bluuebunny/crossref_metadata_2025 huggingface dataset:
reactIDR: Evaluation of the statistical reproducibility of high-throughput structural analyses for a robust RNA reactivity classification
Authors: Kawaguchi Risa , Kiryu Hisanori , Iwakiri Junichi , Sese Jun
Published: March 2018

Motivation

Recently, next-generation sequencing techniques have been applied for the detection of RNA secondary structures called high-throughput RNA structural (HTS) analy- sis, and dozens of different protocols were used to detect comprehensive RNA structures at single-nucleotide resolution. However, the existing computational analyses heavily depend on experimental data generation methodology, which results in many difficulties associated with statistically sound comparisons or combining the results obtained using different HTS methods.

Results

Here, we introduced a statistical framework, reactIDR, which is applicable to the experimental data obtained using multiple HTS methodologies, and it classifies the nucleotides into three structural categories, stem, loop, and unmapped. reactIDR uses the irreproducible discovery rate (IDR) with a hidden Markov model (HMM) to discriminate accurately between the true and spurious signals obtained in the replicated HTS experiments. In reactIDR, IDR and HMM parameters are efficiently optimized by using an expectation-maximization algorithm. Furthermore, if known reference structures are given, a supervised learning can be applicable in a semi-supervised manner. The results of our analyses for real HTS data showed that reactIDR achieved the highest accuracy in the classification problem of stem/loop structures of rRNA using both individual and integrated HTS datasets as well as the best correspondence with the three-dimensional structure. Because reactIDR is the first method to compare HTS datasets obtained from multiple sources in a single unified model, it has a great potential to increase the accuracy of RNA secondary structure prediction at transcriptome-wide level with further experiments performed.

Availability

reactIDR is implemented in Python. Source code is publicly available at https://github.com/carushi/reactIDRhttps://github.com/carushi/reactIDR.

Contact

kawaguchi-rs@aist.go.jp

Supplementary information

Supplementary data are available at online.
Protease target prediction via matrix factorization
Authors: Marini Simone , Vitali Francesca , Rampazzi Sara , Demartini Andrea , Akutsu Tatsuya
Published: March 2018

Motivation

Protein cleavage is an important cellular event, involved in a myriad of processes, from apoptosis to immune response. Bioinformatics provides in silico tools, such as machine learning-based models, to guide target discovery. State-of-the-art models have a scope limited to specific protease families (such as Caspases), and do not explicitly include biological or medical knowledge (such as the hierarchical protein domain similarity, or gene-gene interactions). To fill this gap, we present a novel approach for protease target prediction based on data integration.

Results

By representing protease-protein target information in the form of relational matrices, we design a model that: (a) is general, i.e., not limited to a single protease family; and (b) leverages on the available knowledge, managing extremely sparse data from heterogeneous data sources, including primary sequence, pathways, domains, and interactions from nine databases. When compared to other algorithms on test data, our approach provides a better performance even for models specifically focusing on a single protease family.

Availability

https://gitlab.com/smarini/MaDDA/ (Matlab code and utilized data.)

Contact

smarini@med.umich.edu, or takutsu@kuicr.kyoto-u.ac.jp
CELLector: Genomics Guided Selection of Cancer in vitro Models
Authors: Najgebauer Hanna , Yang Mi , Francies Hayley E , Pacini Clare , Stronach Euan A , Garnett Mathew J , Saez-Rodriguez Julio , Iorio Francesco
Published: March 2018

The selection of appropriate cancer models is a key prerequisite for maximising translational potential and clinical relevance of in vitro oncology studies. We developed CELLector: a computational method (implemented in an open source R Shiny application and R package) allowing researchers to select the most relevant cancer cell lines in a patient-genomic guided fashion. CELLector leverages tumour genomics data to identify recurrent sub-types with associated genomic signatures. It then evaluates these signatures in cancer cell lines to rank them and prioritise their selection. This enables users to choose appropriate models for inclusion/exclusion in retrospective analyses and future studies. Moreover, this allows bridging data from cancer cell line screens to precisely defined sub-cohorts of primary tumours. Here, we demonstrate usefulness and applicability of our method through example use cases, showing how it can be used to prioritise the development of new in vitro models and to effectively unveil patient-derived multivariate prognostic and therapeutic markers.
Obesogenic diet exposure alters uterine natural killer cell biology and impairs vasculature remodeling in mice
Authors: Baltayeva Jennet , Konwar Chaini , Castellana Barbara , Mara Danielle , Christians Julian K , Beristain Alexander G
Published: March 2018

