bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic profile and functional proteomics of anal squamous cell carcinoma: proposal for a molecular classification
Authors: Trilla-Fuertes Lucía , Ghanem Ismael , Gámez-Pozo Angelo , Maurel Joan , G-Pastrián Laura , Mendiola Marta , Peña Cristina , López-Vacas Rocío , Prado-Vázquez Guillermo , López-Camacho Elena , Zapater-Moros Andrea , Heredia Victoria , Cuatrecasas Miriam , García-Alfonso Pilar , Capdevila Jaume , Conill Carles , García-Carbonero Rocío , Ramos-Ruiz Ricardo , Fortes Claudia , Llorens Carlos , Nanni Paolo , Fresno Vara Juan Ángel , Feliu Jaime
Published: October 2019

Background

Anal squamous cell carcinoma is a rare tumor. Chemo-radiotherapy yields a 50% 3-year relapse-free survival rate in advanced anal cancer, so improved predictive markers and therapeutic options are needed.

Methods

High-throughput proteomics and whole-exome sequencing were performed in 46 paraffin samples from anal squamous cell carcinoma patients. Hierarchical clustering was used to establish groupsde novo. Then, probabilistic graphical models were used to study the differences between groups of patients at the biological process level.

Results

A molecular classification into two groups of patients was established, one group with increased expression of proteins related to adhesion, T lymphocytes and glycolysis; and the other group with increased expression of proteins related to translation and ribosomes. The probabilistic graphical model showed that these two groups presented differences in metabolism, mitochondria, translation, splicing and adhesion processes. Additionally, these groups showed different frequencies of genetic variants in some genes, such asATM, SLFN11andDST. Finally, genetic and proteomic characteristics of these groups suggested the use of some possible targeted therapies, such as PARP inhibitors or immunotherapy.

Conclusions

In this study, a molecular classification of anal squamous cell carcinoma using high-throughput proteomics and whole-exome sequencing data was proposed. Moreover, differences between the two established groups suggested some possible therapies.
Trade Study of Population Age Groups for a Clinical Trial in Attention Deficit Hyperactivity Disorder
Authors: Lovinsand Dalton B. , Lodder Robert A.
Published: October 2019

ADHD is a neurodevelopmental disorder characterized by difficulty paying attention, impulsivity, and hyperactivity that is treated by an array of different modalities in order to decrease functional impairment. Despite the variety of available pharmacologic treatment options and their widespread use, there still remains a strong need to create innovative therapies. Game Based Therapy (GBT) is a type of cognitive behavioral therapy that seeks to increase the efficacy of currently available pharmacological treatments through improving cognitive deficits and reducing the current dose of such treatments. At the University of Kentucky, a clinical trial was implemented to assess the effects of combining stimulant pharmacotherapy with the popular video game Minecraft as Game Based Therapy on ADHD symptoms in children ages 10-15. However, the low subject recruitment played a large role in the trial failing to produce conclusive data from that site.

This trade study serves to address the difficulties of subject recruitment and determine an optimal population and location for future adoption of the clinical trial. Through statistical analysis of state, national, and survey data it was found that in Lexington, Kentucky, 18-21 year olds are the optimal population for future GBT with pharmacotherapy clinical trials.
Development of population and Bayesian models for applied use in patients receiving cefepime
Authors: Liu Jiajun , Neely Michael , Lipman Jeffrey , Sime Fekade , Roberts Jason , Kiel Patrick J , Avedissian Sean N. , Rhodes Nathaniel J. , Scheetz Marc H.
Published: October 2019

Understanding exposures of cefepime, a β-lactam antibiotic, is crucial for developing regimens to achieve optimal exposure and improved clinical outcomes. This study sought to develop and evaluate a unified population pharmacokinetic model in both pediatric and adult patients receiving cefepime treatment. Multiple physiologically relevant models were fit to pediatric and adult subject data. To evaluate the final model performance, a withheld group of twelve pediatric and two separate adult populations were assessed. Seventy subjects with a total of 604 cefepime concentrations were included in this study. All adults (n=34) on average weighed 82.7 kg and displayed a mean creatinine clearance (CrCL) of 106.7 mL/min. All pediatric subjects (n=36) had mean weight and CrCL of 16.0 kg and 195.64 mL/min, respectively. A covariate-adjusted two compartment model described the observed concentrations well (population model R2, 87.0%; Bayesian model R2, 96.5%). In the evaluation subsets, the model performed similarly well (population R2, 84.0%; Bayesian R2, 90.2%). The identified model serves well for population dosing and as a Bayesian prior for precision dosing.

Key points

A unified cefepime population pharmacokinetic model has been developed from adult and pediatric patients and evaluates well in independent populations.

