bluuebunny/crossref_metadata_2025 huggingface dataset:
Complex-centric proteome profiling by SEC-SWATH-MS
Authors: Heusel Moritz , Bludau Isabell , Rosenberger George , Hafen Robin , Frank Max , Banaei-Esfahani Amir , Collins Ben , Gstaiger Matthias , Aebersold Ruedi
Published: May 2018

Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction and the computational framework CCprofiler to detect and quantify protein complexes by error-controlled, complex-centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2127 protein subunits. The technique identifies novel subcomplexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible, and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.
De novoassembly of a young Drosophila Y chromosome using Single-Molecule sequencing and Chromatin Conformation capture
Authors: Mahajan Shivani , Wei Kevin , Nalley Matthew , Giblisco Lauren , Bachtrog Doris
Published: May 2018

While short-read sequencing technology has resulted in a sharp increase in the number of species with genome assemblies, these assemblies are typically highly fragmented. Repeats pose the largest challenge for reference genome assembly, and pericentromeric regions and the repeat-rich Y chromosome are typically ignored from sequencing projects. Here, we assemble the genome ofDrosophila mirandausing long reads for contig formation, chromatin interaction maps for scaffolding and short reads, optical mapping and BAC clone sequencing for consensus validation. Our assembly recovers entire chromosomes and contains large fractions of repetitive DNA, including~41.5 Mb of pericentromeric and telomeric regions, and >100Mb of the recently formed highly repetitive neo-Y chromosome. While Y chromosome evolution is typically characterized by global sequence loss and shrinkage, the neo-Y increased in size by almost 3-fold, due to the accumulation of repetitive sequences. Our high-quality assembly allows us to reconstruct the chromosomal events that have led to the unusual sex chromosome karyotype inD. miranda, including the independentde novoformation of a pair of sex chromosomes at two distinct time points, or the reversion of a former Y chromosome to an autosome.
SLIMEr: probing flexibility of lipid metabolism in yeast with an improved constraint-based modeling framework
Authors: Sánchez Benjamín J. , Li Feiran , Kerkhoven Eduard J. , Nielsen Jens
Published: May 2018

A recurrent problem in genome-scale metabolic models (GEMs) is to correctly represent lipids as biomass requirements, due to the numerous of possible combinations of individual lipid species and the corresponding lack of fully detailed data. In this study we present SLIMEr, a formalism for correctly representing lipid requirements in GEMs using commonly available experimental data. SLIMEr enhances a GEM with mathematical constructs where we Split Lipids Into Measurable Entities (SLIME reactions), in addition to constraints on both the lipid classes and the acyl chain distribution. By implementing SLIMEr on the consensus GEM of Saccharomyces cerevisiae, we can predict accurate amounts of lipid species, analyze the flexibility of the resulting distribution, and compute the energy costs of moving from one metabolic state to another. The approach shows potential for better understanding lipid metabolism in yeast under different conditions. SLIMEr is freely available at https://github.com/SysBioChalmers/SLIMEr.
Metanalysis of genome-wide association studies for panic disorder suggest pathways and mechanisms of pathogenesis
Authors: Silva Rhayra Xavier do Carmo , Rocha Sueslene Prado , Souza Dainara Pereira dos Santos , Lima-Maximino Monica Gomes , Maximino Caio
Published: May 2018

Panic disorder (PD) is characterized by abrupt surges of intense fear and distress. There is evidence for a genetic component in this disorder. We ran a meta-analysis of genome-wide association studies of patients with PD, and found 25 single-nucleotide polymorphisms that were associated with the disorder. Causal gene prediction based on these polymorphisms uncovered 20 hits. Exploratory analyses suggested that these genes formed interactor networks, which was enriched in signaling pathways associated with immune and inflammatory responses, as well as growth factors and other developmental mediators. A subset of genes is enriched in limbic regions of the human brain and in microglia and myelinating oligodendrocytes of mice. While these genes were not associated with relevant neurobehavioral phenotypes in mutant mice, expression levels of several causal genes in the amygdala, prefrontal cortex, hippocampus, hypothalamus, and adrenal gland of recombinant mouse strains was associated with endophenotypes of fear conditioning. Drug repositioning prediction was unsuccessful, but this does not discard these genes and pathways as targets for investigational drugs. In general,ASB3,EIF2S2, RASGRF2, andTRMT2B(and its coded proteins) emerged as interesting targets for mechanistic research on PD. These exploratory findings point towards hypotheses of pathogenesis and neuropharmacology that need to be further investigated.
Species-habitat networks: Bridging applied ecology and network theory
Authors: Marini Lorenzo , Bartomeus Ignasi , Rader Romina , Lami Francesco
Published: May 2018

