SUMMARY Ki67 staining is widely used as a proliferation indicator in the clinic, despite poor understanding of this protein’s function or dynamics. Here, we track Ki67 levels under endogenous control in single cells over time and find that Ki67 accumulation occurs only during S, G2, and M phases. Ki67 is degraded continuously in G1 and G0 phases, regardless of the cause of entry into G0/quiescence. Consequently, the level of Ki67 during G0 and G1 in individual cells is highly heterogeneous and depends on how long an individual cell has spent in G0. Thus, Ki67 is a graded rather than a binary marker both for cell-cycle progression and time since entry into quiescence.

Multicellular organisms use mitogens to regulate cell proliferation, but how fluctuating mitogenic signals are converted into proliferation-quiescence decisions is poorly understood. In this work, we combined live-cell imaging with temporally controlled perturbations to determine the time scale and mechanisms underlying this system in human cells. Contrary to the textbook model that cells sense mitogen availability only in the G1 cell cycle phase, we find that mitogenic signaling is temporally integrated throughout the entire mother cell cycle and that even a 1-hour lapse in mitogen signaling can influence cell proliferation more than 12 hours later. Protein translation rates serve as the integrator that proportionally converts mitogen history into corresponding levels of cyclin D in the G2 phase of the mother cell, which controls the proliferation-quiescence decision in daughter cells and thereby couples protein production with cell proliferation.

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.DOI: http://dx.doi.org/10.7554/eLife.08931.001

Assignment of cell types from single-cell RNA sequencing (scRNA-seq) data remains a time-consuming and error-prone process. Current packages for identity assignment use limited types of reference data and often have rigid data structure requirements. We developed the clustifyr R package to leverage several external data types, including gene expression profiles to assign likely cell types using data from scRNA-seq, bulk RNA-seq, microarray expression data, or signature gene lists. We benchmark various parameters of a correlation-based approach and implement gene list enrichment methods. clustifyr is a lightweight and effective cell-type assignment tool developed for compatibility with various scRNA-seq analysis workflows. clustifyr is publicly available at https://github.com/rnabioco/clustifyr

SUMMARY Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs) that converge on the nuclear factor κB (NF-κB) pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term “non-integrative” processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback.

Despite the increasing number of effective anti-cancer therapies, successful treatment is limited by the development of drug resistance. While the contribution of genetic factors to drug resistance is undeniable, little is known about how drug-sensitive cells first evade drug action to proliferate in drug. Here we track the responses of thousands of single melanoma cells to BRAF inhibitors and show that a subset of cells escapes drug via non-genetic mechanisms within the first three days of treatment. Cells that escape drug rely on ATF4 stress signalling to cycle periodically in drug, experience DNA replication defects leading to DNA damage, and yet out-proliferate other cells over extended treatment. Together, our work reveals just how rapidly melanoma cells can adapt to drug treatment, generating a mutagenesis-prone subpopulation that expands over time.

Toxin–antitoxin (TA) loci are widespread in bacteria including important pathogenic species. Recent studies suggest that TA systems play a key role in persister formation. However, the persistence phenotype shows only weak dependence on the number of TA systems, i.e. they are functionally redundant. We use a mathematical model to investigate the interaction of multiple TA systems in the switching between growth and persistence. We explore two scenarios: (i) TA systems are bistable and each TA system experiences its own noise and (ii) the noise in the level of common stress signal (e.g. (p)ppGpp) coordinates all TA systems simultaneously. We find that in the first scenario the exit from the persister state strongly depends on the number of TA systems. However in the second case, we could reproduce the weak dependence. The duration of the high (p)ppGpp state was found to be the key parameter for persistence. The (p)ppGpp-driven synchronized transition of all TA systems results in the redundancy.

Synthetic genetic circuits are programmed in living cells to perform predetermined cellular functions. However, designing higher-order genetic circuits for sophisticated cellular activities remains a substantial challenge. Here we program a genetic circuit that executes Pavlovianlike conditioning, an archetypical sequential-logic function, in Escherichia coli. The circuit design is first specified by the subfunctions that are necessary for the single simultaneous conditioning, and is further genetically implemented using four function modules. During this process, quantitative analysis is applied to the optimization of the modules and fine-tuning of the interconnections. Analogous to classical Pavlovian conditioning, the resultant circuit enables the cells to respond to a certain stimulus only after a conditioning process. We show that, although the conditioning is digital in single cells, a dynamically progressive conditioning process emerges at the population level. This circuit, together with its rational design strategy, is a key step towards the implementation of more sophisticated cellular computing.