title: Modeling the effects of Aedes aegypti's larval environment on adult body mass at emergence

abstract:
Mosquitoes vector harmful pathogens that infect millions of people every year, and developing approaches to effectively control mosquitoes is a topic of great interest. However, the success of many control measures is highly dependent upon ecological, physiological, and life history traits of the mosquito species. The behavior of mosquitoes and their potential to vector pathogens can also be impacted by these traits. One trait of interest is mosquito body mass, which depends upon many factors associated with the environment in which juvenile mosquitoes develop. Our experiments examined the impact of larval density on the body mass of Aedes aegypti mosquitoes, which are important vectors of dengue, Zika, yellow fever, and other pathogens. To investigate the interactions between the larval environment and mosquito body mass, we built a discrete time mathematical model that incorporates body mass, larval density, and food availability and fit the model to our experimental data. We considered three categories of model complexity informed by data, and selected the best model within each category using Akaikes Information Criterion. We found that the larval environment is an important determinant of the body mass of mosquitoes upon emergence. Furthermore, we found that larval density has greater impact on body mass of adults at emergence than on development time, and that inclusion of density dependence in the survival of female aquatic stages in models is important. We discuss the implications of our results for the control of Aedes mosquitoes and on their potential to spread disease.

Author summaryIn this work we examined how the environment in which young mosquitoes develop affects their adult body size as measured by adult body mass. Adult size has potential impacts on mosquito behavior and the ability of mosquitoes to transmit disease. We used a combination of experimental work and mathematical modeling to determine important factors affecting adult mosquito body size. In our model, we incorporated potentially interacting aspects of the mosquito life cycle and traits that affect mosquito growth as juveniles. These aspects include body mass, density of the population, and level of available resource. We compared different models to determine the one that best describes the data. As mass at emergence is linked to the success of adult mosquitoes to produce offspring and to their ability transmit pathogens, we discuss how important influences on development and survival of young mosquitoes affect mosquito control and disease spread.


title: Impact of Grazing Intensity on Plant Functional Groups richness, Biomass and Diversity in Hulunbuir Meadow Steppe, China

abstract: Livestock grazing is one of the major land uses, causing changes in the plant community's structure and grasslands composition. We assessed the effect of grazing intensity on aboveground biomass, species richness, and plant functional group (PFG) diversity in a temperature meadow steppe in Hulunbuir in northern China, involving 78 plant species from eight functional groups. Four grazing intensity classes were characterized, including light, moderate, heavy, and no grazing, based on stocking rates of 0.23, 0.46, 0.92, and 0.00 animal units per hectare. Our results show that the richness of short species, including perennial short grass, perennial short grass, and legume increased under light to moderate grazing, while no effect of grazing was observed on the richness of shrubs. With increasing grazing intensity, the aboveground biomass of perennial tall grasses and perennial tall forbs decreased significantly, while that of annual/biennial plant functional groups increased. The community diversity and evenness of annual/biennial plants increased significantly with grazing intensity. We concluded that heavy grazing has negative impacts on plant functional group richness and aboveground biomass.

category: ecology


title: Scelestial: fast and accurate single-cell lineage tree inference based on a Steiner tree approximation algorithm

abstract: Single-cell genome sequencing provides a highly granular view of biological systems but is affected by high error rates, allelic amplification bias, and uneven genome coverage. This creates a need for data-specific computational methods, for purposes such as for cell lineage tree inference. The objective of cell lineage tree reconstruction is to infer the evolutionary process that generated a set of observed cell genomes. Lineage trees may enable a better understanding of tumor formation and growth, as well as of organ development for healthy body cells. We describe a method, Scelestial, for lineage tree reconstruction from single-cell data, which is based on an approximation algorithm for the Steiner tree problem and is a generalization of the neighbor-joining method. We adapt the algorithm to efficiently select a limited subset of potential sequences as internal nodes, in the presence of missing values, and to minimize cost by lineage tree-based missing value imputation. In a comparison against seven state-of-the-art single-cell lineage tree reconstruction algorithms - BitPhylogeny, OncoNEM, SCITE, SiFit, SASC, SCIPhI, and SiCloneFit - on simulated and real single-cell tumor samples, Scelestial performed best at reconstructing trees in terms of accuracy and run time. Scelestial has been implemented in C++. It is also available as an R package named RScelestial.

