bluuebunny/crossref_metadata_2025_split huggingface dataset:
3,3′-Diindolylmethane Dose-Dependently Prevents Advanced Prostate Cancer
Authors: Li Yufei , Mahloch Nathaniel W. , Starkey Nicholas J.E. , Peña-Luna Mónica , Rottinghaus George E. , Fritsche Kevin L. , Besch-Williford Cynthia , Lubahn Dennis B. 
Published: April 2019

Abstract3,3′-Diindolylmethane (DIM) is an acid-derived dimer of indole-3-carbinol, found in many cruciferous vegetables, such as broccoli, and has been shown to inhibit prostate cancer (PCa) in several in vitro and in vivo models. We demonstrated that DIM stimulated both estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ) transcriptional activities and propose that ERβ plays a role in mediating DIM’s inhibition on cancer cell growth. To further study the effects of DIM on inhibiting advanced PCa development, we tested DIM in TRAMP (TRansgenic Adenocarcinoma of the Mouse Prostate) mice. The control group of mice were fed a high fat diet. Three additional groups of mice were fed the same high fat diet supplemented with 0.04%, 0.2% and 1% DIM. Incidence of advanced PCa, poorly differentiated carcinoma (PDC), in the control group was 60%. 1% DIM dramatically reduced PDC incidence to 24% (p=0.0012), while 0.2% and 0.04% DIM reduced PDC incidence to 38% (p=0.047) and 45% (p=0.14) respectively. Though DIM did affect mice weights, statistical analysis showed a clear negative association between DIM concentration and PDC incidence with p=0.004, while the association between body weight and PDC incidence was not significant (p=0.953). In conclusion, our results show that dietary DIM can inhibit the most aggressive stage of prostate cancer at concentration lower than previously demonstrated, possibly working through an estrogen receptor mediated mechanism.
Machine learning predicts rapid relapse of triple negative breast cancer
Authors: Zhang Yiqing , Nock William , Wyse Meghan , Weber Zachary , Adams Elizabeth , Asad Sarah , Stockard Sinclair , Tallman David , Winer Eric P. , Lin Nancy U. , Cherian Mathew , Lustberg Maryam B. , Ramaswamy Bhuvaneswari , Sardesai Sagar , VanDeusen Jeffrey , Williams Nicole , Wesolowski Robert , Stover Daniel G. 
Published: April 2019

ABSTRACTPurposeMetastatic relapse of triple-negative breast cancer (TNBC) within 2 years of diagnosis is associated with particularly aggressive disease and a distinct clinical course relative to TNBCs that relapse beyond 2 years. We hypothesized that rapid relapse TNBCs (rrTNBC; metastatic relapse or death <2 years) reflect unique genomic features relative to late relapse (lrTNBC; >2 years).Patients and MethodsWe identified 453 primary TNBCs from three publicly-available datasets and characterized each as rrTNBc, lrTNBC, or ‘no relapse’ (nrTNBC: no relapse/death with at least 5 years follow-up). We compiled primary tumor clinical and multi-omic data, including transcriptome (n=453), copy number alterations (CNAs; n=317), and mutations in 171 cancer-related genes (n=317), then calculated published gene expression and immune signatures.ResultsPatients with rrTNBC were higher stage at diagnosis (Chi-square p<0.0001) while lrTNBC were more likely to be non-basal PAM50 subtype (Chi-square p=0.03). Among 125 expression signatures, five immune signatures were significantly higher in nrTNBCs while lrTNBC were enriched for eight estrogen/luminal signatures (all FDR p<0.05). There was no significant difference in tumor mutation burden or percent genome altered across the groups. Among mutations, onlyTP53mutations were significantly more frequent in rrTNBC compared to lrTNBC (Fisher exact FDR p=0.009). To develop an optimal classifier, we used 77 significant clinical and ‘omic features to evaluate six modeling approaches encompassing simple, machine learning, and artificial neural network (ANN). Support vector machine outperformed other models with average receiver-operator characteristic area under curve >0.75.ConclusionsWe provide a new approach to define TNBCs based on timing of relapse. We identify distinct clinical and genomic features that can be incorporated into machine learning models to predict rapid relapse of TNBC.
Decoding Complex Sounds Using Broadband Population Recordings from Secondary Auditory Cortex of Macaques
Authors: Heelan Christopher , Lee Jihun , O’Shea Ronan , Brandman David M. , Truccolo Wilson , Nurmikko Arto V. 
Published: April 2019