Pre-pregnancy obesity associates with adverse reproductive outcomes that impact maternal and fetal health. While obesity-driven mechanisms linked to poor pregnancy outcomes remain unclear, it is possible that obesity affects local uterine immune cells. Uterine immune cells, particularly uterine natural killer cells (uNK), play central roles in orchestrating developmental events in pregnancy. However, the effect of obesity on uNK biology is poorly understood. Using a high fat/high sugar diet (HFD) obesogenic mouse model, we set out to examine the effects of maternal obesity on uNK composition and establishment of the maternal-fetal interface. HFD exposure resulted in weight gain-dependent increases in systemic inflammation and rates of fetal resorption. Within HFD mice, both weight gain-dependent (diet-induced obese; DIO) and -independent (DIO-resistant; DIO-R) effects on natural cytotoxicity receptor-1 frequency and uNK activity were observed. Importantly, HFD-associated changes in uNK coincided with impairments in uterine artery remodeling in mid but not late pregnancy. Comparison of uNK mRNA transcripts in control diet mice to gene signatures in DIO or DIO-R identified differentially expressed genes that play roles in promoting activity/cytotoxicity and impeding vascular biology. Together, this work provides new insight into how obesity, and particularly how diet-induced weight-gain, may impact uNK processes important in pregnancy.
Method for Improving Psychophysical Threshold Estimates by Detecting Sustained Inattention
Authors: Rinderknecht Mike D. , Ranzani Raffaele , Popp Werner L. , Lambercy Olivier , Gassert Roger
Published: March 2018

Psychophysical procedures are applied in various fields to assess sensory thresholds. During experiments, sampled psychometric functions are usually assumed to be stationary. However, perception can be altered, for example by loss of attention to the presentation of stimuli, leading to biased data which results in poor threshold estimates. The few existing approaches attempting to identify non-stationarities either detect only whether there was a change in perception, or are not suitable for experiments with a relatively small number of trials (e.g., < 300). We present a method to detect inattention periods on a trial-by-trial basis to improve threshold estimates in psychophysical experiments using the adaptive sampling procedure Parameter Estimation by Sequential Testing (PEST). The performance of the algorithm was evaluated in computer simulations modeling inattention, and tested in a behavioral experiment on proprioceptive difference threshold assessment in 20 stroke patients, a population where attention deficits are likely to be present. Simulations showed that estimation errors could be reduced by up to 77% for inattentive subjects, even in sequences with less than 100 trials. In the behavioral data, inattention was detected in 14% of assessments, and applying the proposed algorithm resulted in reduced test-retest variability in 73% of these corrected assessments pairs. The algorithm complements existing approaches and can be adapted to sampling procedures other than PEST. Besides being applicable post-hoc, it could also be used online to prevent collection of biased data. This could have important implications in assessment practice by shortening experiments and improving estimates.
Deep learning predicts tuberculosis drug resistance status from genome sequencing data
Authors: Chen Michael L. , Doddi Akshith , Royer Jimmy , Freschi Luca , Schito Marco , Ezewudo Matthew , Kohane Isaac S. , Beam Andrew , Farhat Maha
Published: March 2018

Background

The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinicalMycobacteriumtuberculosis isolates promises to circumvent the long wait times and limited scope of conventional phenotypic antimicrobial susceptibility, but gaps remain for predicting phenotype accurately from genotypic data.

Methods and Findings

Using targeted or whole genome sequencing and conventional drug resistance phenotyping data from 3,601Mycobacterium tuberculosisstrains, 1,228 of which were multidrug resistant, we investigated the use of machine learning to predict phenotypic drug resistance to 10 anti-tuberculosis drugs. The final model, a multitask wide and deep neural network (MD-WDNN), achieved improved high predictive performance: the average AUCs were 0.979 for first-line drugs and 0.936 for second-line drugs during repeated cross-validation. On an independent validation set, the MD-WDNN showed average AUCs, sensitivities, and specificities, respectively, of 0.937, 87.9%, and 92.7% for first-line drugs and 0.891, 82.0% and 90.1% for second-line drugs. In addition to being able to learn from samples that have only been partially phenotyped, our proposed multidrug architecture shares information across different anti-tuberculosis drugs and genes to provide a more accurate phenotypic prediction. We uset-distributed Stochastic Neighbor Embedding (t-SNE) visualization and feature importance analyses to examine inter-drug similarities.

Conclusions

Machine learning is capable of accurately predicting resistant status using genomic information and holds promise in bringing sequencing technologies closer to the bedside.
Interplay of size and shape in miniaturized land snails
Authors: Örstan Aydin
Published: March 2018

The distribution of the mean greater shell dimensions of 2446 genera of stylommatophoran land snails consists of two groups peaking at 3 mm and 15.3 mm. The 3-mm group includes the miniature snails whose adult shell dimensions range from almost 0.8 mm to less than 1.5 mm. Relative surface area, shell thickness and egg size are discussed as potential factors that may limit the minimum shell dimensions. To obtain uniform distributions, the shell shape is expressed as the expanse angle, defined as the apex angle of a right triangle the height and the base of which are the shell height and diameter, respectively. In terms of expanse angles there are three shell shapes: tall (< 40°), flat (> 50°) and roughly equiaxial (40°-50°). The variation of shell shape with size was analyzed within the morphospace they form. At shell dimensions above 10 mm the lowest expanse angle is about 10°. Below 10 mm, the lower limit of the expanse angle increases as shells get smaller. As a result, no miniature species has a tall shell. It is proposed that two evolutionary functional constraints render small and narrow shells of miniaturized snails nonadaptive. These are the requirements to reduce surface areas to decrease water loss and to have enough volume and a wide enough body whorl to accommodate at least one egg.
Channelrhodopsin variants engage distinct patterns of network activity
Authors: Jun Na Young , Cardin Jessica A.
Published: March 2018