category: bioinformatics


title: Quantification of long-term doxorubicin response dynamics in breast cancer cell lines to direct treatment schedules

abstract: While acquired chemoresistance is recognized as a key challenge to treating many types of cancer, the dynamics with which drug sensitivity changes after exposure are poorly characterized. Most chemotherapeutic regimens call for repeated dosing at regular intervals, and if drug sensitivity changes on a similar time scale then the treatment interval could be optimized to improve treatment performance. Theoretical work suggests that such optimal schedules exist, but experimental confirmation has been obstructed by the difficulty of deconvolving the simultaneous processes of death, adaptation, and regrowth taking place in cancer cell populations. Here we present work characterizing dynamic changes in sensitivity to the chemotherapeutic doxorubicin in three breast cancer cell lines subjected to treatment schedules varying in concentration, interval between pulse treatments, and number of sequential pulse treatments. Cell populations are monitored longitudinally through automated imaging for 600-800 hours, and this data is used to calibrate a family of cancer growth models derived from the bi-exponential model which characterizes resistant and sensitive subpopulations. We identify a model incorporating both a period of growth arrest in surviving cells and a delay in the death of chemosensitive cells which outperforms the original bi-exponential growth model in Akaike Information Criterion based model selection, and use the calibrated model to quantify the performance of each drug schedule. We find that the inter-treatment interval is a key variable in determining the performance of sequential dosing schedules and identify an optimal retreatment time for each cell line which extends regrowth time by 40%-106%, demonstrating that the time scale of changes in chemosensitivity following doxorubicin exposure allows optimization of drug scheduling by varying this inter-treatment interval.

category: cancer biology


title: A panel of single nucleotide polymorphism (SNP) markers identifies potential duplicates in cassava (Manihot esculenta Crantz) varieties from Cote dIvoire

abstract: Accurate identification of varieties is paramount to optimizing efficiencies in the management and conservation of genetic resources. A relatively inexpensive, rapid methodology is required to identify putative duplicates from any collection, when morphological traits give insufficient discrimination. Here we select a panel of 36 SNPs, visualized using the Kompetitive Allele-specific PCR (KASP) system. We used a panel of 95 cassava genotypes from Cote dIvoire to identify varieties that are not duplicates and few potential duplicates which could be put forward for further verification. The genetic variability and population structure of the germplasm is also described. 36 SNPs were polymorphic across the panel of 95 varieties with polymorphic information contents ranging from 0.23 to 0.37. Using these SNPs, we were able to identify 66 unique genotypes from the panel of 95 genotypes, discriminate three sets of known duplicates and identify 11 sets of unknown putative duplicates which can be subjected to further verification using higher density genotyping. As expected in an outcrossing species, both expected heterozygosity (0.46) and observed heterozygosity (0.48) were high with an analysis of molecular variance (AMOVA) indicating that the majority of variation was within individuals. Three statistical approaches i.e., hierarchical ascending clustering, Bayesian analysis and discriminant analysis of principal components were used and all revealed low genetic differentiation between sub-populations, a conclusion that was supported by the low value of the fixation index (0.05). This panel of SNPs can be used to enhance cost-effectiveness and efficiency of germplasm conservation and enhance quality control at various stages in the breeding process through varietal tracking.

category: plant biology


title: The Molecular Logic Organizing the Functional Compartmentalization of Reciprocal Synapses

abstract: Reciprocal synapses are formed by neighboring dendritic processes that create the smallest possible neural circuit. Reciprocal synapses are widespread in brain and essential for information processing, but constitute a conceptual conundrum: How are adjacent pre- and post-synaptic specializations maintained as separate functional units? Here, we reveal an organizational principle for reciprocal synapses, using dendrodendritic synapses between mitral and granule cells in the mouse olfactory bulb as a paradigm. We show that mitral cells secrete cerebellin-1 to block the cis-interaction of mitral cell neurexins with neuroligins, thereby enabling their separate trans-interactions. Ablating either cerebellin-1 or neuroligins in mitral cells severely impaired granule cell[->]mitral cell synapses, as did overexpression of postsynaptic neurexins that form cis-complexes with neuroligins, but not of mutant neurexins unable to bind to neuroligins. Our data uncover a cis/trans-protein interaction network as a general design principle that organizes reciprocal dendro-dendritic synapses by compartmentalizing neurexin-based trans-synaptic protein complexes.