When paired with real time beta-lactam assays, precision dosing approach will optimize drug exposure and improve clinical outcomes.
The interoceptive hippocampus: mouse brain endocrine receptor expression highlights a dentate gyrus (DG)–cornu ammonis (CA) challenge– sufficiency axis
Authors: Lathe Richard , Singadia Sheena , Jordan Crispin , Riedel Gernot
Published: October 2019

The primeval function of the mammalian hippocampus (HPC) remains uncertain. Implicated in learning and memory, spatial navigation, and neuropsychological disorders, evolutionary theory suggests that the HPC evolved from a primeval chemosensory epithelium. Internal sensing deficits in patients with HPC lesions argue that internal sensing may be conserved in higher vertebrates. We studied the expression of 250 endocrine receptors in mouse brain. Key findings are (i) the proportions and levels of endocrine receptor expression in the HPC are significantly higher than in all other comparable brain regions. (ii) Surprisingly, the distribution of endocrine receptor expression within mouse HPC was found to be highly structured: receptors signaling ‘challenge’ are segregated in dentate gyrus (DG), whereas those signaling ‘sufficiency’ are principally found in cornu ammonis (CA) regions. Selective expression of endocrine receptors in the HPC argues that internal sensing remains a core feature of hippocampal function. Further, we report that ligands of DG receptors predominantly inhibit both synaptic potentiation and neurogenesis, whereas CA receptor ligands conversely promote both synaptic potentiation and neurogenesis. These findings suggest that the hippocampus acts as an integrator of body status, extending its role in context-dependent memory encoding from ‘where’ and ‘when’ to ‘how I feel’. Implications for anxiety and depression are discussed.
Diffuse X-ray Scattering from Correlated Motions in a Protein Crystal
Authors: Meisburger Steve P. , Case David A. , Ando Nozomi
Published: October 2019

Protein dynamics are integral to biological function, yet few techniques are sensitive to collective atomic motions. A long-standing goal of X-ray crystallography has been to combine structural information from Bragg diffraction with dynamic information contained in the diffuse scattering background. However, the origin of macromolecular diffuse scattering has been poorly understood, limiting its applicability. We present a detailed diffuse scattering map from triclinic lysozyme that resolves both inter- and intramolecular correlations. These correlations are studied theoretically using both all-atom molecular dynamics and simple vibrational models. Although lattice dynamics reproduce most of the diffuse pattern, protein internal dynamics, which include hinge-bending motions, are needed to explain the short-ranged correlations revealed by Patterson analysis. These insights lay the groundwork for animating crystal structures with biochemically relevant motions.
Frost and drought: effects of extreme weather events on stem carbon dynamics in a Mediterranean beech forest
Authors: D’Andrea Ettore , Rezaie Negar , Prislan Peter , Gričar Jozica , Muhr Jan , Collalti Alessio , Matteucci Giorgio
Published: October 2019

The effects of short-term extreme events on tree functioning and physiology are still rather elusive. European beech is one of the most sensitive species to late frost and water shortage. We investigated the intra-annual C dynamics in stems under such conditions.

Wood formation and stem CO2efflux were monitored in a Mediterranean beech forest for three years (2015–2017), including a late frost (2016) and a summer drought (2017).

The late frost reduced radial growth and, consequently, the amount of carbon fixed in the stem biomass by 80%. Stem carbon efflux in 2016 was reduced by 25%, which can be attributed to the reduction of effluxes due to growth respiration. Counter to our expectations, we found no effects of the 2017 summer drought on radial growth and stem carbon efflux.

The studied extreme weather events had various effects on tree growth. Even though late spring frost had a devastating impact on beech radial growth in the current year, trees fully recovered in the following growing season, indicating high resilience of beech to this stressful event.
Nickel induced transcriptional changes persist post exposure through epigenetic reprograming
Authors: Jose Cynthia C , Wang Zhenjia , Tanwar Vinay Singh , Zhang Xiaoru , Zang Chongzhi , Cuddapah Suresh
Published: October 2019

Nickel is an occupational and environmental toxicant associated with a number of diseases in humans including pulmonary fibrosis, bronchitis and lung and nasal cancers. Our earlier studies showed that the nickel-exposure-induced genome-wide transcriptional changes, which persist even after the termination of exposure may underlie nickel pathogenesis. However, the mechanisms that drive nickel-induced persistent changes to the transcriptome remain elusive. To elucidate the mechanisms that underlie nickel induced long-term transcriptional changes, in this study, we examined the transcriptome and the epigenome of human lung epithelial cells during nickel exposure and after the termination of exposure. We identified two categories of persistently differentially expressed genes based on the timing of expression changes: i) the genes that were differentially expressed during nickel exposure; and ii) the genes that were differentially expressed only after the termination of nickel exposure. Interestingly, the majority of nickel-induced transcriptional changes occurred only after the termination of exposure. We found robust genome-wide alterations to the activating histone modification, H3K4me3, after the termination of nickel exposure, which coincided with the post-exposure gene expression changes. In addition, we found significant post-exposure alterations to the repressive histone modification, H3K27me3. By uncovering a new category of transcriptional and epigenetic changes, which occur only after the termination of exposure, this study sheds new light on the post-exposure effects of nickel and provides a novel understanding of the long-term deleterious consequences of nickel exposure on human health.
Soil microbial communities associated with giant sequoia: How does the world’s largest tree affect some of the world’s smallest organisms?
Authors: Carey Chelsea J. , Glassman Sydney I. , Bruns Thomas D. , Aronson Emma L. , Hart Stephen C.
Published: October 2019

