Real-time imaging of Arc/Arg3.1 transcription ex vivo reveals input-specific immediate early gene dynamics

The ability of neurons to process and store salient environmental features underlies information processing in the brain. Long-term information storage requires synaptic plasticity and regulation of gene expression. While distinct patterns of activity have been linked to synaptic plasticity, their impact on immediate early gene (IEG) expression remains poorly understood. The activity regulated cytoskeleton associated (Arc) gene has received wide attention as an IEG implicated in synaptic plasticity and memory. Yet, to date, the transcriptional dynamics of Arc in response to compartment and input-specific activity is unclear. By developing a knock-in mouse to fluorescently tag Arc alleles, we studied real-time transcription dynamics after stimulation of dentate granule cells (GCs) in acute hippocampal slices. To our surprise, we found that Arc transcription displayed distinct temporal kinetics depending on the activation of excitatory inputs that convey functionally distinct information, i.e. medial and lateral perforant paths (MPP and LPP, respectively). Moreover, the transcriptional dynamics of Arc after synaptic stimulation was similar to direct activation of GCs, although the contribution of ionotropic glutamate receptors, L-type voltage gated calcium channel, and the endoplasmic reticulum (ER) differed. Specifically, we observed an ER-mediated synapse-to-nucleus signal that supported elevations in nuclear calcium, and rapid induction of Arc transcription following MPP stimulation. However, activation of LPP inputs displayed lower nuclear calcium rise, which could underlie the delayed transcriptional onset of Arc. Our findings highlight how input-specific activity distinctly impacts transcriptional dynamics of an IEG linked to learning and memory.

Mapping SOX9 transcriptional dynamics during multi-lineage differentiation of human mesenchymal stem cells

The master transcription factor SOX9 is a key player during chondrocyte differentiation, cartilage development, homeostasis and disease. Modulation of SOX9 and its target gene expression is essential during chondrogenic, osteogenic and adipogenic differentiation of human mesenchymal stem cells (hMSCs). However, lack of sufficient knowledge about the signaling interplay during differentiation remains one of the main reasons preventing successful application of hMSCs in regenerative medicine. We previously showed that Transcription Factor - Fluorescence Recovery After Photobleaching (TF-FRAP) can be used to study SOX9 dynamics at the single cell level. We showed that changes in SOX9 dynamics are linked to its transcriptional activity. Here, we investigated SOX9 dynamics during differentiation of hMSCs into the chondrogenic, osteogenic and adipogenic lineages. We show that there are clusters of cells in hMSCs with distinct SOX9 dynamics, indicating that there are a number of subpopulations present in the heterogeneous hMSCs. SOX9 dynamics data at the single cell resolution revealed novel insights about its activity in these subpopulations (cell types). In addition, the response of SOX9 to differentiation stimuli varied in these subpopulations. Moreover, we identified donor specific differences in the number of cells per cluster in undifferentiated hMSCs, and this correlated to their differentiation potential.

Single-Cell Genomic Analysis Identifies Prognostically Significant Gene Expression Programs in Infant Acute Lymphoblastic Leukemia