Land-use change is massively reshaping terrestrial ecosystems worldwide, and is recognized as a key driver of biodiversity loss with negative consequences on ecosystem functioning. Understanding how species use resources across landscapes is essential for the design of effective management strategies. Despite recent advances in theoretical ecology, there is still a gap between theory and applied ecological science and we lack the tools to manage entire landscapes to maximize biodiversity conservation and ecosystem service delivery. Here, we propose a new approach that uses existing bipartite networks to create species-habitat networks. Networks enable powerful visualizations via a common language that defines most processes in terms of nodes and links. This approach explicitly links multiple species and habitat resources, provides tools to estimate the importance of particular species in a given landscape, and quantifies emerging properties of entire habitat networks. Most existing metrics used to study properties of bipartite ecological networks can easily be adapted to investigate species-habitat relationships. One key advantage of this approach is that the scale of the derived ecological information will match the scale of management interventions. The flexibility of the proposed approach is that it can be easily applied across a range of ecological fields such as species conservation, habitat restoration, ecosystem services management, or invasion ecology. Network emerging properties could also be used to test the effects of large scale drivers of global change upon ecosystem structure and stability.
Regional neutrality evolves through local adaptive niche evolution
Authors: Leibold Mathew A. , Urban Mark C. , De Meester Luc , Klausmeier Christopher A. , Vanoverbeke Joost
Published: May 2018

Joost Vanoverbeke, Department of Biology, Katholieke Universiteit Leuven, Leuven, Belgium. Abstract:
Biodiversity in natural systems can be maintained either because niche differentiation among competitors facilitates stable coexistence or because equal fitness among neutral species allows for their long-term co-occurrence despite a slow drift toward extinction. Whereas the relative importance of these two ecological mechanisms has been well-studied in the absence of evolution, the role of local adaptive evolution in maintaining biological diversity through these processes is less clear. Here we study the contribution of local adaptive evolution to coexistence in a landscape of interconnected patches subject to disturbance. Under these conditions, early colonists to empty patches following disturbance can often adapt to novel local conditions sufficiently fast to prevent successful colonization by other pre-adapted species. Over the long term, the iteration of these local-scale priority effects results in niche convergence of species at the regional scale even though species tend to monopolize local patches. Thus, the dynamics evolve from stable coexistence through niche differentiation to neutral co-occurrence at the landscape level while still maintaining strong local niche differentiation. Our model results show that neutrality can emerge at the regional scale from local, niche-based adaptive evolution, potentially resolving why ecologists often observe neutral distribution patterns at the landscape level despite strong niche divergence among local communities. Our results also demonstrate how local adaptive evolution can shape cryptic eco-evolutionary dynamics and thus alter the regional mechanisms that determine biological diversity and resistance to disturbance.
Simple but Robust Improvement in Multivoxel Pattern Classification
Authors: Lee Sangil , Kable Joseph W.
Published: May 2018

Multivoxel pattern analysis (MVPA) typically begins with the estimation of single trial activation levels, and several studies have examined how different procedures for estimating single trial activity affect the ultimate classification accuracy of MVPA. Here we show that the currently preferred estimation procedures impart spurious shifts in run-level means that cause the estimated activities to be misaligned across runs. These shifts are caused by positive correlations between the means of different category activity estimates within the same scanner run. In other words, if the mean of the estimates for one type of trials is high (low) in a given scanner run, then the mean of the other type of trials is also high (low) for that same scanner run, and the mean across all trials therefore shifts from run to run. Simulations show that these correlations are unavoidable whenever there is a need to deconvolve overlapping trial activities in the presence of noise. We show that subtracting the mean across all trials of a run from all the estimates within that run (i.e., run-level mean centering of estimates), by cancelling out these mean shifts, leads to robust and significant improvements in MVPA classification accuracy. These improvements are seen in both simulated and real data across a wide variety of situations and can provide significant direct benefits with no computational cost. However, we also point out that there could be cases when mean activations are expected to shift across runs and that run-level mean centering could be detrimental in some of these cases (e.g., different proportion of trial types between different runs).
A rational account of human memory search
Authors: Zhang Qiong , Anderson John R.
Published: May 2018

Performing everyday tasks requires the ability to search through and retrieve past memories. A central paradigm to study human memory search is the semantic fluency task, where participants are asked to retrieve as many items as possible from a category (e.g. animals). Observed responses tend to be clustered semantically. To understand when our mind decides to switch from one cluster/patch to the next, recent work has proposed two competing mechanisms. Under the first switching mechanism, people make strategic decision to switch away from a depleted patch based on marginal value theorem, similar to optimal foraging in a spatial environment. The second switching mechanism demonstrates that similar behavior patterns can emerge using a random walk on a semantic network, without necessarily involving strategic switches. In the current work, instead of comparing competing switching mechanisms over observed human data, we propose a rational account of the problem by examining what would be the optimal patch-switching policy under the framework of reinforcement learning. The reinforcement learning agent, a Deep Q-Network (DQN), is built upon the random walk model and allows strategic switches based on features of the local semantic patch. After learning from rewards, the resulted policy of the agent gives rise to a third switching mechanism, which outperforms the previous two switching mechanisms. Our results provide theoretical justification of strategies used in human memory research, and shed light on how an optimal AI agent under realistic human constraints can generate hypothesis about human strategies in the same task.
ICeD-T Provides Accurate Estimates of Immune Cell Abundance in Tumor Samples by Allowing for Aberrant Gene Expression Patterns
Authors: Wilson Douglas R. , Ibrahim Joseph G. , Sun Wei
Published: May 2018