Channelrhodopsins (ChRs) are light-gated ion channels that enable cell type-specific activation of neurons or neural circuits. Channelrhodopsin-2 has been widely used as a tool to probe circuit function in vitro and in vivo. Several recently developed ChR variants are characterized by faster kinetics and reduced desensitization. However, little is known about how their varying properties may regulate their interaction with local network dynamics. We compared ChR-evoked patterns of multi-unit activity and local field potentials in primary visual cortex of mice expressing three ChR variants with distinct temporal profiles: Chronos, Chrimson, and ChR2. We assessed overall activation of by measuring the amplitude and temporal progression of evoked spiking. Using gamma-range (30-80Hz) LFP power as an assay for local network engagement, we examined the recruitment of cortical network activity by each tool. All ChR variants caused light-evoked increases in firing in vivo, but each demonstrated different temporal patterning of evoked activity. In addition, the three ChRs had distinct effects on cortical gamma-band activity. Our findings suggest that variations in the kinetics of optogenetic tools can substantially affect their efficacy in neural networks in vivo, as well as the manner in which their activation engages circuit resonance.
Strong Episodic Selection for Natural Competence for Transformation Due to Host-Pathogen Dynamics
Authors: Palmer Nathan D. , Cartwright Reed A.
Published: March 2018

Sexual recombination only occurs in eukaryotes; however, many bacteria can actively recombine with environmental DNA. This behavior, referred to as transformation, has been described in many species from diverse taxonomic backgrounds. Transformation is hypothesized to carry some selective advantages similar to those postulated for meiotic sex in eukaryotes. However, the accumulation of loss-of-function alleles at transformation loci and an increased mutational load from recombining with DNA from dead cells create additional costs to transformation. These costs have been shown to outweigh many of the benefits of recombination under a variety of likely parameters. We investigate an additional proposed benefit of sexual recombination, the Red Queen hypothesis, as it relates to bacterial transformation. Here we describe a model showing that host-pathogen coevolution may provide a large selective benefit to transformation and allow transforming cells to invade an environment dominated by otherwise equal non-transformers. Furthermore, we observe that host-pathogen dynamics cause the selection pressure on transformation to vary extensively in time, potentially explaining the tight regulation and wide variety of rates observed in naturally competent bacteria. Host-pathogen dynamics may explain the evolution and maintenance of natural competence despite its associated costs.
In vitro transcribed guide RNAs trigger an innate immune response via the RIG-I pathway
Authors: Wienert Beeke , Shin Jiyung , Zelin Elena , Pestal Kathleen , Corn Jacob E.
Published: March 2018

CRISPR-Cas9 genome editing is revolutionizing fundamental research and has great potential for the treatment of many diseases. While editing of immortalized cell lines has become relatively easy, editing of therapeutically relevant primary cells and tissues can remain challenging. One recent advancement is the delivery of a Cas9 protein and an in vitro transcribed (IVT) guide RNA (gRNA) as a precomplexed ribonucleoprotein (RNP). This approach allows editing of primary cells such as T cells and hematopoietic stem cells, but the consequences beyond genome editing of introducing foreign Cas9 RNPs into mammalian cells are not fully understood. Here we show that the IVT gRNAs commonly used by many laboratories for RNP editing trigger a potent innate immune response that can be several thousand times stronger than benchmark immune stimulating ligands. IVT gRNAs are recognized in the cytosol through the RIG-I pathway but not the MDA5 pathway, thereby triggering a type I interferon response. Removal of the 5’-triphosphate from gRNAs ameliorates inflammatory signaling and prevents the loss of viability associated with genome editing in hematopoietic stem cells. The potential for Cas9 RNP editing to induce a potent antiviral response indicates that care must be taken when designing therapeutic strategies to edit primary cells.

Abbreviations

Cas

CRISPR-associated

CIP

calf intestinal alkaline phosphatase

CRISPR

clustered, regularly interspaced, short palindromic repeat

dCas9

nuclease-dead Cas9

HEK293

Human embryonic kidney cells 293

HEK293T

Human embryonic kidney cells 293 SV40 large T antigen

HeLa

Henrietta Lacks cells

HSPCs

CD34+ human hematopoietic stem and progenitor cells

IFNAR1

Interferon Alpha And Beta Receptor Subunit 1

IFNβ/IFNB1

Interferon beta

ISG15

Interferon-stimulated gene 15 IVT – in vitro transcribed

KO

knockout

MAVS

mitochondrial activator of virus signaling

MDA5/IFIH1

melanoma differentiation-associated gene 5/ Interferon Induced with Helicase C Domain 1

PAMP

pathogen-associated molecular pattern

RIG-I/DDX58

retinoic acid-inducible gene I/ DExD-H-box helicase 58

gRNA

guide RNA

SPRI

solid phase reversible immobilization

WT

wild type
Co-option of neurotransmitter signaling for inter-organismal communication in C. elegans
Authors: Chute Christopher D. , DiLoreto Elizabeth M. , Zhang Ying K. , Rayes Diego , Coyle Veronica L. , Choi Hee June , Alkema Mark J. , Schroeder Frank C. , Srinivasan Jagan
Published: March 2018

