Biology subjects

Santos, L. C.

Publications and source records attributed to Santos, L. C..

5 recordsLinked to original sources

bioRxiv2021

Predicting Individual Cell Division Events from Single-Cell ERK and Akt Dynamics

Predictive determinants of stochastic single-cell fates have been elusive, even for the well-studied mammalian cell cycle. What drives proliferation decisions of single cells at any given time? We monitored single-cell dynamics of the ERK and Akt pathways, critical cell cycle progression hubs and anti-cancer drug targets, and paired them to division events in the same single cells using the non-transformed MCF10A epithelial line. Following growth factor treatment, in cells that divide both ERK and Akt activities are significantly higher within the S-G2 time window ([~]8.5-40 hours). Such differences were much smaller in the pre-S-phase, restriction point window which is traditionally associated with ERK and Akt activity dependence, suggesting unappreciated roles for ERK and Akt in S through G2. Machine learning algorithms show that simple metrics of central tendency in this time window are most predictive for subsequent cell division; median ERK and Akt activities classify individual division events with an AUC=0.76. Surprisingly, ERK dynamics alone predict division in individual cells with an AUC=0.74, suggesting Akt activity dynamics contribute little to the decision driving cell division in this context. We also find that ERK and Akt activities are less correlated with each other in cells that divide. Network reconstruction experiments demonstrated that this correlation behavior was likely not due to crosstalk, as ERK and Akt do not interact in this context, in contrast to other transformed cell types. Overall, our findings support roles for ERK and Akt activity throughout the cell cycle as opposed to just before the restriction point, and suggest ERK activity dynamics are substantially more important than Akt activity dynamics for driving cell division in this non-transformed context. Single cell imaging along with machine learning algorithms provide a better basis to understand cell cycle progression on the single cell level.

systems biology↗

bioRxiv2020

Cold-associated mammokines preserve adipocyte identity

Sympathetic activation during cold exposure increases adipocyte thermogenesis via expression of mitochondrial protein uncoupling protein 1 (UCP1)1. The propensity of adipocytes to express UCP1 is under a critical influence of the adipose microenvironment and varies among various fat depots2-7. Here we report that cold-induced adipocyte UCP1 expression in female mouse subcutaneous white adipose tissue (scWAT) is regulated by mammary gland ductal epithelial cells in the adipose niche. Single cell RNA-sequencing (scRNA-seq) show that under cold condition glandular alveolar and hormone-sensing luminal epithelium subtypes express transcripts that encode secretory factors involved in regulating adipocyte UCP1 expression. We term mammary duct secretory factors as "mammokines". Using whole-tissue immunofluorescence 3D visualization, we reveal previously undescribed sympathetic nerve-ductal points of contact and show that sympathetic nerve-activated mammary ducts limit adipocyte UCP1 expression via cold-induced mammokine production. Both in vivo and ex vivo ablation of mammary ductal epithelium enhances cold-induced scWAT adipocyte thermogenic gene program. The mammary duct network extends throughout most scWATs in female mice, which under cold exposure show markedly less UCP1 expression, fat oxidation, energy expenditure, and subcutaneous fat mass loss compared to male mice. These results show a previously uncharacterized role of sympathetic nerve-activated glandular epithelium in adipocyte thermogenesis. Overall, our findings suggest an evolutionary role of mammary duct luminal cells in defending glandular adiposity during cold exposure, highlight mammary gland epithelium as a highly active metabolic cell type, and implicate a broader role of mammokines in mammary gland physiology and systemic metabolism.

cell biology↗

bioRxiv2019

Real-time integration of cell death and proliferation kinetics at the single-cell and population-level using high-throughput live-cell imaging.

Quantifying cytostatic and cytotoxic outcomes are integral components of characterizing perturbagens used as research tools and/or in drug discovery pipelines. Furthermore, data-rich acquisition coupled with robust methods for analysis is required to properly assess the function and impact of these perturbagens. Here, we present a detailed and versatile method for Single-cell and Population-level Analyses using Real-time Kinetic Labeling (SPARKL). SPARKL integrates high-content live-cell imaging with automated detection and analysis of fluorescent reporters of cell death. We outline several examples of zero-handling, non-disruptive protocols for detailing cell death mechanisms and proliferation profiles. Additionally, we suggest several methods for mathematically analyzing these data to best utilize the collected kinetic data. Compared to traditional methods of detection and analysis, SPARKL is more sensitive, accurate, and high-throughput while substantially eliminating sample processing and providing richer data.

cell biology↗

bioRxiv2017

Origins of fractional control in regulated cell death

Individual cells in clonal populations often respond differently to environmental changes; for binary phenotypes, such as cell death, this can be measured as a fractional response. These types of responses have been attributed to cell-intrinsic stochastic processes and variable abundances of biochemical constituents, such as proteins, but the influence of organelles has yet to be determined. We use the response to TNF-related apoptosis inducing ligand (TRAIL) and a new statistical framework for determining parameter influence on cell-to-cell variability through the inference of variance explained, DEPICTIVE, to demonstrate that variable mitochondria abundance correlates with cell survival and determines the fractional cell death response. By quantitative data analysis and modeling we attribute this effect to variable effective concentrations at the mitochondria surface of the pro-apoptotic protein Bax. Further, we demonstrate that inhibitors of antiapoptotic Bcl-2 family proteins, used in cancer treatment, may increase the diversity of cellular responses, enhancing resistance to treatment.

systems biology↗

bioRxiv2017

An Integrated Mechanistic Model of Pan-Cancer Driver Pathways Predicts Stochastic Proliferation and Death

Most cancer cells harbor multiple drivers whose epistasis and interactions with expression context clouds drug sensitivity prediction. We constructed a mechanistic computational model that is context-tailored by omics data to capture regulation of stochastic proliferation and death by pan-cancer driver pathways. Simulations and experiments explore how the coordinated dynamics of RAF/MEK/ERK and PI-3K/AKT kinase activities in response to synergistic mitogen or drug combinations control cell fate in a specific cellular context. In this context, synergistic ERK and AKT inhibitor-induced death is likely mediated by BIM rather than BAD. AKT dynamics explain S-phase entry synergy between EGF and insulin, but stochastic ERK dynamics seem to drive cell-to-cell proliferation variability, which in simulations are predictable from pre-stimulus fluctuations in C-Raf/B-Raf levels. Simulations predict MEK alteration negligibly influences transformation, consistent with clinical data. Our model mechanistically interprets context-specific landscapes between driver pathways and cell fates, moving towards more rational cancer combination therapy.

systems biology↗