Giant sequoia (Sequoiadendron giganteum) is an iconic conifer that lives in relic populations on the western slopes of the California Sierra Nevada. In these settings it is unusual among the dominant trees in that it associates with arbuscular mycorrhizal fungi rather than ectomycorrhizal fungi. However, it is unclear whether differences in microbial associations extends more broadly to non-mycorrhizal components of the soil microbial community. To address this question we characterized microbiomes associated with giant sequoia and co-occurring sugar pine (Pinus lambertiana) by sequencing 16S and ITS1 of the bulk soil community at two groves with distinct parent material. We found tree-associated differences were apparent despite a strong grove effect. Bacterial/archaeal richness was greater beneath giant sequoia than sugar pine, with a unique core community that was double the size. The tree species also harbored compositionally distinct fungal communities. This pattern depended on grove but was associated with a consistently elevated relative abundance ofHygrocybespecies beneath giant sequoia. Compositional differences between host trees correlated with soil pH, calcium availability, and soil moisture. We conclude that the effects of giant sequoia extend beyond mycorrhizal mutualists to include the broader community, and that some but not all host tree differences are grove-dependent.
Bacterial community profiling highlights complex diversity and novel organisms in wildlife ticks
Authors: Egan Siobhon L. , Loh Siew-May , Banks Peter B. , Gillett Amber , Ahlstrom Liisa , Ryan Una M. , Irwin Peter J. , Oskam Charlotte L.
Published: October 2019

Ticks (Acari: Ixodida) transmit a greater variety of pathogens than any other blood-feeding group of arthropods. While numerous microbes have been identified inhabiting Australian Ixodidae, some of which are related to globally important tick-borne pathogens, little is known about the bacterial communities within ticks collected from Australian wildlife. In this study, 1,019 ticks were identified on 221 hosts spanning 27 wildlife species. Next-generation sequencing was used to amplify the V1-2 hypervariable region of the bacterial 16S rRNA gene from 238 ticks;Amblyomma triguttatum(n=6),Bothriocroton auruginans(n=11),Bothriocroton concolor(n=20),Haemaphysalis bancrofti(n=10),Haemaphysalis bremneri(n=4),Haemaphysalis humerosa(n=13), Haemaphysalis longicornis(n=4),Ixodes antechini(n=29),Ixodes australiensis(n=26),Ixodes fecialis(n=13),Ixodes holocyclus(n=37),Ixodes myrmecobii (n=1), Ixodes ornithorhynchi(n=10),Ixodes tasmani(n=51) andIxodes trichosuri(n=3). After bioinformatic analyses, over 14 million assigned bacterial sequences revealed the presence of recently described bacteria ‘CandidatusBorrelia tachyglossi’, ‘CandidatusNeoehrlichia australis’, ‘CandidatusNeoehrlichia arcana’ and ‘CandidatusEhrlichia ornithorhynchi’. Furthermore, three novel Anaplasmataceae species were identified in the present study including; aNeoehrlichiasp. inI. australiensisandI. fecialiscollected from quenda (Isoodon fusciventer) (Western Australia), anAnaplasmasp. from oneB. concolorfrom echidna (Tachyglossus aculeatus) (New South Wales), and anEhrlichiasp. from a singleI. fecialisparasitising a quenda (WA). This study highlights the diversity of bacterial genera harboured within wildlife ticks, which may prove to be of medical and/or veterinary importance in the future.
Integrating multi-omics data through deep learning for accurate cancer prognosis prediction
Authors: Chai Hua , Zhou Xiang , Zhang Zhongyue , Rao Jiahua , Zhao Huiying , Yang Yuedong
Published: October 2019

Background

Genomic information is nowadays widely used for precise cancer treatments. Since the individual type of omics data only represents a single view that suffers from data noise and bias, multiple types of omics data are required for accurate cancer prognosis prediction. However, it is challenging to effectively integrate multi-omics data due to the large number of redundant variables but relatively small sample size. With the recent progress in deep learning techniques, Autoencoder was used to integrate multi-omics data for extracting representative features. Nevertheless, the generated model is fragile from data noises. Additionally, previous studies usually focused on individual cancer types without making comprehensive tests on pan-cancer. Here, we employed the denoising Autoencoder to get a robust representation of the multi-omics data, and then used the learned representative features to estimate patients’ risks.

Results

By applying to 15 cancers from The Cancer Genome Atlas (TCGA), our method was shown to improve the C-index values over previous methods by 6.5% on average. Considering the difficulty to obtain multi-omics data in practice, we further used only mRNA data to fit the estimated risks by training XGboost models, and found the models could achieve an average C-index value of 0.627. As a case study, the breast cancer prognosis prediction model was independently tested on three datasets from the Gene Expression Omnibus (GEO), and shown able to significantly separate high-risk patients from low-risk ones (C-index>0.6, p-values<0.05). Based on the risk subgroups divided by our method, we identified nine prognostic markers highly associated with breast cancer, among which seven genes have been proved by literature review.

