Gene Expression Measurements Research Articles

Cohesin-mediated 3D contacts tune enhancer-promoter regulation.

Enhancers are key drivers of gene regulation thought to act via 3D physical interactions with the promoters of their target genes. However, genome-wide depletions of architectural proteins such as cohesin result in only limited changes in gene expression, despite a loss of contact domains and loops. Consequently, the role of cohesin and 3D contacts in enhancer function remains debated. Here, we developed CRISPRi of regulatory elements upon degron operation (CRUDO), a novel approach to measure how changes in contact frequency impact enhancer effects on target genes by perturbing enhancers with CRISPRi and measuring gene expression in the presence or absence of cohesin. We systematically perturbed all 1,039 candidate enhancers near five cohesin-dependent genes and identified 34 enhancer-gene regulatory interactions. Of 26 regulatory interactions with sufficient statistical power to evaluate cohesin dependence, 18 show cohesin-dependent effects. A decrease in enhancer-promoter contact frequency upon removal of cohesin is frequently accompanied by a decrease in the regulatory effect of the enhancer on gene expression, consistent with a contact-based model for enhancer function. However, changes in contact frequency and regulatory effects on gene expression vary as a function of distance, with distal enhancers (e.g., >50Kb) experiencing much larger changes than proximal ones (e.g., <50Kb). Because most enhancers are located close to their target genes, these observations can explain how only a small subset of genes - those with strong distal enhancers - are sensitive to cohesin. Together, our results illuminate how 3D contacts, influenced by both cohesin and genomic distance, tune enhancer effects on gene expression.

Effects of gestational hypothyroidism on mouse brain development: Gabaergic systems and oxidative stress

Hormonal imbalance during pregnancy is a risk factor for neuropsychiatric impairment in the offspring. It has been suggested that hypothyroidism leads to dysfunction of cortical GABAergic interneurons and inhibitory system development that in turn underlies impairment of the central nervous system. Here we investigated how gestational hypothyroidism affected offspring GABAergic system development as well as redox regulation parameters, because of previous links identified between the two. Experimental Gestational Hypothyroidism (EGH) was induced in CD-1 mice with 0.02% methimazole (MMI) in drinking water from embryonic day 9 (E9) until tissue collection at embryonic day 14 (E14) or E18. We examined GABAergic cell distribution and inhibitory system development gene expression as well as redox relevant gene expression and direct measures across all embryos regardless of sex. Intrauterine restriction of maternal thyroid hormones significantly impacted both of these outcomes in brain, as well as altering redox regulation in the placenta. GAD67+ neuronal migration was reduced, accompanied by a disruption in gene expression influencing GABAergic cell migration and cortical inhibitory neural system development. EGH also altered embryonic brain gene expression of Gpx1, Nfe2l2, Cat levels in the dorsal E14 brains. Additionally, EGH resulted in elevated TBARS, Gpx1 and Nfe2l2 in the ventral E18 brains. Furthermore, EGH downregulated placental Gpx1 gene expression at E14 and increased protein oxidation at E18. These findings support the hypothesis that sufficient maternal thyroid hormone supply to the fetus influences central nervous system development, including processes of GABAergic system development and redox equilibrium.

Symbolic recording of signalling and cis-regulatory element activity to DNA.

Measurements of gene expression or signal transduction activity are conventionally performed using methods that require either the destruction or live imaging of a biological sample within the timeframe of interest. Here we demonstrate an alternative paradigm in which such biological activities are stably recorded to the genome. Enhancer-driven genomic recording of transcriptional activity in multiplex (ENGRAM) is based on the signal-dependent production of prime editing guide RNAs that mediate the insertion of signal-specific barcodes (symbols) into a genomically encoded recording unit. We show how this strategy can be used for multiplex recording of the cell-type-specific activities of dozens to hundreds of cis-regulatory elements with high fidelity, sensitivity and reproducibility. Leveraging signal transduction pathway-responsive cis-regulatory elements, we also demonstrate time- and concentration-dependent genomic recording of WNT, NF-κB and Tet-On activities. By coupling ENGRAM to sequential genome editing via DNA Typewriter1, we stably record information about the temporal dynamics of two orthogonal signalling pathways to genomic DNA. Finally we apply ENGRAM to integratively record the transient activity of nearly 100 transcription factor consensus motifs across daily windows spanning the differentiation of mouse embryonic stem cells into gastruloids, an in vitro model of early mammalian development. Although these are proof-of-concept experiments and much work remains to fully realize the possibilities, the symbolic recording of biological signals or states within cells, to the genome and over time, has broad potential to complement contemporary paradigms for how we make measurements in biological systems.

