Genome-wide gene expression responses to experimental manipulation of Saccharomyces cerevisiae repressor activator protein 1 (Rap1) expression level

Precise regulation of transcription in gene expression is critical for all aspects of normal organism form, fitness, and function and even minor alterations in the level, location, and timing of gene expression can result in phenotypic variation within and between species including evolutionary innovations and human disease states. Eukaryotic transcription is regulated by a complex interplay of multiple factors working both at a physical and molecular levels influencing this process. In Saccharomyces cerevisiae, the TF with the greatest number of putative regulatory targets is the essential gene Repressor Activator Protein 1 (RAP1). While much is known about the roles of Rap1 in gene regulation and numerous cellular processes, the response of Rap1 target genes to systematic titration of RAP1 expression level remains unknown. To fill this knowledge gap, we used a strain with a tetracycline-titratable promoter replacing wild-type regulatory sequences of RAP1 to systematically reduce the expression level of RAP1 and followed this with RNA sequencing (RNA-seq) to measure genome-wide gene expression responses. Previous research indicated that Rap1 plays a significant regulatory role in particular groups of genes including telomere-proximal genes, homothallic mating (HM) loci, glycolytic genes, DNA repair genes, and ribosomal protein genes; therefore, we focused our analyses on these groups and downstream targets to determine how they respond to reductions in RAP1 expression level. Overall, despite being known as both an activator and as a repressor of its target genes, we found that Rap1 acts as an activator for more target genes than as a repressor. Additionally, we found that Rap1 functions as an activator of ribosomal protein genes and a repressor of the silent mating locus genes consistent with predictions from the literature. Unexpectedly, we found that Rap1 functions as a repressor of glycolytic enzyme genes contrary to prior reports of it having the opposite effect. We also compared the expression of RAP1 to five different genes related to DNA repair pathway and found that decreasing RAP1 downregulated four of those five genes. Finally, we found no effect of RAP1 depletion on telomere-proximal genes despite its functioning to silence telomeric repeat-containing RNAs. Together our results enrich our understanding of this important transcriptional regulator. The graphical abstract is provided as a supplementary fig. (S-Fig 1).

3 Tesla magnetic resonance imaging in patients with cardiac electronic implantable devices: a single center experience

Background

Cardiac magnetic resonance imaging (MRI), a key method guiding medical diagnosis and therapy, is increasingly performed at 3 Tesla (T) field strength. Growing evidence suggests a relatively safe conductance of 1.5 T MRI in patients with cardiac implantable electronic devices (CIEDs), leading to conditional certification of some CIEDs for MRI. However, data on the safety of MRI imaging at 3 T in patients with CIEDs are scarce.

Purpose

We analysed the safety of clinically indicated 3 T MRI in patients with “3T MRI-conditional” and “3 T MRI-non-conditional” CIEDs.

Methods

We performed a retrospective single-center analysis of consecutive patients with CIEDs labelled by the manufacturer as “MRI non-conditional”, “1.5 T MRI-conditional” and “3 T MRI-conditional”. Patients underwent clinically indicated 3 T MRI of different thoracic and non-thoracic body regions from April 2020 to February 2022. Devices were interrogated and programmed appropriately before and after scanning. Statistics included median and interquartile range. Measurements of device and lead function and integrity before and after scanning were assessed. Adverse events included all-cause death, arrhythmias, loss of capture, inappropriate anti-tachycardia therapies, electrical reset and lead or generator failure during or shortly after MRI scan.

Results

One hundred twenty-eight 3 T MRI scans were performed in 94 patients (mean age 72±16 years, 36.2% female). 3T MRI scans were performed in patients with “non-MRI-conditional” devices (n=9), “1.5 T MRI-conditional” devices (n=22), and “3 T MRI-conditional” devices (n=97). Patients were pacemaker-dependent in 24 MRI scans. After MRI, lead impedance had changed by 100 Ohms or more in seven cases (4 atrial and 3 right ventricular leads). P-wave (−25%) reduction was noted in one, R-wave (−50%) reduction in two cases. Right atrial and ventricular threshold exceeded the limit of 0,5V in one case each only in “3 T MRI-conditional” devices. No clinically relevant adverse events occurred.

Conclusion

3 T MRI was safely conducted in patients with “3 T MRI-conditional” and “non-MRI conditional” CIEDs in our single-center study. Pending verification in independent series, our data suggest that clinically indicated 3T MRI scans should not be withheld from patients with cardiac pacemakers or defibrillators.

