Raman spectroscopy of brain and skin tissue in a minipig model of Huntington's disease.

We applied Raman spectroscopy to brain and skin tissues from a minipig model of Huntington's disease. Differences were observed between measured spectra of tissues with and without Huntington's disease, for both brain tissue and skin tissue. There are linked to changes in the chemical composition between tissue types. Using machine learning we correctly classified 96% of test spectra as diseased or wild type, indicating that the test would have a similar accuracy when used as a diagnostic tool for the disease. This suggests the technique has great potential in the rapid and accurate diagnosis of Huntington's and other neurodegenerative diseases in a clinical setting.

Detection of acquired radioresistance in breast cancer cell lines using Raman spectroscopy and machine learning.

Radioresistance-a living cell's response to, and development of resistance to ionising radiation-can lead to radiotherapy failure and/or tumour recurrence. We used Raman spectroscopy and machine learning to characterise biochemical changes that occur in acquired radioresistance for breast cancer cells. We were able to distinguish between wild-type and acquired radioresistant cells by changes in chemical composition using Raman spectroscopy and machine learning with 100% accuracy. In studying both hormone receptor positive and negative cells, we found similar changes in chemical composition that occur with the development of acquired radioresistance; these radioresistant cells contained less lipids and proteins compared to their parental counterparts. As well as characterising acquired radioresistance in vitro, this approach has the potential to be translated into a clinical setting, to look for Raman signals of radioresistance in tumours or biopsies; that would lead to tailored clinical treatments.

An Engineered E.†coli Strain for Direct in Vivo Fluorination.

Selectively fluorinated compounds are found frequently in pharmaceutical and agrochemical products where currently 25-30 % of optimised compounds emerge from development containing at least one fluorine atom. There are many methods for the site-specific introduction of fluorine, but all are chemical and they often use environmentally challenging reagents. Biochemical processes for C-F bond formation are attractive, but they are extremely rare. In this work, the fluorinase enzyme, originally identified from the actinomycete bacterium Streptomyces cattleya, is engineered into Escherichia coli in such a manner that the organism is able to produce 5'-fluorodeoxyadenosine (5'-FDA) from S-adenosyl-l-methionine (SAM) and fluoride in live E. coli cells. Success required the introduction of a SAM transporter and deletion of the endogenous fluoride efflux capacity in order to generate an E. coli host that has the potential for future engineering of more elaborate fluorometabolites.