Acute, chronic and conditioned effects of intranasal oxytocin in the mu-opioid receptor knockout mouse model of autism: Social context matters

Autism Spectrum Disorders (ASD) are neurodevelopmental disorders whose diagnosis relies on deficient social interaction and communication together with repetitive behaviours. Multiple studies have highlighted the potential of oxytocin (OT) to ameliorate behavioural abnormalities in animal models and subjects with ASD. Clinical trials, however, yielded disappointing results. Our study aimed at assessing the behavioural effects of different regimens of OT administration in the Oprm1 null mouse model of ASD. We assessed the effects of intranasal OT injected once at different doses (0.15, 0.3, and 0.6 IU) and time points (5, 15, and 30 min) following administration, or chronically, on ASD-related behaviours (social interaction and preference, stereotypies, anxiety, nociception) in Oprm1+/+and Oprm1-/- mice. We then tested whether pairing intranasal OT injection with social experience would influence its outcome on ASD-like symptoms, and measured gene expression in the reward/social circuit. Acute intranasal OT at 0.3 IU improved social behaviour in Oprm1-/- mice 5 min after administration, with limited effects on non-social behaviours. Chronic (8–17 days) OT maintained rescuing effects in Oprm1 null mice but was deleterious in wild-type mice. Finally, improvements in the social behaviour of Oprm1-/- mice were greater and longer lasting when OT was administered in a social context. Under these conditions, the expression of OT and vasopressin receptor genes, as well as marker genes of striatal projection neurons, was suppressed. We detected no sex difference in OT effects. Our results highlight the importance of considering dosage and social context when evaluating the effects of OT treatment in ASD.

Roles of programmed death-1 and muscle innate lymphoid cell-derived interleukin 13 in sepsis-induced intensive care unit-acquired weakness.

