dCas9 fusion to computer-designed PRC2 inhibitor reveals functional TATA box in distal promoter region

Levy, Shiri; Somasundaram, Logeshwaran; Raj, Infencia Xavier; Ic-Mex, Diego; Phal, Ashish; Schmidt, Sven; Ng, Weng I.; Mar, Daniel; Decarreau, Justin; Moss, Nicholas; Alghadeer, Ammar; Honkanen, Henrik; Sarthy, Jay F.; Vitanza, Nicholas A.; Hawkins, R. David; Mathieu, Julie; Wang, Yuliang; Baker, David C.; Bomsztyk, Karol

doi:10.1016/j.celrep.2022.110457

Cited by 21 publications

(27 citation statements)

References 87 publications

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“…The epigenome has been previously shown to be regulated by mitochondrial metabolites, and epigenomic changes have been identified in quiescent stem cell states ( van Velthoven and Rando, 2019 ; Cho et al., 2019 ; Hussein et al., 2020 ; Somasundaram et al., 2020 ; Hu et al., 2020 ; Martínez-Reyes and Chandel, 2020 ; Moody et al., 2017 ; Levy et al., 2022 ). We now show that KD of the PRC1 (Pc/CBX and Sce/RING1) or PRC2 (Jarid2, Su(z)12, E(z), and Jing) components in GSCs abolishes the normal IR-induced cell-cycle block at 1 dpi, suggesting that these repressive epigenomic modifiers are required for entry into GSC quiescence ( Figures 4 A, 4B, and S3 ).…”

Section: Resultsmentioning

confidence: 99%

Stress-induced reversible cell-cycle arrest requires PRC2/PRC1-mediated control of mitophagy in Drosophila germline stem cells and human iPSCs

Taslim¹,

Hussein²,

Keshri³

et al. 2023

Stem Cell Reports

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Section: Resultsmentioning

confidence: 99%

Stress-induced reversible cell-cycle arrest requires PRC2/PRC1-mediated control of mitophagy in Drosophila germline stem cells and human iPSCs

Taslim¹,

Hussein²,

Keshri³

et al. 2023

Stem Cell Reports

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“…Researchers from the School of Medicine at the University of Washington in Seattle stated that it is feasible to activate specific dormant genes by turning off the chemical "off switches" that keep them silent by merging CRISPR technology with a protein created with AI. This strategy will enable researchers to comprehend the function-specific genes that serve in both healthy cell growth and development, and malignancy [69].…”

Section: Future Directionsmentioning

confidence: 99%

Artificial Intelligence in Cancer Research: Trends, Challenges and Future Directions

Sebastian

Peter

2022

Life

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The World Health Organization (WHO), in their 2022 report, identified cancer as one of the leading causes of death, accounting for about 16% of deaths worldwide. The Cancer-Moonshot community aims to reduce the cancer death rate by half in the next 25 years and wants to improve the lives of cancer-affected people. Cancer mortality can be reduced if detected early and treated appropriately. Cancers like breast cancer and cervical cancer have high cure probabilities when treated early in accordance with best practices. Integration of artificial intelligence (AI) into cancer research is currently addressing many of the challenges where medical experts fail to bring cancer to control and cure, and the outcomes are quite encouraging. AI offers many tools and platforms to facilitate more understanding and tackling of this life-threatening disease. AI-based systems can help pathologists in diagnosing cancer more accurately and consistently, reducing the case error rates. Predictive-AI models can estimate the likelihood for a person to get cancer by identifying the risk factors. Big data, together with AI, can enable medical experts to develop customized treatments for cancer patients. The side effects from this kind of customized therapy will be less severe in comparison with the generalized therapies. However, many of these AI tools will remain ineffective in fighting against cancer and saving the lives of millions of patients unless they are accessible and understandable to biologists, oncologists, and other medical cancer researchers. This paper presents the trends, challenges, and future directions of AI in cancer research. We hope that this paper will be of help to both medical experts and technical experts in getting a better understanding of the challenges and research opportunities in cancer diagnosis and treatment.

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“…We have previously developed a microplate sonicator, PIXUL, that offers unparalleled sample preparation throughput capabilities for a broad range of high throughput analytical applications (1)(2)(3). In sharp contrast, available tissue storing and sampling tools lack the throughput to fully exploit the PIXUL sample preparation capabilities to interrogate solid biospecimens.…”

Section: Introductionmentioning

confidence: 99%

CryoGrid-PIXUL-RNA: High throughput RNA isolation platform for tissue transcript analysis

Schactler

Scheuerman

Lius

et al. 2022

Preprint

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Disease molecular complexity requires high throughput workflows to map disease pathways through analysis of vast tissue repositories. Great progress has been made in life sciences analytical technologies. To match the high throughput of these advanced analytical platforms, we have previously developed a multipurpose microplate sonicator, PIXUL, that can be used in multiple workflows to extract analytes from cultured cells and tissue fragments for various downstream molecular assays. And yet, the sample preparation devices, such as PIXUL, along with the downstream analytical capabilities have not been fully exploited to interrogate tissues because storing and sampling of such specimens remain, in comparison, inefficient. To mitigate this bottleneck, we have developed a low-cost user-friendly system, the CryoGrid, that consists of CryoBlock, thermometer/thermocouple, and QR coded CryoTrays to freeze and store frozen tissue fragments, and hand-held CryoCore tool for tissue sampling supported by iPad and Google apps to display tissues, direct coring and share metadata. RNA is one of the most studied analytes. There is a decades-long history of developing methods to isolate and analyze RNA. Still, the throughput of sampling and RNA extraction from tissues has not matched that of the high throughput transcriptome analytical platforms. To address this need, we have integrated the CryoGrid system with PIXUL-based methods to isolate RNA for gene-specific qPCR and genome-wide transcript analyses. TRIzol is commonly used to isolate RNA but it is labor-intensive, hazardous, requires fume-hoods, and is an expensive reagent. We developed a PIXUL-based TRIzol-free RNA isolation fast protocol that uses a buffer containing proteinase K (PK). Virtually every disease (and often therapeutic agents' toxicity) is a systemic syndrome but often only one organ is examined. CryoGrid-PIXUL, integrated with either TRIzol or PK buffer RNA isolation protocols, yielded similar RNA profiles in a multiorgan (brain, heart, kidney and liver) mouse model of sepsis. Thus, RNA isolation using the CryoGrid-PIXUL system combined with the PK buffer offers an inexpensive user-friendly workflow to study transcriptional responses in tissues in health and disease as well as in therapeutic interventions.

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dCas9 fusion to computer-designed PRC2 inhibitor reveals functional TATA box in distal promoter region

Cited by 21 publications

References 87 publications

Stress-induced reversible cell-cycle arrest requires PRC2/PRC1-mediated control of mitophagy in Drosophila germline stem cells and human iPSCs

Stress-induced reversible cell-cycle arrest requires PRC2/PRC1-mediated control of mitophagy in Drosophila germline stem cells and human iPSCs

Artificial Intelligence in Cancer Research: Trends, Challenges and Future Directions

CryoGrid-PIXUL-RNA: High throughput RNA isolation platform for tissue transcript analysis

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