Disrupting autorepression circuitry generates "open-loop lethality" to yield escape-resistant antiviral agents.

Across biological scales, gene-regulatory networks employ autorepression (negative feedback) to maintain homeostasis and minimize failure from aberrant expression. Here, we present a proof of concept that disrupting transcriptional negative feedback dysregulates viral gene expression to therapeutically inhibit replication and confers a high evolutionary barrier to resistance. We find that nucleic-acid decoys mimicking cis-regulatory sites act as "feedback disruptors," break homeostasis, and increase viral transcription factors to cytotoxic levels (termed "open-loop lethality"). Feedback disruptors against herpesviruses reduced viral replication >2-logs without activating innate immunity, showed sub-nM IC50, synergized with standard-of-care antivirals, and inhibited virus replication in mice. In contrast to approved antivirals where resistance rapidly emerged, no feedback-disruptor escape mutants evolved in long-term cultures. For SARS-CoV-2, disruption of a putative feedback circuit also generated open-loop lethality, reducing viral titers by >1-log. These results demonstrate that generating open-loop lethality, via negative-feedback disruption, may yield a class of antimicrobials with a high genetic barrier to resistance.

Measuring the buffering capacity of gene silencing in Saccharomyces cerevisiae.

Gene silencing in budding yeast is mediated by Sir protein binding to unacetylated nucleosomes to form a chromatin structure that inhibits transcription. Transcriptional silencing is characterized by the high-fidelity transmission of the silent state. Despite its relative stability, the constituent parts of the silent state are in constant flux, giving rise to a model that silent loci can tolerate such fluctuations without functional consequences. However, the level of tolerance is unknown, and we developed methods to measure the threshold of histone acetylation that causes the silent chromatin state to switch to the active state as well as to measure the levels of the enzymes and structural proteins necessary for silencing. We show that loss of silencing required 50 to 75% acetyl-mimic histones, though the precise levels were influenced by silencer strength and upstream activating sequence (UAS) enhancer/promoter strength. Measurements of repressor protein levels necessary for silencing showed that reducing SIR4 gene dosage two- to threefold significantly weakened silencing, though reducing the gene copy numbers for Sir2 or Sir3 to the same extent did not significantly affect silencing suggesting that Sir4 was a limiting component in gene silencing. Calculations suggest that a mere twofold reduction in the ability of acetyltransferases to acetylate nucleosomes across a large array of nucleosomes may be sufficient to generate a transcriptionally silent domain.

A molecular mechanism for probabilistic bet hedging and its role in viral latency.

Probabilistic bet hedging, a strategy to maximize fitness in unpredictable environments by matching phenotypic variability to environmental variability, is theorized to account for the evolution of various fate-specification decisions, including viral latency. However, the molecular mechanisms underlying bet hedging remain unclear. Here, we report that large variability in protein abundance within individual herpesvirus virion particles enables probabilistic bet hedging between viral replication and latency. Superresolution imaging of individual virions of the human herpesvirus cytomegalovirus (CMV) showed that virion-to-virion levels of pp71 tegument protein-the major viral transactivator protein-exhibit extreme variability. This super-Poissonian tegument variability promoted alternate replicative strategies: high virion pp71 levels enhance viral replicative fitness but, strikingly, impede silencing, whereas low virion pp71 levels reduce fitness but promote silencing. Overall, the results indicate that stochastic tegument packaging provides a mechanism enabling probabilistic bet hedging between viral replication and latency.

Relationship of Choroidal Microvasculature Dropout and Beta Zone Parapapillary Area With Visual Field Changes in Glaucoma.

PURPOSE: To evaluate the association between rates of choroidal microvasculature dropout (MvD) change, beta zone parapapillary atrophy (ß-PPA) area change, and visual field (VF) changes in eyes with primary open-angle glaucoma (POAG). DESIGN: Retrospective, observational cohort study. METHODS: In a tertiary glaucoma clinic, we included 76 eyes from 58 patients with POAG with and without localized MvD, who had ≥2 years of follow-up with a minimum of 4 visits with optical coherence tomography angiography and optical coherence tomography scans. ß-PPA area was evaluated using scanning laser ophthalmoscopy-like images and compared with the area of MvD on an en face choroidal vessel density map during the follow-up period. Joint longitudinal mixed effects models were used to estimate the rates of change in ß-PPA area or MvD area and VF mean deviation (MD). RESULTS: Mean rates of change in ß-PPA and MvD area were 0.037 mm2 (95% confidence interval [CI] 0.030-0.043 mm2) per year and 0.039 mm2 (95% CI 0.029-0.048 mm2) per year, respectively, over the mean follow-up of 4.1 years. In multivariable models, MvD area enlargement was significantly associated with faster rates of VF MD loss (0.03 mm2 [95% CI 0.02-0.04 mm2] per 1-dB worse, P < .001) but not ß-PPA area enlargement (0.04 mm2 [95% CI 0.03-0.05 mm2] per 1-dB worse, P = .252). CONCLUSION: MvD area rates, but not ß-PPA area rates, were associated with VF MD loss changes in eyes with POAG. Assessment of MvD is useful for the detection of patients with glaucoma who are at an increased risk of faster VF loss.

Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements.

