SUNrises on the International Plant Nucleus Consortium: SEB Salzburg 2012

The nuclear periphery is a dynamic, structured environment, whose precise functions are essential for global processes-from nuclear, to cellular, to organismal. Its main components-the nuclear envelope (NE) with inner and outer nuclear membranes (INM and ONM), nuclear pore complexes (NPC), associated cytoskeletal and nucleoskeletal components as well as chromatin are conserved across eukaryotes (Fig. 1). In metazoans in particular, the structure and functions of nuclear periphery components are intensely researched partly because of their involvement in various human diseases. While far less is known about these in plants, the last few years have seen a significant increase in research activity in this area. Plant biologists are not only catching up with the animal field, but recent findings are pushing our advances in this field globally. In recognition of this developing field, the Annual Society of Experimental Biology Meeting in Salzburg kindly hosted a session co-organized by Katja Graumann and David E. Evans (Oxford Brookes University) highlighting new insights into plant nuclear envelope proteins and their interactions. This session brought together leading researchers with expertise in topics such as epigenetics, meiosis, nuclear pore structure and functions, nucleoskeleton and nuclear envelope composition. An open and friendly exchange of ideas was fundamental to the success of the meeting, which resulted in founding the International Plant Nucleus Consortium. This review highlights new developments in plant nuclear envelope research presented at the conference and their importance for the wider understanding of metazoan, yeast and plant nuclear envelope functions and properties.

A combinatorial TIR1/AFB-Aux/IAA co-receptor system for differential sensing of auxin

The plant hormone auxin regulates virtually every aspect of plant growth and development. Auxin acts by binding the F-box protein transport inhibitor response 1 (TIR1) and promotes the degradation of the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) transcriptional repressors. Here we show that efficient auxin binding requires assembly of an auxin co-receptor complex consisting of TIR1 and an Aux/IAA protein. Heterologous experiments in yeast and quantitative IAA binding assays using purified proteins showed that different combinations of TIR1 and Aux/IAA proteins form co-receptor complexes with a wide range of auxin-binding affinities. Auxin affinity seems to be largely determined by the Aux/IAA. As there are 6 TIR1/AUXIN SIGNALING F-BOX proteins (AFBs) and 29 Aux/IAA proteins in Arabidopsis thaliana, combinatorial interactions may result in many co-receptors with distinct auxin-sensing properties. We also demonstrate that the AFB5-Aux/IAA co-receptor selectively binds the auxinic herbicide picloram. This co-receptor system broadens the effective concentration range of the hormone and may contribute to the complexity of auxin response.

The auxin signalling network translates dynamic input into robust patterning at the shoot apex

We provide a comprehensive expression map of the different genes (TIR1/AFBs, ARFs and Aux/IAAs) involved in the signalling pathway regulating gene transcription in response to auxin in the shoot apical meristem (SAM).

We demonstrate a relatively simple structure of this pathway using a high-throughput yeast two-hybrid approach to obtain the Aux/IAA-ARF full interactome.

The topology of the signalling network was used to construct a model for auxin signalling and to predict a role for the spatial regulation of auxin signalling in patterning of the SAM.

We used a new sensor to monitor the input in the auxin signalling pathway and to confirm the model prediction, thus demonstrating that auxin signalling is essential to create robust patterns at the SAM.

The plant hormone auxin is a key morphogenetic signal involved in the control of cell identity throughout development. A striking example of auxin action is at the shoot apical meristem (SAM), a population of stem cells generating the aerial parts of the plant. Organ positioning and patterning depends on local accumulations of auxin in the SAM, generated by polar transport of auxin (Vernoux et al, 2010). However, it is still unclear how auxin is distributed at cell resolution in tissues and how the hormone is sensed in space and time during development. A complex ensemble of 29 Aux/IAAs and 23 ARFs is central to the regulation of gene transcription in response to auxin (for review, see Leyser, 2006; Guilfoyle and Hagen, 2007; Chapman and Estelle, 2009). Protein–protein interactions govern the properties of this transduction pathway (Del Bianco and Kepinski, 2011). Limited interaction studies suggest that, in the absence of auxin, the Aux/IAA repressors form heterodimers with the ARF transcription factors, preventing them from regulating target genes. In the presence of auxin, the Aux/IAA proteins are targeted to the proteasome by an SCF E3 ubiquitin ligase complex (Chapman and Estelle, 2009; Leyser, 2006). In this process, auxin promotes the interaction between Aux/IAA proteins and the TIR1 F-box of the SCF complex (or its AFB homologues) that acts as an auxin co-receptor (Dharmasiri et al, 2005a, 2005b; Kepinski and Leyser, 2005; Tan et al, 2007). The auxin-induced degradation of Aux/IAAs would then release ARFs to regulate transcription of their target genes. This includes activation of most of the Aux/IAA genes themselves, thus establishing a negative feedback loop (Guilfoyle and Hagen, 2007). Although this general scenario provides a framework for understanding gene regulation by auxin, the underlying protein–protein network remains to be fully characterized.

