Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles

Short cell cycle duration is a phenotype of human epidermal stem cells

BACKGROUND

A traditional view is that stem cells (SCs) divide slowly. Meanwhile, both embryonic and pluripotent SCs display a shorter cell cycle duration (CCD) in comparison to more committed progenitors (CPs).

METHODS

We examined the in vitro proliferation and cycling behavior of somatic adult human cells using live cell imaging of passage zero keratinocytes and single-cell RNA sequencing.

RESULTS

We found two populations of keratinocytes: those with short CCD and protracted near exponential growth, and those with long CCD and terminal differentiation. Applying the ergodic principle, the comparative numbers of cycling cells in S phase in an enriched population of SCs confirmed a shorter CCD than CPs. Further, analysis of single-cell RNA sequencing of cycling adult human keratinocyte SCs and CPs indicated a shortening of both G1 and G2M phases in the SC.

CONCLUSIONS

Contrary to the pervasive paradigm, SCs progress through cell cycle more quickly than more differentiated dividing CPs. Thus, somatic human adult keratinocyte SCs may divide infrequently, but divide rapidly when they divide. Additionally, it was found that SC-like proliferation persisted in vitro.

Whole cell reconstructions of Leishmania mexicana through the cell cycle

The unicellular parasite Leishmania has a precisely defined cell architecture that is inherited by each subsequent generation, requiring a highly coordinated pattern of duplication and segregation of organelles and cytoskeletal structures. A framework of nuclear division and morphological changes is known from light microscopy, yet this has limited resolution and the intrinsic organisation of organelles within the cell body and their manner of duplication and inheritance is unknown. Using volume electron microscopy approaches, we have produced three-dimensional reconstructions of different promastigote cell cycle stages to give a spatial and quantitative overview of organelle positioning, division and inheritance. The first morphological indications seen in our dataset that a new cell cycle had begun were the assembly of a new flagellum, the duplication of the contractile vacuole and the increase in volume of the nucleus and kinetoplast. We showed that the progression of the cytokinesis furrow created a specific pattern of membrane indentations, while our analysis of sub-pellicular microtubule organisation indicated that there is likely a preferred site of new microtubule insertion. The daughter cells retained these indentations in their cell body for a period post-abscission. By comparing cultured and sand fly derived promastigotes, we found an increase in the number and overall volume of lipid droplets in the promastigotes from the sand fly, reflecting a change in their metabolism to ensure transmissibility to the mammalian host. Our insights into the cell cycle mechanics of Leishmania will support future molecular cell biology analyses of these parasites.

Basic Methods of Cell Cycle Analysis

Cellular growth and the preparation of cells for division between two successive cell divisions is called the cell cycle. The cell cycle is divided into several phases; the length of these particular cell cycle phases is an important characteristic of cell life. The progression of cells through these phases is a highly orchestrated process governed by endogenous and exogenous factors. For the elucidation of the role of these factors, including pathological aspects, various methods have been developed. Among these methods, those focused on the analysis of the duration of distinct cell cycle phases play important role. The main aim of this review is to guide the readers through the basic methods of the determination of cell cycle phases and estimation of their length, with a focus on the effectiveness and reproducibility of the described methods.

An Analysis of Transcriptomic Burden Identifies Biological Progression Roadmaps for Hematological Malignancies and Solid Tumors

Biological paths of tumor progression are difficult to predict without time-series data. Using median shift and abacus transformation in the analysis of RNA sequencing data sets, natural patient stratifications were found based on their transcriptomic burden (TcB). Using gene-behavior analysis, TcB groups were evaluated further to discover biological courses of tumor progression. We found that solid tumors and hematological malignancies (n = 4179) share conserved biological patterns, and biological network complexity decreases at increasing TcB levels. An analysis of gene expression datasets including pediatric leukemia patients revealed TcB patterns with biological directionality and survival implications. A prospective interventional study with PI3K targeted therapy in canine lymphomas proved that directional biological responses are dynamic. To conclude, TcB-enriched biological mechanisms detected the existence of biological trajectories within tumors. Using this prognostic informative novel informatics method, which can be applied to tumor transcriptomes and progressive diseases inspires the design of progression-specific therapeutic approaches.

Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology

Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.

Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology

Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.

Cellular thermogenesis compensates environmental temperature fluctuations for maintaining intracellular temperature

Temperature governs states and dynamics of all biological molecules, and several cellular processes are often heat sources and/or sinks. Technical achievement of intracellular thermometry enables us to measure intracellular temperature, and it can offer novel perspectives in biology and medicine. However, little is known that changes of intracellular temperature throughout the cell-cycle and the manner of which cells regulates their thermogenesis in response to fluctuation of the environmental temperature. Here, cell-cycle-dependent changes of intracellular temperature were reconstructed from the snapshots of cell population at single-cell resolution using ergodic analysis for asynchronously cultured HeLa cells expressing a genetically encoded thermometry. Intracellular temperature is highest at G1 phase, and it gradually decreases along cell-cycle progression and increases abruptly during mitosis. Cells easily heated up are harder to cool down and vice versa, especially at G1/S phases. Together, intracellular thermogenesis depends on cell-cycle phases and it maintains intracellular temperature through compensating environmental temperature fluctuations.

The palette of techniques for cell cycle analysis

The cell division cycle is the generational period of cellular growth and propagation. Cell cycle progression needs to be highly regulated to preserve genomic fidelity while increasing cell number. In multicellular organisms, the cell cycle must also coordinate with cell fate specification during development and tissue homeostasis. Altered cell cycle dynamics play a central role also in a number of pathophysiological processes. Thus, extensive effort has been made to define the biochemical machineries that execute the cell cycle and their regulation, as well as implementing more sensitive and accurate cell cycle measurements. Here, we review the available techniques for cell cycle analysis, revisiting the assumptions behind conventional population-based measurements and discussing new tools to better address cell cycle heterogeneity in the single-cell era. We weigh the strengths, weaknesses, and trade-offs of methods designed to measure temporal aspects of the cell cycle. Finally, we discuss emerging techniques for capturing cell cycle speed at single-cell resolution in live animals.

ImageJ for Partially and Fully Automated Analysis of Trypanosome Micrographs

Trypanosomes and related parasites such as Leishmania are unicellular parasites with a precise internal structure. This makes light microscopy a powerful tool for interrogating their biology-whether considering advance techniques for visualizing the precise localization of proteins within the cell or simply measuring parasite cell shape. Methods to partially or fully automate analysis and interpretation are extremely powerful and provide easier access to microscope images as a source of quantitative data. This chapter provides an introduction to these methods using ImageJ/FIJI, free and open source software for scientific image analysis. It provides an overview of how ImageJ handles images and introduces the ImageJ macro/scripting language for automated images, starting at a basic level and assuming no previous programming/scripting experience. It then outlines three methods using ImageJ for automated analysis of trypanosome micrographs: Semiautomated cropping and setting image contrast for presentation, automated analysis of cell properties from a light micrograph field of view, and example semiautomated tools for quantitative analysis of protein localization. These are not presented as strict methods, but are instead described in detail with the intention of furnishing the reader with the ability to "hack" the scripts for their own needs or write their own scripts for partially and fully automated quantitation of trypanosomes from light micrographs. Most of the methods described here are transferrable to other types of microscope image and other cell types.

Coordination of the Cell Cycle in Trypanosomes

Trypanosomes have complex life cycles within which there are both proliferative and differentiation cell divisions. The coordination of the cell cycle to achieve these different divisions is critical for the parasite to infect both host and vector. From studying the regulation of the proliferative cell cycle of the Trypanosoma brucei procyclic life cycle stage, three subcycles emerge that control the duplication and segregation of ( a) the nucleus, ( b) the kinetoplast, and ( c) a set of cytoskeletal structures. We discuss how the clear dependency relationships within these subcycles, and the potential for cross talk between them, are likely required for overall cell cycle coordination. Finally, we look at the implications this interdependence has for proliferative and differentiation divisions through the T. brucei life cycle and in related parasitic trypanosomatid species.

