Dimeric CRISPR RNA-guided FokI nucleases for highly specific genome editing

Monomeric CRISPR-Cas9 nucleases are widely used for targeted genome editing but can induce unwanted off-target mutations with high frequencies. Here we describe dimeric RNA-guided FokI Nucleases (RFNs) that recognize extended sequences and can edit endogenous genes with high efficiencies in human cells. The cleavage activity of an RFN depends strictly on the binding of two guide RNAs (gRNAs) to DNA with a defined spacing and orientation and therefore show improved specificities relative to wild-type Cas9 monomers. Importantly, direct comparisons show that RFNs guided by a single gRNA generally induce lower levels of unwanted mutations than matched monomeric Cas9 nickases. In addition, we describe a simple method for expressing multiple gRNAs bearing any 5′ end nucleotide, which gives dimeric RFNs a broad targeting range. RFNs combine the ease of RNA-based targeting with the specificity enhancement inherent to dimerization and are likely to be useful in applications that require highly precise genome editing

Secondary Structure, a Missing Component of Sequence- Based Minimotif Definitions

Minimotifs are short contiguous segments of proteins that have a known biological function. The hundreds of thousands of minimotifs discovered thus far are an important part of the theoretical understanding of the specificity of protein-protein interactions, posttranslational modifications, and signal transduction that occur in cells. However, a longstanding problem is that the different abstractions of the sequence definitions do not accurately capture the specificity, despite decades of effort by many labs. We present evidence that structure is an essential component of minimotif specificity, yet is not used in minimotif definitions. Our analysis of several known minimotifs as case studies, analysis of occurrences of minimotifs in structured and disordered regions of proteins, and review of the literature support a new model for minimotif definitions that includes sequence, structure, and function

Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs

<p>Abstract</p> <p>Background</p> <p>Assembling genomic sequences from a set of overlapping reads is one of the most fundamental problems in computational biology. Algorithms addressing the assembly problem fall into two broad categories <b>- </b>based on the data structures which they employ. The first class uses an overlap/string graph and the second type uses a de Bruijn graph. However with the recent advances in short read sequencing technology, de Bruijn graph based algorithms seem to play a vital role in practice. Efficient algorithms for building these massive de Bruijn graphs are very essential in large sequencing projects based on short reads. In an earlier work, an <it>O</it>(<it>n/p</it>) time parallel algorithm has been given for this problem. Here <it>n </it>is the size of the input and <it>p </it>is the number of processors. This algorithm enumerates all possible bi-directed edges which can overlap with a node and ends up generating Θ(<it>n</it>Σ) messages (Σ being the size of the alphabet).</p> <p>Results</p> <p>In this paper we present a Θ(<it>n/p</it>) time parallel algorithm with a communication complexity that is equal to that of parallel sorting and is not sensitive to Σ. The generality of our algorithm makes it very easy to extend it even to the out-of-core model and in this case it has an optimal I/O complexity of <inline-formula><m:math name="1471-2105-11-560-i1" xmlns:m="http://www.w3.org/1998/Math/MathML"><m:mrow><m:mo>Θ</m:mo><m:mo stretchy="false">(</m:mo><m:mfrac><m:mrow><m:mi>n</m:mi><m:mi>log</m:mi><m:mo stretchy="false">(</m:mo><m:mi>n</m:mi><m:mo>/</m:mo><m:mi>B</m:mi><m:mo stretchy="false">)</m:mo></m:mrow><m:mrow><m:mi>B</m:mi><m:mi>log</m:mi><m:mo stretchy="false">(</m:mo><m:mi>M</m:mi><m:mo>/</m:mo><m:mi>B</m:mi><m:mo stretchy="false">)</m:mo></m:mrow></m:mfrac><m:mo stretchy="false">)</m:mo></m:mrow></m:math></inline-formula> (<it>M </it>being the main memory size and <it>B </it>being the size of the disk block). We demonstrate the scalability of our parallel algorithm on a SGI/Altix computer. A comparison of our algorithm with the previous approaches reveals that our algorithm is faster <b>- </b>both asymptotically and practically. We demonstrate the scalability of our sequential out-of-core algorithm by comparing it with the algorithm used by VELVET to build the bi-directed de Bruijn graph. Our experiments reveal that our algorithm can build the graph with a constant amount of memory, which clearly outperforms VELVET. We also provide efficient algorithms for the bi-directed chain compaction problem.</p> <p>Conclusions</p> <p>The bi-directed de Bruijn graph is a fundamental data structure for any sequence assembly program based on Eulerian approach. Our algorithms for constructing Bi-directed de Bruijn graphs are efficient in parallel and out of core settings. These algorithms can be used in building large scale bi-directed de Bruijn graphs. Furthermore, our algorithms do not employ any all-to-all communications in a parallel setting and perform better than the prior algorithms. Finally our out-of-core algorithm is extremely memory efficient and can replace the existing graph construction algorithm in VELVET.</p