In this paper, we combined experimental and theoretical analyses to understand how this pathway contributes to sensing auxin in space and time (Figure 1). We first analysed the expression patterns of the ARFs, Aux/IAAs and TIR1/AFBs genes in the SAM. Our results demonstrate a general tendency for most of the 25 ARFs and Aux/IAAs detected in the SAM: a differential expression with low levels at the centre of the meristem (where the stem cells are located) and high levels at the periphery of the meristem (where organ initiation takes place). We also observed a similar differential expression for TIR1/AFB co-receptors. To understand the functional significance of the distribution of ARFs and Aux/IAAs in the SAM, we next investigated the global structure of the Aux/IAA-ARF network using a high-throughput yeast two-hybrid approach and uncover a rather simple topology that relies on three basic generic features: (i) Aux/IAA proteins interact with themselves, (ii) Aux/IAA proteins interact with ARF activators and (iii) ARF repressors have no or very limited interactions with other proteins in the network.

The results of our interaction analysis suggest a model for the Aux/IAA-ARF signalling pathway in the SAM, where transcriptional activation by ARF activators would be negatively regulated by two independent systems, one involving the ARF repressors, the other the Aux/IAAs. The presence of auxin would remove the inhibitory action of Aux/IAAs, but leave the ARF repressors to compete with ARF activators for promoter-binding sites. To explore the regulatory properties of this signalling network, we developed a mathematical model to describe the transcriptional output as a function of the signalling input that is the combinatorial effect of auxin concentration and of its perception. We then used the model and a simplified view of the meristem (where the same population of Aux/IAAs and ARFs exhibit a low expression at the centre and a high expression in the peripheral zone) for investigating the role of auxin signalling in SAM function. We show that in the model, for a given ARF activator-to-repressor ratio, the gene induction capacity increases with the absolute levels of ARF proteins. We thus predict that the differential expression of the ARFs generates differences in auxin sensitivities between the centre (low sensitivity) and the periphery (high sensitivity), and that the expression of TIR1/AFB participates to this regulation (prediction 1). We also use the model to analyse the transcriptional response to rapidly changing auxin concentrations. By simulating situations equivalent either to the centre or the periphery of our simplified representation of the SAM, we predict that the signalling pathway buffers its response to the auxin input via the balance between ARF activators and repressors, in turn generated by their differential spatial distributions (prediction 2).

To test the predictions from the model experimentally, we needed to assess both the input (auxin level and/or perception) and the output (target gene induction) of the signalling cascade. For measuring the transcriptional output, the widely used DR5 reporter is perfectly adapted (Figure 5) (Ulmasov et al, 1997; Sabatini et al, 1999; Benkova et al, 2003; Heisler et al, 2005). For assaying pathway input, we designed DII-VENUS, a novel auxin signalling sensor that comprises a constitutively expressed fusion of the auxin-binding domain (termed domain II or DII) (Dreher et al, 2006; Tan et al, 2007) of an IAA to a fast-maturating variant of YFP, VENUS (Figure 5). The degradation patterns from DII-VENUS indicate a high auxin signalling input both in flower primordia and at the centre of the SAM. This is in contrast to the organ-specific expression pattern of DR5::VENUS (Figure 5). These results indicate that the signalling pathway limits gene activation in response to auxin at the meristem centre and confirm the differential sensitivity to auxin between the centre and the periphery (prediction 1). We further confirmed the buffering capacities of the signalling pathway (prediction 2) by carrying out live imaging experiments to monitor DII-VENUS and DR5::VENUS expression in real time (Figure 5). This analysis reveals the presence of important temporal variations of DII-VENUS fluorescence, while DR5::VENUS does not show such global variations. Our approach thus provides evidence that the Aux/IAA-ARF pathway has a key role in patterning in the SAM, alongside the auxin transport system. Our results illustrate how the tight spatio-temporal regulation of both the distribution of a morphogenetic signal and the activity of the downstream signalling pathway provides robustness to a dynamic developmental process.