Non-equivalence in old- and new-flagellum daughter cells of a proliferative division in Trypanosoma brucei

Differentiation of Trypanosoma brucei, a flagellated protozoan parasite, between life cycle stages typically occurs through an asymmetric cell division process, producing two morphologically distinct daughter cells. Conversely, proliferative cell divisions produce two daughter cells, which look similar but are not identical. To examine in detail differences between the daughter cells of a proliferative division of procyclic T. brucei we used the recently identified constituents of the flagella connector. These segregate asymmetrically during cytokinesis allowing the new‐flagellum and the old‐flagellum daughters to be distinguished. We discovered that there are distinct morphological differences between the two daughters, with the new‐flagellum daughter in particular re‐modelling rapidly and extensively in early G1. This re‐modelling process involves an increase in cell body, flagellum and flagellum attachment zone length and is accompanied by architectural changes to the anterior cell end. The old‐flagellum daughter undergoes a different G1 re‐modelling, however, despite this there was no difference in G1 duration of their respective cell cycles. This work demonstrates that the two daughters of a proliferative division of T. brucei are non‐equivalent and enables more refined morphological analysis of mutant phenotypes. We suggest all proliferative divisions in T. brucei and related organisms will involve non‐equivalence.

In Vitro Cellular Division of Trypanosoma abeli Reveals Two Pathways for Organelle Replication

Since the observation of the great pleomorphism of fish trypanosomes, in vitro culture has become an important tool to support taxonomic studies investigating the biology of cultured parasites, such as their structure, growth dynamics, and cellular cycle. Relative to their biology, ex vivo and in vitro studies have shown that these parasites, during the multiplication process, duplicate and segregate the kinetoplast before nucleus replication and division. However, the inverse sequence (the nucleus divides before the kinetoplast) has only been documented for a species of marine fish trypanosomes on a single occasion. Now, this previously rare event was observed in Trypanosoma abeli, a freshwater fish trypanosome. Specifically, from 376 cultured parasites in the multiplication process, we determined the sequence of organelle division for 111 forms; 39% exhibited nucleus duplication prior to kinetoplast replication. Thus, our results suggest that nucleus division before the kinetoplast may not represent an accidental or erroneous event occurring in the main pathway of parasite reproduction, but instead could be a species-specific process of cell biology in trypanosomes, such as previously noticed for Leishmania. This "alternative" pathway for organelle replication is a new field to be explored concerning the biology of marine and freshwater fish trypanosomes.

Making sense of snapshot data: ergodic principle for clonal cell populations

Population growth is often ignored when quantifying gene expression levels across clonal cell populations. We develop a framework for obtaining the molecule number distributions in an exponentially growing cell population taking into account its age structure. In the presence of generation time variability, the average acquired across a population snapshot does not obey the average of a dividing cell over time, apparently contradicting ergodicity between single cells and the population. Instead, we show that the variation observed across snapshots with known cell age is captured by cell histories, a single-cell measure obtained from tracking an arbitrary cell of the population back to the ancestor from which it originated. The correspondence between cells of known age in a population with their histories represents an ergodic principle that provides a new interpretation of population snapshot data. We illustrate the principle using analytical solutions of stochastic gene expression models in cell populations with arbitrary generation time distributions. We further elucidate that the principle breaks down for biochemical reactions that are under selection, such as the expression of genes conveying antibiotic resistance, which gives rise to an experimental criterion with which to probe selection on gene expression fluctuations.

Shape, form, function and Leishmania pathogenicity: from textbook descriptions to biological understanding

The shape and form of protozoan parasites are inextricably linked to their pathogenicity. The evolutionary pressure associated with establishing and maintaining an infection and transmission to vector or host has shaped parasite morphology. However, there is not a 'one size fits all' morphological solution to these different pressures, and parasites exhibit a range of different morphologies, reflecting the diversity of their complex life cycles. In this review, we will focus on the shape and form of Leishmania spp., a group of very successful protozoan parasites that cause a range of diseases from self-healing cutaneous leishmaniasis to visceral leishmaniasis, which is fatal if left untreated.

