Boston, MA, USA. A stem cell can simply remain a stem cell or adopt a specialized identity and contribute to the construction of the organs and other features that omprise the human bofy. The conventional view in biology emphasizes the existence of instructions that direct a cell's linear progress along prescribed signaling pathways. A less simplistic idea argues for the collective behavior of multiple genes in a network.

 

Ultimately, cell differentiation has just a few endpoints, similar to the way a marble on a hilltop can travel down a nearly infinite number of downward paths, only to arrive in the same valley. Sidebar, Introduction

 

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Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Hannah H. Chang, Martin Hemberg, Mauricio Barahona, Donald E. Ingber & Sui Huang. Nature 453(7194) 427-562. doi: 10.1038 / nature06965 [ Download Supp Data PDF — description below ]

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The findings, published in the journal Nature, give a glimpse into how that collective behavior works, and show that cell populations maintain a built-in variability that nature can harness for change under the right conditions [Ref. 1]. The findings also help explain why the process of differentiating stem cells into specific lineages in the laboratory has been highly inefficient.

 

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Sui Huang, MD, PhD, a Visiting Associate Professor in the Vascular Biology Program at Children's Hospital Boston (Huang is also on the University of Calgary faculty), led a team that included Hannah Chang, an MD/PhD student in the Children's Vascular Biology Program, and other colleagues.

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To examine the underlying process of cell differentiation, the researchers examined how blood stem cells "decide" to become white blood cell progenitors or red blood cell progenitors.

 

Many Paths to the Same Attractor State.

 

They began by examining populations of seemingly identical blood stem cells, and found that a cell marker of stemness, a protein called Sca-1, was actually present in highly variable amounts from cell to cell  —  in fact, they found a 1,000-fold range. One might think that low Sca-1 cells are simply those cells that have spontaneously differentiated. However, when Huang and Chang divided the cells expressing low, medium and high levels of Sca-1 and cultured them, each descendent cell population recapitulated the same broad range of Sca-1 levels over nine days or more, regardless of what levels they started with.

 

"We then asked, are these cells also biologically different?" says Huang, the paper's senior author. "And it turned out they were dramatically different in differentiation."

Yet, in both experiments, all three groups of cells retained characteristics of stem cells.

 

Huang and Chang then looked at the proteins GATA1 and PU.1, transcription factors that normally favor differentiation into red and white blood cells, respectively.

But most important, the differences in Sca-1, GATA1 and PU.1 levels across the three cell groups became less pronounced over time, as did the variability in the cells' propensity to differentiate, suggesting that the differences are transient.

 

Stem Cell Attractors.

 

Together, the findings make the case that a slow fluctuation or cycling of gene activity tends to maintain cells in a stable state, while also priming them to differentiate when conditions are right.

 

"Even if cells are officially genetically identical and belong to the same clone, individual members of that population are quite different at any given time," says Huang. "This heterogeneity has usually been seen as random 'measurement noise,' and, more recently, as 'gene expression noise.' But it turns out to be very important, and is the basis for stem cells' multipotency — their ability to differentiate into multiple lineages."

 

"Nature has created an incredibly elegant and simple way of creating variability, and maintaining it at a steady level, enabling cells to respond to changes in their environment in a systematic, controlled way," adds Chang, first author on the paper.

 

Practically speaking, the work suggests that stem cell biologists may need to change their approach to differentiating stem cells in the laboratory for therapeutic applications.

 

"So far the process has been highly inefficient — only 10 to 50 percent of cells respond to the hormone or whatever is given to make them differentiate," Huang says. "That is because of the cells' inherent heterogeneity. People have been finding more and more sophisticated stimulator cocktails, but we could make the process more efficient by harnessing the heterogeneity and identifying cells that are already highly poised to differentiate."

 

 

Chang has already done follow-up experiments showing that stem cell differentiation can be made dramatically more efficient by choosing the right subpopulation of stem cells and stimulating them promptly, while they are most apt to differentiate. "I'm not doing anything complicated — just using what nature already has," she says.

 

But the findings also challenge biologists to change how they think about biological processes.

The work supports the idea of biological systems moving toward a stable "attractor state," a concept borrowed from physics. In this case, blood stem cells tend to remain blood stem cells, yet they experience inherent fluctuations in gene activity and protein production that can sometimes be enough to tip the balance and cause them to fall into other attractor states — namely, red or white blood cell progenitors.

 

Specific growth factors can tip the balance, but these factors are part of an overall landscape that guides cells toward different destinies. A marble going downhill will eventually end up in a valley, but which valley it falls into depends on the shape of the landscape.

 

"Growth or differentiation factors merely increases the probability that a cell will grow or differentiate," says Donald Ingber, MD, PhD, a co-author on the paper who, with Huang, served as Chang's mentor on the project.

 

"Cell differentiation is an ensemble property, a collective behavior, inherent in the system's architecture and set of regulatory interactions."

 

A previous study by Huang [Ref. 2] established, for the first time, that a given cell can exhibit a very different pattern of gene activity from its neighbor, taking a very different path through the landscape, yet end up in the same valley. He and his colleagues exposed precursor cells to two completely different drugs (DMSO and retinoic acid) and closely monitored the cells' gene expression. Both groups of cells eventually differentiated to become neutrophils (a type of white blood cell), but the molecular paths they took and their patterns of gene expression were completely different until day seven, when they finally converged.

