs that could specifically eliminate dysregulated microglia in multiple sclerosis are therefore of great interest to the field.ResultsA single-cell analysis of brain tissue from mice subjected to experimental autoimmune encephalomyelitis (EAE), a mouse model of CNS inflammation that models aspects of multiple sclerosis (MS), identified microglia with a strong transcriptional signature of senescence including the presence of BCL2-family gene transcripts. Microglia expressing Bcl2l1 had higher expression of pro-inflammatory and senescence associated genes than their Bcl2l1 negative counterparts in EAE, suggesting they may exacerbate inflammation. Notably, in human single-nucleus sequencing from MS, BCL2L1 positive microglia were enriched in lesions with active inflammatory pathology, and likewise demonstrated increased expression of immune genes suggesting they may be proinflammatory and contribute to disease processes in chronic active lesions. Employing a small molecule BCL2-family inhibitor, Navitoclax (ABT-263), significantly reduced the presence of microglia and macrophages in the EAE spinal cord, suggesting that these cells can be targeted by senolytic treatment. ABT-263 treatment had a profound effect on EAE mice: decreasing motor symptom severity, improving visual acuity, promoting neuronal survival, and decreasing white matter inflammation.ConclusionThese results support the hypothesis that microglia and macrophages exhibit transcriptional features of cellular senescence in EAE and MS, and that microglia expressing Bcl2l1 demonstrate a proinflammatory signature that may exacerbate inflammation resulting in negative outcomes in neuroinflammatory disease. Depleting microglia and macrophages using a senolytic results in robust improvement in EAE disease severity, including across measures of neurodegeneration, inflammation, and demyelination, and may therefore represent a novel strategy to address disease progression in multiple sclerosis.

Somatic DICER1-Mutant Benign Thyroid Nodules in Adults: A Group of Follicular Nodular Disease With Continuous Growth.

Germline DICER1 mutations cause familial multinodular goiter (MNG). However, the prevalence of somatic DICER1 mutations in non-MNG benign thyroid nodules and their characteristics remain unknown. Adult-onset thyroid nodules with a pathological diagnosis were genotyped via targeted sequencing. DICER1-mutant nodules were assessed clinically and pathologically. Organoids were established to investigate follicular formation and growth. Transcriptomic analysis was conducted to evaluate transcriptional features, which were validated by immunofluorescence. Among 931 adult-onset thyroid nodules, we identified 13 benign thyroid nodules with DICER1 hotspot mutations. The majority harbored a somatic DICER1 hotspot mutation with a somatic DICER1 truncating variant. Clinically, 38.5% of the DICER1-mutant nodules exhibited substantial growth. DICER1-mutant nodules with durations longer than 2 years were substantially enlarged (P=.0448). Pathologically, all DICER1-mutant nodules were defined as thyroid follicular nodular disease (TFND). The TFND nodules with DICER1 mutations grew faster than those with wild-type DICER1. Organoid culture of a DICER1-mutant nodule revealed increased active follicular formation. Compared with the normal thyroid tissues, the DICER1-mutant nodules had comparable thyroid differentiation scores, significantly higher ERK scores (P=.0141) and lower epithelial‒mesenchymal transition scores (P=.0001). Moreover, the expression of genes related to follicular polarity, such as CDH16, SLC5A5, TSHR and TPO, was downregulated in the DICER1-mutant nodules. Somatic DICER1 two-hit mutations represent a notable percentage in adult TFND patients, and DICER1-mutant benign thyroid nodules were characterized by continuous growth.

PneumoBrowse 2: an integrated visual platform for curated genome annotation and multiomics data analysis of Streptococcus pneumoniae.