A comprehensive expression and interaction map of auxin signalling factors in the Arabidopsis shoot apical meristem is constructed and used to derive a mathematical model of auxin signalling, from which key predictions are experimentally confirmed.

The plant hormone auxin is thought to provide positional information for patterning during development. It is still unclear, however, precisely how auxin is distributed across tissues and how the hormone is sensed in space and time. The control of gene expression in response to auxin involves a complex network of over 50 potentially interacting transcriptional activators and repressors, the auxin response factors (ARFs) and Aux/IAAs. Here, we perform a large-scale analysis of the Aux/IAA-ARF pathway in the shoot apex of Arabidopsis, where dynamic auxin-based patterning controls organogenesis. A comprehensive expression map and full interactome uncovered an unexpectedly simple distribution and structure of this pathway in the shoot apex. A mathematical model of the Aux/IAA-ARF network predicted a strong buffering capacity along with spatial differences in auxin sensitivity. We then tested and confirmed these predictions using a novel auxin signalling sensor that reports input into the signalling pathway, in conjunction with the published DR5 transcriptional output reporter. Our results provide evidence that the auxin signalling network is essential to create robust patterns at the shoot apex.

Outcomes following infant listing for cardiac transplantation: the impact of strategies introduced to counteract limited donor availability

BACKGROUND

Survival following cardiac transplantation in infancy has improved substantially. There is a growing shortage of donors, the impact of which may be offset by increase in ABO-incompatible transplants, size-mismatching and mechanical support. The authors reviewed their results and outcomes following infant listing for cardiac transplantation over 22 years.

METHODS

Children <12 months at time of listing for cardiac transplant in 1987-2008 were identified using the departmental cardiopulmonary transplant database. Details were obtained from databases and hospital medical records and subdivided into two eras, 1987-1997 and 1998-2008.

RESULTS

In 1987-2008, 49 infants were listed, and 28 (57%) underwent cardiac transplantation (12 in 1987-1997 and 16 in 1998-2008). 15 patients (31%) died on the waiting list, 6 patients were delisted (5 of these because of recovery of cardiac function). There was a decrease in suitable donor offers from a mean of 36 per year in 1996-2000 to 11 per year in 2001-2006 (p=0.008). In 1998-2008, nine listed infants were on mechanical support; there were seven ABO-incompatible transplants, and all transplants were size-mismatched with donors on average 2.7 times heavier than recipients. Waiting times decreased from median 83 to 47 days. Six (21%) of the transplanted patients died, the majority in 1987-1997 and perioperatively.

CONCLUSIONS

There has been a fall in suitable donors for infant cardiac transplants over time despite increased demand. However, the introduction of size-mismatching, ABO-incompatible transplants and mechanical support has enabled an increase in the number of transplants to be carried out despite this fall in donor numbers. Outcomes following transplantation have improved over time.

Evaluation of NT-proBNP to predict outcomes in advanced heart failure

AIMS

To determine which factors predict outcomes in a group of patients with advanced heart failure, and in particular if NT-proBNP provides additional clinical and prognostic information to other haemodynamic and biochemical data.

METHODS AND RESULTS

Ninety-one patients were studied who were being evaluated for heart transplantation, with 166 assessments. The patients had advanced heart failure as determined by median cardiac index of 2.0 l/min/m(2), left ventricular end-diastolic diameter of 7.0 mm and levels of NT-proBNP of 2473 pg/ml. Median follow-up time was 359 days. Clinicians were blinded to NT-proBNP levels. NT-proBNP significantly correlated with cardiac index (R = -0.44, p < 0.001), right atrial pressure (R = 0.40, p < 0.001), pulmonary arterial wedge pressure (R = 0.38, p < 0.001) and albumin (R = -0.52, p < 0.001), and total bilirubin with right atrial pressure (R = 0.59, p < 0.001). Cardiac index was the most important independent predictor of outcome (p = 0.0001), although bilirubin (p = 0.001) and NT-proBNP (p < 0.05) were also significant. In patients with a 50% increase in NT-proBNP, 64% had adverse outcomes, whereas those in whom levels were stable, 22% had adverse outcomes (p < 0.05).