Conclusion

Our comprehensive tests indicated that we have constructed an accurate and robust framework to integrate multi-omics data for cancer prognosis prediction. Moreover, it is an effective way to discover cancer prognosis-related genes.
Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing
Authors: Stangl Christina , de Blank Sam , Renkens Ivo , Verbeek Tamara , Valle-Inclan Jose Espejo , González Rocio Chamorro , Henssen Anton G. , van Roosmalen Markus J. , Stam Ronald W. , Voest Emile E. , Kloosterman Wigard P. , van Haaften Gijs , Monroe Glen
Published: October 2019

Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508 fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.
Selective targeting of an oncogenic KRAS mutant allele by CRISPR/Cas9 induces efficient tumor regression
Authors: Gao Qianqian , Ouyang Wenjie , Kang Bin , Han Xu , Xiong Ying , Ding Renpeng , Li Yijian , Wang Fei , Huang Lei , Chen Lei , Wang Dan , Dong Xuan , Zhang Zhao , Li Yanshan , Ze Baichen , Hou Yong , Yang Huanming , Ma Yuanyuan , Gu Ying , Chao Cheng-chi
Published: October 2019

Background

KRAS is one of the most frequently mutated oncogenes in human cancers, but its activating mutations have remained undruggable due to its picomolar affinity for GTP/GDP and its smooth protein structure resulting in the absence of known allosteric regulatory sites.

Results

With the goal of treating mutated KRAS-driven cancers, two CRISPR systems, CRISPR-SpCas9 genome-editing system and transcription-regulating system dCas9-KRAB, were developed to directly deplete KRAS mutant allele or to repress its transcription in cancer cells, respectively, through guide RNA specifically targeting the mutant but not wild-type allele. The effect of in vitro proliferation and cell cycle on cancer cells as well as in vivo tumor growth was examined after delivery of Cas9 system. SpCas9 and dCas9-KRAB systems with sgRNA targeting the mutant allele both blocked the expression of mutant KRAS gene, leading to an inhibition of cancer cell proliferation. Local adenoviral injections using SpCas9 and dCas9-KRAB systems both suppressed tumor growth in vivo. The gene-depletion system (SpCas9) performed more effectively than the transcription-suppressing system (dCas9-KRAB) on tumor inhibition. Application of both Cas9 systems to wild-type KRAS tumor cells did not affect cell proliferation in vitro and in vivo. Furthermore, through bioinformatic analysis of 31555 SNP mutations of the top 20 cancer driver genes, we showed that our mutant-specific editing strategy could be extended to a list of oncogenic mutations with high editing potentials, and this pipeline can be applied to analyze the distribution of PAM sequence in the genome to survey the best targets for other editing purpose.

Conclusions

We successfully developed both gene-depletion and transcription-suppressing systems to specifically target an oncogenic mutant allele of KRAS which led to significant tumor regression. It provides a promising strategy for the treatment of tumors with driver gene mutations.
Characterizing the Cancer-Associated Microbiome with Small RNA Sequencing Data
Authors: Lee Wei-Hao , Chen Kai-Pu , Wang Kai , Huang Hsuan-Cheng , Juan Hsueh-Fen
Published: October 2019

The microbiome is recognized as a quasi-organ in the human body. In particular, the gut microbiome is correlated with immune function, metabolism, and tumorigenesis. When dysbiosis of the microbiome occurs, this variation may contribute to alterations in the microenvironment, potentially inducing an inflammatory immune response and providing a niche for neoplastic growth. However, there is limited evidence regarding the correlation and interaction between the microbiome and tumorigenesis. By utilizing microRNA sequencing data of patients with colon and rectal cancer from The Cancer Genome Atlas, we designed a novel analytical process to extract non-human small RNA sequences and align them with the microbial genome to obtain a comprehensive view of the cancer-associated microbiome. In the present study, we identified > 1000 genera among 630 colorectal samples and clustered these samples into three distinctive colorectal enterotypes. Each cluster has its own distinctive microbial composition and interactions. Furthermore, we found 12 genera from these clusters that are associated with cancer stages and revealed their putative functions. Our results indicate that the proposed analytical approach can effectively determine the cancer-associated microbiome. It may be readily applied to explore other types of cancer, in which specimens of the microbiome are difficult to collect.
Simultaneous electrophysiological recording and fiber photometry in freely behaving mice
Authors: Patel Amisha A , McAlinden Niall , Mathieson Keith , Sakata Shuzo
Published: October 2019

In vivo electrophysiology is the gold standard technique used to investigate sub-second neural dynamics in freely behaving animals. However, monitoring cell-type-specific population activity is not a trivial task. Over the last decade, fiber photometry based on genetically encoded calcium indicators has been widely adopted as a versatile tool to monitor cell-type-specific population activity in vivo. However, this approach suffers from low temporal resolution. Here, we combine these two approaches to monitor both sub-second field potentials and cell-type-specific population activity in freely behaving mice. By developing an economical custom-made system, and constructing a hybrid implant of an electrode and a fiber optic cannula, we simultaneously monitor artifact-free pontine field potentials and calcium transients in cholinergic neurons across the sleep-wake cycle. We find that pontine cholinergic activity co-occurs with sub-second pontine waves, called P-waves, during rapid eye movement sleep. Given the simplicity of our approach, simultaneous electrophysiological recording and cell-type-specific imaging provides a novel and valuable tool for interrogating state-dependent neural circuit dynamics in vivo.
KOPTIC: A novel approach forin silicoprediction of enzyme kinetics and regulation
Authors: Schroeder Wheaton L. , Saha Rajib
Published: October 2019