Introduction: Infant acute lymphoblastic leukemia (ALL) is an aggressive subtype of leukemia with low rates of survival. Rearrangements involving the KMT2A gene are associated with poor prognosis for infants with this cancer. Although many patients with KMT2A rearrangements (KMT2A-r) ultimately relapse, some do not. The molecular basis for this distinction has not yet been determined. There is evidence to suggest that cancers with distinct KMT2A fusion partners show distinct patterns of gene expression, though these differences have not previously been linked to prognostic outcomes. Here we utilize single-cell genomic analysis for infant ALL samples with and without KMT2A-r taken at diagnosis to explore transcriptional dynamics and identify gene expression programs with potential prognostic value. Methods: We performed 10x Chromium single-cell multiome sequencing to obtain both gene expression (scRNA-seq) and chromatin accessibility (scATAC-seq) data for blood and/or bone marrow samples obtained from a total of 34 infant ALL patients at time of diagnosis. Of these, 19 KMT2A-r patients later relapsed, 6 KMT2A-r patients did not relapse, and 9 patients did not show KMT2A rearrangement. Sequencing data were processed and aggregated with cellranger-arc, with normalization and differential gene expression performed using the Seurat package for gene expression analysis. Differential gene expression was performed between the three groups described above, (KMT2A-r + relapse, KMT2A-r no relapse, no KMT2A-r), then further subdivided for KMT2A-r cases based on the KMT2A partner gene (MLLT1 n=13 or AFF1 n=12). Results: In preliminary scRNA- and scATAC-seq in infant ALL patients, we had observed that cancer cells from individual patients tend to cluster separately, while non-blast cell populations showed similar interindividual patterns, suggesting a high degree of divergence among blast cell transcriptional programs. We replicated this finding here in larger patient samples, demonstrating no overt similarity based on KMT2A-r status or whether patients later relapsed. Strikingly, samples did broadly cluster according to KMT2A rearrangement partner gene, indicating that this appears to be a major driver of the transcriptional program in infant ALL patients. Differential expression analysis within the KMT2A-MLLT1 and KMT2A-AFF1 samples separately revealed expression of other genes associated with particular KMT2A fusion genes. Specifically, we observed that expression of HOXA genes was mostly restricted to KMT2A-MLLT1 samples. Consistent with previous results, we observed that within KMT2A-AFF1 samples there were two distinct groups of cells with mutually exclusive expression of HOXA9 or IRX1. Furthermore, the limited HOX gene expression observed in KMT2A-AFF1 samples was enriched in patients who did not relapse, supporting previous observations that the KMT2A-AFF1 samples expressing IRX1 comprise a more aggressive leukemia. Conclusions: Utilizing a single-cell transcriptomic approach enabled us to identify gene expression programs associated with good and poor prognosis in KMT2A-r infant ALL cases. We found that the KMT2A fusion partner gene appears to drive a large portion of the transcriptional heterogeneity observed across KMT2A-r samples. By treating the KMT2A-MLLT1 and KMT2A-AFF1 samples separately and exploring transcriptional dynamics within these groups, we identified transcriptional differences between patients who did and did not relapse in the presence of a KMT2A-AFF1 fusion. We are continuing to explore these data to identify prognostic markers in KMT2A-MLLT1 patients. Figure 1. Mutually exclusive gene expression programs distinguish subsets of infant ALL samples. A) Uniform manifold approximation and projection (UMAP) visualization of gene expression in individual cells across all patient samples at diagnosis, each color corresponding to a single patient (n=34). B) Cells colored according to KMT2A-r status and relapse or lack thereof. C) Cells colored according to KMT2A fusion partner gene. D) HOXA9 expression among KMT2A-AFF1 patients is strongly biased to patients that do not relapse. E) In KMT2A-AFF1 samples, HOXA9 and IRX1 show mutually exclusive expression patterns. Figure 1 Figure 1. Disclosures Brown: Novartis: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Kura: Membership on an entity's Board of Directors or advisory committees; KIte: Membership on an entity's Board of Directors or advisory committees.

TAMI-72. DIVERSITY OF CELLULAR COMMUNICATION IN GLIOBLASTOMA

OBJECTIVE Owing to recent advances in understanding of the active functional states exhibited within glioblastoma (GBM), intra-tumoral cellular signaling has moved into focus of neuro-oncology. In this study, we aim to explore the diversity of transcellular signaling and investigate correlations between transcriptional dynamics and functional signaling. METHODS Electrophysiological characterization of GBM was carried out using planar microelectrodes and Ca2+ imaging, in both 2D cell culture as well as in our novel human cortical GBM model. Exposure to physiologically relevant conditions present within the tumor was carried out to identify specific signaling cells of interest and capture the signaling diversity in response to environmental conditions. Transcriptional dynamics and plasticity were examined by means of scRNA-sequencing with CRISPR based perturbation, spatial transcriptomics and deep long-read RNA-sequencing. RESULTS Electrophysiological profiles of multiple primary GBM cell lines revealed characteristics of scale-free networks (R2=0.875), confirmed in both 2D culture as well as a human neocortical GBM model. When GBM was cultured in a “in-vivo” like environment, basal activity was significantly higher (50%, p=0.01). Cellular signaling was directly correlated to changes in the environment, like hypoxia or glutamatergic activation, and total inhibition of electrical signaling required the usage of synaptic inhibitors. Using single-cell RNA sequencing and proteomics, several synaptogenesis related genes were identified to play a crucial role in the lineage states present in GBM. CRISPR based perturbation of these genes resulted in alterations in cellular morphology and decreased cellular connectivity (p< 0.01), with loss of scale free features (R2=0.35), and transcriptomic loss of developmental lineages (FDR< 0.01), leading to significant inhibition of GBM stress response. CONCLUSION Our findings highlight the role of electrical signaling in glioblastoma. Cellular stressors induce intercellular signaling, leading to transcriptional adaptation suggesting that there exists a highly complex and powerful mechanism for dynamic transcriptional state adaptation.