Intensive care unit-acquired weakness (ICU-AW) is a syndrome characterized by a long-term muscle weakness often observed in sepsis-surviving patients during the chronic phase. Although ICU-AW is independently associated with increased mortality, effective therapies have yet to be established. Programmed death-1 (PD-1) inhibitors have attracted attention as potential treatments for reversing immune exhaustion in sepsis; however, its impact on ICU-AW remains to be elucidated. Here, we study how PD-1 deficiency affects sepsis-induced skeletal muscle dysfunction in a preclinical sepsis model. Chronic sepsis model was developed by treating wild-type (WT) and PD-1 knockout (KO) mice with caecal slurry, followed by resuscitation with antibiotics and saline. Mice were euthanized on days 15-17. Body weights, muscle weights, and limb muscle strengths were measured. Interleukin 13 (IL-13)and PD-1 expressions were examined by flow cytometry. Messenger RNA (mRNA) expressions of slow-twitch muscles were measured by reverse transcription and quantitative polymerase chain reaction (RT-qPCR). In an in vitro study, C2C12 myotubes were treated with lipopolysaccharide (LPS) and recombinant IL-13 followed by gene expression measurements. WT septic mice exhibited decreased muscle weight (quadriceps, P<0.01; gastrocnemius, P<0.05; and tibialis anterior, P<0.01) and long-term muscle weakness (P<0.0001), whereas PD-1 KO septic mice did not exhibit any reduction in muscle weights and strengths. Slow-twitch specific mRNAs, including myoglobin (Mb), troponin I type 1 (Tnni1), and myosin heavy chain 7 (Myh7) were decreased in WT skeletal muscle (Mb, P<0.0001; Tnni1, P<0.05; and Myh7, P<0.05) after sepsis induction, but mRNA expressions of Tnni1 and Myh7 were increased in PD-1 KO septic mice (Mb, not significant; Tnni1, P<0.0001; and Myh7, P<0.05). Treatment of C2C12 myotube cells with LPS decreased the expression of slow-twitch mRNAs, which was restored by IL-13 (Mb, P<0.0001; Tnni1, P<0.001; and Myh7, P<0.05). IL-13 production was significantly higher in ILC2s compared to T cells in skeletal muscle (P<0.05). IL-13-producing ILC2s in skeletal muscle were examined and found to increase in PD-1 KO septic mice, compared with WT septic mice (P<0.05). ILC2-derived IL-13 was increased by PD-1 KO septic mice and thought to protect the muscles from experimental ICU-AW. Long-term muscle weakness in experimental ICU-AW was ameliorated in PD-1 KO mice. ILC2-derived IL-13 production in skeletal muscles was increased in PD-1 KO mice, thereby suggesting that IL-13 alleviates muscle weakness during sepsis. This study demonstrates the effects of PD-1 blockade in preserving muscle strength during sepsis through an increase in ILC2-derived IL-13 and may be an attractive therapeutic target for sepsis-induced ICU-AW.

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors

Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and spliced RNA in single cells is greatly desired. However, the majority of single-cell RNA-seq chemistry primarily captures mature RNA species to measure gene expressions. Here, we develop a one-step total-RNA chemistry-based single-cell RNA-seq method: snapTotal-seq. We benchmark this method with multiple single-cell RNA-seq assays in their performance in kinetic analysis of cell cycle by RNA velocity. Next, with LASSO regression between transcription factors, we identify the critical regulatory hubs mediating the cell cycle dynamics. We also apply snapTotal-seq to profile the oncogene-induced senescence and identify the key regulatory hubs governing the entry of senescence. Furthermore, from the comparative analysis of unspliced RNA and spliced RNA, we identify a significant portion of genes whose expression changes occur in spliced RNA but not to the same degree in unspliced RNA, indicating these gene expression changes are mainly controlled by post-transcriptional regulation. Overall, we demonstrate that snapTotal-seq can provide enriched information about gene regulation, especially during the transition between cell states.

Toxicity of environmental and polystyrene plastic particles on the bivalve Corbicula fluminea: focus on the molecular responses.

Among aquatic organisms, filter feeders are particularly exposed to the ingestion of microplastics (MPs) and nanoplastics (NPs). The present study investigates the effect of environmental microplastics (ENV MPs) and nanoplastics (ENV NPs) generated from macro-sized plastic debris collected in the Garonne River (France), and polystyrene NPs (PS NPs) on the freshwater bivalve Corbicula fluminea. Organisms were exposed to plastic particles at three concentrations: 0.008, 10, and 100 μg L-1 for 21 days. Gene expression measurements were conducted in gills and visceral mass at 7 and 21 days to assess the effects of plastic particles on different functions. Our results revealed: (i) an up-regulation of genes, mainly involved in endocytosis, oxidative stress, immunity, apoptosis, and neurotoxicity, at 7 days of exposure for almost all environmental plastic particles and at 21 days of exposure for PS NPs in the gills, (ii) PS NPs at the three concentrations tested and ENV MPs at 0.008 μg L-1 induced strong down-regulation of genes involved in detoxication, oxidative stress, immunity, apoptosis, and neurotoxicity at 7 days of exposure in the visceral mass whereas ENV MPs at 10 and 100 μg L-1 and all ENV NPs induced less pronounced effects, (iii) overall, PS NPs and ENV MPs 0.008 μg L-1 did not trigger the same effects as ENV MPs 10 and 100 μg L-1 and all ENV NPs, either in the gills or the visceral mass at 7 and 21 days of exposure. This study highlighted the need to use MPs and NPs sampled in the environment for future studies as their properties induce different effects at the molecular level to living organisms.