Biogenic amine neurotransmitters play a central role in metazoan biology, and both their chemical structures and cognate receptors are evolutionarily conserved. Their primary roles are in intra-organismal signaling, whereas biogenic amines are not normally recruited for communication between separate individuals. Here, we show that in C. elegans, a neurotransmitter-sensing G protein-coupled receptor, TYRA-2, is required for avoidance responses to osas#9, an ascaroside pheromone that incorporates the neurotransmitter octopamine. Neuronal ablation, cell-specific genetic rescue, and calcium imaging show that tyra-2 expression in the nociceptive neuron ASH is necessary and sufficient to induce osas#9 avoidance. Ectopic expression in the AWA neuron, which is generally associated with attractive responses, reverses the response to osas#9, resulting in attraction instead of avoidance behavior, confirming that TYRA-2 partakes in sensing osas#9. The TYRA-2/osas#9 signaling system thus represents an inter-organismal communication channel that evolved via co-option of a neurotransmitter and its cognate receptor.
Enterococcus faecalisAHG0090 is a genetically tractable bacterium and produces a secreted peptidic bioactive that suppresses NF-kB activation in human gut epithelial cells
Authors: Cuív Páraic Ó , Giria Rabina , Hoedt Emily C. , McGuckin Michael A. , Begun Jakob , Morrison Mark
Published: March 2018

Enterococcus faecalisis an early coloniser of the human infant gut and contributes to the development of intestinal immunity. To better understand the functional capacity ofE. faecaliswe constructed a broad host range RP4 mobilisable vector, pEHR513112, that confers chloramphenicol resistance and used a metaparental mating approach to isolateE. faecalisAHG0090 from a faecal sample collected from a healthy human infant. We demonstrated thatE. faecalisAHG0090 is genetically tractable and could be manipulated using traditional molecular microbiology approaches.E. faecalisAHG0090 was comparable to the gold-standard anti-inflammatory bacteriumFaecalibacterium prausnitziiA2-165 in its ability to suppress cytokine mediated NF-КB activation in human gut derived LS174T goblet cell-like and Caco-2 enterocyte-like cell lines.E. faecalisAHG0090 andF. prausnitziiA2-165 produced secreted low molecular weight NF-КB suppressive peptidic bioactives. Both bioactives were sensitive to heat and proteinase K treatments although theE. faecalisAHG0090 bioactive was more resilient to both forms of treatment. As expected,E. faecalisAHG0090 suppressed IL-1β induced NF-КB-p65 subunit nuclear translocation and expression of the NF-КB regulated genes IL-6, IL-8 and CXCL-10. Finally, we determined thatE. faecalisAHG0090 is distantly related to other commensal strains and likely encodes niche factors that support effective colonisation of the infant gut.
The latency of a visual evoked potential tracks the onset of decision making
Authors: Nunez Michael D. , Gosai Aishwarya , Vandekerckhove Joachim , Srinivasan Ramesh
Published: March 2018

Encoding of a sensory stimulus is believed to be the first step in perceptual decision making. Previous research has shown that electrical signals recorded from the human brain track evidence accumulation during perceptual decision making (Gold and Shadlen, 2007; O’Connell et al., 2012; Philiastides et al., 2014). In this study we directly tested the hypothesis that the latency of the N200 recorded by EEG (a negative peak occurring between 150 and 275 ms after stimulus presentation in human participants) reflects the visual encoding time (VET) required for completion of figure-ground segregation before evidence accumulation. We show that N200 latencies vary across individuals, are modulated by external visual noise, and increase response time byxmilliseconds when they increase byxmilliseconds, reflecting a linear regression slope of 1. Simulations of cognitive decision-making theory show that variation in human response times not related to evidence accumulation (including VET) are tracked by the fastest response times. A relationship with a slope of 1 between N200 latencies and VET was found by fitting a linear model between trial-averaged N200 latencies and the 10th percentiles of response times. A slope of 1 was also found between single-trial N200 latencies and response times. Fitting a novel neuro-cognitive model of decision-making also yielded a slope of 1 between N200 latency and non-decision time in multiple visual noise conditions, indicating that N200 latencies track the completion of visual encoding and the onset of evidence accumulation. The N200 waveforms were localized to the cortical surface at distributed temporal and extrastriate locations, consistent with a distributed network engaged in figure-ground segregation of the target stimulus.

Significance Statement

Encoding of a sensory stimulus is believed to be the first step in perceptual decision making. In this study, we report evidence that visual evoked potentials (EPs) around 200 ms after stimulus presentation track the time of visual figure-ground segregation before the onset of evidence accumulation during decision making. These EP latencies vary across individuals, are modulated by external visual noise, and increase response time byxmilliseconds when they increase byxmilliseconds. Hierarchical Bayesian model-fitting was also used to relate these EPs to a specific cognitive parameter that tracks time related to visual encoding in a decision-making model of response time. This work adds to the growing literature that suggests that EEG signals can track the component cognitive processes of decision making.
Task-evoked pupil responses reflect internal belief states
Authors: Colizoli O. , de Gee J.W. , Urai A.E. , Donner T.H.
Published: March 2018

