Gene Expression States Research Articles

Inheritance of Stress Responses via Small Non-Coding RNAs in Invertebrates and Mammals.

While reports on the generational inheritance of a parental response to stress have been widely reported in animals, the molecular mechanisms behind this phenomenon have only recently emerged. The booming interest in epigenetic inheritance has been facilitated in part by the discovery that small non-coding RNAs are one of its principal conduits. Discovered 30 years ago in the Caenorhabditis elegans nematode, these small molecules have since cemented their critical roles in regulating virtually all aspects of eukaryotic development. Here, we provide an overview on the current understanding of epigenetic inheritance in animals, including mice and C. elegans, as it pertains to stresses such as temperature, nutritional, and pathogenic encounters. We focus on C. elegans to address the mechanistic complexity of how small RNAs target their cohort mRNAs to effect gene expression and how they govern the propagation or termination of generational perdurance in epigenetic inheritance. Presently, while a great amount has been learned regarding the heritability of gene expression states, many more questions remain unanswered and warrant further investigation.

Cross-linking breast tumor transcriptomic states and tissue histology

Identification of the gene expression state of a cancer patient from routine pathology imaging and characterization of its phenotypic effects have significant clinical and therapeutic implications. However, prediction of expression of individual genes from whole slide images (WSIs) is challenging due to co-dependent or correlated expression of multiple genes. Here, we use a purely data-driven approach to first identify groups of genes with co-dependent expression and then predict their status from WSIs using a bespoke graph neural network. These gene groups allow us to capture the gene expression state of a patient with a small number of binary variables that are biologically meaningful and carry histopathological insights for clinical and therapeutic use cases. Prediction of gene expression state based on these gene groups allows associating histological phenotypes (cellular composition, mitotic counts, grading, etc.) with underlying gene expression patterns and opens avenues for gaining biological insights from routine pathology imaging directly.

A guide to ERK dynamics, part 2: downstream decoding.

Signaling by the extracellular signal-regulated kinase (ERK) pathway controls many cellular processes, including cell division, death, and differentiation. In this second installment of a two-part review, we address the question of how the ERK pathway exerts distinct and context-specific effects on multiple processes. We discuss how the dynamics of ERK activity induce selective changes in gene expression programs, with insights from both experiments and computational models. With a focus on single-cell biosensor-based studies, we summarize four major functional modes for ERK signaling in tissues: adjusting the size of cell populations, gradient-based patterning, wave propagation of morphological changes, and diversification of cellular gene expression states. These modes of operation are disrupted in cancer and other related diseases and represent potential targets for therapeutic intervention. By understanding the dynamic mechanisms involved in ERK signaling, there is potential for pharmacological strategies that not only simply inhibit ERK, but also restore functional activity patterns and improve disease outcomes.

Primary Acute Myeloid Leukemia Cells Trigger Distinct Activation Patterns in Expanded NK Cells