A novel method for measurements of sleep/wake states, feeding and drinking behaviors using the tracking technique of 3D positions in freely moving mice

We have previously developed a 3D video tracking system which enables us to analyze long-term quantitative analysis of gene expression in freely moving mice. In the present study, we improved 3D video tracking and developed a system that analyzes more detailed behavioral data. We succeeded in simultaneously analyzing sleep-wake, feeding, and drinking behavior rhythms in the same individual using our tracking system. This system will make it possible to measure gene expression in each tissue in vivo in real time in relation to the various behavioral rhythms mentioned above.

Effective target genes for RNA interference-based management of the cabbage stem flea beetle.

The cabbage stem flea beetle (CSFB, Psylliodes chrysocephala) is a key pest of oilseed rape. The ban on neonicotinoids in the European Union due to environmental concerns and the emergence of pyrethroid-resistant populations have made the control of CSFB extremely challenging. In search of a solution, we have recently shown that RNA interference (RNAi) has potential in the management of CSFB. However, the previously tested target genes for RNAi-mediated pest control (subsequently called target genes) exhibited moderate and slow-acting lethal effects. In this study, 27 double-stranded RNAs (dsRNAs) were orally delivered to identify highly effective target genes in CSFB adults by leveraging the findings of a genome-wide RNAi screen in Tribolium castaneum. Our screen using 500 ng of dsRNA identified 10 moderately effective (> 50% mortality) and 4 highly effective target genes (100% mortality in 8-13 days). The latter mainly included proteasome subunits. Gene expression measurements confirmed target gene silencing and dose-response studies revealed LD50 values as low as ~20 ng in 14 days following a single exposure to dsRNA. Four highly effective dsRNAs also inhibited leaf damage (up to ~75%) and one affected locomotion. The sequences of promising target genes were subjected to in silico target prediction in non-target organisms, for example, beneficials such as honeybees, to design environmentally friendly dsRNAs. Overall, the study provides valuable insights for the development of dsRNA-based insecticides against CSFB.

Systematic comparison of sequencing-based spatial transcriptomic methods

Recent developments of sequencing-based spatial transcriptomics (sST) have catalyzed important advancements by facilitating transcriptome-scale spatial gene expression measurement. Despite this progress, efforts to comprehensively benchmark different platforms are currently lacking. The extant variability across technologies and datasets poses challenges in formulating standardized evaluation metrics. In this study, we established a collection of reference tissues and regions characterized by well-defined histological architectures, and used them to generate data to compare 11 sST methods. We highlighted molecular diffusion as a variable parameter across different methods and tissues, significantly affecting the effective resolutions. Furthermore, we observed that spatial transcriptomic data demonstrate unique attributes beyond merely adding a spatial axis to single-cell data, including an enhanced ability to capture patterned rare cell states along with specific markers, albeit being influenced by multiple factors including sequencing depth and resolution. Our study assists biologists in sST platform selection, and helps foster a consensus on evaluation standards and establish a framework for future benchmarking efforts that can be used as a gold standard for the development and benchmarking of computational tools for spatial transcriptomic analysis.

O-097 Implantation-on-chip: precise quantification for functional implantation failure studies