AbstractDirect electronic communication with sensory areas of the neocortex is a challenging ambition for brain-computer interfaces. Here, we report the first successful neural decoding of English words with high intelligibility from intracortical spike-based neural population activity recorded from the secondary auditory cortex of macaques. We acquired 96-channel full-broadband population recordings using intracortical microelectrode arrays in the rostral and caudal parabelt regions of the superior temporal gyrus (STG). We leveraged a new neural processing toolkit to investigate the choice of decoding algorithm, neural preprocessing, audio representation, channel count, and array location on neural decoding performance. The results illuminated a view of the auditory cortex as a spatially distributed network and a general purpose processor of complex sounds. The presented spike-based machine learning neural decoding approach may further be useful in informing future encoding strategies to deliver direct auditory percepts to the brain as specific patterns of microstimulation.
Walking kinematics in the polymorphic seed harvester antMessor barbarus:influence of body size and load carriage
Authors: Merienne Hugo , Latil Gérard , Moretto Pierre , Fourcassié Vincent 
Published: April 2019

AbstractAnts are famous in the animal kingdom for their amazing load carriage performances. Yet, the mechanisms that allow these insects to maintain their stability when carrying heavy loads have been poorly investigated. Here we present a study of the kinematics of loaded locomotion in the polymorphic seed-harvesting antMessor barbarus. In this species big ants have larger heads relative to their size than small ants. Hence, their center of mass is shifted forward, and the more so when they are carrying a load in their mandibles. We tested the hypothesis that this could lead to big ants being less statically stable than small ants, thus explaining their lower load carriage performances. When walking unloaded we found that big ants were indeed less statically stable than small ants but that they were nonetheless able to adjust their stepping pattern to partly compensate for this instability. When ants were walking loaded on the other hand, there was no evidence of different locomotor behaviors in individuals of different sizes. Loaded ants, whatever their size, move too slowly to maintain their balance through dynamic stability. Rather, they seem to do so by clinging to the ground with their hind legs during part of a stride. We show through a straightforward model that allometric relationships have a minor role in explaining the differences in load carriage performances between big ants and small ants and that a simple scale effect is sufficient to explain these differences.
Modulating Fis and IHF binding specificity, crosstalk and regulatory logic through the engineering of complex promoters
Authors: Monteiro Lummy Maria Oliveira , Sanches-Medeiros Ananda , Westmann Cauã Antunes , Silva-Rocha Rafael 
Published: April 2019

AbstractBacterial promoters are usually formed by multiplecis-regulatory elements recognized by a plethora of transcriptional factors (TFs). From those, global regulators are key elements since these TFs are responsible for the regulation of hundreds of genes in the bacterial genome. For instance, Fis and IHF are two global regulators which play a major role in gene expression control inEscherichia coliand usually multiplecis-regulatory elements for these proteins co-occur at target promoters. Here, we investigated the relationship between the architecture of thecis-regulatory elements for Fis and IHF inE. coli. For this, we constructed 42 synthetic promoter variants harboring consensuscis-elements for Fis and IHF at different distances from a core −35/−10 region and in different numbers and combinations. We first demonstrated that although Fis preferentially recognizes its consensuscis-element, it can also recognize, to some extent, the consensus binding site for IHF, and the same was true for IHF, which was also able of recognizing Fis binding sites. However, changing the arrangement of thecis-elements (i.e., the position or the number of sites) can completely abolish unspecific binding of both TFs. More remarkably, we demonstrate that combiningcis-elements for both TFs could result in Fis and IHF repressed or activated promoters depending on the final architecture of the promoters in an unpredictable way. Taken together, the data presented here demonstrate how small changes in the architecture of bacterial promoters could result in drastic changes in the final regulatory logic of the system, with important implications for the understanding of natural complex promoters in bacteria and their engineering for novel applications.ImportanceThe understanding of the regulatory complex in bacteria is a key issue in modern microbiology. Here, we constructed synthetic bacterial promoters in order to investigate how binding of transcriptional factors to multiple target sites at the promoters can influence gene expression. Our results demonstrate in a systematic way that the arrangement and number of thesecis-regulatory elements are crucial for the final expression dynamics of the target promoters. In particular, we show that TF binding specificity or promiscuity can be modulated using different promoter architectures based on consensuscis-regulatory elements, and that transcriptional repression and activation can also be affected by promoter architecture. These results are relevant both for the understanding of natural systems and for the construction of synthetic circuits for biotechnological applications.
Benchmarking algorithms for genomic prediction of complex traits
Authors: Azodi Christina B. , McCarren Andrew , Roantree Mark , de los Campos Gustavo , Shiu Shin-Han 
Published: April 2019