Immunotherapies have achieved phenomenal success in the treatment of cancer and promise even more breakthroughs in the near future. The need to understand the underlying mechanisms of immunotherapies and to develop precision immunotherapy regimens has spurred great interest in characterizing immune cell composition within the tumor microenvironment. Several methods have been developed to estimate immune cell composition using gene expression data from bulk tumor samples. However, these methods are not flexible enough to handle aberrant patterns of gene expression data, e.g., inconsistent cell type-specific gene expression between purified reference samples and this cell type in tumor samples. In this paper, we present a novel statistical model for expression deconvolution called ICeD-T (Immune Cell Deconvolution in Tumor tissues), which models gene expression by a log-normal distribution that is appropriate for both microarray and RNA-seq data. ICeD-T automatically identifies aberrant genes whose expressions are inconsistent with the deconvolution model and down-weights their contributions to cell type abundance estimates. We evaluated the performance of ICeD-T versus existing methods in simulation studies and several real data analyses. ICeD-T displayed comparable or superior performance to these competing methods. Applying these methods to assess the relationship between immunotherapy response and immune cell composition, ICeD-T is able to identify significant associations that are missed by its competitors.
The Effect of Previous Life Cycle Phase on the Growth Kinetics, Morphology and Antibiotic Resistance ofSalmonellaTyphimurium DT104 in Brain Heart Infusion and Ground Chicken Extract
Authors: Hawkins Jabari L. , Uknalis Joseph , Oscar Tom P. , Schwarz Jurgen G. , Vimini Bob , Parveen Salina
Published: May 2018

Growth models are predominately used in the food industry to estimate the potential growth of select microorganisms under environmental conditions. The growth kinetics, cellular morphology and antibiotic resistance were studied throughout the life cycle ofSalmonellaTyphimurium. The effect of the previous life cycle phase (late log phase [LLP], early stationary phase [ESP], late stationary phase [LSP] and early death phase [EDP]) ofSalmonellaafter reinoculation in brain heart infusion broth (BHI), ground chicken extract (GCE) and BHI at pH 5, 7 and 9 and salt concentrations 2, 3 and 4% was investigated. The growth media and previous life cycle phase had significant effects on the lag time (λ), specific growth rate (μmax) and maximum population density (Ymax). At 2% and 4% salt concentration the LLP had the significantly (P<0.05) fastest μmax(1.07 and 0.69 log CFU/mL/h, respectively). As the cells transitioned from the late log phase (LLP) to the early death phase (EDP), the λ significantly (P<0.05) increased. At pH 5 and 9 the EDP had a significantly (P<0.05) lower Ymaxthan the LLP, ESP and LSP. As the cells transitioned from a rod shape to a coccoid shape in the EDP, the cells were more susceptible to antibiotics. The cells regained their resistance as they transitioned back to a rod shape from the EDP to the log and stationary phase. Our results revealed that growth kinetics, cell’s length, shape and antibiotic resistance were significantly affected by the previous life cycle phase.
Inflammation is the main risk factor of voriconazole overdose in hematological patients
Authors: Gautier-Veyret Elodie , Truffot A , Bailly S , Fonrose X , Thiebaut-Bertrand A , Tonini J , Cahn JY , Stanke-Labesque F
Published: May 2018

Aim: Voriconazole (VRC) overdoses are frequent and expose patients at high risk of adverse effects. This case-control study performed in hematological patients who benefited from VRC therapeutic drug monitoring from January 2012 to December 2015 aimed to identify risk factors of VRC overdose.

Methods: Pharmacogenetic, biological, and demographic parameters at the time of VRC trough concentration (Cmin) were retrospectively collected from medical records. Cases (VRC overdose: defined by a VRC Cmin ≥ 4 mg/l; n = 31) were compared to controls (no VRC overdose: defined by VRC Cmin < 4 mg/L; n = 31) using non-parametric or Chi-square tests followed by multivariable analysis.

Results: VRC overdoses were significantly associated with high CRP and bilirubin levels, intra-venous administration, and age in univariable analysis. In contrast, the proportion of CYP genotypes (CYP2C19, CYP3A4, or CYP3A5, considered alone or combined in a genetic score1) were not significantly different between patients who experienced a VRC overdose and those who did not. In multivariable analysis, the class of CRP level (defined by median CRP levels of 96 mg/l) was the sole independent risk factor of VRC overdose (p < 0.01). Patients with CRP levels > 96 mg/l had a 27-fold (IC 95%: [6-106]) higher risk of VRC overdose than patients with CRP levels ≤ 96 mg/l.