Abstract Study question How can we obtain precise quantitative information about what factors causally affect the first steps of embryo implantation and Repeated Implantation Failure (RIF)? Summary answer We have developed a personalized implantation-on-chip model, based on novel in vitro models of the endometrium and the embryo (i.e., blastoids), to quantify functional attachment. What is known already RIF is a multifactorial condition characterized by the persistent inability to achieve clinical pregnancy, despite the transfer of high-quality embryos. Typically diagnosed within the context of assisted reproductive technology (ART) treatment, RIF arises due to disruptions in the endometrium receptivity, the interaction between the endometrium and early embryo, or both. The endometrial factors of RIF can be linked to disrupted hormone signaling and timing, impacting endometrial receptivity and therefore the chance of conceiving. Synchronization between the blastocyst and receptive endometrium is critical for successful implantation. Ethical and technical limitations of in vivo patient research restricts our understanding of implantation failure. Study design, size, duration Organoids were transformed into endometrial monolayers within custom-made microfluidic chips. These monolayers on chip were either treated with EPCX; β-estradiol (E2), progesterone (P4), 8-Br-cAMP (C) and XAV939 (X) (referred as induced), or not treated (referred as control) for 6 days. Large number of blastoids (&amp;gt;100) were then infused per chip followed by 48 hours of culture. Then, the rate of adhered blastoids was measured under exposure to controlled flow rates (50, 100 and 400 µl/min). Participants/materials, setting, methods Human naïve induced pluripotent stem cells were used to form blastoids, stem cell-based models of the blastocyst, to alleviate the ethical concerns and limited access of blastocysts. Blastoids present the three blastocyst lineages required for development and offer limitless production in number. Endometrium organoids, derived from parous fertile patients (N = 3), was used to recapitulate molecular and functional receptivity by RT-qPCR-based gene expression measurements and microfluidic flow-dependent adhesion rates of blastoids, respectively. Main results and the role of chance 2-D monolayers that maintained their epithelial identity and responsiveness to hormones as measured by expression of receptivity-related genes (PAEP, SPP1 and GPX3), which were upregulated in EPCX condition. Further characterization of the epithelial monolayers showed reduced MUC1 expression in the EPCX condition, suggesting increased receptivity. Additionally, reduced acetylated α-tubulin, indicating a reduction in the number of ciliated cells, aligning with our observations. Through controlled exposure to increasing flow, functional receptivity through blastoid adhesion was precisely quantified, which showed 35% of the blastoid remained adhered in the EPCX condition, whereas only 15% remained adhered in the control. A 48 hours culture period presented a blastoid-induced endometrial gap in 45.54% of the remaining blastoids, with an average of 110.287,3 µm2 in surface area, which was associated with trophoblast cells infiltration, measuring an average migration distance of 174.8 µm from the pluripotent cell core. In addition, the substantial difference in receptivity profiles established a baseline for subsequent experiments, including the study of temporal alterations in hormone signaling, a potential problem associated with RIF. Hormone administration variations, timing and a progesterone-deficient condition are currently being tested. These results will underscore the sensitivity of our system and demonstrate its potential for applications in drug screening. Limitations, reasons for caution Currently our endometrium model consists of epithelial cells, which are only representative for implantation to a limited extent. A more complex endometrium including stromal, endothelial and immune cells could highly increase the physiological relevance of the model. Wider implications of the findings This platform has the potential to provide a diagnostic platform to identify patients with endometrium epithelium-associated RIF and factors that may improve embryo receptivity and implantation. Moreover, this approach has the potential to be pivotal for toxicological studies, and furthering our understanding of human reproductive biology. Trial registration number not applicable

Schistosoma haematobium and Schistosoma bovis first generation hybrids undergo gene expressions changes consistent with species compatibility and heterosis.

