ALBERT

Description: by Eva R. M. Joosten, Shihab A. Shamma, Christian Lorenzi, Peter Neri Sound waveforms convey information largely via amplitude modulations (AM). A large body of experimental evidence has provided support for a modulation (bandpass) filterbank. Details of this model have varied over time partly reflecting different experimental conditions and diverse datasets from distinct task strategies, contributing uncertainty to the bandwidth measurements and leaving important issues unresolved. We adopt here a solely data-driven measurement approach in which we first demonstrate how different models can be subsumed within a common ‘cascade’ framework, and then proceed to characterize the cascade via system identification analysis using a single stimulus/task specification and hence stable task rules largely unconstrained by any model or parameters. Observers were required to detect a brief change in level superimposed onto random level changes that served as AM noise; the relationship between trial-by-trial noisy fluctuations and corresponding human responses enables targeted identification of distinct cascade elements. The resulting measurements exhibit a dynamic complex picture in which human perception of auditory modulations appears adaptive in nature, evolving from an initial lowpass to bandpass modes (with broad tuning, Q∼1) following repeated stimulus exposure.

Description: by Bihai Shi, Cui Zhang, Caihuan Tian, Jin Wang, Quan Wang, Tengfei Xu, Yan Xu, Carolyn Ohno, Robert Sablowski, Marcus G. Heisler, Klaus Theres, Ying Wang, Yuling Jiao Shoot branching requires the establishment of new meristems harboring stem cells; this phenomenon raises questions about the precise regulation of meristematic fate. In seed plants, these new meristems initiate in leaf axils to enable lateral shoot branching. Using live-cell imaging of leaf axil cells, we show that the initiation of axillary meristems requires a meristematic cell population continuously expressing the meristem marker SHOOT MERISTEMLESS ( STM ). The maintenance of STM expression depends on the leaf axil auxin minimum. Ectopic expression of STM is insufficient to activate axillary buds formation from plants that have lost leaf axil STM expressing cells. This suggests that some cells undergo irreversible commitment to a developmental fate. In more mature leaves, REVOLUTA ( REV ) directly up-regulates STM expression in leaf axil meristematic cells, but not in differentiated cells, to establish axillary meristems. Cell type-specific binding of REV to the STM region correlates with epigenetic modifications. Our data favor a threshold model for axillary meristem initiation, in which low levels of STM maintain meristematic competence and high levels of STM lead to meristem initiation.

Description: by Lauren A. Richardson Our first ever Open Highlights explores recent Open Access research into the complex relationship between host and pathogen during the course of an infection, and the factors that determine its eventual outcome.

Description: by Cuncong Zhong, Anna Edlund, Youngik Yang, Jeffrey S. McLean, Shibu Yooseph Analyses of metagenome data (MG) and metatranscriptome data (MT) are often challenged by a paucity of complete reference genome sequences and the uneven/low sequencing depth of the constituent organisms in the microbial community, which respectively limit the power of reference-based alignment and de novo sequence assembly. These limitations make accurate protein family classification and abundance estimation challenging, which in turn hamper downstream analyses such as abundance profiling of metabolic pathways, identification of differentially encoded/expressed genes, and de novo reconstruction of complete gene and protein sequences from the protein family of interest. The profile hidden Markov model (HMM) framework enables the construction of very useful probabilistic models for protein families that allow for accurate modeling of position specific matches, insertions, and deletions. We present a novel homology detection algorithm that integrates banded Viterbi algorithm for profile HMM parsing with an iterative simultaneous alignment and assembly computational framework. The algorithm searches a given profile HMM of a protein family against a database of fragmentary MG/MT sequencing data and simultaneously assembles complete or near-complete gene and protein sequences of the protein family. The resulting program, HMM-GRASPx, demonstrates superior performance in aligning and assembling homologs when benchmarked on both simulated marine MG and real human saliva MG datasets. On real supragingival plaque and stool MG datasets that were generated from healthy individuals, HMM-GRASPx accurately estimates the abundances of the antimicrobial resistance (AMR) gene families and enables accurate characterization of the resistome profiles of these microbial communities. For real human oral microbiome MT datasets, using the HMM-GRASPx estimated transcript abundances significantly improves detection of differentially expressed (DE) genes. Finally, HMM-GRASPx was used to reconstruct comprehensive sets of complete or near-complete protein and nucleotide sequences for the query protein families. HMM-GRASPx is freely available online from http://sourceforge.net/projects/hmm-graspx.

Description: by Dazhe Meng, Manu Dubin, Pei Zhang, Edward J. Osborne, Oliver Stegle, Richard M. Clark, Magnus Nordborg The extent to which epigenetic variation affects complex traits in natural populations is not known. We addressed this question using transcriptome and DNA methylation data from a sample of 135 sequenced A. thaliana accessions. Across individuals, expression was significantly associated with cis -methylation for hundreds of genes, and many of these associations remained significant after taking SNP effects into account. The pattern of correlations differed markedly between gene body methylation and transposable element methylation. The former was usually positively correlated with expression, and the latter usually negatively correlated, although exceptions were found in both cases. Finally, we developed graphical models of causality that adapt to a sample with heavy population structure, and used them to show that while methylation appears to affect gene expression more often than expression affects methylation, there is also strong support for both being independently controlled. In conclusion, although we find clear evidence for epigenetic regulation, both the number of loci affected and the magnitude of the effects appear to be small compared to the effect of SNPs.