category: neuroscience


title: Multiple Causal Variants Underlie Genetic Associations in Humans

abstract: The majority of associations between genetic variation and human traits and diseases are non-coding and in strong linkage disequilibrium (LD) with surrounding genetic variation. In these cases, a single causal variant is often assumed to underlie the association, however no systematic assessment of the number of causal variants has been performed. In this study, we applied a massively parallel reporter assay (MPRA) in lymphoblastoid cells to functionally evaluate 49,256 allelic pairs, representing 30,893 genetic variants in high, local linkage disequilibrium for 744 independent cis-expression quantitative trait loci (eQTL) and assessed each for colocalization across 114 traits. We identified 8,502 allele-independent regulatory regions containing 1,264 allele-specific regulatory variants, and found that 17.7% of eQTL contained more than one significant allelic effect. We show that detected regulatory variants are highly and specifically enriched for activating chromatin structures and allelic transcription factor binding, for which ETS-domain family members are a large driver. Integration of MPRA profiles with eQTL/complex trait colocalizations identified causal variant sets for associations with blood cell measurements, Asthma, Multiple Sclerosis, Inflammatory Bowel Disease, and Crohns Disease. These results demonstrate that a sizable number of association signals are manifest through multiple, tightly-linked causal variants requiring high-throughput functional assays for fine-mapping.

category: genetics


title: On the intersection between data quality and dynamical modelling of large-scale fMRI signals

abstract: Large-scale dynamics of the brain are routinely modelled using systems of nonlinear dynamical equations that describe the evolution of population-level activity, with distinct neural populations often coupled according to an empirically measured structural connection matrix. This modelling approach has been used to generate insights into the neural underpinnings of spontaneous brain dynamics, as recorded with techniques such as resting state functional MRI (fMRI). In fMRI, researchers have many degrees of freedom in the way that they can process the data and recent evidence indicates that the choice of pre-processing steps can have a major effect on empirical estimates of functional connectivity. However, the potential influence of such variations on modelling results are seldom considered. Here we show, using three popular whole-brain dynamical models, that different choices during fMRI preprocessing can dramatically affect model fits and interpretations of findings. Critically, we show that the ability of these models to accurately capture patterns in fMRI dynamics is mostly driven by the degree to which they fit global signals rather than interesting sources of coordinated neural dynamics. We show that widespread deflections can arise from simple global synchronisation. We introduce a simple two-parameter model that captures these fluctuations and which performs just as well as more complex, multi-parameter biophysical models. From our combined analyses of data and simulations, we describe benchmarks to evaluate model fit and validity. Although most models are not resilient to denoising, we show that relaxing the approximation of homogeneous neural populations by more explicitly modelling inter-regional effective connectivity can improve model accuracy at the expense of increased model complexity. Our results suggest that many complex biophysical models may be fitting relatively trivial properties of the data, and underscore a need for tighter integration between data quality assurance and model development.


title: ABO blood group is involved in the quality of the specific immune response

abstract:
Since December 2019, the coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread throughout the world. To eradicate it, it is crucial to acquire a strong and long-lasting anti-SARS-CoV-2 immunity, by either natural infection or vaccination. We collected blood samples 12-305 days after positive polymerase chain reactions (PCRs) from 35 recovered individuals infected by SARS-CoV-2. Peripheral blood mononuclear cells were stimulated with SARS-CoV-2-derived peptide pools, such as the Spike (S), Nucleocapsid (N), and Membrane (M) proteins, and we quantified anti-S immunoglobulins in plasma. After 10 months post-infection, we observed a sustained SARS-CoV-2-specific CD4+ T-cell response directed against M-protein, but responses against S- or N-proteins were lost over time. Besides, we demonstrated that A-group individuals presented significantly higher frequencies of specific CD4+ T-cell responses against Pep-M than O-group individuals. The A-group subjects also needed longer to clear the virus and they lost cellular immune responses over time, compared to the O-group individuals, who showed a persistent specific immune response against SARS-CoV-2. Therefore, the S-specific immune response was lost over time, and individual factors determine the sustainability of the bodys defences, which must be considered in the future design of vaccines to achieve continuous anti-SARS-CoV-2 immunity.