A tunable delivery platform to provide local chemotherapy for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most devastating and painful cancers. It is often highly resistant to therapy owing to inherent chemoresistance and the desmoplastic response that creates a barrier of fibrous tissue preventing transport of chemotherapeutics into the tumor. The growth of the tumor in pancreatic cancer often leads to invasion of other organs and partial or complete biliary obstruction, inducing intense pain for patients and necessitating tumor resection or repeated stenting. Here, we have developed a delivery device to provide enhanced palliative therapy for pancreatic cancer patients by providing high concentrations of chemotherapeutic compounds locally at the tumor site. This treatment could reduce the need for repeated procedures in advanced PDAC patients to debulk the tumor mass or stent the obstructed bile duct. To facilitate clinical translation, we created the device out of currently approved materials and drugs. We engineered an implantable poly(lactic-co-glycolic)-based biodegradable device that is able to linearly release high doses of chemotherapeutic drugs for up to 60 days. We created five patient-derived PDAC cell lines and tested their sensitivity to approved chemotherapeutic compounds. These in vitro experiments showed that paclitaxel was the most effective single agent across all cell lines. We compared the efficacy of systemic and local paclitaxel therapy on the patient-derived cell lines in an orthotopic xenograft model in mice (PDX). In this model, we found up to a 12-fold increase in suppression of tumor growth by local therapy in comparison to systemic administration and reduce retention into off-target organs. Herein, we highlight the efficacy of a local therapeutic approach to overcome PDAC chemoresistance and reduce the need for repeated interventions and biliary obstruction by preventing local tumor growth. Our results underscore the urgent need for an implantable drug-eluting platform to deliver cytotoxic agents directly within the tumor mass as a novel therapeutic strategy for patients with pancreatic cancer. Keywords: Pancreatic cancer; Chemoresistance; Local delivery; Patient-derived xenograft; Paclitaxel; Poly(lactic-co-glycolic acid)National Institutes of Health (U.S.) (Grant P30-CA14051

Secondary Structure, a Missing Component of Sequence-Based Minimotif Definitions

Minimotifs are short contiguous segments of proteins that have a known biological function. The hundreds of thousands of minimotifs discovered thus far are an important part of the theoretical understanding of the specificity of protein-protein interactions, posttranslational modifications, and signal transduction that occur in cells. However, a longstanding problem is that the different abstractions of the sequence definitions do not accurately capture the specificity, despite decades of effort by many labs. We present evidence that structure is an essential component of minimotif specificity, yet is not used in minimotif definitions. Our analysis of several known minimotifs as case studies, analysis of occurrences of minimotifs in structured and disordered regions of proteins, and review of the literature support a new model for minimotif definitions that includes sequence, structure, and function. © 2012 Sargeant et al

EWS-FLI1 Utilizes Divergent Chromatin Remodeling Mechanisms to Directly Activate or Repress Enhancer Elements in Ewing Sarcoma

SummaryThe aberrant transcription factor EWS-FLI1 drives Ewing sarcoma, but its molecular function is not completely understood. We find that EWS-FLI1 reprograms gene regulatory circuits in Ewing sarcoma by directly inducing or repressing enhancers. At GGAA repeat elements, which lack evolutionary conservation and regulatory potential in other cell types, EWS-FLI1 multimers induce chromatin opening and create de novo enhancers that physically interact with target promoters. Conversely, EWS-FLI1 inactivates conserved enhancers containing canonical ETS motifs by displacing wild-type ETS transcription factors. These divergent chromatin-remodeling patterns repress tumor suppressors and mesenchymal lineage regulators while activating oncogenes and potential therapeutic targets, such as the kinase VRK1. Our findings demonstrate how EWS-FLI1 establishes an oncogenic regulatory program governing both tumor survival and differentiation

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Information mining algorithms for bioinformatics problems

The simple world of algorithms can be applied to various problems all around us. With significant growth of bio-molecular sequence data in the last decade the need for algorithms to extract patterns and meaningful information from such data has been felt strongly. Multiple sequence alignment is an area in biology that has been studied extensively and many algorithms have been suggested in literature for the problem. Alignment of sequences, in order to determine regions of common descent, has also been an important area of research as it helps scientist discover the evolution of species. We employ sampling to improve the time as well as accuracy for multiple sequence alignment. ^ With growing publications in the area of bioinformatics in particular and science in general, it has become almost impossible to go through every single paper available on the internet on a research subject. Several researchers are putting in a lot of effort into finding new ways for document summarization so that the most relevant information in a document can be filtered out as a summary and can thus reduce the time and effort required to go through the entire document. ^ As the lower bound for computation is being met for various algorithms in bioinformatics, to further expedite the computing on large data sets, parallelization has become imperative. New multiprocessor architectures like the Cell Broadband Engine have the potential to do extensive calculations and act as mini-supercomputers. Other applications for these include onboard aircraft fault diagnosis and prognosis. ^ In this research work we aim to propose novel algorithms as well as implementations to address these problems in the field of bioinformatics.