 

The landscape analogy and collective "decision-making" are concepts unfamiliar to biologists, who have tended to focus on single genes acting in linear pathways. This made the work initially difficult to publish, notes Huang. "It's hard for biologists to move from thinking about single pathways to thinking about a landscape, which is the mathematical manifestation of the entirety of all the possible pathways," he says. "A single pathway is not a good way to understand a whole process. Our goal has been to understand the driving force behind it."

 

This study was funded by the US Air Force Office of Scientific Research (AFOSR), the US National Institutes of Health (NIH), the Presidential Scholarship, the Ashford Fellowship of Harvard University, and the US Army Research Office (ARO).

 

[1] Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Hannah H. Chang, Martin Hemberg, Mauricio Barahona, Donald E. Ingber & Sui Huang. Nature 453(7194) 427-562. doi: 10.1038 / nature06965

[ Download Supplemental Data PDF ]

Editor's Summary: Pluripotency: Cell-to-cell variations. Even in clonal populations of cells, there is significant phenotypic variation from cell to cell. This could reflect the 'noise' inherent in gene expression: or the various cell states could represent stable phenotypic variants. Chang et al. analysed the behaviour of an 'outlier' in clonal populations of mouse haematoipoietic stem cells that had very high expressions of the stem cell marker Sca-1 and found that outliers possessed distinct transcriptomes. Though the transcriptomes eventually reverted back to that of the median cells, while they differed they could drive the cells to express characteristics of distinct cell fates. Thus clonal heterogeneity of gene expression may not be due to noise in the expression of individual genes, but rather is a manifestation of metastable states of a slowly fluctuating transcriptome. These fluctuations may govern the reversible, stochastic priming of multipotent progenitor cells in cell fate decision.

First paragraph. Phenotypic cell-to-cell variability within clonal populations may be a manifestation of 'gene expression noise', or it may reflect stable phenotypic variants7. Such 'non-genetic cell individuality' can arise from the slow fluctuations of protein levels in mammalian cells. These fluctuations produce persistent cell individuality, thereby rendering a clonal population heterogeneous. However, it remains unknown whether this heterogeneity may account for the stochasticity of cell fate decisions in stem cells. Here we show that in clonal populations of mouse haematopoietic progenitor cells, spontaneous 'outlier' cells with either extremely high or low expression levels of the stem cell marker Sca-1 (also known as Ly6a) reconstitute the parental distribution of Sca-1 but do so only after more than one week. This slow relaxation is described by a gaussian mixture model that incorporates noise-driven transitions between discrete subpopulations, suggesting hidden multi-stability within one cell type. Despite clonality, the Sca-1 outliers had distinct transcriptomes. Although their unique gene expression profiles eventually reverted to that of the median cells, revealing an attractor state, they lasted long enough to confer a greatly different proclivity for choosing either the erythroid or the myeloid lineage. Preference in lineage choice was associated with increased expression of lineage-specific transcription factors, such as a >200-fold increase in Gata1 among the erythroid-prone cells, or a >15-fold increased PU.1 (Sfpi1) expression among myeloid-prone cells. Thus, clonal heterogeneity of gene expression level is not due to independent noise in the expression of individual genes, but reflects metastable states of a slowly fluctuating transcriptome that is distinct in individual cells and may govern the reversible, stochastic priming of multipotent progenitor cells in cell fate decision.

Supplementary Information file sections:

S1. Supplementary Methods: This section contains additional experimental methods not included in the "Methods" section at the end of the main text.

S2. Supplementary Discussion: This section contains additional discussions regarding two questions: (1) What other factors could contribute to the observed level of heterogeneity in Sca-1 within one clonal population (Fig. 1 in the main text)? (2) What biological process may drive the (re)generation of the parental Sca-1 distribution from the three sorted, more homogeneous population fractions? These discussions were originally part of the main text but have been restructured for the Supplementary Information due to considerations for text length.

S3. Supplementary Figures and Legends: This section contains experimental supplementary figures along with their legends (Supplementary Figures 1-12).

S4. Supplementary Table: This section contains one experimental supplementary table along with its legend (Supplementary Table 1).

S5. Theoretical Methods: This is an extended section outlying the theoretical methods employed in the paper, including relevant theoretical supplementary figures (Supplementary Figures 13-18) and tables (Supplementary Table 2-4).

S6. Supplementary Notes: This section contains the references for the entire Supplementary Information. The numbering of references here is independent of that for the main text.zzzzz[ Download Supplemental Data PDF ]

[2] Cell Fates as High-Dimensional Attractor States of a Complex Gene Regulatory Network. Sui Huang, Gabriel Eichler, Yaneer Bar-Yam, and Donald E. Ingber. Physical Review Letters 94, 128701 (2005). doi: 10.1103 / PhysRevLett.94.128701

Abstract. Cells in multicellular organisms switch between distinct cell fates, such as proliferation or differentiation into specialized cell types. Genome-wide gene regulatory networks govern this behavior. Theoretical studies of complex networks suggest that they can exhibit ordered (stable) dynamics, raising the possibility that cell fates may represent high-dimensional attractor states. We used gene expression profiling to show that trajectories of neutrophil differentiation converge to a common state from different directions of a 2773-dimensional gene expression state space, providing the first experimental evidence for a high-dimensional stable attractor that represents a distinct cellular phenotype.

 

 

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