Increasing efforts are devoted to implement immunotherapies for the treatment of acute myeloid leukemia (AML). Recently, natural killer (NK) cell-based immunotherapy has shown initial encouraging results. However, which patients are most likely to benefit from NK cell-based treatments remains poorly understood. Here, we investigate the responses of NK cells to ex vivo co-cultures with 55 primary AML samples using single-cell transcriptomics. We identify a subgroup of AML patients eliciting strong responses in NK cells and define the molecular programs in NK cells and other microenvironmental cell types triggered by diverse AML cells. We performed functional single-cell immune profiling on co-cultures of primary expanded NK cells and 55 bone marrow (BM) samples from AML patients at diagnosis. We used NK cells expanded using irradiated K562-41BB-L-mbIL-21 feeder cells, resulting in a product commonly used in clinical trials. All expanded NK cells were from one single healthy donor displaying an HLA-C1C2 allotype.We investigated NK cell-treated and untreated cultures through multiplexed single-cell RNA sequencing (scRNA-seq) to dissect adaptive changes in both NK and AML BM cells upon their interaction. In total, we investigated 121 samples through scRNA-seq: 11 monocultures of expanded NK cells, 55 AML BM cells and 55 co-cultures of AML BM cells and expanded NK cells. scRNA-seq yielded 95,715 high quality cells (791 cells per sample on average), including 31,882 NK cells (483 cells per sample on average) and 63,833 AML BM cells (580 cells per sample on average). Unsupervised clustering of the cells revealed distinct clusters separating expanded NK cells from AML cells (Fig. 1a). We studied the sensitivity of leukemic cells to NK cytotoxicity using high-throughput flow cytometry. We further integrated the results with genetic and clinical data of the AML patients to characterize the mechanisms of action driving the transcriptomic responses and leukemic cell susceptibility to NK cell killing. After 24 h co-culture, scRNA-seq revealed that AML BM cells induced distinct gene expression states in the NK cells. The observed tumor-induced NK states were predominantly enriched in co-cultured samples and not found in NK cell monocultures which mostly consisted of resting-state NK cells. Across the co-cultures, half of the AML samples triggered at least 30% of NK cells to change from resting to tumor-induced states (Fig. 1b). Out of the 28 AML samples causing the strongest NK cell induction, 54% primarily triggered a type I interferon (IFN) signature, characterised by expression of genes encoding MX1, OAS1, and IRF7. In contrast, the other 46% mainly induced an activated phenotype, including expression of TNFRSF18 ( GITR), TNFRSF9 ( 4-1BB), TIGIT and HAVCR2 ( TIM-3). Killer cell immunoglobulin-like receptors-HLA ligand mismatchesare well known causes of NK alloreactivity. Thus, we explored whether HLA-C matched (C1C2, n=24) and mismatched (C1C1 or C2C2, n=28) AML samples influenced NK cell responses. Interestingly, no significant difference in the NK cell induction states was observed between matched and mismatched samples (Mann-Whitney p = 0.57). NK cell treatment also induced responses in the patients' own T cells. Both CD4+ and CD8+ T cells upregulated IFN-ɣ and type I IFN genes upon co-culture. The type I IFN signature in CD8+ T cells was mainly found in AML samples triggering strong NK cell induction. CD8+ T cells also upregulated cytotoxicity genes including FASLG and TNFSF10 (TRAIL), along with inhibitory molecules such as LAG3, suggesting that NK cells can promote effector functions of T cells. Our results suggest that AML BM cells from different patients trigger a heterogeneous response in expanded NK cells. Only in half of the cases, the leukemic BM cells induced substantial activation of NK cells. The observed variation in NK states was not determined by HLA-C allotypes, suggesting that other tumor cell features are responsible for the responses. This underscores the importance of understanding the molecular drivers of tumor and NK cell interaction. Our data additionally show that NK cell-based immunotherapy may be able to promote the functionality of the patient's own T cells, demonstrating how our ex vivo modeling approach can help to refine the mechanism of action of immunotherapies. Our work paves the way for identifying subgroups of AML patients responding to NK cell-based immunotherapies.

Atypical Modes of CTCF Binding Facilitate Tissue-Specific and Neuronal Activity-Dependent Gene Expression States.

Multivalent binding of CTCF to variable DNA sequences is thought to underlie its ability to mediate diverse cellular functions. CTCF typically binds a 20 base-pair consensus DNA sequence, but the full diversity of CTCF binding sites (CBS) within the genome has not been interrogated. We assessed CTCF occupancy in cultured cortical neurons and observed surprisingly that ~ 22% of CBS lack the consensus CTCF motif. We report here that sequence diversity at most of these atypical CBS involves degeneracy at specific nucleotide positions within the consensus CTCF motif, which likely affect the binding of CTCF zinc fingers 6 and 7. This mode of atypical CTCF binding defines most CBS at gene promoters, as well as CBS that are dynamically altered during neural differentiation and following neuronal stimulation, revealing how atypical CTCF binding could influence gene activity. Dynamic CBS are distributed both within and outside loop anchors and TAD boundaries, suggesting both looping-dependent and independent roles for CTCF. Finally, we describe a second mode of atypical CTCF binding to DNA sequences that are completely unrelated to the consensus CTCF motif, which are enriched within the bodies of tissue-specific genes. These tissue-specific atypical CBS are also enriched in H3K27ac, which marks cis-regulatory elements within chromatin, including enhancers. Overall, these results indicate how atypical CBS could dynamically regulate gene activity patterns during differentiation, development, and in response to environmental cues.