Conclusion: This study demonstrates that inflammatory status, assessed by CRP levels, is the main risk factor of VRC overdose in French hematological patients, whereas pharmacogenetic determinants do not appear to be involved.
Low frequency ultrasound enhances chemotherapy sensitivity and induces autophagy in human paclitaxel resistance prostate cancer PC-3R cells through the ERs-mediated PI3K/Akt/mTOR signaling pathway
Authors: Wu Yuqi , Liu Xiaobing , Qin Zizhen , Wang Xiangwei
Published: May 2018

Sonodynamic therapy (SDT) as an emerging tumor-assisting method has attracted a great deal of interest in tumor therapy research in recent years. However, autophagy has been observed in several cancer cells treated with SDT and its role and mechanism are not clear. In the present study, we have investigated the effect of low frequency ultrasound on paclitaxel(PTX) resistance prostate cancer PC-3R cells and demonstrated that low frequency ultrasound could induce cancer cell apoptosis, inhibit the expression of multiple drug resistance genes (MRP3, MRP7 and P-glycoprotein) and reverse drug resistance; we further found that low frequency ultrasound induced autophagy in PC-3R cells. Our results demonstrated that low frequency ultrasound enhanced chemotherapy sensitivity and induced autophagy in PC-3R cells by inhibiting the PI3K/AKT/mTOR pathway. Moreover, we observed that low frequency ultrasound-induced cell autophagy was correlated with endoplasmic reticulum stress (ERs). 4-phenylbutyric acid (4-PBA) - mediated protection against ERs clearly implicated ERs in the activation of autophagy and cell apoptosis. In addition, the results showed that ERs served as an upstream effector of the PI3K/AKT/mTOR pathway. More importantly, we observed that inhibition of low frequency ultrasound-induced autophagy enhanced ERs and improved the role of low frequency ultrasound in reversing drug resistance. Over all, our findings provide new insights into the molecular mechanisms underlying low frequency ultrasound-mediated reversal of drug resistance and autophagy in PC-3R cells and support autophagy as a potential agent for enhancing anti-cancer effect of SDT.
Social learning strategies regulate the wisdom and madness of interactive crowds
Authors: Toyokawa Wataru , Whalen Andrew , Laland Kevin N.
Published: May 2018

Why groups of individuals sometimes exhibit collective ‘wisdom’ and other times maladaptive ‘herding’ is an enduring conundrum. Here we show that this apparent conflict is regulated by the social learning strategies deployed. We examined the patterns of human social learning through an interactive online experiment with 699 participants, varying both task uncertainty and group size, then used hierarchical Bayesian model-ftting to identify the individual learning strategies exhibited by participants. Challenging tasks elicit greater conformity amongst individuals, with rates of copying increasing with group size, leading to high probabilities of herding amongst large groups confronted with uncertainty. Conversely, the reduced social learning of small groups, and the greater probability that social information would be accurate for less-challenging tasks, generated ‘wisdom of the crowd’ effects in other circumstances. Our model-based approach provides evidence that the likelihood of collective intelligence versus herding can be predicted, resolving a longstanding puzzle in the literature.
Sensory cheating: adversarial body patterns can fool a convolutional visual system during signaling
Authors: Laan Andres , de Polavieja Gonzalo.G
Published: May 2018

Animals often assess each other by paying special attention to signals, which help to communicate the quality of each individual. When there is a conflict of interest between the signaler and the receiver, then the signaler has an incentive to cheat by producing signals which exaggerate its apparent quality. One opportunity for cheating might be to rely on sensory illusions, but it has been difficult to study sensory cheating because we have lacked quantitative models of complex visual perception. Here we address this problem by taking advantage of recent advances in modeling visual brain areas as convolutional neural networks. Given these models, we use the technique of adversarial perturbations to show how sensory cheating can shape animal appearance while nevertheless resulting in an evolutionarily stable signaling system. In our simulations, animals typically evolve exaggerated color patterns which might be analogous to the evolution of colorful body patterns in guppies.
A whole-brain and cross-diagnostic perspective on functional brain network dysfunction
Authors: Spronk Marjolein , Kulkarni Kaustubh , Ji Jie Lisa , Keane Brian P. , Anticevic Alan , Cole Michael W
Published: May 2018

A wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations have seemed to support various theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in broad, whole-brain perspective. Using a graph distance measure – connectome-wide correlation – we found that whole-brain resting-state functional network organization in humans is highly similar across a variety of mental diseases and healthy controls. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease those differences are informative. Such small network alterations may reflect the fact that most psychiatric patients maintain overall cognitive abilities similar to those of healthy individuals (relative to, e.g., the most severe schizophrenia cases), such that whole-brain functional network organization is expected to differ only subtly even for mental diseases with devastating effects on everyday life. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases.
EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame
Authors: Koodli Rohan V. , Keep Benjamin , Coppess Katherine R. , Portela Fernando ,   Eterna participants, Das Rhiju
Published: May 2018