SummaryThis work describes that cellular responses against SARS-CoV-2 M-protein can be detected after 10 months but were lost against S- and N-proteins. Moreover, the individual factors; ABO-group and age influence the sustainability of the specific humoral and cellular immunity against SARS-CoV-2.

category: immunology


title: Signatures of genetic variation in human microRNAs point to processes of positive selection related to population-specific disease risks

abstract: The occurrence of natural variation in human microRNAs has been the focus of numerous studies during the last twenty years. Most of them have been dedicated to study the role of specific mutations in diseases, like cancer, while a minor fraction seek to analyse the diversity profiles of microRNAs in the genomes of human populations. In the present study we analyse the latest human microRNA annotations in the light of the most updated catalog of genetic variation provided by the 1000 Genomes Project. We show by means of the in silico analysis of noncoding variation of microRNAs that the level of evolutionary constraint of these sequences is governed by the interplay of different factors, like their evolutionary age or the genomic location where they emerged. The role of mutations in the shaping of microRNA-driven regulatory interactions is emphasized with the acknowledgement that, while the whole microRNA sequence is highly conserved, the seed region shows a pattern of higher genetic diversity that appears to be caused by the dramatic frequency shifts of a fraction of human microRNAs. We highlight the participation of these microRNAs in population-specific processes by identifying that not only the seed, but also the loop, are particularly differentiated regions among human populations. The quantitative computational comparison of signatures of population differentiation showed that candidate microRNAs with the largest differences are enriched in variants implicated in gene expression levels (eQTLs), selective sweeps and pathological processes. We explore the implication of these evolutionary-driven microRNAs and their SNPs in human diseases, such as different types of cancer, and discuss their role in population-specific disease risk.

category: evolutionary biology


title: Mating duration and prolonged post-copulatory associations in Arrenurus water mites (Actinotrichida: Parasitengonina: Hydrachnidiae)

abstract: Conflicts of interest between the sexes over control of mating can be reflected in various aspects of morphology and behaviour, including structure of genitalia and copulation duration. In Arrenurus water mites (Hydrachnidia: Arrenuridae) there are two main patterns of sperm transfer that differ in degree of potential male control of sperm uptake by females. In some species, males are equipped with an intromittent organ (the  petiole) that is used to forcefully insert sperm into the female reproductive tract. In others, males lack an intromittent organ and females appear to push sperm into their reproductive opening themselves. Theory suggests that the amount of time spent in courtship after sperm transfer should differ between males with and without an intromittent structure. We predicted that male Arrenurus able to push sperm into the females reproductive tract (petiolate males) should spend less time courting females after transferring sperm than apetiolate males, which may have to  convince females to take up their sperm. Here, we examined durations of mating for 10 species of Arrenurus with males that differ in genital morphology: six species with males equipped with a well developed petiole (=  petiolate species) and four species with males that either completely lack a petiole or have a minute peg-like petiole that does not appear to function as an intromittent organ (=  apetiolate species). We tested whether males of petiolate species spend less time in the stage of courtship that takes place after sperm transfer (=  post-transfer courtship) than apetiolate males. In contrast to our prediction, we found that species with well developed petioles spent significantly more time in post-transfer behaviours than species lacking petioles. The possible function of protracted post-transfer courtship in the genus Arrenurus is discussed.


title: Preliminary genetic assessment of three goatfish species in the Mediterranean Sea

abstract: We examined genetic diversity and connectivity of two indigenous Mediterranean goatfish species (Mullus barbatus and M. surmuletus), and a Lessepsian migrant species (Upeneus moluccensis), across the Nile Delta outflow using two mitochondrial DNA markers (COI and cyt b). Genetic diversity was high for the two Mediterranean species but relatively lower for the migrant species, suggesting founder effects after invasion from the Red Sea. Confirmation of this hypothesis, however, would require comparison with populations of origin in the Red Sea and the Indo-West Pacific. AMOVA and network analyses revealed no genetic partitioning for all species, indicating the Nile outflow does not currently, and may not have historically, posed a significant barrier to larval dispersal in these goatfish despite a present-day temperature and salinity gradient along the Mediterranean coastline of Egypt.