Mask exhibits trxG-like behavior and associates with H3K27ac marked chromatin

The Trithorax group (trxG) proteins counteract the repressive effect of Polycomb group (PcG) complexes and maintain transcriptional memory of active states of key developmental genes. Although chromatin structure and modifications appear to play a fundamental role in this process, it is not clear how trxG prevents PcG-silencing and heritably maintains an active gene expression state. Here, we report a hitherto unknown role of Drosophila Multiple ankyrin repeats single KH domain (Mask), which emerged as one of the candidate trxG genes in our reverse genetic screen. The genome-wide binding profile of Mask correlates with known trxG binding sites across the Drosophila genome. In particular, the association of Mask at chromatin overlaps with CBP and H3K27ac, which are known hallmarks of actively transcribed genes by trxG. Importantly, Mask predominantly associates with actively transcribed genes in Drosophila. Depletion of Mask not only results in the downregulation of trxG targets but also correlates with diminished levels of H3K27ac. The fact that Mask positively regulates H3K27ac levels in flies was also found to be conserved in human cells. Strong suppression of Pc mutant phenotype by mutation in mask provides physiological relevance that Mask contributes to the anti-silencing effect of trxG, maintaining expression of key developmental genes. Since Mask is a downstream effector of multiple cell signaling pathways, we propose that Mask may connect cell signaling with chromatin mediated epigenetic cell memory governed by trxG.

PATH-11. POOLED IN VIVO ASSAY TO CHARACTERIZE GLIOBLASTOMA INVASION AT THE SINGLE-CELL RESOLUTION

Abstract Tumor cell invasion is the main characteristic of glioblastoma and one of the obstacles to successful treatments. Nonetheless, molecular features of invading glioblastoma cells remain elusive and poorly characterized, such as their gene expression states and microenvironmental influences. Recently, we described cell state heterogeneity in glioblastoma by single-cell RNA-sequencing (scRNA-seq) and uncovered the contribution of immune cells to the heterogeneity. However, it is unclear whether the cell states observed in clinical specimens are implicated in invading glioblastoma cells in the surgically inaccessible brain parenchyma. It is also unclear whether the cell states are correlated to the non-immune microenvironment. As a tool for probing these questions, we developed an in vivo approach with mixtures of human glioblastoma spheroid lines for mouse intracranial xenografts. We validated this with 20 patient-derived models and identified, by scRNA-seq, in vivo models capable of infiltrating along the periphery of either neurons or blood vessels. We profiled and characterized programs, states, and clonality of invading glioblastoma cells by comparing cells from the contralateral invasive edge to their counterparts at the original bulk tumor. This comparative analysis showed evidence of a bi-directional transitioning model for cells residing in different spatial niches. Importantly, presence of an OPC-like state was significantly associated with invasion phenotype regardless of the infiltration routes. Our results suggest that cellular plasticity may be a prerequisite for the invasive phenotypes, urging further assessment to identify critical regulators of the cell states. In conclusion, this work describes pooled in vivo assays for the rapid interrogation of patient-derived xenografts, coupling the gene expression phenotypes with cellular functions such as invasion.

MODL-29. EXPLORING CELL STATE TRANSITIONS IN GLIOBLASTOMA WITH LIVE REPORTING OF CELL STATES USING CRISPR/CAS9

Abstract Glioblastoma (GBM) is the most common malignant primary brain tumor, with a median survival time of 12-15 months. The heterogeneity of GBM, ranging from inter-patient to intra-tumoral, poses a significant challenge in identifying effective treatments. At the single-cell level, GBMs comprise a multiplicity of transcriptional cell states that can change over time and in response to therapy. To explore how cell state plasticity shapes tumor progression, new experimental tools to monitor cell state dynamics in real-time will be important, if not essential. Here, we describe a live reporting of GBM cell states that utilize CRISPR/Cas9 and fluorescent proteins for tracking individual glioblastoma patient-derived cells’ (GBM-PDC) physiological gene expression, and cell state transitions over time and during treatment. The method aims to provide real-time reporting of accurate transcriptional phenotypes (e.g. OPC/NPC-like, Mesenchymal, Astrocyte states) over extended periods or in relevant in vitro or in vivo contexts. Our protocols achieved successful endogenous tagging of a common stem cell marker with full-length mCherry in up to 15 % of GBM-PDC (an order of magnitude more effective than previous reports). Real-time imaging (Incucyte S3 and IMX-C) allows us to trace individual cells’ states over time and during treatment, supported by ICC, qPCR, and Western blot, providing a reliable approach. Our next objective is to employ this method to tag several cell-state marker genes with fluorescent proteins. We can directly follow gene expression and cellular state transitions when several state-selective genes are fused with different fluorescent proteins. We anticipate establishing a robust framework to investigate the temporal plasticity and invasion patterns within GBM cells across different patients which may open for new therapeutic opportunities.