Emerging RNA-based approaches to disease detection and gene therapy require RNA sequences that fold into specific base-pairing patterns, but computational algorithms generally remain inadequate for these secondary structure design tasks. The Eterna project has crowdsourced RNA design to human video game players in the form of puzzles that reach extraordinary difficulty. Here, we demonstrate that Eterna participants’ moves and strategies can be leveraged to improve automated computational RNA design. We present an eternamoves-large repository consisting of 1.8 million of player moves on 12 of the most-played Eterna puzzles as well as an eternamoves-select repository of 30,477 moves from the top 72 players on a select set of more advanced puzzles. On eternamoves-select, we present a multilayer convolutional neural network (CNN) EternaBrain that achieves test accuracies of 51% and 34% in base prediction and location prediction, respectively, suggesting that top players’ moves are partially stereotyped. Pipelining this CNN’s move predictions with single-action-playout (SAP) of six strategies compiled by human players solves 61 out of 100 independent puzzles in the Eterna100 benchmark. EternaBrain-SAP outperforms previously published RNA design algorithms and achieves similar or better performance than a newer generation of deep learning methods, while being largely orthogonal to these other methods. Our study provides useful lessons for future efforts to achieve human-competitive performance with automated RNA design algorithms.
T Cell Repertoire Evolution After Allogeneic Bone Marrow Transplantation: An Organizational Perspective
Authors: Meier Jeremy A. , Fawaz Mohamed , Abdeen Hamdi , Reed Jason , Kanakry Christopher G. , Luznik Leo , Toor Amir A.
Published: May 2018

High throughput sequencing (HTS) of human T cell receptors has revealed a high level of complexity in the T cell repertoire. In an attempt to correlate T cell reconstitution with clinical outcomes several measures of T cell repertoire complexity have emerged. However, the associations identified are of a broadly statistical nature, not allowing precise modeling of outcomes based on T cell repertoire development in clinical contexts such as following bone marrow transplantation (BMT). Previous work demonstrated that there is an inherent, mathematically definable order observed in the T cell population that is conserved in a diverse group of donors, and which is perturbed in recipients following BMT. Herein, we use a public database of human leukocyte antigen matched related-donor and recipient T cell receptor (TCR) β sequences to further develop this methodology. TCR β sequencing from unsorted T cells and sorted T cell subsets isolated from peripheral blood samples from BMT donors and recipients show remarkable conservation and symmetry of VJ segment usage in the clonal frequencies, linked to the organization of the gene segments along the TCR locus. This TCR β VJ segment translational symmetry is preserved post-transplant, and even in cases of acute GVHD (aGVHD), suggesting that GVHD occurrence represents a polyclonal donor T cell response to recipient antiges. We also observe that the complexity of the repertoire is significantly diminished after BMT and is not restored even years out post-transplant. The results here provide a new method of quantifying and characterizing post-transplant T cell repertoire reconstitution by further analyzing the mathematical rules governing TCR usage in the context of BMT. This approach may allow for a new means to correlate clinical outcomes with the evolving T cell repertoire post-transplant.
Transformation from auditory to linguistic representations across auditory cortex is rapid and attention dependent for continuous speech
Authors: Brodbeck Christian , Hong L. Elliot , Simon Jonathan Z.
Published: May 2018

During speech perception, a central task of the auditory cortex is to analyze complex acoustic patterns to allow detection of the words that encode a linguistic message. It is generally thought that this process includes at least one intermediate, phonetic, level of representations [1–6], localized bilaterally in the superior temporal lobe [7–10]. Phonetic representations reflect a transition from acoustic to linguistic information, classifying acoustic patterns into linguistically meaningful units, which can serve as input to mechanisms that access abstract word representations [11–13]. While recent research has identified neural signals arising from successful recognition of individual words in continuous speech [14–17], no explicit neurophysiological signal has been found demonstrating the transition from acoustic/phonetic to symbolic, lexical representations. Here we report a response reflecting the incremental integration of phonetic information for word identification, dominantly localized to the left temporal lobe. The short response latency, approximately 110 ms relative to phoneme onset, suggests that phonetic information is used for lexical processing as soon as it becomes available. Responses also tracked word boundaries, confirming previous reports of immediate lexical segmentation [18,19]. These new results were further investigated using a cocktail-party paradigm [20,21] in which participants listened to a mix of two talkers, attending to one and ignoring the other. Analysis indicates neural lexical processing of only the attended, but not the unattended, speech stream. Thus, while responses to acoustic features reflect attention through selective amplification of attended speech, responses consistent with a lexical processing model reveal categorically selective processing.
Emergent Elasticity in the Neural Code for Space
Authors: Ocko Samuel , Hardcastle Kiah , Giocomob Lisa , Ganguli Surya
Published: May 2018

