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CBCB faculty Mihai Pop is mentioned in the Wall Street Journal for sequencing UMD's mascot

Fri Mar 18, 2016

The article can be found here: http://www.wsj.com/article_email/does-your-mascot-have-a-dna-sequence-sc...

A youtube video has been posted that shows Dr. Pop working with UMD freshmen to sequence the genome of the University's mascot, the diamondback terrapin: https://www.youtube.com/watch?v=oBoV5j-oQes&feature=youtu.be

CBCB scientists Mahfuza Sharmin, Hector Corrada Bravo, and Sridhar Hannenhalli publish a paper in BMC Cancer on hypomethylated blocks in colon cancer

Fri Feb 19, 2016
Lead author and CBCB doctoral student Mahfuza Sharmin, and CBCB faculty Hector Corrada Bravo and Sridhar Hannenhalli, have published a paper titled "Distinct genomic and epigenomic features demarcate hypomethylated blocks in colon cancer" on February 11, 2016 in the journal BMC Cancer. In this paper, they found that the classical promoter epigenomic mark - H3K4me3, is highly enriched at Hypomethylated Block (HMB) boundaries, as are insulator protein CTCF bound sites. HMB boundaries harbor distinct combinations of transcription factor (TF) motifs. A Random Forest machine learning model based on TF motifs can accurately distinguish boundaries not only from regions inside and outside HMBs, but surprisingly, from active promoters as well. Interestingly, the distinguishing TFs and their interacting proteins are involved in chromatin modification. Finally, HMB boundaries significantly coincide with the boundaries of Topologically Associating Domains of the chromatin. Their analyses suggest that the overall architecture of HMBs is guided by pre-existing chromatin architecture, and are associated with aberrant activity of promoter-like sequences at the boundary.

"Distinct genomic and epigenomic features demarcate hypomethylated blocks in colon cancer" article: https://bmccancer.biomedcentral.com/articles/10.1186/s12885-016-2128-1

CBCB scientists Senthil Kumar and Sridhar Hannenhalli publish a paper in PLOS Computational Biology on the dynamical model of CRISPR-mediated prokaryote-phage coevolution

Wed Feb 17, 2016
Lead author and CBCB doctoral student Senthil Kumar, CBCB faculty Sridhar Hannenhalli, and Dr. Plotkin of U Penn have published a paper titled “Regulated CRISPR Modules Exploit a Dual Defense Strategy of Restriction and Abortive Infection in a Model of Prokaryote-Phage Coevolution” on November 6, 2015 in the journal PLOS Computational Biology. In this paper, they develop and analyze a dynamical model of CRISPR-mediated prokaryote-phage coevolution that incorporates classical CRISPR kinetics along with the recently discovered infection-induced activation and autoimmunity side effects. Their results indicate that except in limited growth rates, regulated CRISPRs exploit both autoimmunity and target restriction and can therefore be considered a hybrid class that leverages both restriction and suicide mechanisms to limit phage infection.

"Regulated CRISPR Modules Exploit a Dual Defense Strategy of Restriction and Abortive Infection in a Model of Prokaryote-Phage Coevolution” article: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.10...

CBCB faculty Eytan Ruppin’s group publishes a paper in Nature Communications on Non-Alcoholic Fatty Liver Disease

Mon Feb 08, 2016

CBCB faculty Eytan Ruppin’s group has published a paper titled “Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease” on February 3, 2016 in the journal Nature Communications.

For further information, please see: https://www.cs.umd.edu/article/2016/02/researchers-steno-center-eytan-ru...

“Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease” article: http://www.nature.com/ncomms/2016/160203/ncomms9994/full/ncomms9994.html

Jeremy Selengut on Thompson's highly cited researcher list

Thu Jan 14, 2016
Dr. Jeremy Selengut has been selected by Thompson Reuters as one of the most highly cited researchers in the field of Microbiology. The "Highly Cited Researchers 2015" list includes scientists ranking among the 1% most cited in their field.