AbstractThe usefulness of Genomic Prediction (GP) in crop and livestock breeding programs has led to efforts to develop new and improved GP approaches including non-linear algorithm, such as artificial neural networks (ANN) (i.e. deep learning) and gradient tree boosting. However, the performance of these algorithms has not been compared in a systematic manner using a wide range of GP datasets and models. Using data of 18 traits across six plant species with different marker densities and training population sizes, we compared the performance of six linear and five non-linear algorithms, including ANNs. First, we found that hyperparameter selection was critical for all non-linear algorithms and that feature selection prior to model training was necessary for ANNs when the markers greatly outnumbered the number of training lines. Across all species and trait combinations, no one algorithm performed best, however predictions based on a combination of results from multiple GP algorithms (i.e. ensemble predictions) performed consistently well. While linear and non-linear algorithms performed best for a similar number of traits, the performance of non-linear algorithms vary more between traits than that of linear algorithms. Although ANNs did not perform best for any trait, we identified strategies (i.e. feature selection, seeded starting weights) that boosted their performance near the level of other algorithms. These results, together with the fact that even small improvements in GP performance could accumulate into large genetic gains over the course of a breeding program, highlights the importance of algorithm selection for the prediction of trait values.
CyMIRA: The Cytonuclear Molecular Interactions Reference forArabidopsis
Authors: Forsythe Evan S. , Sharbrough Joel , Havird Justin C. , Warren Jessica M. , Sloan Daniel B. 
Published: April 2019

ABSTRACTThe function and evolution of eukaryotic cells depends upon direct molecular interactions between gene products encoded in nuclear and cytoplasmic genomes. Understanding how these cytonuclear interactions drive molecular evolution and generate genetic incompatibilities between isolated populations and species is of central importance to eukaryotic biology. Plants are an outstanding system to investigate such effects because of their two different genomic compartments present in the cytoplasm (mitochondria and plastids) and the extensive resources detailing subcellular targeting of nuclear-encoded proteins. However, the field lacks a consistent classification scheme for mitochondrial- and plastid-targeted proteins based on their molecular interactions with cytoplasmic genomes and gene products, which hinders efforts to standardize and compare results across studies. Here, we take advantage of detailed knowledge about the model angiospermArabidopsis thalianato provide a curated database of plant cytonuclear interactions at the molecular level. CyMIRA (CytonuclearMolecularInteractionsReference forArabidopsis) is available athttp://cymira.colostate.edu/andhttps://github.com/dbsloan/cymiraand will serve as a resource to aid researchers in partitioning evolutionary genomic data into functional gene classes based on organelle targeting and direct molecular interaction with cytoplasmic genomes and gene products. It includes 11 categories (and 27 subcategories) of different cytonuclear complexes and types of molecular interactions, and it reports residue-level information for cytonuclear contact sites. We hope that this framework will make it easier to standardize, interpret and compare studies testing the functional and evolutionary consequences of cytonuclear interactions.
The ancillary N-terminal region of the yeast AP-1 transcription factor Yap8 contributes to its DNA binding specificity
Authors: Maciaszczyk-Dziubinska Ewa , Reymer Anna , Vijay Kumar Nallani , Białek Wojciech , Mizio Katarzyna , Tamás Markus J. , Wysocki Robert 
Published: April 2019