Kinetic models of metabolism (kMMs) provide not only a more accurate method for designing novel biological systems but also characterization of system regulations; however, the multi-‘omics’ data required is prohibitive to their development and widespread use. Here, we introduce a new approach namedKineticOPTimization usingIntegerConditions (KOPTIC), which can circumvent the ‘omics’ data requirement and semi-automate kMM construction usingin silicoreaction flux data and metabolite concentration estimates derived from a metabolic network model to return plausible reaction mechanisms, regulations, and kinetic parameters (defined as ‘reactomics’) using an optimization-based approach. As a benchmark for the performance of KOPTIC, a previously published, four-tissue (leaf, root, seed, and stem) metabolic model ofArabidopsis thalianawas used, consisting of major primary carbon metabolism pathways, named p-ath780 (1015 reactions, 901 metabolites, and 780 genes). Data required for KOPTIC was derived from an Arabidopsis’ lifecycle of 61 days. Nine separate regulator restriction sets (allowing multiple solutions) defining KOPTIC runs hypothesized 3577 total regulatory interactions involving metabolic, allosteric, and transcriptional regulatory mechanisms (with nearly 40 verified by existing literature) with a median fit error of 13.44%. Flux rates of most KOPTIC fits were found to be significantly correlated with (93.6% withp< 0.05) and approximately 1:1 (r= 0.775,p≪ 0.001) to the input time-series data. Thus, KOPTIC can hypothesize maps the regulatory landscape for a specific reaction, out of which the most relevant regulatory interaction(s) can be defined by the desired growth/stress conditions or the desired genetic interventions for use in the creation of kMMs.
Dynamics of apomictic and sexual reproduction during primary succession on a glacier forefield in the Swiss Alps
Authors: Sailer Christian , Stöcklin Jürg , Grossniklaus Ueli
Published: October 2019

Apomixis, the asexual reproduction through seeds, is thought to provide reproductive assurance when ploidy is not even and/or when population density is low. Therefore, apomicts are expected to be more abundant, and the frequency of apomictic offspring higher, at early stages of primary succession when mates are rare.

To test this hypothesis, we sampled facultative apomictic Hieracium pilosella L. along the successional gradient on a glacier forefield and determined their ploidy, the level of apomixis in their offspring, and the genetic diversity of the entire meta-population and within subpopulations.

We found that apomixis is more common in odd- and aneuploid cytotypes, which are more frequent at early stages of primary succession. However, apomixis was uncommon at all successional stages and sexual hexaploids were dominating throughout. Reproductive assurance was reflected in the higher fertility of all odd-ploid apomictic plants (3x, 5x) by avoiding meiosis, illustrating that apomixis provides an escape from sterility, as proposed by Darlington. Odd-ploid plants are supposedly better colonizers (Baker’s law), which is supported by their higher occurrence close to the glacier snout. Independent of succession, we found gene flow between apomicts and sexuals, which allows for the continuous creation of new apomictic and sexual genotypes.

We conclude that apomixis in H. pilosella does indeed provide an escape from sterility, and therefore reproductive assurance, in aneuploid cytotypes. We further propose that apomixis preserves beneficial combinations of unlinked alleles in every generation for as long as apomictic genotypes persist in the population.
A theory of actions and habits: The interaction of rate correlation and contiguity systems in free-operant behavior
Authors: Perez Omar D. , Dickinson Anthony
Published: October 2019

Contemporary theories of instrumental performance assume that responding can be controlled by two behavioral systems, one goal-directed that encodes the outcome of an action, and one habitual that reinforces the response strength of the same action. Here we present a model of free-operant behavior in which goal-directed control is determined by the correlation between the rates of the action and the outcome whereas the total prediction error generated by contiguous reinforcement by the outcome controls habitual response strength. The outputs of these two systems summate to generate a total response strength. This cooperative model addresses the difference in the behavioral impact of ratio and interval schedules, the transition from goal-directed to habitual control with extended training, the persistence of goal-directed control under choice procedures and following extinction, among other phenomena. In these respects, this dual-system model is unique in its account of free-operant behavior.
Association of SYNE2 variants in accelerating the progress of DYT1 early-onset isolated dystonia
Authors: Lee Feng-Chin , Wu Steve , Hsu Chih-Sin , Huang Shih-Ming , Hong Jau-Shyong , Hu Chih-Fen
Published: October 2019

