Fridolin Gross

Bub3 reads phosphorylated MELT repeats to promote spindle assembly checkpoint signaling

Regulation of macromolecular interactions by phosphorylation is crucial in signaling networks. In the spindle assembly checkpoint (SAC), which enables errorless chromosome segregation, phosphorylation promotes recruitment of SAC proteins to tensionless kinetochores. The SAC kinase Mps1 phosphorylates multiple Met-Glu-Leu-Thr (MELT) motifs on the kinetochore subunit Spc105/Knl1. The phosphorylated MELT motifs (MELTP) then promote recruitment of downstream signaling components. How MELTP motifs are recognized is unclear. In this study, we report that Bub3, a 7-bladed β-propeller, is the MELTP reader. It contains an exceptionally well-conserved interface that docks the MELTP sequence on the side of the β-propeller in a previously unknown binding mode. Mutations targeting the Bub3 interface prevent kinetochore recruitment of the SAC kinase Bub1. Crucially, they also cause a checkpoint defect, showing that recognition of phosphorylated targets by Bub3 is required for checkpoint signaling. Our data provide the first detailed mechanistic insight into how phosphorylation promotes recruitment of checkpoint proteins to kinetochores. DOI: http://dx.doi.org/10.7554/eLife.01030.001

Adaptation to the spindle checkpoint is regulated by the interplay between Cdc28/Clbs and PP2ACdc55

PP2ACdc55 dephosphorylates APC/CCdc20 to prevent anaphase, an effect that is counteracted by Cdc28/Clbs to allow for spindle checkpoint adaptation.

The Relevance of Irrelevance: Explanation in Systems Biology

In this chapter I investigate explanations in systems biology that rely on dynamical models of biological systems. I argue that accounts of mechanistic explanation cannot easily make sense of certain features of dynamical patterns if they restrict themselves to change-relating relationships. When investigating the use of such models, one has to distinguish between the concepts of causal or constitutive relevance on the one hand, and explanatorily relevant information on the other. I show that an important explanatory function of mathematical models consists in elucidating relationships of non-dependence. Notably, the fundamental concept of robustness can often be accounted for in this way, and not by invoking separate mechanistic features. Drawing on examples from the scientific literature, I suggest that an important aspect of explaining the behavior of a biological mechanism consists in elucidating how in the systemic context components are not, or only weakly, dependent on each other.

Transcription factor co-occupied regions in the murine genome constitute T-helper-cell subtype-specific enhancers

Transcription factors (TFs) regulate cell‐type‐specific gene expression programs by combinatorial binding to cis‐genomic elements, particularly enhancers, subsequently leading to the recruitment of cofactors, and the general transcriptional machinery to target genes. Using data integration of genome‐wide TF binding profiles, we defined regions with combinatorial binding of lineage‐specific master TFs (T‐BET, GATA3, and ROR‐γt) and STATs (STAT1 and STAT4, STAT6, and STAT3) in murine T helper (Th) 1, Th2, and Th17 cells, respectively. Stringently excluding promoter regions, we revealed precise genomic elements which were preferentially associated with the enhancer marks p300 and H3K4me1. Furthermore, closely adjacent TF co‐occupied regions constituted larger enhancer domains in the respective Th‐cell subset (177 in Th1, 141 in Th2, and 266 in Th17 cells) with characteristics of so‐called super‐enhancers. Importantly, 89% of these super‐enhancer regions were Th‐cell subtype‐specific. Genes associated with super‐enhancers, including relevant Th‐cell genes (such as Ifng in Th1, Il13 in Th2, and Il17a in Th17 cells), showed strong transcriptional activity. Altogether, the discovered catalog of enhancers provides information about crucial Th‐cell subtype‐specific regulatory hubs, which will be useful for revealing cell‐type‐specific gene regulation processes.

Identification of Novel Nuclear Factor of Activated T Cell (NFAT)-associated Proteins in T Cells.