ABSTRACTActivator protein 1 (AP-1) is one of the largest families of basic leucine zipper (bZIP) transcription factors in eukaryotic cells. How AP-1 proteins achieve target DNA binding specificity remains elusive. In Saccharomyces cerevisiae, the AP-1-like protein (Yap) family comprises eight members (Yap1 to Yap8) that display distinct genomic target sites despite high sequence homology of their DNA binding bZIP domains. In contrast to the other members of the Yap family, which preferentially bind to short (7-8 bp) DNA motifs, Yap8 binds to an unusually long DNA motif (13 bp). It has been unclear what determines this unique specificity of Yap8. In this work, we use molecular and biochemical analysis combined with computer-based structural design and molecular dynamics simulations of Yap8-DNA interactions to better understand the structural basis of DNA binding specificity determinants. We identify specific residues in the N-terminal tail preceding the basic region, which define stable association of Yap8 with the ACR3 promoter. We propose that the N-terminal tail directly interacts with DNA and stabilizes Yap8 binding to the 13 bp motif. Thus, beside the core basic region, the adjacent N-terminal region contributes to alternative DNA binding selectivity within the AP-1 family.
Integrase-mediated differentiation circuits improve evolutionary stability of burdensome and toxic functions in E. coli
Authors: Williams Rory. L , Murray Richard M. 
Published: April 2019

AbstractAdvances in synthetic biology, bioengineering, and computation allow us to rapidly and reliably program cells with increasingly complex and useful functions. However, because the functions we engineer cells to perform are typically unnecessary for cellular survival and burdensome to cell growth, they can be rapidly lost due to the processes of mutation and natural selection. To improve the evolutionary stability of engineered functions in a general manner, we developed an integrase-recombination-based differentiation gene circuit in Escherichia coli. In this system, differentiated cells uniquely carry out burdensome or toxic engineered functions but have limited capacity to grow (terminal differentiation), preventing the propagation of selectively advantageous loss of function mutations that inevitably arise. To experimentally implement terminal differentiation, we co-opted the R6K plasmid system, using differentiation to simultaneously activate T7 RNAP-driven expression of arbitrary engineered functions, and inactivate expression of π protein (an essential factor for R6K plasmid replication), thereby allowing limitation of differentiated cell growth through antibiotic selection. We experimentally demonstrate terminal differentiation increases both duration and magnitude of high-burden T7 RNAP-driven expression, and that its evolutionary stability can be further improved with strategic redundancy. Using burdensome overexpression of a fluorescent protein as a model engineered function, our terminal differentiation circuit results in a ~2.8-fold (single-cassette) and ~4.2-fold (two-cassette) increase of total fluorescent protein produced compared to high-burden naive expression in which all cells inducibly express T7 RNAP. Finally, we demonstrate that differentiation can enable the expression of even toxic functions, a feat not achieved to our knowledge by any other strategy for addressing long-term evolutionary stability. Overall, this study provides an effective generalizable strategy for protecting engineered functions from evolutionary degradation.
A Method for Cost-Effective and Rapid Characterization of Engineered T7-based Transcription Factors by Cell-Free Protein Synthesis Reveals Insights into the Regulation of T7 RNA Polymerase-Driven Expression
Authors: McManus John B. , Murray Richard M. , Emanuel Peter A. , Lux Matthew W. 
Published: April 2019