Glycogen synthase kinase 3β inhibition enhances Notch1 recycling

The Notch signaling pathway is essential throughout development and remains active into adulthood, where it performs a critical role in tissue homeostasis. The fact that defects in signaling can lead to malignancy illustrates the need to control Notch activity tightly. GSK3β is an established regulator of the Notch signaling pathway, although its mechanism of action remains unclear. Given the emerging role for GSK3β in receptor trafficking, we tested the idea that GSK3β controls signaling by regulating Notch transport. Consistent with published reports, we find that GSK3β inhibition enhances Notch1 signaling activity. Immunolocalization analysis reveals that Notch1 localization within a tubulovesicular compartment is altered when GSK3β activity is disrupted. We also find that receptor cell surface levels increase following acute GSK3β inhibition. This is followed by elevated Notch intra-cellular domain (NICD) production and a corresponding increase in signaling activity. Moreover, Notch transport assays reveal that receptor recycling rates increase when GSK3β activity is inhibited. Collectively, results presented here support a model where GSK3β regulates signaling by controlling postendocytic transport of Notch1. Given that GSK3β activity is suppressed following stimulation by multiple signal transduction pathways, our findings also suggest that cells can modulate Notch1 activity in response to extracellular signals by mobilizing Notch1 from endosomal stores.

Let's get fISSical: fast in silico synchronization as a new tool for cell division cycle analysis

Cell cycle progression is a question of fundamental biological interest. The coordinated duplication and segregation of all cellular structures and organelles is however an extremely complex process, and one which remains only partially understood even in the most intensively researched model organisms. Trypanosomes are in an unusual position in this respect - they are both outstanding model systems for fundamental questions in eukaryotic cell biology, and pathogens that are the causative agents of three of the neglected tropical diseases. As a failure to successfully complete cell division will be deleterious or lethal, analysis of the cell division cycle is of relevance both to basic biology and drug design efforts. Cell division cycle analysis is however experimentally challenging, as the analysis of phenotypes associated with it remains hypothesis-driven and therefore biased. Current methods of analysis are extremely labour-intensive, and cell synchronization remains difficult and unreliable. Consequently, there exists a need - both in basic and applied trypanosome biology - for a global, unbiased, standardized and high-throughput analysis of cell division cycle progression. In this review, the requirements - both practical and computational - for such a system are considered and compared with existing techniques for cell cycle analysis.

Proteomic analysis of cell cycle progression in asynchronous cultures, including mitotic subphases, using PRIMMUS

The temporal regulation of protein abundance and post-translational modifications is a key feature of cell division. Recently, we analysed gene expression and protein abundance changes during interphase under minimally perturbed conditions (Ly et al., 2014, 2015). Here, we show that by using specific intracellular immunolabelling protocols, FACS separation of interphase and mitotic cells, including mitotic subphases, can be combined with proteomic analysis by mass spectrometry. Using this PRIMMUS (PRoteomic analysis of Intracellular iMMUnolabelled cell Subsets) approach, we now compare protein abundance and phosphorylation changes in interphase and mitotic fractions from asynchronously growing human cells. We identify a set of 115 phosphorylation sites increased during G2, termed 'early risers'. This set includes phosphorylation of S738 on TPX2, which we show is important for TPX2 function and mitotic progression. Further, we use PRIMMUS to provide the first a proteome-wide analysis of protein abundance remodeling between prophase, prometaphase and anaphase.

On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models

Cyclic processes, in particular the cell cycle, are of great importance in cell biology. Continued improvement in cell population analysis methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell omics made mathematical methods based on ergodic principles a powerful tool in studying these processes. In this paper, we establish the relationship between cell cycle analysis with ergodic principles and age structured population models. To this end, we describe the progression of a single cell through the cell cycle by a stochastic differential equation on a one dimensional manifold in the high dimensional dataspace of cell cycle markers. Given the assumption that the cell population is in a steady state, we derive transformation rules which transform the number density on the manifold to the steady state number density of age structured population models. Our theory facilitates the study of cell cycle dependent processes including local molecular events, cell death and cell division from high dimensional "snapshot" data. Ergodic analysis can in general be applied to every process that exhibits a steady state distribution. By combining ergodic analysis with age structured population models we furthermore provide the theoretic basis for extensions of ergodic principles to distribution that deviate from their steady state.