Longitudinal single-cell transcriptional dynamics throughout neurodegeneration in SCA1

Neurodegeneration is a protracted process involving progressive changes in myriad cell types that ultimately result in neuronal death. Changes in vulnerable neuronal populations are highly influenced by concomitant changes in surrounding cells, complicating experimental approaches to interrogate the simultaneous events that underlie neurodegeneration. To dissect how individual cell types within a heterogeneous tissue contribute to the pathogenesis and progression of a neurodegenerative disorder, we performed longitudinal single-nucleus RNA sequencing of the mouse and human spinocerebellar ataxia type 1 (SCA1) cerebellum, establishing continuous dynamic trajectories of each population. Furthermore, we defined the precise transcriptional changes that precede loss of Purkinje cells and identified early oligodendroglial impairments that can profoundly impact cerebellar function. Finally, we applied a deep learning method to accurately predict disease state and identify drivers of disease. Together, this work uncovers new roles for diverse cerebellar cell types in SCA1 and provides a generalizable analysis framework for studying neurodegeneration.

Viral Decoys: The Only Two Herpesviruses Infecting Invertebrates Evolved Different Transcriptional Strategies to Deflect Post-Transcriptional Editing

The highly versatile group of Herpesviruses cause disease in a wide range of hosts. In invertebrates, only two herpesviruses are known: the malacoherpesviruses HaHV-1 and OsHV-1 infecting gastropods and bivalves, respectively. To understand viral transcript architecture and diversity we first reconstructed full-length viral genomes of HaHV-1 infecting Haliotis diversicolor supertexta and OsHV-1 infecting Scapharca broughtonii by DNA-seq. We then used RNA-seq over the time-course of experimental infections to establish viral transcriptional dynamics, followed by PacBio long-read sequencing of full-length transcripts to untangle viral transcript architectures at two selected time points. Despite similarities in genome structure, in the number of genes and in the diverse transcriptomic architectures, we measured a ten-fold higher transcript variability in HaHV-1, with more extended antisense gene transcription. Transcriptional dynamics also appeared different, both in timing and expression trends. Both viruses were heavily affected by post-transcriptional modifications performed by ADAR1 affecting sense-antisense gene pairs forming dsRNAs. However, OsHV-1 concentrated these modifications in a few genomic hotspots, whereas HaHV-1 diluted ADAR1 impact by elongated and polycistronic transcripts distributed over its whole genome. These transcriptional strategies might thus provide alternative potential roles for sense-antisense transcription in viral transcriptomes to evade the host’s immune response in different virus–host combinations.

Transcriptional dynamics of methane-cycling microbiomes are linked to seasonal CH4 fluxes in two hydromorphic and organic-rich grassland soils

Soil CH4 fluxes are driven by CH4-producing and -consuming microorganisms that determine whether soils are sources or sinks of this potent greenhouse gas. Using quantitative metatranscriptomics, we linked CH4-cycling microbiomes to net surface CH4 fluxes throughout a year in two drained peatland soils differing in grassland land-use intensity and physicochemical properties. CH4 fluxes were highly dynamic; both soils were net CH4 sources in autumn and winter and sinks in spring and summer. Despite similar net CH4 emissions, methanogen and methanotroph loads, as determined by small subunit rRNA transcripts per gram soil, differed strongly between sites. In contrast, mRNA transcript abundances were similar in both soils and correlated well with CH4 fluxes. The methane monooxygenase to methanogenesis mRNA ratio was higher in spring and summer, when the soils were net CH4 sinks. CH4 uptake was linked to an increased proportion of USCα and γ and pmoA2 pmoA transcripts. We assume that methanogen transcript abundance may be useful to approximate changes in net surface CH4 emissions from drained peat soils; high methanotroph to methanogen ratios would indicate CH4 sink properties. Our study shows the strength of quantitative metatranscriptomics; mRNA transcript abundance holds promising indicator to link soil microbiome functions to ecosystem-level processes.

Pubertal sex hormones control transcriptional trajectories in the medial preoptic area

Pubertal maturation aids development of emotion, cognition, and reproduction. We investigated transcriptional dynamics in the medial preoptic area (MPOA), a hypothalamic center for reproductive behaviors, in male and female mice at single-cell resolution (scRNAseq) during puberty. Defined subsets of neurons expressing Slc32a1 and Esr1 (Vgat+ Esr1+) were the most transcriptionally dynamic compared to other cell types throughout puberty. These cell type specific transcriptional progressions towards adulthood were bidirectionally controlled by the levels of circulating testosterone and estradiol. Selective deletion of Esr1 in Slc32a1-expressing cells in the MPOA prior to puberty arrested transcriptional progression and revealed a sexually dimorphic gene-regulatory network governed by Esr1. Deletion of Esr1 in Vgat+ cells prevented the development of mating behavior in both sexes. These analyses reveal both sexually common and dimorphic transcriptional progressions during puberty as well as their regulatory mechanisms, which have important implications towards understanding adaptative and maladaptive processes governing adolescent brain development.