Broodstock nutritional programming differentially affects the hepatic transcriptome and genome-wide DNA methylome of farmed gilthead sea bream (Sparus aurata) depending on genetic background

BackgroundBroodstock nutritional programming improves the offspring utilization of plant-based diets in gilthead sea bream through changes in hepatic metabolism. Attention was initially focused on fatty acid desaturases, but it can involve a wide range of processes that remain largely unexplored. How all this can be driven by a different genetic background is hardly underlined, and the present study aimed to assess how broodstock nutrition affects differentially the transcriptome and genome-wide DNA methylome of reference and genetically selected fish within the PROGENSA® selection program.ResultsAfter the stimulus phase with a low fish oil diet, two offspring subsets of each genetic background received a control or a FUTURE-based diet. This highlighted a different hepatic transcriptome (RNA-seq) and genome-wide DNA methylation (MBD-seq) pattern depending on the genetic background. The number of differentially expressed transcripts following the challenge phase varied from 323 in reference fish to 2,009 in genetically selected fish. The number of discriminant transcripts, and associated enriched functions, were also markedly higher in selected fish. Moreover, correlation analysis depicted a hyper-methylated and down-regulated gene expression state in selected fish with the FUTURE diet, whereas the opposite pattern appeared in reference fish. After filtering for highly represented functions in selected fish, 115 epigenetic markers were retrieved in this group. Among them, lipid metabolism genes (23) were the most reactive following ordering by fold-change in expression, rendering a final list of 10 top markers with a key role on hepatic lipogenesis and fatty acid metabolism (cd36, pitpna, cidea, fasn, g6pd, lipt1, scd1a, acsbg2, acsl14, acsbg2).ConclusionsGene expression profiles and methylation signatures were dependent on genetic background in our experimental model. Such assumption affected the magnitude, but also the type and direction of change. Thus, the resulting epigenetic clock of reference fish might depict an older phenotype with a lower methylation for the epigenetically responsive genes with a negative methylation-expression pattern. Therefore, epigenetic markers will be specific of each genetic lineage, serving the broodstock programming in our selected fish to prevent and mitigate later in life the risk of hepatic steatosis through changes in hepatic lipogenesis and fatty acid metabolism.

Disrupting cellular memory to overcome drug resistance

Gene expression states persist for varying lengths of time at the single-cell level, a phenomenon known as gene expression memory. When cells switch states, losing memory of their prior state, this transition can occur in the absence of genetic changes. However, we lack robust methods to find regulators of memory or track state switching. Here, we develop a lineage tracing-based technique to quantify memory and identify cells that switch states. Applied to melanoma cells without therapy, we quantify long-lived fluctuations in gene expression that are predictive of later resistance to targeted therapy. We also identify the PI3K and TGF-β pathways as state switching modulators. We propose a pretreatment model, first applying a PI3K inhibitor to modulate gene expression states, then applying targeted therapy, which leads to less resistance than targeted therapy alone. Together, we present a method for finding modulators of gene expression memory and their associated cell fates.