Streptococcus pneumoniae is an opportunistic human pathogen responsible for high morbidity and mortality rates. Extensive genome sequencing revealed its large pangenome, serotype diversity, and provided insight into genome dynamics. However, functional genome analysis has lagged behind, as that requires detailed and time-consuming manual curation of genome annotations and integration of genomic and phenotypic data. To remedy this, PneumoBrowse was presented in 2018, a user-friendly interactive online platform, which provided the detailed annotation of the S. pneumoniae D39V genome, alongside transcriptomic data. Since 2018, many new studies on S. pneumoniae genome biology and protein functioning have been performed. Here, we present PneumoBrowse 2 (https://veeninglab.com/pneumobrowse), fully rebuilt in JBrowse 2. We updated annotations for transcribed and transcriptional regulatory features in the D39V genome. We added genome-wide data tracks for high-resolution chromosome conformation capture (Hi-C) data, chromatin immunoprecipitation coupled to high-throughput sequencing (ChIP-Seq), ribosome profiling, CRISPRi-seq gene essentiality data and more. Additionally, we included 18 phylogenetically diverse S. pneumoniae genomes and their annotations. By providing easy access to diverse high-quality genome annotations and links to other databases (including UniProt and AlphaFold), PneumoBrowse 2 will further accelerate research and development into preventive and treatment strategies, through increased understanding of the pneumococcal genome.

The Use of Automatic AI-based Notes and Transcription Services in Qualitative Research: Ethical and Methodological Concerns

The rise of online interviewing using videoconferencing platforms has impacted the way qualitative researchers conduct their data collection. Previous studies have investigated the use of Zoom Meetings for online data collection (Archibald et al., 2019; Lobe et al., 2020), yet other studies also have outlined ethical challenges when collecting data remotely (Bamdad et al., 2022; Lim &amp; Kaveri, 2024). In LIS studies, researchers have examined ethical considerations for qualitative research methods in a virtual setting (Newman et al., 2021), although the discussion surrounding the advancement of AI-based technology in online data collection has been limited. With the growing interest in the use of transcription features in Zoom Meetings to support data analysis (Handler et al., 2022), issues surrounding automatic AI-based notes and transcription services integrated with this platform may have been overlooked. This study reflected ethical and methodological concerns when collecting data on student mothers’ use of mobile devices via Zoom Meetings synced with Otter.ai services. Ten participants were involved in online interviews from February to May 2023, resulting in nine transcripts from Zoom Meetings and Otter.ai services each. Ethical and methodological concerns surrounding AI-based meeting assistants’ use were outlined, including data ownership and intellectual property management, data repository and flow strategies, real-time nature of interactions, implicit speech bias, and decision-making accountability. The study contributes to broadening the understanding of the ethical and methodological concerns for qualitative researchers when using AI meeting assistants and further calls for specific LIS guidelines in online research using AI technology.

The Use of Automatic AI-based Notes and Transcription Services in Qualitative Research: Ethical and Methodological Concerns

The rise of online interviewing using videoconferencing platforms has impacted the way qualitative researchers conduct their data collection. Previous studies have investigated the use of Zoom Meetings for online data collection (Archibald et al., 2019; Lobe et al., 2020), yet other studies also have outlined ethical challenges when collecting data remotely (Bamdad et al., 2022; Lim &amp; Kaveri, 2024). In LIS studies, researchers have examined ethical considerations for qualitative research methods in a virtual setting (Newman et al., 2021), although the discussion surrounding the advancement of AI-based technology in online data collection has been limited. With the growing interest in the use of transcription features in Zoom Meetings to support data analysis (Handler et al., 2022), issues surrounding automatic AI-based notes and transcription services integrated with this platform may have been overlooked. This study reflected ethical and methodological concerns when collecting data on student mothers’ use of mobile devices via Zoom Meetings synced with Otter.ai services. Ten participants were involved in online interviews from February to May 2023, resulting in nine transcripts from Zoom Meetings and Otter.ai services each. Ethical and methodological concerns surrounding AI-based meeting assistants' use were outlined, including data ownership and intellectual property management, data repository and flow strategies, real-time nature of interactions, implicit speech bias, and decision-making accountability. The study contributes to broadening the understanding of the ethical and methodological concerns for qualitative researchers when using AI meeting assistants and further calls for specific LIS guidelines in online research using AI technology.

An analysis of the clinical significance of the TKI-resistant gene ZNF687 for hepatocellular carcinoma patients.