Perceptual decisions about the state of the environment are often made in the face of uncertain evidence. Internal uncertainty signals are considered important regulators of learning and decision-making. A growing body of work has implicated the brain’s arousal systems in uncertainty signaling. Here, we found that two specific computational variables, postulated by recent theoretical work, evoke boosts of arousal at different times during a perceptual decision: decision confidence (the observer’s internally estimated probability that a choice was correct given the evidence) before feedback, and prediction errors (deviations from expected reward) after feedback. We monitored pupil diameter, a peripheral marker of central arousal state, while subjects performed a challenging perceptual choice task with a delayed monetary reward. We quantified evoked pupil responses during decision formation and after reward-linked feedback. During both intervals, decision difficulty and accuracy had interacting effects on pupil responses. Pupil responses negatively scaled with decision confidence prior to feedback and scaled with uncertainty-dependent prediction errors after feedback. This pattern of pupil responses during both intervals was in line with a model using the observer’s graded belief about choice accuracy to anticipate rewards and compute prediction errors. We conclude that pupil-linked arousal systems are modulated by internal belief states.
Differences in cognitive functions between cytomegalovirus-infected and cytomegalovirus-free university students: a case control study
Authors: Chvátalová Veronika , Šebánková Blanka , Hrbáčková Hana , Tureček Petr , Flegr Jaroslav
Published: March 2018

Cytomegalovirus (CMV) is the herpetic virus, which infects 45 – 100% people worldwide. Many reports suggest that CMV could impair cognitive functions of infected subjects. Here we searched for indices of effects of CMV on infected subjects’ intelligence and knowledge. The Intelligence Structure Test I-S-T 2000 R was used to compare IQ of 148 CMV-infected and 135 CMV-free university students. Infected students expressed higher intelligence. Paradoxically, their IQ decreased with decreasing concentration of anti-CMV antibodies, which can be used, statistically, as a proxy of the time passed from the moment of infection in young subjects when the age of subjects is statistically controlled. The paradox of seemingly higher intelligence of CMV infected subjects could be explained by the presence of the subpopulation of about 5 – 10 % CMV-positive individuals in the population of “CMV-negative students”. These false negative subjects had probably not only the oldest infections and therefore the lowest concentration of anamnestic antibodies, but also the lowest intelligence among the infected students. Prevalence of CMV infection in all countries is very high, approaching sometimes 90 %. Therefore, the total impact of CMV on human intelligence may be large.
Depressiveness and Neuroticism in Bartonella Seropositive and Seronegative Subjects – Preregistered Case-Controls Study
Authors: Flegr Jaroslav , Preiss Marek , Balatova Pavla
Published: March 2018

Several recent studies have demonstrated the association of cat-related injuries with major depression and with depressiveness in the general population. It was suggested that cat-scratch disease, the infection with the bacteriumBartonella henselae, can be responsible for the observed association. However, no direct evidence for the role of theBartonellainfection in this association has been published until now. In this preregistered case-controls study performed on 250 healthy subjects tested earlier for the presence of anti-ToxoplasmaIgG antibodies, we searched for the positive association between presence of anamnestic anti-BartonellaIgG antibodies and depressiveness measured with Beck II inventory, depression subscale of neuroticism measured with N-70 questionnaire, and self-reported health problems. We found that thatBartonella-seropositivity was positively correlated with Beck depression only inToxoplasma-seronegative men and negatively correlated with health inToxoplasma-seronegative women.Bartonellaseropositivity expressed protective effects againstToxoplasmaseropositivity-associated increased neuroticism in men whileToxoplasma-seropositivity expressed protective effects againstBartonellaseropositivity-associated health problems in women. A comparison of the patterns of association of mental and physical health problems withBartonellaseropositivity and with reported cat-related injury suggests that different factor, possibly infection with different pathogen transmitted by cat related-injuries than theBartonella henselae, is responsible for the observed association of cat related-injuries with depressiveness and major depression. The existence of complex interactions betweenBartonellaseropositivity,Toxoplasmaseropositivity, and sex also suggest that the effect of symbionts on the host’s phenotype must by always studied in the context of other infections, and separately for men and women.
Task-induced deactivation in diverse brain systems correlates with interindividual differences in distinct autonomic indices
Authors: Iacovella Vittorio , Faes Luca , Hasson Uri
Published: March 2018

Neuroimaging research has shown that different cognitive tasks induce relatively specific activation patterns, as well as less task-specific deactivation patterns. Here we examined whether individual differences in Autonomic Nervous System (ANS) activity during task performance correlate with the magnitude of task-induced deactivation. In an fMRI study, participants performed a continuous mental arithmetic task in a task/rest block design, while undergoing combined fMRI and heart / respiration rate acquisitions using photoplethysmograph and respiration belt. As expected, task performance increased heart-rate and reduced the RMSSD, a cardiac index related to vagal tone. Across participants, higher heart rate during task was linked to increased activation in fronto-parietal regions, as well as to stronger deactivation in ventromedial prefrontal regions. Respiration frequency during task was associated with similar patterns, but in different regions than those identified for heart-rate. Finally, in a large set of regions, almost exclusively limited to the Default Mode Network, lower RMSSD was associated with greater deactivation, and furthermore, the vast majority of these regions were task-deactivated at the group level. Together, our findings show that inter-individual differences in ANS activity are strongly linked to task-induced deactivation. Importantly, our findings suggest that deactivation is a multifaceted construct potentially linked to ANS control, because distinct ANS measures correlate with deactivation in different regions. We discuss the implications for current theories of cortical control of the ANS and for accounts of deactivation, with particular reference to studies documenting a “failure to deactivate” in multiple clinical states.
A synthetic, three-dimensional bone marrow hydrogel
Authors: Jansen Lauren E. , McCarthy Thomas P. , Lee Michael J. , Peyton Shelly R.
Published: March 2018