Upon encountering a novel environment, an animal must construct a consistent environmental map, as well as an internal estimate of its position within that map, by combining information from two distinct sources: self-motion cues and sensory landmark cues. How do known aspects of neural circuit dynamics and synaptic plasticity conspire to accomplish this feat? Here we show analytically how a neural attractor model that combines path integration of self-motion cues with Hebbian plasticity in synaptic weights from landmark cells can self-organize a consistent map of space as the animal explores an environment. Intriguingly, the emergence of this map can be understood as an elastic relaxation process between landmark cells mediated by the attractor network. Moreover, our model makes several experimentally testable predictions, including: (1) systematic path-dependent shifts in the firing field of grid cells towards the most recently encountered landmark, even in a fully learned environment, (2) systematic deformations in the firing fields of grid cells in irregular environments, akin to elastic deformations of solids forced into irregular containers, and (3) the creation of topological defects in grid cell firing patterns through specific environmental manipulations. Taken together, our results conceptually link known aspects of neurons and synapses to an emergent solution of a fundamental computational problem in navigation, while providing a unified account of disparate experimental observations.
The first one hundred nanometers inside the pre-synaptic terminal where calcium diffusion triggers vesicular release
Authors: Guerrier C. , Holcman D.
Published: May 2018

Calcium diffusion in the thin one hundred nanometers layer located between the plasma membrane and docked vesicles in the pre-synaptic terminal of neuronal cells mediates vesicular fusion and synaptic transmission. Accounting for the narrow-cusp geometry located underneath the vesicle is a key ingredient that defines the probability and the time scale of calcium diffusion to bind calcium sensors for the initiation of vesicular release. We study here the time scale, the calcium binding dynamics and the consequences for asynchronous versus synchronous release. To conclude, threedimensional modeling approaches and the associated coarse-grained simulations can now account efficiently for the precise co-organization of vesicles and Voltage-Gated-Calcium-Channel (VGCC). This co-organization is a key determinant of short-term plasticity and it shapes asynchronous release. Moreover, changing the location of VGCC from few nanometers underneath the vesicle modifies significantly the release probability. Finally, by modifying the calcium buffer concentration, a single synapse can switch from facilitation to depression.
Decreased RORC expression and downstream signaling in HTLV-1-associated Adult T-cell Lymphoma/Leukemia uncovers an antiproliferative IL17 link: a potential target for immunotherapy?
Authors: Subramanian Kritika , Dierckx Tim , Khouri Ricardo , Menezes Soraya Maria , Farre Lourdes , Bittencourt Achilea , Kataoka Keisuke , Ogawa Seishi , Van Weyenbergh Johan
Published: May 2018

Retinoic acid-related drugs have shown promising pre-clinical activity in Adult T-cell Leukemia/Lymphoma (ATL), but RORC (Retinoic acid Orphan Receptor C) signaling has not been explored. Therefore, we investigated transcriptome-wide interactions of the RORC pathway in Human T-cell Leukemia Virus-1 (HTLV-1) infection and ATL, using our own and publicly available gene expression data for ATL and other leukemias, HTLV-1-infected individuals and healthy controls. Gene expression data from ATL patients were analyzed using Weighted Gene Correlation Network Analysis (WGCNA) to determine gene modules and their correlation to clinical and molecular data. Both PBMCs and CD4+ T-cells showed decreased RORC expression in four different ATL cohorts. A small subset of RORChi ATL patients was identified with significantly lower pathognomonic CADM1 and HBZ levels but similar levels of other ATL markers (CD4/CD25/CCR4), hinting at a less aggressive ATL subtype. In addition, an age-dependent decrease in RORC expression was found in HTLV-1-infected individuals, but not in healthy controls, suggesting an early molecular event predisposing to leukemogenesis. Genes upstream of RORC signaling were members of a proliferative gene module (containing proliferation markers PCNA/MKI67), whereas downstream members clustered in an antiproliferative gene module. IL17C transcripts showed the strongest negative correlation to PCNA in both ATL cohorts, which was replicated in two large cohorts of T- and B-cell acute leukemias. In conclusion, decreased RORC expression and downstream signaling might represent an early event in ATL pathogenesis. An antiproliferative IL17C/PCNA link is shared between ATL, T-ALL and B-ALL, suggesting (immuno)therapeutic benefit of boosting RORC/IL17 signaling.