When two species hybridize, the two parental genomes are brought together and some alleles might interact for the first time. To date, the extent of the transcriptomic changes in first hybrid generations, along with their functional outcome constitute an important knowledge gap, especially in parasite species. Here we explored the molecular and functional outcomes of hybridization in first-generation hybrids between the blood fluke parasites Schistosoma haematobium and S. bovis. Through a transcriptomic approach, we measured gene expression in both parental species and hybrids. We described and quantified expression profiles encountered in hybrids along with the main biological processes impacted. Up to 7,100 genes fell into a particular hybrid expression profile (intermediate between the parental expression levels, over-expressed, under-expressed, or expressed like one of the parental lines). Most of these genes were different depending on the direction of the parental cross (S. bovis mother and S. haematobium father or the reverse) and depending on the sex. For a given sex and cross direction, the vast majority of genes were hence unassigned to a hybrid expression profile: either they were differentially expressed genes but not typical of any hybrid expression profiles or they were not differentially expressed neither between hybrids and parental lines nor between parental lines. The most prevalent profile of gene expression in hybrids was the intermediate one (24% of investigated genes). These results suggest that transcriptomic compatibility between S. haematobium and S. bovis remains quite high. We also found support for an over-dominance model (over- and under-expressed genes in hybrids compared to parental lines) potentially associated with heterosis. In females in particular, processes such as reproductive processes, metabolism and cell interactions as well as signaling pathways were indeed affected. Our study hence provides new insight on the biology of Schistosoma hybrids with evidences supporting compatibility and heterosis.

Biomarker identification by interpretable maximum mean discrepancy.

In many biomedical applications, we are confronted with paired groups of samples, such as treated versus control. The aim is to detect discriminating features, i.e. biomarkers, based on high-dimensional (omics-) data. This problem can be phrased more generally as a two-sample problem requiring statistical significance testing to establish differences, and interpretations to identify distinguishing features. The multivariate maximum mean discrepancy (MMD) test quantifies group-level differences, whereas statistically significantly associated features are usually found by univariate feature selection. Currently, few general-purpose methods simultaneously perform multivariate feature selection and two-sample testing. We introduce a sparse, interpretable, and optimized MMD test (SpInOpt-MMD) that enables two-sample testing and feature selection in the same experiment. SpInOpt-MMD is a versatile method and we demonstrate its application to a variety of synthetic and real-world data types including images, gene expression measurements, and text data. SpInOpt-MMD is effective in identifying relevant features in small sample sizes and outperforms other feature selection methods such as SHapley Additive exPlanations and univariate association analysis in several experiments. The code and links to our public data are available at https://github.com/BorgwardtLab/spinoptmmd.

The cacao gene atlas: a transcriptome developmental atlas reveals highly tissue-specific and dynamically-regulated gene networks in Theobroma cacao L

BackgroundTheobroma cacao, the cocoa tree, is a tropical crop grown for its highly valuable cocoa solids and fat which are the basis of a 200-billion-dollar annual chocolate industry. However, the long generation time and difficulties associated with breeding a tropical tree crop have limited the progress of breeders to develop high-yielding disease-resistant varieties. Development of marker-assisted breeding methods for cacao requires discovery of genomic regions and specific alleles of genes encoding important traits of interest. To accelerate gene discovery, we developed a gene atlas composed of a large dataset of replicated transcriptomes with the long-term goal of progressing breeding towards developing high-yielding elite varieties of cacao.ResultsWe describe the creation of the Cacao Transcriptome Atlas, its global characterization and define sets of genes co-regulated in highly organ- and temporally-specific manners. RNAs were extracted and transcriptomes sequenced from 123 different tissues and stages of development representing major organs and developmental stages of the cacao lifecycle. In addition, several experimental treatments and time courses were performed to measure gene expression in tissues responding to biotic and abiotic stressors. Samples were collected in replicates (3–5) to enable statistical analysis of gene expression levels for a total of 390 transcriptomes. To promote wide use of these data, all raw sequencing data, expression read mapping matrices, scripts, and other information used to create the resource are freely available online. We verified our atlas by analyzing the expression of genes with known functions and expression patterns in Arabidopsis (ACT7, LEA19, AGL16, TIP13, LHY, MYB2) and found their expression profiles to be generally similar between both species. We also successfully identified tissue-specific genes at two thresholds in many tissue types represented and a set of genes highly conserved across all tissues.ConclusionThe Cacao Gene Atlas consists of a gene expression browser with graphical user interface and open access to raw sequencing data files as well as the unnormalized and CPM normalized read count data mapped to several cacao genomes. The gene atlas is a publicly available resource to allow rapid mining of cacao gene expression profiles. We hope this resource will be used to help accelerate the discovery of important genes for key cacao traits such as disease resistance and contribute to the breeding of elite varieties to help farmers increase yields.