title: Testing the maintenance of natural responses to survival-relevant calls in the conservation breeding population of a critically endangered corvid (Corvus hawaiiensis)

abstract:
Vocal communication serves an important role in driving many animals social interactions and ultimately their survival. However, both the structure of and responses towards natural vocal behavior can be lost or subject to alteration under human care. Determining if animals in conservation breeding programs exhibit and respond appropriately to species-specific vocalizations is therefore important for ensuring their survival and persistence post-release. We tested whether endangered  alal[a] (Corvus hawaiiensis), which are extinct in nature, have retained their natural responses to vocal calls that were previously linked to survival and reproduction in the wild. We conducted our studies on breeding populations derived from a small number of founding  alal[a] maintained under human care since their extinction in the wild in 2002. We presented pairs of  alal[a] with alarm, territorial intrusion, and two types of control playback calls (a non-threatening territorial maintenance call and a novel heterospecific call).  Alal[a] were significantly more likely to approach the speaker following alarm call playback than other call types, and were more likely to respond to territorial intrusion calls with the same aggressive territorial calls. Males were more likely to make these aggressive calls than females, mirroring their roles in territory defense. We also found individual consistency in the level of vocal behavior response across all call types, indicating that some individuals are more vocal than others. These results are encouraging, showing that  alal[a] exhibit relevant, species-specific behaviors despite generations under human care. They do illustrate, however, that not all individuals respond appropriately, so animals responses to vocal stimuli may be an important factor to consider in determining the release suitability of individuals.

Significance StatementEffective communication is crucial to the survival of many animals, but can erode without natural selection. Therefore, testing the flexibility and maintenance of communication and vocal responses in contexts where animals are isolated from conspecifics or from survival consequences, such as in conservation breeding centers, can help determine species susceptibility to communication loss. We used playbacks of survival-related conspecific calls to test if  alal[a] (Corvus hawaiiensis), retained species-specific responses to these calls after generations under human care. We found that birds maintained a species-level natural response, however these natural responses were not consistent across individuals, suggesting that some birds may not be well equipped to survive in the wild without additional training or care.

category: animal behavior and cognition


title: A note on decoding elicited and self-generated inner speech

abstract: A recent result shows that inner speech can, with proper care, be decoded to the same high-level of accuracy as articulated speech. This relies, however, on neural data obtained while subjects perform elicited tasks, such as covert reading and repeating, whereas a neural speech prosthetic will require the decoding of inner speech that is self-generated. Prior work has, moreover, emphasised differences between these two kinds of inner speech, raising the question of how well a decoder optimised for one will generalise to the other. In this study, we trained phoneme-level decoders on an atypically large, elicited inner speech dataset, previously acquired using 7T fMRI in a single subject. We then acquired a second self-generated inner speech dataset in the same subject. Although the decoders were trained exclusively on neural recordings obtained during elicited inner speech, they predicted unseen phonemes accurately in both elicited and selfgenerated test conditions, illustrating the viability of zero-shot task transfer. This has significant practical importance for the development of a neural speech prosthetic, as labelled data is far easier to acquire at scale for elicited than for self-generated inner speech. Indeed, elicited tasks may be the only option for acquiring labelled data in critical patient populations who cannot control their vocal articulators.

category: bioengineering


title: Distance-based Reconstruction of Protein Quaternary Structures from Inter-Chain Contacts

abstract: Predicting the quaternary structure of a protein complex is an important and challenging problem. Inter-chain residue-residue contact prediction can provide useful information to guide the ab initio reconstruction of quaternary structures of protein complexes. However, few methods have been developed to build quaternary structures from predicted inter-chain contacts. Here, we introduce a new gradient descent optimization algorithm (GD) to build quaternary structures of protein dimers utilizing inter-chain contacts as distance restraints. We evaluate GD on several datasets of homodimers and heterodimers using true or predicted contacts. GD consistently performs better than a simulated annealing method and a Markov Chain Monte Carlo simulation method. Using true inter-chain contacts as input, GD can reconstruct high-quality structural models for homodimers and heterodimers with average TM-score ranging from 0.92 to 0.99 and average interface root mean square distance (I-RMSD) from 0.72 [A] to 1.64 [A]. On a dataset of 115 homodimers, using predicted inter-chain contacts as input, the average TM-score of the structural models built by GD is 0.76. For 46% of the homodimers, high-quality structural models with TM-score >= 0.9 are reconstructed from predicted contacts. There is a strong correlation between the quality of the reconstructed models and the precision and recall of predicted contacts. If the precision or recall of predicted contacts is >20%, GD can reconstruct good models for most homodimers, indicating only a moderate precision or recall of inter-chain contact prediction is needed to build good structural models for most homodimers. Moreover, the accuracy of reconstructed models positively correlates with the contact density in dimers and depends on the initial model and the probability threshold of selecting predicted contacts for the distance-based structure optimization.