Automated Cut&run Brings Scalable Epigenomic Profiling to Hematology

Genome-wide association studies (GWAS) and corresponding transcriptomics research have been leveraged to identify disease risk variants in hematological disorders with the hopes of developing more personalized treatment regimens. Interestingly, >90% of GWAS-identified variants are found in non-coding regions of the genome, indicating they likely affect the regulatory machinery that governs chromatin structure. Non-coding elements, such as enhancers, play important roles in supporting chromatin mechanisms, including cell-type specific gene expression, cell fates and disease states. However, these variants are difficult to study compared to protein-coding mutations and have been challenging to directly associate with phenotypic readouts. To date, efforts to understand the effects of non-coding variants on chromatin dynamics have been focused on chromatin accessibility (ATAC-seq) and DNA methylation profiling. Notably, these assays can only provide a binary, “open-or-closed,” view of chromatin and often fail to provide mechanistic insight into disease etiology. Epigenomic features - such as histone post-translational modifications (PTMs) and chromatin-associated proteins - mark distinct genomic compartments (e.g., promoters, enhancers) and regulate chromatin structure, gene expression, and cell function. Mapping these features provides a rich context to study cell fate and has great potential for discovering new biomarkers and drug targets. Despite this, efforts to integrate epigenomics into large scale lymphatic and myeloid research have been hampered by the poor sensitivity, high background, and low throughput of traditional chromatin mapping technology (i.e., ChIP-seq). Here, we present autoCUT&RUN, a high throughput assay for rapid, ultra-sensitive profiling of epigenomic features from FACS-isolated primary cells or tissues. This workflow generates reliable profiles from <10,000 cells per reaction, and is supported by a rigorous optimization strategy, high-quality antibodies, and quantitative spike-in controls. As part of a multi-site collaboration with the Immunological Genome Consortium, we used our autoCUT&RUN platform to build a comprehensive epigenomic database of mouse immune cells - composed of >1,500 epigenomic profiles from >100 different FACS-isolated primary immune cell types. These studies set the stage to leverage high-throughput epigenomics for multi-site clinical studies to identify and/or characterize novel biomarkers for precision medicine applications. Further, we will discuss our integration of CUT&RUN and Enzymatic Methylation-sequencing (CUT&RUN-EM) to deliver a true multiomic view of the co-occurrence of epigenomic features and DNA methylation, which can reveal multivalent cellular mechanisms and deconvolute sample heterogeneity.

Novel method for prediction of combinatorial phase-variable gene expression states

Short sequence repeat mediated phase variation results in diverse phenotype presentation in many bacteria including Campylobacter and Neisseria species. Current methods for identifying the expression states of phase-variable genes involve taking a high number of single colonies. This approach is subject to bias, sampling effects and high workloads that reduce the ability to perform intermediary sampling. The use of high concentration colony sweeps provides a work around but reduces the resolution of combinatorial expression profiles (termed phasotypes). A parsimonious approach combining both single colony and sweep data was developed to overcome these limitations. The critical methodological advance is the use of an algorithm that utilises the experimental data from the two sample types and a parsimonious, iterative mathematical analysis that outputs the phasotype distribution with the highest likelihood of underpinning the experimental data sets. The advantages of this unified method are increased resolution and accuracy of gene expression state combinations as compared to conventional single colony sampling, reduced requirement for sampling large numbers of colonies leading to reduced costs, and a higher capacity for collecting samples and replicates.•Inputting of sweep and single colony data into an algorithm for a rapid determination of the combinatorial phase variation states (phasotypes) for repeat-mediated phase-variable bacterial genes•This method reduces the number of single colony samples required to produce accurate estimates of phasotypes•This method will reduce the costs of phasotype analyses and increase potential to analyse more time points or sample sites leading to an improved understanding of how phase variation contributes to bacterial host persistence and the ability to cause disease

A data-driven Boolean model explains memory subsets and evolution in CD8+ T cell exhaustion

T cells play a key role in a variety of immune responses, including infection and cancer. Upon stimulation, naïve CD8+ T cells proliferate and differentiate into a variety of memory and effector cell types; however, failure to clear antigens causes prolonged stimulation of CD8+ T cells, ultimately leading to T cell exhaustion (TCE). The functional and phenotypic changes that occur during CD8+ T cell differentiation are well characterized, but the underlying gene expression state changes are not completely understood. Here, we utilize a previously published data-driven Boolean model of gene regulatory interactions shown to mediate TCE. Our network analysis and modeling reveal the final gene expression states that correspond to TCE, along with the sequence of gene expression patterns that give rise to those final states. With a model that predicts the changes in gene expression that lead to TCE, we could evaluate strategies to inhibit the exhausted state. Overall, we demonstrate that a common pathway model of CD8+ T cell gene regulatory interactions can provide insights into the transcriptional changes underlying the evolution of cell states in TCE.

Intrinsic and Induced Neuronal Regeneration in the Mammalian Retina.