DYT1 early-onset isolated dystonia (DYT1 dystonia), a rare autosomal dominant (AD) primary dystonia, is categorized as a monogenic disease. While it is a well-known AD inherited disease, the relatively low penetrance rate implicates potential modifiers in play for disease progression. In this report, an affected individual withTOR1Agene (c.907_909delGAG, p.E303del) variant, was identified along with three additional AD carriers in the family. Since we failed to find the second hit variant from TOR1A (D216H, F323_Y328del and F205I) and major binding proteins, including TOR1AIP1 and 2 or HSPA8 proteins, subsequent whole exome sequencing on the patient, the carriers and a non-carrier family member were performed to screen for candidate modifiers of TOR1A (E303del). The result reveals that this patient distinctly carries one copy ofTOR1Agene (c.907_909delGAG, p.E303del) and one or two copy ofSYNE2gene (c.1721T>C, c.12001T>C, and c.12002G>A), encoding I574T, W4001R, and W4001Ter variants. We propose that these SYNE2 variants are linked to earlier disease onset in this patient by impacting the protein-protein interaction between TOR1A and SYNE2. Our study suggestsSYNE2gene maybe a culprit to lower the threshold for DYT1 dystonia progression and provides one novel gene target for further screening diagnosis of DYT1 dystonia.
Predicting the fMRI signal fluctuation with echo-state neural networks trained on vascular network dynamics
Authors: Sobczak Filip , He Yi , Sejnowski Terrence J. , Yu Xin
Published: October 2019

Resting-state functional MRI (rs-fMRI) studies have revealed specific low-frequency hemodynamic signal fluctuations (<0.1 Hz) in the brain, which could be related to oscillations in neural activity through several mechanisms. Although the vascular origin of the fMRI signal is well established, the neural correlates of global rs-fMRI signal fluctuations are difficult to separate from other confounding sources. Recently, we reported that single-vessel fMRI slow oscillations are directly coupled to brain state changes. Here, we used an echo-state network (ESN) to predict the future temporal evolution of the rs-fMRI slow oscillatory feature from both rodent and human brains. rs-fMRI signals from individual blood vessels that were strongly correlated with neural calcium oscillations were used to train an ESN to predict brain state-specific rs-fMRI signal fluctuations. The ESN-based prediction model was also applied to recordings from the Human Connectome Project (HCP), which classified variance-independent brain states based on global fluctuations of rs-fMRI features. The ESN revealed brain states with global synchrony and decoupled internal correlations within the default-mode network.
Epigenetic gene silencing by heterochromatin primes fungal resistance
Authors: Torres-Garcia Sito , Audergon Pauline N. C. B. , Shukla Manu , White Sharon A. , Pidoux Alison L. , Allshire Robin C.
Published: October 2019

Genes embedded in H3 lysine 9 methylation (H3K9me)–dependent heterochromatin are transcriptionally silenced1-3. In fission yeast,Schizosaccharomyces pombe, H3K9me heterochromatin silencing can be transmitted through cell division provided the counteracting demethylase Epe1 is absent4,5. It is possible that under certain conditions wild-type cells might utilize heterochromatin heritability to form epimutations, phenotypes mediated by unstable silencing rather than changes in DNA6,7. Here we show that resistant heterochromatin-mediated epimutants are formed in response to threshold levels of the external insult caffeine. ChIP-seq analyses of unstable resistant isolates revealed new distinct heterochromatin domains, which in some cases reduce the expression of underlying genes that are known to confer resistance when deleted. Targeting synthetic heterochromatin at implicated loci confirmed that resistance results from heterochromatin-mediated silencing. Our analyses reveal that epigenetic processes allow wild-type fission yeast to adapt to non-favorable environments without altering their genotype. In some isolates, subsequent or co-occurring gene amplification events enhance resistance. Thus, heterochromatin-dependent epimutant formation provides a bet-hedging strategy that allows cells to remain genetically wild-type but transiently adapt to external insults. As unstable caffeine-resistant isolates show cross-resistance to the fungicide clotrimazole it is likely that related heterochromatin-dependent processes contribute to anti-fungal resistance in both plant and human pathogenic fungi.
Broad and thematic remodeling of the surface glycoproteome on isogenic cells transformed with driving proliferative oncogenes
Authors: Leung Kevin K. , Wilson Gary M. , Kirkemo Lisa L. , Riley Nicholas M. , Coon Joshua J. , Wells James A.
Published: October 2019

The cell surface proteome, the surfaceome, is the interface for engaging the extracellular space in normal and cancer cells. Here we apply quantitative proteomics of N-linked glycoproteins to reveal how a collection of some 700 surface proteins is dramatically remodeled in an isogenic breast epithelial cell line stably expressing any of six of the most prominent proliferative oncogenes, including the receptor tyrosine kinases, EGFR and HER2, and downstream signaling partners such as KRAS, BRAF, MEK and AKT. We find that each oncogene has somewhat different surfaceomes but the functions of these proteins are harmonized by common biological themes including up-regulation of nutrient transporters, down-regulation of adhesion molecules and tumor suppressing phosphatases, and alteration in immune modulators. Addition of a potent MEK inhibitor that blocks MAPK signaling brings each oncogene-induced surfaceome back to a common state reflecting their strong dependence on the MAPK pathway to propagate signaling. Using a recently developed glyco-proteomics method of activated ion electron transfer dissociation (AI-ETD) we found massive oncogene-induced changes in 142 N-linked glycans and differential increases in complex hybrid glycans especially for KRAS and HER2 oncogenes. Overall, these studies provide a broad systems level view of how specific driver oncogenes remodel the surface glycoproteome in a cell autologous fashion, and suggest possible surface targets, and combinations thereof, for drug and biomarker discovery.