Description: by Minghua Nie, Emily Arner, John Prudden, Lana Schaffer, Steven Head, Michael N. Boddy Posttranslational modifications (PTMs) provide dynamic regulation of the cellular proteome, which is critical for both normal cell growth and for orchestrating rapid responses to environmental stresses, e.g. genotoxins. Key PTMs include ubiquitin, the Small Ubiquitin-like MOdifier SUMO, and phosphorylation. Recently, SUMO-targeted ubiquitin ligases (STUbLs) were found to integrate signaling through the SUMO and ubiquitin pathways. In general, STUbLs are recruited to target proteins decorated with poly-SUMO chains to ubiquitinate them and drive either their extraction from protein complexes, and/or their degradation at the proteasome. In fission yeast, reducing or preventing the formation of SUMO chains can circumvent the essential and DNA damage response functions of STUbL. This result indicates that whilst some STUbL "targets" have been identified, the crucial function of STUbL is to antagonize SUMO chain formation. Herein, by screening for additional STUbL suppressors, we reveal crosstalk between the serine/threonine phosphatase PP2A-Pab1 B55 and the SUMO pathway. A hypomorphic Pab1 B55 mutant not only suppresses STUbL dysfunction, but also mitigates the phenotypes associated with deletion of the SUMO protease Ulp2, or mutation of the STUbL cofactor Rad60. Together, our results reveal a novel role for PP2A-Pab1 B55 in modulating SUMO pathway output, acting in parallel to known critical regulators of SUMOylation homeostasis. Given the broad evolutionary functional conservation of the PP2A and SUMO pathways, our results could be relevant to the ongoing attempts to therapeutically target these factors.

Description: by Edoardo Pasolli, Duy Tin Truong, Faizan Malik, Levi Waldron, Nicola Segata Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus ) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the “healthy” microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

Description: by Anja S. Ziegler, Simon J. McIlroy, Poul Larsen, Mads Albertsen, Aviaja A. Hansen, Nicolas Heinen, Per Halkjær Nielsen Membrane fouling presents the greatest challenge to the application of membrane bioreactor (MBR) technology. Formation of biofilms on the membrane surface is the suggested cause, yet little is known of the composition or dynamics of the microbial community responsible. To gain an insight into this important question, we applied 16S rRNA gene amplicon sequencing with a curated taxonomy and fluorescent in situ hybridization to monitor the community of a pilot-scale MBR carrying out enhanced biological nitrogen and phosphorus removal with municipal wastewater. In order to track the dynamics of the fouling process, we concurrently investigated the communities of the biofilm, MBR bulk sludge, and the conventional activated sludge system used to seed the MBR system over several weeks from start-up. As the biofilm matured the initially abundant betaproteobacterial genera Limnohabitans , Hydrogenophaga and Malikia were succeeded by filamentous Chloroflexi and Gordonia as the abundant species. This study indicates that, although putative pioneer species appear, the biofilm became increasingly similar to the bulk community with time. This suggests that the microbial population in bulk water will largely determine the community structure of the mature biofilm.

Description: by Petra E. Verburg, Graeme Tucker, Wendy Scheil, Jan Jaap H. M. Erwich, Gus A. Dekker, Claire Trelford Roberts Objectives Sexual inequality starts in utero . The contribution of biological sex to the developmental origins of health and disease is increasingly recognized. The aim of this study was to assess and interpret sexual dimorphisms for three major adverse pregnancy outcomes which affect the health of the neonate, child and potentially adult. Methods Retrospective population-based study of 574,358 South Australian singleton live births during 1981–2011. The incidence of three major adverse pregnancy outcomes [preterm birth (PTB), pregnancy induced hypertensive disorders (PIHD) and gestational diabetes mellitus (GDM)] in relation to fetal sex was compared according to traditional and fetus-at-risk (FAR) approaches. Results The traditional approach showed male predominance for PTB [20–24 weeks: Relative Risk (RR) M/F 1.351, 95%-CI 1.274–1.445], spontaneous PTB [25–29 weeks: RR M/F 1.118, 95%-CI 1.044–1.197%], GDM [RR M/F 1.042, 95%-CI 1.011–1.074], overall PIHD [RR M/F 1.053, 95%-CI 1.034–1.072] and PIHD with term birth [RR M/F 1.074, 95%-CI 1.044–1.105]. The FAR approach showed that males were at increased risk for PTB [20–24 weeks: RR M/F 1.273, 95%-CI 1.087–1.490], for spontaneous PTB [25–29 weeks: RR M/F 1.269, 95%-CI 1.143–1.410] and PIHD with term birth [RR M/F 1.074, 95%-CI 1.044–1.105%]. The traditional approach demonstrated female predominance for iatrogenic PTB [25–29 weeks: RR M/F 0.857, 95%-CI 0.780–0.941] and PIHD associated with PTB [25–29 weeks: RR M/F 0.686, 95%-CI 0.581–0.811]. The FAR approach showed that females were at increased risk for PIHD with PTB [25–29 weeks: RR M/F 0.779, 95%-CI 0.648–0.937]. Conclusions This study confirms the presence of sexual dimorphisms and presents a coherent framework based on two analytical approaches to assess and interpret the sexual dimorphisms for major adverse pregnancy outcomes. The mechanisms by which these occur remain elusive, but sex differences in placental gene expression and function are likely to play a key role. Further research on sex differences in placental function and maternal adaptation to pregnancy is required to delineate the causal molecular mechanisms in sex-specific pregnancy outcome. Identifying these mechanisms may inform fetal sex specific tailored antenatal and neonatal care.

Description: by Harald Schrem, Valentin Schneider, Marlene Kurok, Alon Goldis, Maren Dreier, Alexander Kaltenborn, Wilfried Gwinner, Marc Barthold, Jan Liebeneiner, Markus Winny, Jürgen Klempnauer, Moritz Kleine Background The aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. Patients and Methods 1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences. Results Cancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33–3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age 62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m 2 (p