CONCLUSION

Cardiac index is the primary independent predictor of outcome in advanced heart failure when haemodynamic deterioration is evident. In situations where invasive haemodynamics are not available, total bilirubin (reflecting hepatic congestion) and NT-proBNP (related to haemodynamics) also provide important prognostic information.

Multiple Subtypes of HER-2/Neu-Positive Metastatic Breast Cancer

Background: Using IHC or FISH to select patients for trastuzumab-based therapy, only half of HER2-positive patients show evidence of response. In vitro data implicate HER2:HER3 heterodimers and p95HER2 (p95), the truncated 95-kilodalton C-terminal fragment of HER-2 lacking the trastuzumab binding site, as mediators of resistance to trastuzumab at the receptor level. We have previously reported that central FISH-positive patients with low HER2 protein expression by VeraTag had significantly reduced response to trastuzumab compared to patients who had FISH-positive tumors with high HER2 protein expression (Lipton, SABCS 2008). Adding quantitative measurements of HER3 and p95, we offer evidence for the existence of multiple sub-types of HER2-positive tumors that respond differently to trastuzumab.Methods: Using the VeraTag assay, quantitative protein measurements of HER2, HER3, and p95 were made in FFPE specimens from a cohort of patients with metastatic breast cancer (MBC) and correlated with time to progression (TTP) and overall survival (OS) following treatment with first-line trastuzumab using Kaplan-Meier (KM) and Cox proportional hazards regression analyses.Results: Measurements of HER2 (H2T), HER3 (H3T) and p95 were made in FFPE tumor samples from 95 patients treated with first-line trastuzumab for metastatic breast cancer. Within the group that overexpressed HER2 by the VeraTag Assay (n=60), a group with highly overexpressed HER2 (n=15) had shorter TTP and OS than those that had moderate HER2 overexpression (median TTP 4.6 vs. 12 mos, HR=2.1; p=0.011; median OS 29 vs. 40 mos, HR=2.0; p=0.047). Within the subgroup with moderate H2T overexpression (n=45), bivariate Cox analyses demonstrated that p95 and H3T were independent predictors of TTP (p95 HR=2.1; p=0.031; H3T HR=3.5; p=0.0037). For OS, p95 was significant and H3T showed a strong trend (p95 HR=2.5; p=0.025, H3T HR=2.2; p=0.089). Univariate KM analysis with the p95+ and H3T+ groups combined, gives the results in the table below. These data suggest that HER2-positive breast cancer patients can be classified into at least 4 sub-groups with different outcomes following trastuzumab treatment.Conclusions: These data suggest the existence of multiple subgroups of HER2-positive patients expressing varying HER2, p95, and HER3 levels that experience different clinical outcomes following treatment with trastuzumab. Furthermore, the association of HER3 and p95 overexpression with poor response to trastuzumab in otherwise HER2-positive tumors suggests possible treatment approaches with combinations of targeted therapies.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2030.

Minimal response levels for visual reinforcement audiometry in infants: Niveles mínimos de respuesta en la audiometría por reforzamiento visual en niños

The aim of this study was to determine normative values for minimal response levels (MRLs) for normal-hearing young infants using insert earphone visual reinforcement audiometry (VRA). The subjects were 46 normally developing infants aged between 33 and 50 weeks who had hearing sensitivity assumed to be within normal limits and no evidence of middle ear dysfunction. VRA was carried out using insert earphones with warble tone stimuli, generated from an AC33 audiometer and calibrated to ISO 389-2 for insert earphones in adults. The frequencies assessed were 500 Hz, 1 kHz, 2 kHz and 4 kHz. In total, 102 MRLs were obtained, with an approximately equal number of MRLs per frequency. Mean MRLs for 500 Hz, 1 kHz, 2 kHz and 4kHz were 16 dB HL, 13 dB HL, 7 dB HL and 6 dB HL, respectively. Standard deviations were close to 6 dB for all frequencies. Mean MRLs at the lower frequencies were significantly greater than MRLs at the two higher frequencies. MRLs did not vary significantly with age. The results obtained from this study suggest significant infant adult differences when testing hearing using VRA with insert earphones, particularly at lower frequencies. Possible reasons for this and the clinical use of these normative values are discussed.