Abbreviations

HTLV-1

Human T-cell Leukemia Virus-1

ATL

Adult T-cell Leukemia/Lymphoma

WGCNA

Weighted Gene Correlation Network Analysis

ATRA

All-trans retinoic acid

RARa

Retinoic acid receptor alpha

RORC

Retinoic acid orphan receptor C

TBLV

Type B Leukomogenic Virus

AML

Acute Myeloid Leukemia

T-ALL

T-cell acute lymphoblastic leukemia

IL

Interleukin

PCNA

Proliferating cell nuclear antigen

ID

Infectious Dermatitis
The EVcouplings Python framework for coevolutionary sequence analysis
Authors: Hopf Thomas A. , Green Anna G. , Schubert Benjamin , Mersmann Sophia , Schäerfe Charlotta P. I. , Ingraham John B. , Toth-Petroczy Agnes , Brock Kelly , Riesselman Adam , Kang Chan , Dallago Christian , Sander Chris , Marks Debora S.
Published: May 2018

Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. This approach requires extensive computational pipelines that integrate multiple tools, databases, and data processing steps. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The application has an easy to use command line interface to run workflows with user control over all analysis parameters, while the underlying modular Python package allows interactive data analysis and rapid development of new workflows. Through this multi-layered approach, the EVcouplings framework makes the full power of coevolutionary analyses available to entry-level and advanced users.

Availability

https://github.com/debbiemarkslab/evcouplings

Contact

sander.research@gmail.com, debbie@hms.harvard.edu
Comprehensive profiling of translation initiation in influenza virus infected cells
Authors: Machkovech Heather M. , Bloom Jesse D. , Subramaniam Arvind R.
Published: May 2018

Translation can initiate at alternate, non-canonical start codons in response to stressful stimuli in mammalian cells. Recent studies suggest that viral infection and anti-viral responses alter sites of translation initiation, and in some cases, lead to production of novel immune epitopes. Here we systematically investigate the extent and impact of alternate translation initiation in cells infected with influenza virus. We perform evolutionary analyses that suggest selection against non-canonical initiation at CUG codons in influenza virus lineages that have adapted to mammalian hosts. We then use ribosome profiling with the initiation inhibitor lactidomycin to experimentally delineate translation initiation sites in a human lung epithelial cell line infected with influenza virus. We identify several candidate sites of alternate initiation in influenza mRNAs, all of which occur at AUG codons that are downstream of canonical initiation codons. One of these candidate downstream start sites truncates 14 amino acids from the N-terminus of the N1 neuraminidase protein, resulting in loss of its cytoplasmic tail and a portion of the transmembrane domain. This truncated neuraminidase protein is expressed on the cell surface during influenza virus infection, is enzymatically active, and is conserved in most N1 viral lineages. Host transcripts induced by the anti-viral response are enriched for translation initiation at non-canonical start sites and non-AUG start codons. Together, our results systematically map the landscape of translation initiation during influenza virus infection, and shed light on the evolutionary forces shaping this landscape.
Mitochondrial ClpX activates an essential metabolic enzyme through partial unfolding
Authors: Kardon Julia R. , Moroco Jamie A. , Engen John R. , Baker Tania A.
Published: May 2018

Mitochondria can control the activity, quality, and lifetime of their proteins with their autonomous system of chaperones, but the signals that direct substrate-chaperone interaction and outcome are poorly understood. We previously discovered that the mitochondrial AAA+ protein unfoldase ClpX (mtClpX) activates the initiating enzyme for heme biosynthesis, 5-aminolevulinic acid synthase (ALAS), by promoting incorporation of cofactor. Here, we ask how unfolding by mtClpX directs activation. We identified sequence and structural features in ALAS that position mtClpX and provide a grip for acting on ALAS. Observation of ALAS undergoing remodeling by mtClpX revealed that unfolding was limited to a subdomain extending from the mtClpX-binding site to the active site. Unfolding along this path was required for mtClpX to gate cofactor access to the ALAS active site. This targeted unfolding contrasts with the global unfolding canonically executed by ClpX homologs and suggests how substrate-chaperone interactions can direct the outcome of remodeling.
Structural relationship between the putative hair cell mechanotransduction channel TMC1 and TMEM16 proteins
Authors: Ballesteros Angela , Fenollar-Ferrer Cristina , Swartz Kenton J.
Published: May 2018

The hair cell mechanotransduction (MET) channel complex is essential for hearing, yet it’s molecular identity and structure remain elusive. The transmembrane channel-like 1 (TMC1) protein localizes to the site of the MET channel, interacts with the tip-link responsible for mechanical gating, and genetic alterations in TMC1 alter MET channel properties and cause deafness, supporting the hypothesis that TMC1 forms the MET channel. We generated a model of TMC1 based on X-ray and cryo-EM structures of TMEM16 proteins, revealing the presence of a large cavity near the protein-lipid interface that also harbors the Beethoven mutation, suggesting that it could function as a permeation pathway. We also find that hair cells are permeable to 3 kDa dextrans, and that dextran permeation requires TMC1/2 proteins and functional MET channels, supporting the presence of a large permeation pathway and the hypothesis that TMC1 is a pore forming subunit of the MET channel complex.
Urine proteome changes in a TNBS-induced colitis rat model
Authors: Qin Weiwei , Wang Ting , Li Lujun , Huang He , Gao Youhe
Published: May 2018