Liquid Biopsy in Whole Blood for Identification of Gene Expression Patterns (mRNA and miRNA) Associated with Recurrence of Glioblastoma WHO CNS Grade 4.

GBM WHO CNS Grade 4 represents a major challenge for oncology due to its aggressive behavior. Conventional imaging has restrictions in detecting tumor recurrence. This prospective study aims to identify gene-based biomarkers in whole blood instead of isolating exosomes for the early detection of tumor recurrence. Blood samples (n = 33) were collected from seven GBM patients at time points before and after surgery as well as upon tumor recurrence. Four tumor tissue samples were assessed in parallel. Next-generation sequencing (NGS), including mRNA-seq and small RNA-seq, was used to analyze gene expression profiles in blood samples and tumor tissues. A novel filtering pipeline was invented to narrow down potential candidate genes. In total, between 6-93 mRNA and 1-19 small RNA candidates could be identified among the seven patients. The overlap of genes between the patients was minimal, indicating significant inter-individual variance among GBM patients. In summary, this prospective study supports the applicability of gene expression measurements in whole blood for the detection of tumor recurrence. It might provide an alternative to the challenging workflow of liquid biopsy after laborious exosome isolation from whole blood.

Repurposing metformin as adjuvant therapy in patients with ulcerative colitis treated with mesalamine: A randomized controlled double-blinded study

BackgroundUlcerative colitis (UC) is a type of inflammatory bowel disease associated with persistent inflammation. Animal studies proved the efficacy of metformin in UC. AimTo investigate the potential role of metformin and its protective pathways in patients with UC. MethodsThis is a randomized, controlled, and double-blinded clinical trial that included 60 participants with mild to moderate UC and was divided randomly into two groups (n = 30). For 6 months, the mesalamine group received 1 g of mesalamine three times daily (t.i.d.). For six months, the metformin group received mesalamine 1 g t.i.d. and metformin 500 mg twice daily. A gastroenterologist evaluated patients at baseline and 6 months after starting the treatment in order to measure serum levels of zonulin, sphingosine 1 phosphate (S1P), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Biopsies from the colon were used to measure gene expression of zonula occuldin-1 (ZO-1), signal transducer and activator of factor-3 (STAT-3), and intracellular adhesion molecule-1 (ICAM-1). The numeric pain rating scale (NRS) and partial Mayo score were also assessed for each patient. ResultsWhen compared to the mesalamine group, the metformin group demonstrated a statistical decrease in serum IL-6, zonulin, TNF-α, SIP, gene expression of ICAM-1 and STAT-3, and a significant increase in colonic ZO-1 when compared to the mesalamine group. The metformin group also showed a significant decrease in NRS and partial Mayo score index in comparison with the mesalamine group. ConclusionMetformin may be a promising additional therapy for UC patients.Trial registration identifier: NCT05553704.

β3-adREnoceptor Analysis in CORD Blood of Neonates (β3 RECORD): Study Protocol of a Pilot Clinical Investigation.