Significant statement

The cell surface glycoproteome (surfaceome) mediates interactions between the cell and the extracellular environment, and is a major target for immunotherapy in cancer. Using state-of-the-art proteomics methods, we compared how six neighboring proliferative oncogenes cause large and bidirectional expression of some 700 surface proteins and the 142 different glycans that decorate them. While each oncogene induces large and somewhat unique glycoproteomes relative to non-transformed cells, we find common functional consequences that are massively reversed by small molecule inhibition of the MAPK pathway. This large-scale comparative study provides important insights for how oncogenes remodel isogenic cells in a cell autologous fashion, and suggest possible new opportunities for antibody drug discovery in more complex tumor settings.
Synchrotron FTIR as a tool for studying populations and individual living cells of green algae
Authors: Goff Kira L. , Ellis Thomas , Wilson Kenneth E.
Published: October 2019

Fourier transform infrared (FTIR) spectromicroscopy was used to study individual living cells of three closely-related species of the green algae Chlamydomonas. This study differentiated these three species based on differences in lipid and protein profiles, as well explored sources of variation in our measurements. Significant spectral variation was observed between individual cells within a single culture, as well as between control cultures of a species obtained on different days. Despite this, we were able to differentiate between the three close-related species. Differences in the spectra were confirmed using principal component analysis. Understanding the interplay of underlying variation and the degree of induced spectral differences is essential for the deployment of FTIR measurements in both bulk cultures and for individual living cells.
Beyond generalization: Enhancing accurate interpretation of flexible models
Authors: Genkin Mikhail , Engel Tatiana A.
Published: October 2019

Machine learning optimizes flexible models to predict data. In scientific applications, there is a rising interest in interpreting these flexible models to derive hypotheses from data. However, it is unknown whether good data prediction guarantees accurate interpretation of flexible models. We test this connection using a flexible, yet intrinsically interpretable framework for modeling neural dynamics. We find that many models discovered during optimization predict data equally well, yet they fail to match the correct hypothesis. We develop an alternative approach that identifies models with correct interpretation by comparing model features across data samples to separate true features from noise. Our results reveal that good predictions cannot substitute for accurate interpretation of flexible models and offer a principled approach to identify models with correct interpretation.
Investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis
Authors: Zhang Yuhua , Quick Corbin , Yu Ketian , Barbeira Alvaro ,   The GTEx Consortium, Luca Francesca , Pique-Regi Roger , Im Hae Kyung , Wen Xiaoquan
Published: October 2019

Transcriptome-wide association studies (TWAS), an integrative framework using expression quantitative trait loci (eQTLs) to construct proxies for gene expression, have emerged as a promising method to investigate the biological mechanisms underlying associations between genotypes and complex traits. However, challenges remain in interpreting TWAS results, especially regarding their causality implications. In this paper, we describe a new computational framework, probabilistic TWAS (PTWAS), to detect associations and investigate causal relationships between gene expression and complex traits. We use established concepts and principles from instrumental variables (IV) analysis to delineate and address the unique challenges that arise in TWAS. PTWAS utilizes probabilistic eQTL annotations derived from multi-variant Bayesian fine-mapping analysis conferring higher power to detect TWAS associations than existing methods. Additionally, PTWAS provides novel functionalities to evaluate the causal assumptions and estimate tissue- or cell-type specific causal effects of gene expression on complex traits. These features make PTWAS uniquely suited for in-depth investigations of the biological mechanisms that contribute to complex trait variation. Using eQTL data across 49 tissues from GTEx v8, we apply PTWAS to analyze 114 complex traits using GWAS summary statistics from several large-scale projects, including the UK Biobank. Our analysis reveals an abundance of genes with strong evidence of eQTL-mediated causal effects on complex traits and highlights the heterogeneity and tissue-relevance of these effects across complex traits. We distribute software and eQTL annotations to enable users performing rigorous TWAS analysis by leveraging the full potentials of the latest GTEx multi-tissue eQTL data.
Stress-induced dendritic branching inC. elegansrequires both common arborization effectors and stress-responsive molecular pathways
Authors: Androwski Rebecca J. , Asad Nadeem , Wood Janet G. , Hofer Allison , Locke Steven , Smith Cassandra M. , Rose Becky , Schroeder Nathan E.
Published: October 2019

