Research

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Synthetic Biology underpins advances in the bioeconomy

Biological systems - including the simplest cells - exhibit a broad range of functions to thrive in their environment. Research in the Imperial College Centre for Synthetic Biology is focused on the possibility of engineering the underlying biochemical processes to solve many of the challenges facing society, from healthcare to sustainable energy. In particular, we model, analyse, design and build biological and biochemical systems in living cells and/or in cell extracts, both exploring and enhancing the engineering potential of biology. 

As part of our research we develop novel methods to accelerate the celebrated Design-Build-Test-Learn synthetic biology cycle. As such research in the Centre for Synthetic Biology highly multi- and interdisciplinary covering computational modelling and machine learning approaches; automated platform development and genetic circuit engineering ; multi-cellular and multi-organismal interactions, including gene drive and genome engineering; metabolic engineering; in vitro/cell-free synthetic biology; engineered phages and directed evolution; and biomimetics, biomaterials and biological engineering.

Publications

Citation

BibTex format

@article{Papathanos:2018:10.1089/crispr.2017.0012,
author = {Papathanos, PA and Windbichler, N},
doi = {10.1089/crispr.2017.0012},
journal = {The Crispr Journal},
pages = {88--98},
title = {Redkmer: An assembly-free pipeline for the identification of abundant and specific X-chromosome target sequences for X-shredding by CRISPR endonucleases},
url = {http://dx.doi.org/10.1089/crispr.2017.0012},
volume = {1},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - CRISPR-based synthetic sex ratio distorters, which operate by shredding the X-chromosome during male meiosis, are promising tools for the area-wide control of harmful insect pest or disease vector species. X-shredders have been proposed as tools to suppress insect populations by biasing the sex ratio of the wild population toward males, thus reducing its natural reproductive potential. However, to build synthetic X-shredders based on CRISPR, the selection of gRNA targets, in the form of high-copy sequence repeats on the X chromosome of a given species, is difficult, since such repeats are not accurately resolved in genome assemblies and cannot be assigned to chromosomes with confidence. We have therefore developed the redkmer computational pipeline, designed to identify short and highly abundant sequence elements occurring uniquely on the X chromosome. Redkmer was designed to use as input minimally processed whole genome sequence data from males and females. We tested redkmer with short- and long-read whole genome sequence data of Anopheles gambiae, the major vector of human malaria, in which the X-shredding paradigm was originally developed. Redkmer established long reads as chromosomal proxies with excellent correlation to the genome assembly and used them to rank X-candidate kmers for their level of X-specificity and abundance. Among these, a high-confidence set of 25-mers was identified, many belonging to previously known X-chromosome repeats of Anopheles gambiae, including the ribosomal gene array and the selfish elements harbored within it. Data from a control strain, in which these repeats are shared with the Y chromosome, confirmed the elimination of these kmers during filtering. Finally, we show that redkmer output can be linked directly to gRNA selection and off-target prediction. In addition, the output of redkmer, including the prediction of chromosomal origin of single-molecule long reads and chromosome specific kmers, could also be used for the charact
AU  - Papathanos,PA
AU  - Windbichler,N
DO  - 10.1089/crispr.2017.0012
EP  - 98
PY  - 2018///
SN  - 2573-1599
SP  - 88
TI  - Redkmer: An assembly-free pipeline for the identification of abundant and specific X-chromosome target sequences for X-shredding by CRISPR endonucleases
T2  - The Crispr Journal
UR  - http://dx.doi.org/10.1089/crispr.2017.0012
UR  - https://www.ncbi.nlm.nih.gov/pubmed/30627701
UR  - http://hdl.handle.net/10044/1/66867
VL  - 1
ER  -
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