Background and Objective: The embryo and the fetus develop in a physiologically hypoxic environment, where vascularization is sustained by HIF-1, VEGF, and the β-adrenergic system. In animals, β3-adrenoceptors (β3-ARs), up-regulated by hypoxia, favor global fetal wellness to such an extent that most diseases related to prematurity are hypothesized to be induced or aggravated by a precocious β3-AR down-regulation, due to premature exposure to a relatively hyperoxic environment. In animals, β3-AR pharmacological agonism is currently investigated as a possible new therapeutic opportunity to counteract oxygen-induced damages. Our goal is to translate the knowledge acquired in animals to humans. Recently, we have demonstrated that fetuses become progressively more hypoxemic from mid-gestation to near-term, but starting from the 33rd-34th week, oxygenation progressively increases until birth. The present paper aims to describe a clinical research protocol, evaluating whether the expression level of HIF-1, β3-ARs, and VEGF is modulated by oxygen during intrauterine and postnatal life, in a similar way to animals. Materials and Methods: In a prospective, non-profit, single-center observational study we will enroll 100 preterm (group A) and 100 full-term newborns (group B). We will collect cord blood samples (T0) and measure the RNA expression level of HIF-1, β3-ARs, and VEGF by digital PCR. In preterms, we will also measure gene expression at 48-72h (T1), 14 days (T2), and 30 days (T3) of life and at 40 ± 3 weeks of post-menstrual age (T4), regardless of the day of life. We will compare group A (T0) vs. group B (T0) and identify any correlations between the values obtained from serial samples in group A and the clinical data of the patients. Our protocol has been approved by the Pediatric Ethical Committee for Clinical Research of the Tuscany region (number 291/2022). Expected Results: The observation that in infants, the HIF-1/β3-ARs/VEGF axis shows similar modulation to that of animals could suggest that β3-ARs also promote fetal well-being in humans.

Deep Cell-Type Deconvolution from Bulk Gene Expression Data Using DECODE

It is becoming clear that bulk gene expression measurements represent an average over very different cells. Elucidating the expression and abundance of each of the encompassed cells is key to disease understanding and precision medicine approaches. A first step in any such deconvolution is the inference of cell type abundances in the given mixture. Numerous approaches to cell-type deconvolution have been proposed, yet very few take advantage of the emerging discipline of deep learning and most approaches are limited to input data regarding the expression profiles of the cell types in question. Here we present DECODE, a deep learning method for the task that is data-driven and does not depend on input expression profiles. DECODE builds on a deep unfolded non-negative matrix factorization technique. It is shown to outperform previous approaches on a range of synthetic and real data sets, producing abundance estimates that are closer to and better correlated with the real values.

IIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis

Current clustering analysis of spatial transcriptomics data primarily relies on molecular information and fails to fully exploit the morphological features present in histology images, leading to compromised accuracy and interpretability. To overcome these limitations, we have developed a multi-stage statistical method called iIMPACT. It identifies and defines histology-based spatial domains based on AI-reconstructed histology images and spatial context of gene expression measurements, and detects domain-specific differentially expressed genes. Through multiple case studies, we demonstrate iIMPACT outperforms existing methods in accuracy and interpretability and provides insights into the cellular spatial organization and landscape of functional genes within spatial transcriptomics data.

Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation.

Recent advances in spatial transcriptomics allow spatially resolved gene expression measurements with cellular or even sub-cellular resolution, directly characterizing the complex spatiotemporal gene expression landscape and cell-to-cell interactions in their native microenvironments. Due to technology limitations, most spatial transcriptomic technologies still yield incomplete expression measurements with excessive missing values. Therefore, gene imputation is critical to filling in missing data, enhancing resolution, and improving overall interpretability. However, existing methods either require additional matched single-cell RNA-seq data, which is rarely available, or ignore spatial proximity or expression similarity information. To address these issues, we introduce Impeller, a path-based heterogeneous graph learning method for spatial transcriptomic data imputation. Impeller has two unique characteristics distinct from existing approaches. First, it builds a heterogeneous graph with two types of edges representing spatial proximity and expression similarity. Therefore, Impeller can simultaneously model smooth gene expression changes across spatial dimensions and capture similar gene expression signatures of faraway cells from the same type. Moreover, Impeller incorporates both short- and long-range cell-to-cell interactions (e.g. via paracrine and endocrine) by stacking multiple GNN layers. We use a learnable path operator in Impeller to avoid the over-smoothing issue of the traditional Laplacian matrices. Extensive experiments on diverse datasets from three popular platforms and two species demonstrate the superiority of Impeller over various state-of-the-art imputation methods. The code and preprocessed data used in this study are available at https://github.com/aicb-ZhangLabs/Impeller and https://zenodo.org/records/11212604.