Funding Acknowledgement

Type of funding sources: None.

Cardiovascular magnetic resonance deformation imaging: method comparison and considerations regarding reproducibility

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): German Centre for Cardiovascular Research

Purpose

Myocardial Feature-Tracking (FT) deformation imaging is superior for risk-stratification compared to volumetric approaches. Since there is no clear recommendation regarding FT post-processing, we compared different FT-strain analyses with reference standard techniques, including tagging and strain encoded (SENC) magnetic resonance imaging.

Methods

FT software from 4 different vendors (TomTec/Medis/Circle(CVI)/Neosoft), tagging (Segment), and fastSENC (MyoStrain) were used to determine left ventricular global circumferential and longitudinal strains (GCS/GLS) in 12 healthy volunteers and 12 heart failure patients. Variability and agreements were assessed using intraclass correlation coefficients for absolute agreement (ICCa) and consistency (ICCc) as well as pearson correlation coefficients.

Results

For FT-GCS, consistency was excellent comparing different FT-vendors (ICCc = 0.84-0.97, r = 0.86-0.95) and compared to fSENC (ICCc = 0.78-0.89, r = 0.73-0.81). FT-GCS consistency was excellent compared to tagging (ICCc = 0.79-0.85, r = 0.74-0.77) except for TomTec (ICCc = 0.68, r = 0.72). Absolute FT-GCS agreements between FT-vendors were highest for CVI and Medis (ICCa = 0.96) and lowest for TomTec and Neosoft (ICCa = 0.32). Similarly, absolute FT-GCS agreements were excellent for CVI and Medis compared to both tagging and fSENC (ICCa = 0.84-0.88), good to excellent for Neosoft (ICCa = 0.77 and 0.64) and lowest for TomTec (ICCa = 0.41 and 0.47).

For FT-GLS, consistency was excellent (ICCc≥0.86, r≥0.76). Absolute agreements between FT-vendors were excellent (ICCa = 0.91-0.93) or good to excellent for TomTec (ICCa = 0.69-0.85). Absolute agreements (ICCa) were good (CVI 0.70, Medis 0.60) and fair (TomTec 0.41, Neosoft 0.59) compared to tagging but excellent compared to fSENC (ICCa = 0.77-0.90).

Conclusion

Although absolute agreements differ depending on deformation assessment approaches, consistency and correlation are consistently high irrespective of the method chosen, thus indicating reliable strain assessment. Further standardisation and introduction of uniform references is warranted for routine clinical implementation.

Performance of different myocardial tissue tracking algorithms and acquisition-based strain imaging to characterise myocardial pathology

Background

Myocardial deformation imaging is superior in risk-stratification compared to volumetric approaches. Myocardial Feature-Tracking (FT) allows easy post-processing of routinely acquired cine images. Since there is no clear recommendation regarding FT post-processing we sought to compare different FT-strains with reference standard techniques including tagging and strain encoded (SENC) magnetic resonance imaging.

Methods

CMR-FT software from 4 different vendors (TomTec, Medis, Circle, Neosoft), CMR tagging (Segment) and fastSENC (MyoStrain) were used to determine left ventricular (LV) global longitudinal and circumferential strains (GLS and GCS) in 12 healthy volunteers and 12 heart failure patients. Variability and agreements were assessed using intraclass correlation coefficients, coefficients of variation and Bland Altman plots.

Results

Compared to tagging, FT-based strain was software independently significantly higher except for GCS using Medis (p=0.178). Compared to fSENC, mean-differences of GLS were smaller within a range of ±1.5%. For GCS this only applied to CVI and Medis (<1.5%) but not TomTec (>7%) or Neosoft (>4%). Absolute agreements comparing FT to tagging were best for CVI (GLS ICC0.70) and Medis (GCS ICC0.85). Compared to fSENC agreement of GLS was generally excellent (ICC>0.77), but only CVI and Medis revealed excellent agreement for GCS (ICC0.88 and 0.85). Consistency and correlation of GLS were software independently high compared with tagging and fSENC (ICC>0.86, r>0.76) while being lower for GCS (ICC>0.68, r>0.72).

Conclusion

Although agreement differs between deformation assessment approaches, consistency and correlation are high irrespective of the method chosen, thus indicating reliable strain assessment. Further standardisation and introduction of uniform references is warranted for clinical routine implementation.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): DZHK - German Centre for Cardiovascular Research