Three-dimensional (3D) synthetic hydrogels have recently emerged as desirablein vitrocell culture platforms capable of representing the extracellular geometry, elasticity, and water content of tissue in a tunable fashion. However, they are critically limited in their biological functionality. Hydrogels are typically decorated with a scant 1-3 peptide moieties to direct cell behavior, which vastly underrepresents the proteins found in the extracellular matrix (ECM) of real tissues. Further, peptides chosen are ubiquitous in ECM, and are not derived from specific proteins. We developed an approach to incorporate the protein complexity of specific tissues into the design of biomaterials, and created a hydrogel with the elasticity of marrow, and 20 marrow-specific cell-instructive peptides. Compared to generic PEG hydrogels, our marrow-inspired hydrogel improves stem cell differentiation and proliferation. We propose this tissue-centric approach as the next generation of 3D hydrogel design for applications in tissue engineering.
Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning
Authors: Shvets Alexey A. , Rakhlin Alexander , Kalinin Alexandr A. , Iglovikov Vladimir I.
Published: March 2018

Semantic segmentation of robotic instruments is an important problem for the robot-assisted surgery. One of the main challenges is to correctly detect an instrument’s position for the tracking and pose estimation in the vicinity of surgical scenes. Accurate pixel-wise instrument segmentation is needed to address this challenge. In this paper we describe our deep learning-based approach for robotic instrument segmentation. Our approach demonstrates an improvement over the state-of-the-art results using several novel deep neural network architectures. It addressed the binary segmentation problem, where every pixel in an image is labeled as an instrument or background from the surgery video feed. In addition, we solve a multi-class segmentation problem, in which we distinguish between different instruments or different parts of an instrument from the background. In this setting, our approach outperforms other methods for automatic instrument segmentation thereby providing state-of-the-art results for these problems. The source code for our solution is made publicly available.
The Rumen Metatranscriptome Landscape Reflects Dietary Adaptation and Methanogenesis in Lactating Dairy Cows
Authors: Hornung Bastian , den Bogert Bartholomeus van , Davids Mark , Martins dos Santos Vitor A.P. , Plugge Caroline M. , Schaap Peter J. , Smidt Hauke
Published: March 2018

Methane eructed by ruminant animals is a main contributor to greenhouse gas emissions and is solely produced by members of the phylumEuryarchaeotawithin the domainArchaea. Methanogenesis depends on the availability of hydrogen, carbon dioxide, methanol and acetate produced, which are metabolic products of anaerobic microbial degradation of feed-derived fibers. Changing the feed composition of the ruminants has been proposed as a strategy to mitigate methanogenesis of the rumen microbiota.

We investigated the impact of corn silage enhanced diets on the rumen microbiota of rumen-fistulated dairy cows, with a special focus on carbohydrate breakdown and methanogenesis. Metatranscriptome analysis of rumen samples taken from animals fed corn silage enhanced diets revealed that genes involved in starch metabolism were significantly more expressed while archaeal genes involved in methanogenesis showed lower expression values. The nutritional intervention also influenced the cross-feeding betweenArchaeaandBacteria.

The results indicate that the ruminant diet is important in methanogenesis. The diet-induced changes resulted in a reduced methane emission. The metatranscriptomic analysis provided insights into key underlying mechanisms and opens the way for new rational methods to further reduce methane output of ruminant animals.
Integrating cross-linking experiments withab initioprotein-protein docking
Authors: Vreven Thom , Schweppe Devin K. , Chavez Juan D. , Weisbrod Chad R. , Shibata Sayaka , Zheng Chunxiang , Bruce James E. , Weng Zhiping
Published: March 2018

Ab initioprotein-protein docking algorithms often rely on experimental data to identify the most likely complex structure. We integrated protein-protein docking with the experimental data of chemical cross-linking followed by mass spectrometry. We tested our approach using 12 cases that resulted from an exhaustive search of the Protein Data Bank for protein complexes with cross-links identified in our experiments. We implemented cross-links as constraints based on Euclidean distance or void-volume distance. For most test cases the rank of the top-scoring near-native prediction was improved by at least two fold compared with docking without the cross-link information, and the success rates for the top 5 and top 10 predictions doubled. Our results demonstrate the delicate balance between retaining correct predictions and eliminating false positives. Several test cases had multiple components with distinct interfaces, and we present an approach for assigning cross-links to the interfaces. Employing the symmetry information for these cases further improved the performance of complex structure prediction.

Highlights

Incorporating low-resolution cross-linking experimental data in protein-protein docking algorithms improves performance more than two fold.

Integration of protein-protein docking with chemical cross-linking reveals information on the configuration of higher order complexes.