Significance: Retinal neurons are vulnerable to disease and injury, which can result in neuronal death and degeneration leading to irreversible vision loss. The human retina does not regenerate to replace neurons lost to disease or injury. However, cells within the retina of other animals are capable of regenerating neurons, and homologous cells within the mammalian retina could potentially be prompted to do the same. Activating evolutionarily silenced intrinsic regenerative capacity of the mammalian retina could slow, or even reverse, vision loss, leading to an improved quality of life for millions of people. Recent Advances: During development, neurons in the retina are generated progressively by retinal progenitor cells, with distinct neuron types born over developmental time. Many genes function in this process to specify the identity of newly generated neuron types, and these appropriate states of gene expression inform recent regenerative work. When regeneration is initiated in other vertebrates, including birds and fish, specific signaling pathways control the efficiency of regeneration, and these conserved pathways are likely to be important in mammals as well. Critical Issues: Using insights from development and from other animals, limited regeneration from intrinsic cell types has been demonstrated in the mammalian retina, but it is able only to generate a subset of partially differentiated retinal neuron types. Future Directions: Future studies should aim at increasing the efficiency of regeneration, activating regeneration in a targeted fashion across the retina, and improving the ability to generate specific types of retinal neurons to replace those lost to disease or injury. Antioxid. Redox Signal. 39, 1039-1052.

Transcriptomic forecasting with neural ordinary differential equations

Single-cell transcriptomics technologies can uncover changes in the molecular states that underlie cellular phenotypes. However, understanding the dynamic cellular processes requires extending from inferring trajectories from snapshots of cellular states to estimating temporal changes in cellular gene expression. To address this challenge, we have developed a neural ordinary differential-equation-based method, RNAForecaster, for predicting gene expression states in single cells for multiple future time steps in an embedding-independent manner. We demonstrate that RNAForecaster can accurately predict future expression states in simulated single-cell transcriptomic data with cellular tracking over time. We then show that by using metabolic labeling single-cell RNA sequencing (scRNA-seq) data from constitutively dividing cells, RNAForecaster accurately recapitulates many of the expected changes in gene expression during progression through the cell cycle over a 3-day period. Thus, RNAForecaster enables short-term estimation of future expression states in biological systems from high-throughput datasets with temporal information.

#3195 PATIENTS ON HD WITH CENTRAL CATHETERS LOCKED WITH TAUROLIDINE HAVE A SIMILAR INFLAMMATORY PROFILE TO SUBJECTS WITH NATIVE ARTERIOVENOUS FISTULA

Abstract Background and Aims Inflammation is a near-universal condition in haemodialysis (HD) patients, which contributes to increased complications, morbidity and mortality. The inflammatory profile is enhanced in subjects who need a central venous catheter (CVC) as vascular access in comparison with patients with native arteriovenous fistula (AVF), the optimal vascular access for HD. The aim of the present study was to analyse the inflammatory profile of HD patients according to their vascular access (CVC vs AVF), and to evaluate whether Taurolidine-citrate-heparin lock solution (TCH; taurolidine 1.35%, citrate 4% and heparin 500 IU) is able to modulate the inflammatory state of patients with CVC towards an inflammatory profile similar to that observed in subjects with AVF. Method A total of 109 patients with AVF or tunneled CVC under regular haemodialysis for more than 6 months were screened. Exclusion criteria included intercurrent infections in the previous 3 months, active inflammatory or immunologic diseases, and treatment with antibiotics or drugs affecting the immune system. Finally, 85 patients were included in the study and classified according to the vascular access: 25 patients with AVF and 60 with CVC. Subsequently, two subgroups were formed from the group of patients with tunneled CVC according to a heparin-containing catheter lock solution with (CVC-TCH) and without taurolidine-citrate (CVC-Hep). Subsequently, high sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6) and tumour necrosis factor alpha (TNF-alpha) concentrations in serum and messenger ribonucleic acid (mRNA) gene expression levels of IL-6 and TNF-alpha in peripheral blood mononuclear cells (PBMC) were measured at inclusion and after three months follow-up. Results Altogether eighty-five subjects (42 males and 43 females; mean age 61 ± 9 yrs; 39% diabetics) were initially included in the study. In 25 subjects the vascular access was AVF, while the rest used tunneled CVC; of these 31 used standard CVC-Hep and 29 used CVC-TCH. Five patients dropped out the study and thus 80 patients completed the 3-month follow-up and were finally evaluated. At inclusion, patients with CVC had significantly higher serum and expression levels of inflammatory parameters compared to subjects with AVF. After 3 months, there were no significant changes in inflammatory markers in subjects with AVF compared to baseline, whereas in subjects with CVC-Hep a significant increase in serum and gene expression of IL-6 could be observed. On the contrary, subjects with CVC-TCH experienced a decrease of all parameters compared to baseline, of which differences in serum IL-6 and gene expression levels of IL-6 and TNF-alpha were significant. After 3 months of follow-up there was no significant difference in any inflammatory parameter when comparing patients with CVD-TCH with those with AVF (Table). Conclusion In patients under HD with cuffed tunneled CVC, the use of TCH lock solution after each HD session is associated with a significant improvement in the inflammatory serum and gene expression state. Thus, the inflammatory profile of patients with CVC using TCH does not differ from that of patients with native AVF after at least three months of CVC-TCH use.

