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Evans, S. M.

Publications and source records attributed to Evans, S. M..

5 recordsLinked to original sources

Adventitial leptin receptor-expressing fibroblasts are preferential contributors to fibrotic remodeling of the heart post infarction

BackgroundCardiac fibrosis, a hallmark of heart failure and an unmet clinical need, arises from pathological activation of pre-existing cardiac fibroblasts (CFs), but the contribution of CF heterogeneity to this process remains unclear. MethodsMurine models were used to lineage trace or deplete a specific sub-population of CFs at baseline and after myocardial infarction (MI). Transcriptional and epigenetic differences between fibroblast subsets were assessed using next-generation sequencing. Conservation in humans was evaluated through single-cell RNA-seq datasets and histological examination. ResultsIn mice, fibroblasts were the sole cardiac cell type expressing the signaling-capable isoform of the leptin receptor (LepR). LepR+ CFs emerged neonatally, occupied a defined niche in the coronary adventitia, exhibited enhanced hedgehog signaling, and responded to leptin. After MI, LepR-Cre+ CFs proliferated more than interstitial CFs, became a predominant fibroblast lineage in the scar, and their genetic ablation reduced fibrosis while improving function. LepR+ CFs were also detected in the human heart, where they were embedded in an adipocyte-rich niche. ConclusionsThese findings identify adventitial fibroblasts as key drivers of pathological remodeling and demonstrate that fibroblasts, rather than cardiomyocytes, are the principal responders to leptin in the heart, redefining how this major endocrine pathway influences cardiac remodeling and disease.

cell biology↗

Transcriptional Readthrough at Atf4 Locus Suppresses Rps19bp1 and Impairs Heart Development

BACKGROUNDActivating Transcription Factor 4 (ATF4) functions as a transcriptional regulator in various cell types and tissues under both physiological and pathological conditions. While previous studies have linked ATF4 activation with promoting cardiomyocyte (CM) death in dilated cardiomyopathy (DCM), atrial fibrillation, and heart failure, its role in developing CMs remains unexplored. METHODSWe generated multiple distinct CM-specific (Atf4cKO(e2/3/pA) and Atf4cKO(e2)) and global Atf4 knockout (Atf47del/7del and Atf41ins/1ins) mouse models targeting different Atf4 regions, as well as cardiomyocyte-specific deletion of Rps19bp1 to study cardiac phenotypes. Detailed morphological and molecular analyses were performed. RESULTSAtf4cKO(e2/3/pA) (targeting exon 2-3 including the polyadenylation signal (polyA)) mice exhibited severe cardiac defects and died before E17.5, likely due to ectopic activation of p53 signaling pathway resulting from Rps19bp1 downregulation, a potent suppressor of p53. Further investigation revealed that deleting the polyA signal of Atf4 in Atf4cKO(e2/3/pA) mice led to transcriptional readthrough, resulting in the formation of an Atf4-Cacna1i fusion transcript and Rps19bp1 downregulation. To avoid readthrough while abolishing ATF4 function, we introduced small indels into exon 3 of Atf4 in mice (Atf47del/7del and Atf41ins/1ins), which showed normal Rps19bp1 expression and cardiac morphology. Importantly, CM-specific deletion of Rps19bp1 recapitulated the cardiac defects and transcriptional change seen in Atf4cKO(e2/3/pA) mice. CONCLUSIONSWe found that the downregulation of Rps19bp1, not loss of ATF4 function, underlying the cardiac phenotypes in Atf4cKO(e2/3/pA) mice. The reduced expression of Rps19bp1 in Atf4cKO(e2/3/pA) mice is likely due to the unintentional deletion of Atf4 polyA signal and subsequent transcriptional readthrough, underscoring the essential role of RPS19BP1, not ATF4, in cardiac development. Consistent Rps19bp1 downregulation has been observed in other tissue-specific Atf4 knockout models utilizing the Atf4fl(e2/3/pA) allele, suggesting that previously reported Atf4 KO phenotypes may result from Atf4 transcriptional readthrough effects. These findings reveal a locus-dependent transcriptional interference mechanism and emphasize the importance of avoiding confounding cis effects in genetically engineered models. TRANSLATIONAL PERSPECTIVEOur findings clarify ATF4s role in heart development by showing that cardiac defects in cardiomyocyte-specific ATF4 knockout mice--using a widely employed floxed ATF4 line--result from unintended downregulation of RPS19BP1 caused by transcriptional readthrough. This shifts the focus from ATF4 to RPS19BP1, a key regulator of p53 activity, as a potential driver of cardiac developmental abnormalities. Clinically, these insights caution against misinterpretation of genetic knockout models and highlight RPS19BP1 as a promising target for congenital heart disease and related cardiac dysfunctions, with potential implications for future therapies.

genetics↗

The epigenetic modifier DOT1L regulates gene regulatory networks necessary for cardiac patterning and cardiomyocyte cell cycle withdrawal