title: BaySiCle: A Bayesian Inference joint kNN method for imputation of single-cell RNA-sequencing data making use of local effect

abstract:
There is a marked technical variability and a high amount of missing observations in the single-cell data that we obtain from experiments. Apart from that clearly each of the batch of experiments have a batch effect on every cell in the batch. This batch effect can be taken into advantage for dealing with imputation, given that all the cells in a given batch belong to the same tissue. Here we introduce  BaySiCle, a novel Bayesian inference based method combined with k-nearest neighbors algorithm for the imputation of missing data in scRNA-seq counts. The priors are found out based on expression value across cells for all the single cells of the same batch. We demonstrate using sample scRNA-seq datasets and simulated expression data that BaySiCle allows robust imputation of missing values generating realistic transcript distributions that match single molecule fluorescence in situ hybridization measurements. By using priors as obtained by the dataset structures in the not just the experimental set-up batch, but also the same group of cells, BaySiCle improves accuracy of imputation to be that much closer to its similar alternatives.

Availability and implementationThe Python Jupyter notebook  BaySiCle is published on GitHub GitHub - abinarain/BaySiCel: Single Cell Data Imputation using Bayesian statistics and kNN


title: Improved HIV-1 drug resistance mutation prediction using quasispecies reconstruction supported analysis

abstract: Accurate and sensitive approaches to detect HIV-1 drug resistance mutations (DRMs) are indispensable for the paradigm of  treatment as prevention. While HIV-1 proviral DNA allows sensitive high throughput sequencing (HTS)-based DRM detection, its applicability is limited by presence of defective genomes. This study demonstrates application of quasispecies reconstruction algorithms (QRAs) to improve DRM detection sensitivity from proviral DNA. A robust benchmarking of 5 QRAs was performed with 2 distinct experimental control-datasets including a stringent, novel control: DCPM, simulating in-vivo variant distribution (0.08%-86.5%). Selected QRA was further evaluated for its ability to differentiate DRMs from hypermutated sequences using an in-silico control. PredictHaplo outperformed all others in terms of precision and was selected for further analysis. Near full-genome HTS was performed on proviral DNA from 20 HIV-1C infected individuals, at different stages of ART, from Mumbai, India. DRM detection was performed through residue-wise variation analysis and implementation of QRAs. Both analyses were highly concordant for DRM frequencies >10% (spearman r=0.91, p<0.0001). Phylogenetic association in HTS datasets with shared transmission history could also be demonstrated by PredictHaplo. This study highlights utility of QRAs as an adjunct to traditional residue-wise variation-based DRM detection leading to optimal personalized ART as well as better disease management.


title: ProteinBERT: A universal deep-learning model of protein sequence and function

abstract: Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. However, existing models and pretraining methods are designed and optimized for text analysis. We introduce ProteinBERT, a deep language model specifically designed for proteins. Our pretraining scheme consists of masked language modeling combined with a novel task of Gene Ontology (GO) annotation prediction. We introduce novel architectural elements that make the model highly efficient and flexible to very large sequence lengths. The architecture of ProteinBERT consists of both local and global representations, allowing end-to-end processing of these types of inputs and outputs. ProteinBERT obtains state-of-the-art performance on multiple benchmarks covering diverse protein properties (including protein structure, post translational modifications and biophysical attributes), despite using a far smaller model than competing deep-learning methods. Overall, ProteinBERT provides an efficient framework for rapidly training protein predictors, even with limited labeled data. Code and pretrained model weights are available at https://github.com/nadavbra/protein_bert.