Symmetry analysis of protein-protein docking results improves the predictions of multimeric complex structures
Age differences in head motion and estimates of cortical morphology
Authors: Madan Christopher R.
Published: March 2018

Cortical morphology is known to differ with age, as measured by cortical thickness, fractal dimensionality, and gyrification. However, head motion during MRI scanning has been shown to influence estimates of cortical thickness as well as increase with age. Studies have also found task-related differences in head motion and relationships between body-mass index (BMI) and head motion. Here I replicated these prior findings, as well as several others, within a large, open-access dataset (Centre for Ageing and Neuroscience, CamCAN). This is a larger dataset than these results have been demonstrated previously, within a sample size of more than 600 adults across the adult lifespan. While replicating prior findings is important, demonstrating these key findings concurrently also provides an opportunity for additional related analyses: Critically, I test for the influence of head motion on cortical fractal dimensionality and gyrification; effects were statistically significant in some cases, but small in magnitude.
Bacterial swarming reducesProteus mirabilisandVibrio parahaemolyticuscell stiffness and increases β-lactam susceptibility
Authors: Auer George K. , Oliver Piercen M. , Rajendram Manohary , Lin Ti-Yu , Yao Qing , Jensen Grant J. , Weibel Douglas B.
Published: March 2018

Swarmer cells of the gram-negative pathogenic bacteriaProteus mirabilisandVibrio parahaemolyticusbecome long (>10-100 μm) and multinucleate during their growth and motility on polymer surfaces. We demonstrate increasing cell length is accompanied by a large increase in flexibility. Using a microfluidic assay to measure single-cell mechanics, we identified large differences in swarmer cell stiffness of (bending rigidity ofP. mirabilis, 9.6 × 10−22N m2;V. parahaemolyticus, 9.7 × 10−23N m2) compared to vegetative cells (1.4 × 10−20N m2and 3.2 × 10−22N m2, respectively). The reduction in bending rigidity (~3-15 fold) was accompanied by a decrease in the average polysaccharide strand length of the peptidoglycan layer of the cell wall from 28-30 to 19-22 disaccharides. Atomic force microscopy revealed a reduction inP. mirabilispeptidoglycan thickness from 1.5 nm (vegetative) to 1.0 nm (swarmer) and electron cryotomography indicated changes in swarmer cell wall morphology.P. mirabilisandV. parahaemolyticusswarmer cells became increasingly sensitive to osmotic pressure and susceptible to cell wall-modifying antibiotics (compared to vegetative cells)—they were ~30% more likely to die after 3 h of treatment with minimum inhibitory concentrations of the β-lactams cephalexin and penicillin G. The adaptive cost of swarming is offset by the increase in cell susceptibility to physical and chemical changes in their environment, thereby suggesting the development of new chemotherapies for bacteria that leverage swarming for colonization of hosts and survival.

Importance

Proteus mirabilisandVibrio parahaemolyticusare bacteria that infect humans. To adapt to environmental changes, these bacteria alter their cell morphology and move collectively to access new sources of nutrients in a process referred to as ‘swarming’. We found that a change in the composition and thickness of the peptidoglycan layer of the cell wall makes swarmer cells ofP. mirabilisandV. parahaemolyticusmore flexible (i.e., reduced cell stiffness) and increases their sensitivity to osmotic pressure and cell-wall targeting antibiotics (e.g., β-lactams). These results highlight the importance of assessing the extracellular environment in determining antibiotic doses and the use of β-lactams antibiotics for treating infections caused by swarmer cells ofP. mirabilisandV. parahaemolyticus.
Adrenergic agonist induces rhythmic firing in quiescent cardiac preganglionic neurons in nucleus ambiguous via activation of intrinsic membrane excitability
Authors: Aiba Isamu , Noebels Jeffrey L.
Published: March 2018

Cholinergic vagal nerves projecting from neurons in the brainstem nucleus ambiguus (NAm) play a predominant role in cardiac parasympathetic pacemaking control. Central adrenergic signaling modulates the tone of this vagal output; however the exact excitability mechanisms are not fully understood. We investigated responses of NAm neurons to adrenergic agonists using in vitro mouse brainstem slices. Preganglionic NAm neurons were identified by Chat-tdtomato fluorescence in young adult transgenic mice and their cardiac projection confirmed by retrograde dye tracing. Juxtacellular recordings detected sparse or absent spontaneous action potentials (AP) in NAm neurons. However bath application of epinephrine or norepinephrine strongly and reversibly activated most NAm neurons regardless of their basal firing rate. Epinephrine was more potent than norepinephrine, and this activation largely depends on α1-adrenoceptors. Interestingly, adrenergic activation of NAm neurons does not require an ionotropic synaptic mechanism, since postsynaptic excitatory or inhibitory receptor blockade did not occlude the excitatory effect, and bath-applied adrenergic agonists did not alter excitatory or inhibitory synaptic transmission. Instead, adrenergic agonists significantly elevated intrinsic membrane excitability to facilitate generation of recurrent action potentials. T-type calcium current (ICaT) and hyperpolarization-activated current (Ih) are involved in this excitation pattern, while not required for spontaneous AP induction by epinephrine. In contrast, pharmacological blockade of persistent sodium current (INaP) significantly inhibited the adrenergic effects. Our results demonstrate that central adrenergic signaling enhances the intrinsic excitability of NAm neurons, and persistent sodium current is required for this effect. This central balancing mechanism may counteract excessive peripheral cardiac excitation during increased sympathetic tone.