Mechanisms by which specific histone modifications regulate distinct gene regulatory networks remain little understood. We investigated how H3K79me2, a modification catalyzed by DOT1L and previously considered a general transcriptional activation mark, regulates gene expression in mammalian cardiogenesis. Early embryonic cardiomyocyte ablation of Dot1l revealed that H3K79me2 does not act as a general transcriptional activator, but rather regulates highly specific gene regulatory networks at two critical cardiogenic junctures: left ventricle patterning and postnatal cardiomyocyte cell cycle withdrawal. Mechanistic analyses revealed that H3K79me2 in two distinct domains, gene bodies and regulatory elements, synergized to promote expression of genes activated by DOT1L. Surprisingly, these analyses also revealed that H3K79me2 in specific regulatory elements contributed to silencing genes usually not expressed in cardiomyocytes. As DOT1L mutants had increased numbers of postnatal mononuclear cardiomyocytes and prolonged cardiomyocyte cell cycle activity, controlled inhibition of DOT1L might be a strategy to promote cardiac regeneration post-injury.

developmental biology↗

Assembly of functionally antagonistic visual circuits for controlling pupil dynamics

HighlightsO_LITbx20 plays a role in the development of non-image-forming pathways.\nC_LIO_LILoss of Tbx20-expressing RGCs alters specific aspects of the pupil reflex arc.\nC_LIO_LIPreviously unknown role for a specific subset of Tbx20-expressing RGCs in modulating pupil size.\nC_LI\n\neTOCDhande et al. identify a novel genetic program that marks and is required for the development of non-image-forming parallel visual pathways. Moreover, chemogenetic activation of a specific retina-to-OPN pathway reveals a novel circuit element controlling pupil size. These findings provide new insight into the mechanisms that establish defining features of functionally specialized sensory pathways.\n\nSummaryThe functional attributes of parallel sensory circuits are determined by the properties of the individual cell types that comprise them, and their connectivity. The mechanisms controlling the specification and establishment of parallel sensory pathways remain unclear. Here we report the non-uniform distribution of retinal ganglion cells (RGCs) expressing the transcription factor Tbx20 in mice. Owing to their layout within the retina, Tbx20-RGCs are positioned to preferentially encode light information from dorsal visual space. We discovered that Tbx20 expression is mostly restricted to three RGC-types: M1 intrinsically photosensitive RGCs (ipRGCs), M2 ipRGCs and diving RGCs. The axonal projections of Tbx20-RGCs innervate non-image-forming brain centers including the suprachiasmatic nucleus, the medial division of the posterior pretectal nucleus, and the olivary pretectal nucleus (OPN), a principal station in the neural pathway for generating the pupillary light reflex (PLR). Conditional deletion of Tbx20 resulted in reduced Tbx20-RGC axonal innervation of these targets and revealed a key role of these neurons in driving specific phases of the PLR. Furthermore, chemogenetic activation uncovered a novel role for a specific subset of Tbx20-RGCs in controlling pupil dilation. These data offer a new understanding of the genetic and molecular mechanisms that establish specific, behaviorally-relevant visual circuits.

neuroscience↗

Evaluating the effects of data visualisation techniques on interpretation and preference in clinical quality reports: A cross-sectional study.

ObjectiveTo evaluate the different methods of data visualisation and how it affects preference and data interpretation.\n\nDesignA cross-sectional survey, assessing interpretation and preference for four methods of data presentation, was distributed to participants.\n\nSettingMelbourne, Victoria\n\nParticipantsMembers of Prostate Cancer Outcome Registry-Victoria (PCOR-Vic) and senior hospital staff in three metropolitan Victorian hospitals.\n\nInterventionsDifferent methods of data visualisation. Mainly, funnel plots, league charts, risk adjusted sequential probability ratio test (RASPRT) charts and dashboard.\n\nMain Outcome MeasureInterpretation scores assessed capacity by participants to identify outliers and poor performers. Preference was based on a 9-point Likert-scale (0 - 9).\n\nResultsIn total, 113 participants responded to the online survey (16/58 urologists and 97/297 senior hospital staff, response rate 32%). Respondents reported that funnel plots were easier to interpret compared to league charts (mean interpretability score difference of 28% (95% CI: 19.2% - 37.0%, P<0.0001). Predictors of worse interpretability of charts in the adjusted model were being a hospital executive compared to a urologist (coefficient= -2.50, 95% CI = -3.82, - 1.18, P<0.01) and having no statistical training compared to those with statistical training (coefficient = -1.71, 95% CI=-2.85, -0.58, P=0.003). Participants preferred funnel plots and dashboards compared to league charts and RASPRT charts (median score 7/9 vs 5/9), and preferred charts which were traffic-light coloured versus greyscale charts (43/60 (71.6%) vs 17/60 (28.3%)).\n\nConclusionWhen developing reports for clinicians and hospitals, consideration should be given to preference of end-users and ability of groups to interpret the graphs.

epidemiology↗