PURPOSE: To develop deep learning (DL) models estimating the central visual field (VF) from optical coherence tomography angiography (OCTA) vessel density (VD) measurements. DESIGN: Development and validation of a deep learning model. METHODS: A total of 1051 10-2 VF OCTA pairs from healthy, glaucoma suspects, and glaucoma eyes were included. DL models were trained on en face macula VD images from OCTA to estimate 10-2 mean deviation (MD), pattern standard deviation (PSD), 68 total deviation (TD) and pattern deviation (PD) values and compared with a linear regression (LR) model with the same input. Accuracy of the models was evaluated by calculating the average mean absolute error (MAE) and the R2 (squared Pearson correlation coefficients) of the estimated and actual VF values. RESULTS: DL models predicting 10-2 MD achieved R2 of 0.85 (95% confidence interval [CI], 74-0.92) for 10-2 MD and MAEs of 1.76 dB (95% CI, 1.39-2.17 dB) for MD. This was significantly better than mean linear estimates for 10-2 MD. The DL model outperformed the LR model for the estimation of pointwise TD values with an average MAE of 2.48 dB (95% CI, 1.99-3.02) and R2 of 0.69 (95% CI, 0.57-0.76) over all test points. The DL model outperformed the LR model for the estimation of all sectors. CONCLUSIONS: DL models enable the estimation of VF loss from OCTA images with high accuracy. Applying DL to the OCTA images may enhance clinical decision making. It also may improve individualized patient care and risk stratification of patients who are at risk for central VF damage.

Impact of smoking on choroidal microvasculature dropout in glaucoma: a cross-sectional study.

OBJECTIVE: To investigate the effect of smoking on choroidal microvasculature dropout (MvD) in glaucoma. DESIGN: Cross-sectional study. SETTING: Tertiary glaucoma centre. PARTICIPANTS: 223 eyes of 163 patients with primary open-angle glaucoma who had undergone imaging with optical coherence tomography angiography and completed a questionnaire on smoking from the Diagnostic Innovations in Glaucoma Study. PRIMARY OUTCOME MEASURES: Linear mixed-effects models were used to determine the effect of each parameter on MvD area and angular circumference. The sensitivity analysis was performed by categorising the glaucoma severity determined by visual field mean deviation (MD). RESULTS: MvD was found in 37 (51.4%) eyes with smoking history and in 67 (44.4%) eyes with non-smokers (p=0.389). Larger MvD area and wider angular circumference were found in smokers compared with non-smokers (p=0.068 and p=0.046, respectively). In a multivariable model, smoking intensity was significantly associated with MvD area (0.30(95% CI 0.01 to 0.60) each 0.01 mm2 per 10 pack-years; p=0.044). In eyes with moderate-severe glaucoma (MD <-6), smoking intensity was associated with larger MvD area (0.47 (95% CI 0.11 to 0.83) each 0.01 mm2 per 10 pack-years; p=0.011), whereas no significant association was found in early glaucoma (MD ≥-6) (-0.08 (95% CI -0.26 to 0.11), p=0.401). CONCLUSIONS: Smoking intensity was associated with larger choroidal MvD area in eyes with glaucoma, especially in patients with more severe disease. TRIAL REGISTRATION NUMBER: NCT00221897.

Intraocular pressure increases the rate of macular vessel density loss in glaucoma.

BACKGROUND/AIMS: To evaluate the relationship over time between intraocular pressure (IOP) and the rate of macula whole image vessel density (wiVD) loss and whole image ganglion cell complex (wiGCC) thinning in glaucoma METHODS: From 62 patients in the Diagnostic Innovations in Glaucoma Study, 59 Primary open-angle glaucoma and 27 glaucoma suspect eyes with mean follow-up of 3.2 years were followed. Optical coherence tomography angiography (OCT-A)-based vessel density and OCT-based structural thickness of the same 6×6 mm GCC scan slab were evaluated. Univariable and multivariable linear mixed models were performed for all eyes and also a subset of them in which peak IOP <18 mm Hg to investigate the effect of IOP parameters on the rate of wiVD and wiGCC change. RESULTS: The mean baseline visual field mean deviation (95% CI) was -3.3 dB (-4.4 to -2.1). Higher mean IOP (-0.07%/year per 1 mm Hg (-0.14 to -0.01), p=0.033), peak IOP (-0.07%/year per 1 mm Hg (-0.13 to -0.02), p=0.004) and IOP fluctuation (IOP SD) (-0.17%/year per 1 mm Hg (-0.32 to 0.02), p=0.026) were associated with faster macular vessel density loss. Faster wiGCC thinning was associated with higher mean IOP (-0.05 µm/year per 1 mm Hg (-0.10 to -0.01), p=0.015), peak IOP (-0.05 µm/year per 1 mm Hg (-0.08 to -0.02), p=0.003) and IOP fluctuation (-0.12 µm/year per 1 mm Hg (-0.22 to -0.01), p=0.032). In eyes with peak <18 mm Hg, faster wiVD progression was associated with higher mean IOP (p=0.042). Faster wiGCC progression was associated with higher mean IOP in these eyes (p=0.025). CONCLUSION: IOP metrics were associated with faster rates of overall macular microvascular loss and also in the eyes with peak IOP <18 mm Hg. Future studies are needed to examine whether additional IOP lowering reduces the rate of microvascular loss in patients with glaucoma. TRIAL REGISTRATION NUMBER: NCT00221897.