Transcription factors of the nuclear factor of activated T cell (NFAT) family are essential for antigen-specific T cell activation and differentiation. Their cooperative DNA binding with other transcription factors, such as AP1 proteins (FOS, JUN, and JUNB), FOXP3, IRFs, and EGR1, dictates the gene regulatory action of NFATs. To identify as yet unknown interaction partners of NFAT, we purified biotin-tagged NFATc1/αA, NFATc1/βC, and NFATc2/C protein complexes and analyzed their components by stable isotope labeling by amino acids in cell culture-based mass spectrometry. We revealed more than 170 NFAT-associated proteins, half of which are involved in transcriptional regulation. Among them are many hitherto unknown interaction partners of NFATc1 and NFATc2 in T cells, such as Raptor, CHEK1, CREB1, RUNX1, SATB1, Ikaros, and Helios. The association of NFATc2 with several other transcription factors is DNA-dependent, indicating cooperative DNA binding. Moreover, our computational analysis discovered that binding motifs for RUNX and CREB1 are found preferentially in the direct vicinity of NFAT-binding motifs and in a distinct orientation to them. Furthermore, we provide evidence that mTOR and CHEK1 kinase activity influence NFATs transcriptional potency. Finally, our dataset of NFAT-associated proteins provides a good basis to further study NFATs diverse functions and how these are modulated due to the interplay of multiple interaction partners.

Adequate immune response ensured by binary IL-2 and graded CD25 expression in a murine transfer model

The IL-2/IL-2Ralpha (CD25) axis is of central importance for the interplay of effector and regulatory T cells. Nevertheless, the question how different antigen loads are translated into appropriate IL-2 production to ensure adequate responses against pathogens remains largely unexplored. Here we find that at single cell level, IL-2 is binary (digital) and CD25 is graded expressed whereas at population level both parameters show graded expression correlating with the antigen amount. Combining in vivo data with a mathematical model we demonstrate that only this binary IL-2 expression ensures a wide linear antigen response range for Teff and Treg cells under real spatiotemporal conditions. Furthermore, at low antigen concentrations binary IL-2 expression safeguards by its spatial distribution selective STAT5 activation only of closely adjacent Treg cells regardless of their antigen specificity. These data show that the mode of IL-2 secretion is critical to tailor the adaptive immune response to the antigen amount. DOI: http://dx.doi.org/10.7554/eLife.20616.001

Prospects and problems for standardizing model validation in systems biology

There are currently no widely shared criteria by which to assess the validity of computational models in systems biology. Here we discuss the feasibility and desirability of implementing validation standards for modeling. Having such a standard would facilitate journal review, interdisciplinary collaboration, model exchange, and be especially relevant for applications close to medical practice. However, even though the production of predictively valid models is considered a central goal, in practice modeling in systems biology employs a variety of model structures and model-building practices. These serve a variety of purposes, many of which are heuristic and do not seem to require strict validation criteria and may even be restricted by them. Moreover, given the current situation in systems biology, implementing a validation standard would face serious technical obstacles mostly due to the quality of available empirical data. We advocate a cautious approach to standardization. However even though rigorous standardization seems premature at this point, raising the issue helps us develop better insights into the practices of systems biology and the technical problems modelers face validating models. Further it allows us to identify certain technical validation issues which hold regardless of modeling context and purpose. Informal guidelines could in fact play a role in the field by helping modelers handle these.

Implications of alternative routes to APC/C inhibition by the mitotic checkpoint complex

The mitotic checkpoint (also called spindle assembly checkpoint) is a signaling pathway that ensures faithful chromosome segregation. Mitotic checkpoint proteins inhibit the anaphase-promoting complex (APC/C) and its activator Cdc20 to prevent precocious anaphase. Checkpoint signaling leads to a complex of APC/C, Cdc20, and checkpoint proteins, in which the APC/C is inactive. In principle, this final product of the mitotic checkpoint can be obtained via different pathways, whose relevance still needs to be fully ascertained experimentally. Here, we use mathematical models to compare the implications on checkpoint response of the possible pathways leading to APC/C inhibition. We identify a previously unrecognized funneling effect for Cdc20, which favors Cdc20 incorporation into the inhibitory complex and therefore promotes checkpoint activity. Furthermore, we find that the presence or absence of one specific assembly reaction determines whether the checkpoint remains functional at elevated levels of Cdc20, which can occur in cancer cells. Our results reveal the inhibitory logics behind checkpoint activity, predict checkpoint efficiency in perturbed situations, and could inform molecular strategies to treat malignancies that exhibit Cdc20 overexpression.

Towards a Methodology for Systems Biology

“In general there is a risk that mathematical modeling, very much like statistics, turns into a large toolbox that is unmanageable for all but the most experienced scholars because there is no manual that helps them to choose the right tool. The prospect for progress in this regard is difficult to evaluate. For philosophers to actually contribute, they must be well acquainted with modeling, data analysis, statistical methods, etc. which is usually not part of their education. For scientists, on the other hand, it often does not pay off to tackle such general methodological problems since the reward for this kind of work is comparatively small. I would predict, however, that in the long run the need for a more standardized methodology will become pressing, and then progress is more likely to occur.”