Urine is an important resource for biomarker research. Without homeostasis, urine accumulates markers of all the changes in the body. Urine proteins reflect not only renal diseases but also changes in other organs in the body. However, urine has rarely been used to reflect inflammatory bowel disease. In the present study, a trinitrobenzene sulfonic acid (TNBS)-induced colitis rat model was used to mimic the human inflammatory bowel disease Crohn’s disease (CD). Urine samples from a control group (n=3), a TNBS 2-day group (n=3) and a TNBS 7-day group (n=3) were analyzed for candidate biomarker discovery by label-free and TMT-labeled proteomic quantitative methods. Seventy-seven urinary proteins were significantly changed in the colitis rats compared with that in the controls. These proteins were further validated by parallel reaction monitoring (PRM) targeted proteomic quantitative methods. Urine samples from the control group (n=8), the TNBS 2-day group (n=11) and the TNBS 7-day group (n=11) were analyzed by PRM. This led to the identification of 9 significantly differential expressed urinary proteins: CAH1, G3P, MMP-8, MANBA, NGAL, RNS1G, SLC31, S6A18, and TMM27. Based on the human protein tissue atlas, CAH1, RNS1G and SLC31 are highly enriched in the gastrointestinal tract. Among the 9 PRM-validated proteins, CAH1, MMP-8 and NGAL were previously reported as IBD-associated proteins (all exhibiting consistent trends with our observation), whereas the others are newly discovered by this study. Our results provide valuable clues for future study of urine biomarker of inflammatory bowel disease and Crohn’s disease.
Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat
Authors: Shaffer Jill A. , Roth Cali L. , Mushet David M.
Published: May 2018

Birds are essential components of most ecosystems and provide many services valued by society. However, many populations have undergone striking declines as habitats have been lost or degraded by human activities. Terrestrial grasslands are vital habitat for birds in the North American Prairie Pothole Region (PPR), but grassland conversion and fragmentation from agriculture and energy-production activities have destroyed or degraded millions of hectares. Conservation grasslands can provide alternate habitat. In the United States, the Conservation Reserve Program (CRP) is the largest program maintaining conservation grasslands on agricultural lands, but conservation grasslands in the PPR have declined by over 1 million ha since the program’s zenith in 2007. We used an ecosystem-services model (InVEST) parameterized for the PPR to quantify grassland-bird habitat remaining in 2014 and to assess degradation status of this remaining habitat as influenced by crop and energy (i.e., oil, natural gas, and wind) production. We compared our resultant habitat-quality ratings to grassland-bird abundance data from the North American Breeding Bird Survey to confirm that ratings were related to grassland-bird abundance. Of the grassland-bird habitat remaining in 2014, about 18% was degraded by nearby crop production, whereas energy production degraded an additional 16%. We further quantified changes in availability of grassland-bird habitat under various land-cover scenarios representing incremental losses (10%, 25%, 50%, 75%, and 100%) of CRP grasslands from 2014 levels. Our model identified 1 million ha (9%) of remaining grassland-bird habitat in the PPR that would be lost or degraded if all CRP conservation grasslands were returned to crop production. In addition to direct losses, an economic climate favoring energy and commodity production over conservation has resulted in substantial degradation of remaining grassland-bird habitat across the PPR. Other grassland regions of the world face similar challenges in maintaining avian habitat.
Reinterpretation of the localization of the ATP binding cassette transporter ABCG1 in insulin-secreting cells and insights regarding its trafficking and function
Authors: Harris Megan T. , Hussain Syed Saad , Inouye Candice M. , Castle Anna M. , Castle J. David
Published: May 2018

The ABC transporter ABCG1 regulates intracellular cholesterol. We showed previously that ABCG1 deficiency inhibits insulin secretion by pancreatic beta cells and, based on its immunolocalization to insulin granules, proposed its essential role in forming cholesterol-enriched granule membranes. While we confirm elsewhere that ABCG1, alongside ABCA1 and oxysterol binding protein OSBP, supports insulin granule formation, the aim here is to update our localization and to provide added insight regarding ABCG1’s trafficking and sites of function. We show that stably expressed GFP-tagged ABCG1 closely mimics the distribution of endogenous ABCG1 in pancreatic INS1 cells and accumulates in the trans-Golgi network (TGN), endosomal recycling compartment (ERC) and on the cell surface but not on insulin granules, early or late endosomes. Notably, ABCG1 is short-lived, and proteasomal and lysosomal inhibitors both decrease its degradation. Following blockade of protein synthesis, GFP-ABCG1 first disappears from the ER and TGN and later from the ERC and plasma membrane. Beyond aiding granule formation, our findings raise the prospect that ABCG1 may act beyond the TGN to regulate activities involving the endocytic pathway, especially as the amount of transferrin receptor is increased in ABCGI-deficient cells. Thus, ABCG1 may function at multiple intracellular sites and the plasma membrane as a roving sensor and modulator of cholesterol distribution and membrane trafficking.