Stress influences the shape of dendritic arbors in neurons. During the stress-induced dauer stage ofCaenorhabditis elegans, the IL2 neurons arborize to cover the anterior body wall. In contrast, the FLP neurons arborize to cover the anterior body wall during non-dauer development. Previous work showed that the membrane-bound receptor DMA-1 regulates FLP branching as part of a larger protein complex. Using forward genetics, we show that the IL2 neurons also use the DMA-1 complex to regulate branching. To understand the coordination of the IL2s and FLPs we conducted a time-course examination of FLPs and found previously undescribed branching patterns indicating a neighborhood effect wherein the FLPs and IL2s in the anterior have differential branching compared to the more posteriorly located PVD arborizing neurons. To determine how the IL2s and FLPs differentially regulate branching, we examined several regulators of DMA-1 localization. We show that the unfolded protein response sensor IRE-1, required for FLP branching, is only required for dauer-specific branching at elevated temperatures. Interestingly, we found thatire-1mutants have broad, organism-wide temperature-dependent effects on dauer remodeling, suggesting a previously undescribed role for IRE-1 in phenotypic plasticity. We also found that defects in other regulators of dauer remodeling including DAF-16/FOXO, DAF-9/Cytochrome P450, and DAF-18/PTEN are required for proper IL2 arborization, but dispensable for FLP branching. Interestingly, we find that TOR adaptor protein DAF-15/RAPTOR is both required for promoting IL2 branching and inhibiting precocious development of the FLPs. Our results demonstrate specific genotypic by environmental interactions regulating dendrite arborization.

SIGNIFICANCE STATEMENT

Neurons have extensions called dendrites that receive information. Dendrites are often elaborately shaped with many branches. Adverse stress can reduce branching in some neurons, while increasing it in others. How stress can cause some neurons to change shape is unclear. We previously found a set of neurons in the head of the well-studied roundwormC. elegansthat undergo reversible branching following exposure to specific adverse environmental conditions. Using various genetic tools, we find that branching in these neurons is controlled by a combination of branching genes common to many neuron types and others that only regulate branching in stress-responsive neurons. Our data demonstrate how experiencing stress acts through genetics pathways to cause changes to specific neurons.
When two are better than one: Modeling the mechanisms of antibody mixtures
Authors: Einav Tal , Bloom Jesse D.
Published: October 2019

It is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitopes. This model requires measuring n individual antibodies and their pairwise interactions to predict the 2n potential combinations. We apply this model to epidermal growth factor receptor (EGFR) antibodies and find that the activity of antibody mixtures can be predicted without positing synergy at the molecular level. In addition, we demonstrate how the model can be used in reverse, where straightforward experiments measuring the activity of antibody mixtures can be used to infer the molecular interactions between antibodies. Lastly, we generalize this model to analyze engineered multidomain antibodies, where components of different antibodies are tethered together to form novel amalgams, and characterize how well it predicts recently designed influenza antibodies.

Author summary

With the rise of new antibody combinations in therapeutic regimens, it is important to understand how antibodies work together as well as individually. Here, we investigate the specific case of monoclonal antibodies targeting a cancer-causing receptor or the influenza virus and develop a statistical mechanical framework that predicts the effectiveness of a mixture of antibodies. The power of this model lies in its ability to make a large number of predictions based on a limited amount of data. For example, once 10 antibodies have been individually characterized and their epitopes have been mapped, our model can predict how any of the 210 = 1024 combinations will behave. This predictive power can aid therapeutic efforts by assessing which combinations of antibodies will elicit the most effective response.
LARP7 is a BRCA1 ubiquitinase substrate and regulates genome stability and tumorigenesis
Authors: Zhang Fang , Yan Pengyi , Yu Huijing , Le Huangying , li Zixuan , Chen Jiahuan , Liang Xiaodong , Wang Shiyan , Wei Weiting , Liu Li , Zhang Yan , Ji Xing , Xie Anyong , Chen Wantao , Han Zeguang , Pu William T. , Chen Sun , Chen Yingwei , Sun Kun , Ge Baoxie , Zhang Bing
Published: October 2019

Attenuated DNA repair leads to genomic instability and tumorigenesis. BRCA1/BARD1 are the best known tumor suppressors that promote homology recombination (HR) and arrest cell cycle at G2/M checkpoint. As E3 ubiquitin ligases, their ubiquitinase activity has been known to involve in the HR and tumor suppression, but the mechanism remains ambiguous. Here, we demonstrated upon genotoxic stress, BRCA1 together with BARD1 catalyzed the K48 ployubiquitination on LARP7, a 7SK RNA binding protein known to control RNAPII pausing, and thereby degraded it through 26S ubiquitin-proteasome pathway. Depleting LARP7 suppressed the expression of CDK1 complex, arrested cell at G2/M DNA damage checkpoint and reduced BRCA2 phosphorylation which thereby facilitated RAD51 recruitment to damaged DNA to enhance HR. Importantly, LARP7 depletion observed in breast patients lead to the chemoradiotherapy resistance both in vitro and in vivo. Together, this study unveils a mechanism by which BRCA1/BARD1 utilizes their E3 ligase activity to control HR and cell cycle, and highlights LARP7 as a potential target for cancer prevention and therapy.

Highlights

DNA damage response downregulates LARP7 through BRCA1/BARD1

BRCA1/BARD1 catalyzes the K48 polyubiquitination on LARP7

LARP7 promotes G2/M cell cycle transition and tumorigenesis via CDK1 complex

LARP7 disputes homology-directed repair that leads to tumor therapy resistance