Automated time-lapse data segmentation reveals in vivo cell state dynamics.

Embryonic development proceeds as a series of orderly cell state transitions built upon noisy molecular processes. We defined gene expression and cell motion states using single-cell RNA sequencing data and in vivo time-lapse cell tracking data of the zebrafish tailbud. We performed a parallel identification of these states using dimensional reduction methods and a change point detection algorithm. Both types of cell states were quantitatively mapped onto embryos, and we used the cell motion states to study the dynamics of biological state transitions over time. The time average pattern of cell motion states is reproducible among embryos. However, individual embryos exhibit transient deviations from the time average forming left-right asymmetries in collective cell motion. Thus, the reproducible pattern of cell states and bilateral symmetry arise from temporal averaging. In addition, collective cell behavior can be a source of asymmetry rather than a buffer against noisy individual cell behavior.

Single-cell Ca2+ parameter inference reveals how transcriptional states inform dynamic cell responses.

Single-cell genomic technologies offer vast new resources with which to study cells, but their potential to inform parameter inference of cell dynamics has yet to be fully realized. Here we develop methods for Bayesian parameter inference with data that jointly measure gene expression and Ca2+ dynamics in single cells. We propose to share information between cells via transfer learning: for a sequence of cells, the posterior distribution of one cell is used to inform the prior distribution of the next. In application to intracellular Ca2+ signalling dynamics, we fit the parameters of a dynamical model for thousands of cells with variable single-cell responses. We show that transfer learning accelerates inference with sequences of cells regardless of how the cells are ordered. However, only by ordering cells based on their transcriptional similarity can we distinguish Ca2+ dynamic profiles and associated marker genes from the posterior distributions. Inference results reveal complex and competing sources of cell heterogeneity: parameter covariation can diverge between the intracellular and intercellular contexts. Overall, we discuss the extent to which single-cell parameter inference informed by transcriptional similarity can quantify relationships between gene expression states and signalling dynamics in single cells.

Selective Functionalisation of 5-Methylcytosine by Organic Photoredox Catalysis.

The epigenetic modification 5-methylcytosine plays a vital role in development, cell specific gene expression and disease states. The selective chemical modification of the 5-methylcytosine methyl group is challenging. Currently, no such chemistry exists. Direct functionalisation of 5-methylcytosine would improve the detection and study of this epigenetic feature. We report a xanthone-photosensitised process that introduces a 4-pyridine modification at a C(sp3 )-H bond in the methyl group of 5-methylcytosine. We propose a reaction mechanism for this type of reaction based on density functional calculations and apply transition state analysis to rationalise differences in observed reaction efficiencies between cyanopyridine derivatives. The reaction is initiated by single electron oxidation of 5-methylcytosine followed by deprotonation to generate the methyl group radical. Cross coupling of the methyl radical with 4-cyanopyridine installs a 4-pyridine label at 5-methylcytosine. We demonstrate use of the pyridination reaction to enrich 5-methylcytosine-containing ribonucleic acid.

Selective Functionalisation of 5-Methylcytosine by Organic Photoredox Catalysis.

The epigenetic modification 5-methylcytosine plays a vital role in development, cell specific gene expression and disease states. The selective chemical modification of the 5-methylcytosine methyl group is challenging. Currently, no such chemistry exists. Direct functionalisation of 5-methylcytosine would improve the detection and study of this epigenetic feature. We report a xanthone-photosensitised process that introduces a 4-pyridine modification at a C(sp3)-H bond in the methyl group of 5-methylcytosine. We propose a reaction mechanism for this type of reaction based on density functional calculations and apply transition state analysis to rationalise differences in observed reaction efficiencies between cyanopyridine derivatives. The reaction is initiated by single electron oxidation of 5-methylcytosine followed by deprotonation to generate the methyl group radical. Cross coupling of the methyl radical with 4-cyanopyridine installs a 4-pyridine label at 5-methylcytosine. We demonstrate use of the pyridination reaction to enrich 5-methylcytosine-containing ribonucleic acid.