Novel treatments such as monotherapy and combined immunotherapy significantly extend overall survival (OS) for hepatocellular carcinoma (HCC) patients, but HCC is susceptible to treatment resistance during long-term therapy. The resistance mechanism to targeted drugs in HCC remains ambiguous, making research on HCC drug resistance targets crucial for the development of precision medicine. To investigate the transcriptional features, biological functions and potential clinical value of the tyrosine kinase inhibitor (TKI)-resistant gene ZNF687 in HCC. The TKI-resistant genes of HCC were identified using clustered regularly interspaced short palindromic repeats (CRISPR) in vitro screening. Then, the dependence of HCC cell lines on ZNF687 was investigated in silico. We collected global mRNA datasets of HCC tissue, integrated the mRNA expression characteristics of ZNF687 in HCC and explored the impact of ZNF687 on HCC patient prognoses using the Kaplan-Meier method (in silico). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were then conducted, and a connectivity map and molecular docking technology were applied to find the underlying agent opposing ZNF687. In vitro, the guide RNA corresponding to ZNF687 was weakly detected in HCC cells, and ZNF687 deficiency was found to inhibit growth in HCC cell lines. ZNF687 mRNA was overexpressed and had a high discriminatory ability for HCC in 2,975 HCC samples, contrasting with 2,340 non-HCC samples. Moreover, an excessive ZNF687 transcript level was related to a worse overall survival (OS) prognosis. Histone modification, spliceosome, transcription coregulator activity, and nucleocytoplasmic transport were the most significant pathways for ZNF687 differential-related gene enrichment. Chaetocin was found to be a candidate compound and presented a strong affinity to ZNF687. ZNF687 represents a TKI-resistant and growth-dependent gene for HCC, the overexpression of which indicates poor OS for HCC patients. Additionally, ZNF687 is expected to be a druggable target for overcoming TKI resistance, and chaetocin may be a candidate therapeutic compound for ZNF687.

CRISPR/Cas9 editing of NKG2A improves the efficacy of primary CD33-directed chimeric antigen receptor natural killer cells

Chimeric antigen receptor (CAR)-modified natural killer (NK) cells show antileukemic activity against acute myeloid leukemia (AML) in vivo. However, NK cell-mediated tumor killing is often impaired by the interaction between human leukocyte antigen (HLA)-E and the inhibitory receptor, NKG2A. Here, we describe a strategy that overcomes CAR-NK cell inhibition mediated by the HLA-E-NKG2A immune checkpoint. We generate CD33-specific, AML-targeted CAR-NK cells (CAR33) combined with CRISPR/Cas9-based gene disruption of the NKG2A-encoding KLRC1 gene. Using single-cell multi-omics analyses, we identified transcriptional features of activation and maturation in CAR33-KLRC1ko-NK cells, which are preserved following exposure to AML cells. Moreover, CAR33-KLRC1ko-NK cells demonstrate potent antileukemic killing activity against AML cell lines and primary blasts in vitro and in vivo. We thus conclude that NKG2A-deficient CAR-NK cells have the potential to bypass immune suppression in AML.

Diverse intrinsic properties shape transcript stability and stabilization in Mycolicibacterium smegmatis.

Mycobacteria regulate transcript degradation to facilitate adaptation to environmental stress. However, the mechanisms underlying this regulation are unknown. Here we sought to gain understanding of the mechanisms controlling mRNA stability by investigating the transcript properties associated with variance in transcript stability and stress-induced transcript stabilization. We measured mRNA half-lives transcriptome-wide in Mycolicibacterium smegmatis in log phase growth and hypoxia-induced growth arrest. The transcriptome was globally stabilized in response to hypoxia, but transcripts of essential genes were generally stabilized more than those of non-essential genes. We then developed machine learning models that enabled us to identify the non-linear collective effect of a compendium of transcript properties on transcript stability and stabilization. We identified properties that were more predictive of half-life in log phase as well as properties that were more predictive in hypoxia, and many of these varied between leadered and leaderless transcripts. In summary, we found that transcript properties are differentially associated with transcript stability depending on both the transcript type and the growth condition. Our results reveal the complex interplay between transcript features and microenvironment that shapes transcript stability in mycobacteria.