CBCB faculty Eytan Ruppin’s group co-authors a paper in Nature on the diversion of aspartate in ASS1-deficient tumours, a study led by Ayelet Erez from the Weizmann Institute

Thu Nov 12, 2015

Keren Yizhak from Eytan Ruppin’s group co-authored a paper titled “Diversion of aspartate in ASS1-deficient tumours fosters de novo pyrimidine synthesis”, published in Nature on November 11, 2015.

Cancer cells hijack and remodel existing metabolic pathways for their benefit. Argininosuccinate synthase (ASS1) is a urea cycle enzyme that is essential in the conversion of nitrogen from ammonia and aspartate to urea. A decrease in nitrogen flux through ASS1 in the liver causes the urea cycle disorder, citrullinaemia. In contrast to the well-studied consequences of loss of ASS1 activity on ureagenesis, the purpose of its somatic silencing in multiple cancers is largely unknown.

In this study, the authors show that decreased activity of ASS1 in cancers supports proliferation by facilitating pyrimidine synthesis via CAD (carbamoyl-phosphate synthase 2, aspartate transcarbamylase, and dihydroorotase complex) activation. Decreasing CAD activity by blocking citrin, the mTOR signalling, or pyrimidine synthesis decreases proliferation and thus may serve as a therapeutic strategy in multiple cancers where ASS1is downregulated. Their results demonstrate that ASS1downregulation is a novel mechanism supporting cancerous proliferation, and that ASS1 downregulation provides a metabolic link between the urea cycle enzymes and pyrimidine synthesis.

“Diversion of aspartate in ASS1-deficient tumours fosters de novo pyrimidine synthesis” article: http://www.nature.com/nature/journal/vaop/ncurrent/pdf/nature15529.pdf

CBCB scientists Eytan Ruppin and Rotem Katzir publish a paper in the Proceedings of the National Academy of Sciences (PNAS) on the quantitative identification of cancer SDLs in a model-based mechanistic manner

Wed Oct 14, 2015

CBCB faculty Eytan Ruppin and CBCB doctoral student Rotem Katzir, along with collaborators, published a paper titled “Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival” on September 29, 2015 in the journal Proceedings of the National Academy of Sciences (PNAS).

Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly.

In this paper, a network-level computational modeling framework is introduced that quantitatively predicts human SDLs in metabolism. The approach presented can be used to identify SDLs in species and cell types in which “omics” data necessary for data-driven identification are missing. As expected, the predicted SDLs are less frequently active in tumors to avoid lethality. Cancer tumors with more and stronger SDLs have smaller tumor size and lead to increased patient survival. Beyond facilitating the development of novel anticancer therapies, model-based identification of metabolic SDLs can be used to model pathogenic bacteria and provide leads to new antibiotic targets.

“Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival” article: http://www.pnas.org/content/112/39/12217.full

CBCB scientists Matthew Oberhardt and Eytan Ruppin publish a paper in Nature Communications on predicting new organism-media pairings

Tue Oct 13, 2015

Lead author and CBCB postdoctoral associate Matthew Oberhardt and CBCB faculty Eytan Ruppin, along with collaborators, have published a paper titled “Harnessing the landscape of microbial culture media to predict new organism-media pairings” on October 13, 2015 in the journal Nature Communications.

Culturing microorganisms is a critical step in understanding and utilizing microbial life. In this paper, Dr. Oberhardt, Dr. Ruppin, and collaborators map the landscape of existing culture media by extracting natural-language media recipes into a Known Media Database (KOMODO).

They leverage KOMODO to predict new organism–media pairings using a transitivity property (74% growth in new in vitro experiments) and a phylogeny-based collaborative filtering tool (83% growth in new in vitro experiments and stronger growth on predicted well-scored versus poorly scored media). These resources are integrated into a web-based platform that predicts media given an organism’s 16S rDNA sequence, facilitating future cultivation efforts.

“Harnessing the landscape of microbial culture media to predict new organism–media pairings” article: http://www.nature.com/ncomms/2015/151013/ncomms9493/full/ncomms9493.html

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