New & Noteworthy

Cardiac preganglionic cholinergic neurons in the Nucleus ambiguus (NAm) are responsible for slowing cardiac pacemaking. This study identified that adrenergic agonists can induce rhythmic action potentials in otherwise quiescent cholinergic NAm preganglionic neurons in brainstem slice preparation. The modulatory influence of adrenaline on central parasympathetic outflow may contribute to both physiological and deleterious cardiovascular regulation.
Intermediate filaments EXC-2 and IFA-4 Maintain Luminal Structure of the Tubular Excretory Canals inCaenorhabditis elegans
Authors: Al-Hashimi Hikmat I. , Hall David H. , Ackley Brian D. , Lundquist Erik A. , Buechner Matthew
Published: March 2018

The excretory canals ofCaenorhabditis elegansare a model for understanding the maintenance of apical morphology in narrow single-celled tubes. Light and electron microscopy shows that mutants inexc-2start to form canals normally, but these swell to develop large fluid-filled cysts that lack a complete terminal web at the apical surface, and accumulate filamentous material in the canal lumen. Here, whole-genome sequencing and gene rescue show thatexc-2encodes intermediate filament protein IFC-2. EXC-2/IFC-2 protein, fluorescently tagged via CRISPR/Cas9, is located at the apical surface of the canals independently of other intermediate filament proteins. EXC-2 is also located in several other tissues, though the tagged isoforms are not seen in the larger intestinal tube. Tagged EXC-2 binds via pulldown to intermediate filament protein IFA-4, which is also shown to line the canal apical surface. Overexpression of either protein results in narrow but shortened canals. These results are consistent with a model whereby three intermediate filaments in the canals, EXC-2, IFA-4, and IFB-1, restrain swelling of narrow tubules in concert with actin filaments that guide the extension and direction of tubule outgrowth, while allowing the tube to bend as the animal moves.

Article Summary

TheC. elegansexcretory canals form a useful model for understanding formation of narrow tubes.exc-2mutants start to form normal canals that then swell into fluid-filled cysts. We show thatexc-2encodes a large intermediate filament (IF) protein previously not thought to be located in the canals. EXC-2 is located at the apical (luminal) membrane, binds to another IF protein, and appears to be one of three IF proteins that form a flexible meshwork to maintain the thin canal diameter. This work provides a genetically useful model for understanding the interactions of IF proteins with other cytoskeletal elements to regulate tube size and growth.
Optogenetic reconstitution reveals that Dynein-Dynactin-NuMA clusters generate cortical spindle-pulling forces as a multi-arm ensemble
Authors: Okumura Masako , Natsume Toyoaki , Kanemaki Masato T. , Kiyomitsu Tomomi
Published: March 2018

To position the mitotic spindle within the cell, dynamic plus ends of astral microtubules are pulled by membrane-associated cortical force-generating machinery. However, in contrast to the chromosome-bound kinetochore structure, how the diffusion-prone cortical machinery is organized to generate large spindle-pulling forces remains poorly understood. Here, we develop a light-induced reconstitution system in human cells. We find that induced cortical targeting of NuMA, but not dynein, is sufficient for spindle pulling. This spindle-pulling activity requires dynein-dynactin recruitment/activation by NuMA’s N-terminal long arm, and NuMA’s direct microtubule-binding activities to achieve a multiplicity of microtubule interactions. Importantly, we demonstrate that cortical NuMA assembles specialized focal structures that cluster multiple force-generating modules to generate cooperative spindle-pulling forces. This clustering activity of NuMA is required for spindle positioning, but not for spindle-pole focusing. We propose that cortical Dynein-Dynactin-NuMA (DDN) clusters act as the core force-generating machinery that organizes a multi-arm ensemble reminiscent of the kinetochore.
Constructing and Visualizing Cancer Genomic Maps in 3D Spatial Context by Phenotype-based High-throughput Laser-aided Isolation and Sequencing (PHLI-seq)
Authors: Kim Sungsik , Lee Amos Chungwon , Lee Han-Byoel , Kim Jinhyun , Jung Yushin , Ryu Han Suk , Lee Yongju , Bae Sangwook , Lee Minju , Lee Kyungmin , Kim Ryong Nam , Park Woong-Yang , Han Wonshik , Kwon Sunghoon
Published: March 2018

A spatially resolved analysis of the heterogeneous cancer genome, in which the data are connected to the three-dimensional space of a tumour, is crucial to understand cancer biology and the clinical impact of cancer heterogeneity on patients. However, despite recent progress in spatially resolved transcriptomics, spatial mapping of genomic data in a high-throughput and high-resolution manner has been challenging due to current technical limitations. Here, we describe a novel approach, phenotype-based high-throughput laser-aided isolation and sequencing (PHLI-seq), which enables high-throughput isolation of a single-cell or a small number of cells and their genome-wide sequence analysis to construct genomic maps within cancer tissue in relation to the phenotypes of the cells. By applying PHLI-seq, we reveal the heterogeneity of breast cancer tissues at a high resolution and map the genomic landscape of the cells to their corresponding spatial locations and phenotypes in the tumour mass. Additionally, with different staining modalities, the genotypes of the cells can be connected to corresponding phenotypic information of the tissue. Together with the spatially resolved genomic analysis, we can infer the histories of heterogeneous cancer cells in two or three dimensions, providing significant insight into cancer biology and precision medicine.