title: Correlated Drug Action as a Baseline Additivity Model for Combination Cancer Therapy in Patient Cohorts and Cell Cultures

abstract: Identifying and characterizing the effect of combination cancer therapies is of paramount importance in cancer research. The benefit of a combination can originate in the inherent heterogeneity in the response across patients, the heterogeneity in the clonal composition of tumors in each patient, or in molecular synergy between the compounds given in combination. The effect of drug combinations is usually studied in cell culture, in patient populations or both. To shed light and help characterize combinations and their enhanced benefits over single therapies, we introduce Correlated Drug Action (CDA) as a baseline additivity model. We formulate the CDA theory and propose to model it using a closed-form expression both in the temporal domain (tCDA) to explain survival curves, and in the dose domain (dCDA), to explain dose-response curves. CDA can be used in clinical trials and cell culture experiments. At the level of clinical trials, we demonstrate tCDAs utility in identifying non-additive combinations, and cases where the combination can be explained in terms of the monotherapies. At the level of cells in culture, dCDA naturally embeds null models such as Bliss additivity, the Highest Single Agent model, the dose equivalence principle and sham combinations. We demonstrate the applicability of dCDA in assessing non-additive combinations in experimental data by introducing a new metric, the Excess over CDA (EOCDA). CDA is a general framework to model additivity at the cell line and patient population levels and can be used to characterize and quantify the degree of non-additivity in drug combination therapy.


title: Maximum Parsimony Reconciliation in the DTLOR Model

abstract:
BackgroundAnalyses of microbial evolution often use reconciliation methods. However, the standard duplication-transfer-loss (DTL) model does not account for the fact that species trees are often not fully sampled and thus, from the perspective of reconciliation, a gene family may enter the species tree from the outside. Moreover, within the species tree, genes are often rearranged, causing them to move to new syntenic "regions."

ResultsWe extend the DTL model to account for two events that commonly arise in the evolution of microbes: evolution occurring outside the sampled species tree and changes in the syntenic regions of genes in the genome due to rearrangement. We describe an efficient algorithm for maximum parsimony reconciliation in this new DTLOR model and then show how it can be extended to account for non-binary gene trees. Finally, we describe preliminary experimental results from the integration of our algorithm into the existing xenoGI tool for reconstructing the histories of genomic islands in closely related bacteria.

ConclusionsReconciliation in the DTLOR model can offer new insights into the evolution of microbes that is not currently possible under the DTL model.


title: Visualizing the Role of Lipid Dynamics during Infrared Neural Stimulation with Hyperspectral Stimulated Raman Scattering Microscopy

abstract: Infrared neural stimulation, or INS, is a method of using pulsed infrared light to yield label-free neural stimulation with broad experimental and translational utility. Despite its robust demonstration, the mechanistic and biophysical underpinnings of INS have been the subject of debate for more than a decade. The role of lipid membrane thermodynamics appears to play an important role in how fast IR-mediated heating nonspecifically drives action potential generation. Direct observation of lipid membrane dynamics during INS remains to be shown in a live neural model system. To directly test the involvement of lipid dynamics in INS, we used hyperspectral stimulated Raman scattering (hsSRS) microscopy to study biochemical signatures of high-speed vibrational dynamics underlying INS in a live neural cell culture model. Findings suggest that lipid bilayer structural changes are occurring during INS in vitro in NG108-15 neuroglioma cells. Lipid-specific signatures of cell SRS spectra were found to vary with stimulation energy and radiant exposure. Spectroscopic observations were verified against high-speed ratiometric fluorescence imaging of a conventional lipophilic membrane structure reporter, di-4-ANNEPS. Overall, the presented data supports the hypothesis that INS causes changes in the lipid membrane of neural cells by changing lipid membrane packing order - which coincides with likelihood of cell stimulation. Furthermore, this work highlights the potential of hsSRS as a method to study biophysical and biochemical dynamics safely in live cells.

category: biophysics


title: CuAAC stabilization of an NMR mixed labeled dimer

abstract: Homo dimers are the most abundant type of enzyme in cells and as such, they represent the archetypal system for studying the remarkable phenomenon of allostery. In these systems, in which the allosteric features are manifest by the effect of the first binding event on the similar event at the second site, the most informative state is the asymmetric single bound (lig1) form, yet it tends to be elusive thermodynamically. Here we take significant steps towards obtaining milligram quantities of pure lig1 of the allosteric homodimer, chorismate mutase, in the form of a mixed isotopically labeled dimer stabilized by Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) between the subunits. Below, we outline several critical steps required to generate high yields of both types of unnatural amino acid-containing proteins, and overcome multiple pitfalls intrinsic to CuAAC to obtain high yields of pure, fully intact, and active mixed labeled dimer. These data not only will make possible NMR-based investigations of allostery envisioned by us, but should also facilitate other structural applications where specific linkage of proteins is helpful.


