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Wong, M.

Publications and source records attributed to Wong, M..

3 recordsLinked to original sources

Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data

We present Epiclomal, a probabilistic clustering method arising from a hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and impute missing values. Using synthetic and published single-cell CpG datasets we show that Epiclomal outperforms non-probabilistic methods and is able to handle the inherent missing data feature which dominates single-cell CpG genome sequences. Using a recently published single-cell 5mCpG sequencing method (PBAL), we show that Epiclomal discovers sub-clonal patterns of methylation in aneuploid tumour genomes, thus defining epiclones. We show that epiclones may transcend copy number determined clonal lineages, thus opening this important form of clonal analysis in cancer. Epiclomal is written in R and Python and is available at https://github.com/shahcompbio/Epiclomal.

genomics

The anthelmintic niclosamide is a potent TMEM16A antagonist that fully bronchodilates airways

There is an unmet need in severe asthma where approximately 40% of patients exhibit poor {beta}-agonist responsiveness, suffer daily symptoms and show frequent exacerbations. Antagonists of the Ca2+-activated-Cl- channel, TMEM16A, offers a new mechanism to bronchodilate airways and block the multiple contractiles operating in severe disease. To identify TMEM16A antagonists we screened a library of ~580,000 compounds. The anthelmintics niclosamide, nitazoxanide and related compounds were identified as potent TMEM16A antagonists that blocked airway smooth muscle depolarization and contraction. To evaluate whether TMEM16A antagonists resist use- and inflammatory-desensitization pathways limiting {beta}-agonist action, we tested their efficacy under harsh conditions using maximally contracted airways or airways pretreated with a cytokine cocktail. Stunningly, TMEM16A antagonists fully bronchodilated airways, while the {beta}-agonist isoproterenol showed only partial effects. Thus, antagonists of TMEM16A and repositioning of niclosamide and nitazoxanide represent an important additional treatment for patients with severe asthma and COPD that is poorly controlled with existing therapies. It is of note that drug repurposing has also attracted wide interest in niclosamide and nitazoxanide as a new treatment for cancer and infectious disease. For the first time we identify TMEM16A as a molecular target for these drugs and thus provide fresh insights into their mechanism for the treatment of these disorders in addition to respiratory disease.

physiology

SMELL-S and SMELL-R: olfactory tests not influenced by odor-specific insensitivity or prior olfactory experience

Smell dysfunction is a common and underdiagnosed medical condition that can have serious consequences. It is also an early biomarker of Alzheimers disease that precedes detectable memory loss. Clinical tests that evaluate the sense of smell face two major challenges. First, human sensitivity to individual odorants varies significantly, leading to potential misdiagnosis of people with an otherwise normal sense of smell but insensitivity to the test odorant. Second, prior familiarity with odor stimuli can bias smell test performance. We have developed new non- semantic tests for olfactory sensitivity (SMELL-S) and olfactory resolution (SMELL-R) that overcome these challenges by using mixtures of odorants that have unfamiliar smells. The tests can be self-administered with minimal training and showed high test-retest reliability. Because SMELL-S uses odor mixtures rather than a single molecule, odor-specific insensitivity is averaged out. Indeed, SMELL-S accurately distinguished people with normal and dysfunctional smell. SMELL-R is a discrimination test in which the difference between two stimulus mixtures can be altered stepwise. This is an advance over current discrimination tests, which ask subjects to discriminate monomolecular odorants whose difference cannot be objectively calculated. SMELL-R showed significantly less bias in scores between North American and Taiwanese subjects than conventional semantically-based smell tests that need to be adapted and translated to different populations. We predict that SMELL-S and SMELL-R will be broadly effective in diagnosing smell dysfunction, including that associated with the earliest signs of memory loss in Alzheimers disease.\n\nSignificance statementCurrently available smell testing methods can misdiagnose subjects with lack of prior experience or insensitivity to the odorants used in the test. This introduces a source of bias into clinical tests aimed at detecting patients with olfactory dysfunction. We have developed smell tests that use mixtures of 30 molecules that average out the variability in sensitivity to individual molecules. Because these mixtures have unfamiliar odors, and the tests are non-semantic, their use eliminates differences in test performance due to the familiarity with the smells or the words used to describe them. The SMELL-S and SMELL-R tests facilitate smell testing of diverse populations, without the need to adapt the test stimuli.

neuroscience