Full-length single-cell BCR sequencing paired with RNA sequencing reveals convergent responses to pneumococcal vaccination

Single-cell RNA sequencing (scRNA-seq) can resolve transcriptional features from individual cells, but scRNA-seq techniques capable of resolving the variable regions of B cell receptors (BCRs) remain limited, especially from widely-used 3′-barcoded libraries. Here, we report a method that can recover paired, full-length variable region sequences of BCRs from 3′-barcoded scRNA-seq libraries. We first verify this method (B3E-seq) can produce accurate, full-length BCR sequences. We then apply this method to profile B cell responses elicited against the capsular polysaccharide of Streptococcus pneumoniae serotype 3 (ST3) by glycoconjugate vaccines in five infant rhesus macaques. We identify BCR features associated with specificity for the ST3 antigen which are present in multiple vaccinated monkeys, indicating a convergent response to vaccination. These results demonstrate the utility of our method to resolve key features of the B cell repertoire and profile antigen-specific responses elicited by vaccination.

Abnormal circadian rhythms exacerbate dilated cardiomyopathy by reducing the ventricular mechanical strength.

Dilated cardiomyopathy (DCM) has etiological and pathophysiological heterogeneity. Abnormal circadian rhythm (ACR) is related to the development of DCM in animal models, but exploration based on clinical samples is lacking. Sleep apnea (SA) is the most common disease related to ACR, and we chose SA as the study object to explore ACR-DCM. We included a derivation cohort (n =105) and a validation cohort (n = 65). DCM patients were divided into SA and without SA group. RT-qPCR was used to determine the change of rhythm gene expression pattern of heart samples from different timepoints. We used single-nucleus RNA sequencing (snRNA-seq) to explore the abnormal transcriptional patterns in the ACR group, and we verified the findings by pathological staining, atomic force microscopy (AFM), and Rev-erbα/β knockout (KO) mice analysis. DCM patients with SA showed decreased amplitude of rhythm gene expression. SA group showed more severe dilation of left heart chambers. From snRNA-seq, ACR-DCM lost the morning transcriptional patterns, detailly, actin cytoskeleton organization of cardiomyocytes (CMs) disrupted and hypertrophy aggravated, and the proportion of activated fibroblasts (Fibs) decreased with the reduction of fibrotic area ratio. The results of pathological staining, mechanical experiments, and transcriptional feature of Rev-erbα/β KO mice supported the above findings. Compared with the non-SA group, left ventricular (LV) wall dilation was more severe and the structural strength was lower in DCM patients with SA, and phenotypic changes in CM and Fib were involved in this process. ACR-DCM was histopathologically characterized by a structurally weak ventricular wall.

Single-cell sequencing of the vermiform appendix during development identifies transcriptional relationships with appendicitis in preschool children

BackgroundThe development of the human vermiform appendix at the cellular level, as well as its function, is not well understood. Appendicitis in preschool children, although uncommon, is associated with a high perforation rate and increased morbidity.MethodsWe performed single-cell RNA sequencing (scRNA-seq) on the human appendix during fetal and pediatric stages as well as preschool-age inflammatory appendices. Transcriptional features of each cell compartment were discussed in the developing appendix. Cellular interactions and differentiation trajectories were also investigated. We compared scRNA-seq profiles from preschool appendicitis to those of matched healthy controls to reveal disease-associated changes. Bulk transcriptomic data, immunohistochemistry, and real-time quantitative PCR were used to validate the findings.ResultsOur analysis identified 76 cell types in total and described the cellular atlas of the developing appendix. We discovered the potential role of the BMP signaling pathway in appendiceal epithelium development and identified HOXC8 and PITX2 as the specific regulons of appendix goblet cells. Higher pericyte coverage, endothelial angiogenesis, and goblet mucus scores together with lower epithelial and endothelial tight junction scores were found in the preschool appendix, which possibly contribute to the clinical features of preschool appendicitis. Preschool appendicitis scRNA-seq profiles revealed that the interleukin-17 signaling pathway may participate in the inflammation process.ConclusionsOur study provides new insights into the development of the appendix and deepens the understanding of appendicitis in preschool children.Graphical

63O Transcriptional features of stage IIT4N0/III colon cancer associated with residual disease and ctDNA status after surgery in the PEGASUS trial

63O Transcriptional features of stage IIT4N0/III colon cancer associated with residual disease and ctDNA status after surgery in the PEGASUS trial