Most of the members of this group are from the Statistics Section and Biomaths research group of the Department of Mathematics. Below you can find a list of research areas that members of this group are currently working on and/or would like to work on by applying their developed mathematical and statistical methods.

Research areas

Research areas



BibTex format

author = {Wills, QF and Mellado-Gomez, E and Nolan, R and Warner, D and Sharma, E and Broxholme, J and Wright, B and Lockstone, H and James, W and Lynch, M and Gonzales, M and West, J and Leyrat, A and Padilla-Parra, S and Filippi, S and Holmes, C and Moore, MD and Bowden, R},
doi = {10.1186/s12864-016-3445-0},
journal = {BMC Genomics},
title = {The nature and nurture of cell heterogeneity: accounting for macrophage gene-environment interactions with single-cell RNA-Seq.},
url = {},
volume = {18},
year = {2017}

RIS format (EndNote, RefMan)

AB - BACKGROUND: Single-cell RNA-Seq can be a valuable and unbiased tool to dissect cellular heterogeneity, despite the transcriptome's limitations in describing higher functional phenotypes and protein events. Perhaps the most important shortfall with transcriptomic 'snapshots' of cell populations is that they risk being descriptive, only cataloging heterogeneity at one point in time, and without microenvironmental context. Studying the genetic ('nature') and environmental ('nurture') modifiers of heterogeneity, and how cell population dynamics unfold over time in response to these modifiers is key when studying highly plastic cells such as macrophages. RESULTS: We introduce the programmable Polaris™ microfluidic lab-on-chip for single-cell sequencing, which performs live-cell imaging while controlling for the culture microenvironment of each cell. Using gene-edited macrophages we demonstrate how previously unappreciated knockout effects of SAMHD1, such as an altered oxidative stress response, have a large paracrine signaling component. Furthermore, we demonstrate single-cell pathway enrichments for cell cycle arrest and APOBEC3G degradation, both associated with the oxidative stress response and altered proteostasis. Interestingly, SAMHD1 and APOBEC3G are both HIV-1 inhibitors ('restriction factors'), with no known co-regulation. CONCLUSION: As single-cell methods continue to mature, so will the ability to move beyond simple 'snapshots' of cell populations towards studying the determinants of population dynamics. By combining single-cell culture, live-cell imaging, and single-cell sequencing, we have demonstrated the ability to study cell phenotypes and microenvironmental influences. It's these microenvironmental components - ignored by standard single-cell workflows - that likely determine how macrophages, for example, react to inflammation and form treatment resistant HIV reservoirs.
AU - Wills,QF
AU - Mellado-Gomez,E
AU - Nolan,R
AU - Warner,D
AU - Sharma,E
AU - Broxholme,J
AU - Wright,B
AU - Lockstone,H
AU - James,W
AU - Lynch,M
AU - Gonzales,M
AU - West,J
AU - Leyrat,A
AU - Padilla-Parra,S
AU - Filippi,S
AU - Holmes,C
AU - Moore,MD
AU - Bowden,R
DO - 10.1186/s12864-016-3445-0
PY - 2017///
SN - 1471-2164
TI - The nature and nurture of cell heterogeneity: accounting for macrophage gene-environment interactions with single-cell RNA-Seq.
T2 - BMC Genomics
UR -
UR -
UR -
VL - 18
ER -