AbstractThe T7 bacteriophage RNA polymerase (T7 RNAP) serves as a model for understanding RNA synthesis, as a tool for protein expression, and as an actuator for synthetic gene circuit design in bacterial cells and cell-free extract. T7 RNAP is an attractive tool for orthogonal protein expression in bacteria owing to its compact single subunit structure and orthogonal promoter specificity. Understanding the mechanisms underlying T7 RNAP regulation is important to the design of engineered T7-based transcription factors, which can be used in gene circuit design. To explore regulatory mechanisms for T7 RNAP-driven expression, we developed a rapid and cost-effective method to characterize engineered T7-based transcription factors using cell-free protein synthesis and an acoustic liquid handler. Using this method, we investigated the effects of the tetracycline operator’s proximity to the T7 promoter on the regulation of T7 RNAP-driven expression. Our results reveal a mechanism for regulation that functions by interfering with the transition of T7 RNAP from initiation to elongation and validates the use of the method described here to engineer future T7-based transcription factors.HighlightsDevelopment of a rapid and cost-effective method for screening synthetic promoters.Insights into the regulation of engineered T7-based transcription factors and T7 RNAP enzyme kinetics.Validation of this method by comparison with the T7 RNAP kinetic model.
An improved method to produce clinical scale natural killer cells from human pluripotent stem cells
Authors: Zhu Huang , Kaufman Dan S. 
Published: April 2019

AbstractHuman natural killer (NK) cell-based adoptive anti-cancer immunotherapy has gained intense interest with many clinical trials actively recruiting patients to treat a variety of both hematological malignancies and solid tumors. Most of these trials use primary NK cells isolated either from peripheral blood (PB-NK cells) or umbilical cord blood (UCB-NK cells), though these sources require NK cell collection for each patient leading to donor variability and heterogeneity in the NK cell populations. In contrast, NK cells derived human embryonic stem cells (hESC-NK cells) or induced pluripotent stem cells (hiPSC-NK cells) provide more homogeneous cell populations that can be grown at clinical scale, and genetically engineered if desired. These characteristics make hESC/iPSC-derived NK cells an ideal cell population for developing standardized, “off-the-shelf” immunotherapy products. Additionally, production of NK cells from undifferentiated human pluripotent stem cells enables studies to better define pathways that regulate human NK cell development and function. Our group previously established a stromal-free, two-stage culture system to derive NK cells from hESC/hiPSC in vitro followed by clinical-scale expansion of these cells using interleukin-21 expressing artificial antigen-presenting cells. However, prior to differentiation, this method requires single cell adaption of hESCs/hiPSCs which takes months. Recently we optimized this method by adapting the mouse embryonic fibroblast-dependent hESC/hiPSC to feeder-free culture conditions. These feeder-free hESC/hiPSCs are directly used to generate hemato-endothelial precursor cells. This new method produces mature, functional NK cells with higher efficiency to enable rapid production of an essentially unlimited number of homogenous NK cells that can be used for standardized, targeted immunotherapy for the treatment of refractory cancers and infectious diseases.
Targeted mRNA demethylation using an engineered dCas13b-ALKBH5 fusion protein
Authors: Li Jiexin , Chen Zhuojia , Chen Feng , Ling Yuyi , Peng Yanxi , Luo Nan , Wang Hongsheng 
Published: April 2019

AbstractStudies on biological functions ofN6-methyladenosine (m6A) modification in mRNA have sprung up in recent years. Here we construct and characterize a CRISPR-Cas13b-based tool for the first time that targeted m6A methylation of mRNA by fusing the catalytically dead Type VI-B Cas13 enzyme from Prevotella sp.P5-125 (dPspCas13b) with the m6A demethylase ALKBH5, which is named as dm6ACRISPR. Subsequently, such system is shown to specific demethylase the m6A of target mRNA such as CYB5A to increase its mRNA stability. In addition, the dm6ACRISPR system appeared to afford efficient demethylation of the target genes with tenuous off-target effects. Together, we provide a programmable andin vivomanipulation tool to study mRNA modification and its potential biological functions of specific gene.
A How-To guide to: Quantitative high-speed video profiling to discriminate between variants of primary ciliary dyskinesia
Authors: Chioccioli M. , Feriani L. , Nguyen Q. , Kotar J. , Dell S. D. , Mennella V. , Amirav I. , Cicuta P. 
Published: April 2019

AbstractThis document presents detailed steps to analysing the waveforms of beating cilia, measured in high speed video microscopy. We show that in the case of PCD caused by mutations inDNAH11andHYDINthe classification by a handful of parameters describing ciliary dynamics allows to distinguish the genotype, as well as (much more easily) distinguishing healthy from PCD samples. This document is intended to complement the brief highlight (1) and presents the details of the datasets used in that letter.