title: DLPacker: Deep Learning for Prediction of Amino Acid Side Chain Conformations in Proteins

abstract: AO_SCPLOWBSTRACTC_SCPLOWPrediction of side chain conformations of amino acids in proteins (also termed  packing) is an important and challenging part of protein structure prediction with many interesting applications in protein design. A variety of methods for packing have been developed but more accurate ones are still needed. Machine learning (ML) methods have recently become a powerful tool for solving various problems in diverse areas of science, including structural biology. In this work we evaluate the potential of Deep Neural Networks (DNNs) for prediction of amino acid side chain conformations. We formulate the problem as image-to-image transformation and train a U-net style DNN to solve the problem. We show that our method outperforms other physics-based methods by a significant margin: reconstruction RMSDs for most amino acids are about 20% smaller compared to SCWRL4 and Rosetta Packer with RMSDs for bulky hydrophobic amino acids Phe, Tyr and Trp being up to 50% smaller.


title: Mechanics of inactive swelling and bursting of porate pollen grains

abstract: The mechanical structure of pollen grains, typically characterized by soft apertures in an otherwise stiff exine shell, guides their response to changes in the humidity of the environment. These changes can lead both to infolding but also to excessive swelling and even bursting of pollen grains. We use an elastic model to explore the mechanics of pollen grain swelling and the role that soft, circular apertures (pores) play in this process. We identify and explore a mechanical weakness of the pores, which are prone to a rapid inflation once the grain swells to a critical extent. This transition leads to the bursting of the grain and the release of its content. Our results shed light on the inactive part of the mechanical response of pollen grains to hydration once they land on a stigma as well as on bursting of airborne pollen grains during rapid changes in air humidity.


title: Cancer Prognosis According to Parthanatos Features

abstract:
For nearly 50 years, translational research studies aimed at improving chemotherapy-induced killing of cancer cells have focused on the induction of apoptosis. Here we show that a PARP-1-mediated programmed cell death mechanism "parthanatos" is associated with the successful, front-line treatment of a common cancer. Peripheral blood mononuclear cells (PBMCs) from healthy human donors (10 of 10 tested), as well as primary cancer cells from approximately 50% of acute myeloid leukemia (AML) patients (n = 18 of 39 tested, French-American-British (FAB) subtypes M4 and M5) exhibited two distinctive features of parthanatos upon treatment with a front-line drug combination of cytarabine and an anthracycline. Statistically significant improvements in survival rates were observed in the parthanatos positive versus parthanatos negative AML patient groups (HR = 0.22 - 0.38, p = 0.002 - 0.05). Near-median expression of PARP1 mRNA was associated with a 50% longer survival time (HR = 0.66, p = 0.01), and the poly [ADP-ribose] polymerase (PARP) inhibitor Olaparib exhibited antagonistic activities against ara-C and idarubicin in primary blood monocytes from healthy donors as well as primary cancer isolates from ~50% of AML patients. Together these results suggest that PARP activity is a prognostic biomarker for AML subtypes M4 and M5 and support the relevance of parthanatos in curative chemotherapy of AML.

In BriefMessikommer and co-workers report that PARP-1-mediated programmed cell death is associated with successful, front-line treatment of acute myeloid leukemia (AML).

HighlightsO_LIThe first-line cancer drug cytarabine (ara-C) induces parthanatos or apoptosis, depending on the specific AML cell line being treated.
C_LIO_LIOCI-AML3 cells undergo parthanatos or apoptosis, depending on the specific drug being added.
C_LIO_LIThe presence of two parthanatos features in primary cancer cells from AML patients (n = 18 of 39 tested) having French-American-British (FAB) subclassifications M4 or M5 is associated with four-fold improved survival (HR = 0.23, p = 0.01) following curative chemotherapy with ara-C and an anthracycline.
C_LIO_LIThe poly [ADP-ribose] polymerase (PARP) inhibitor Olaparib exhibits antagonistic activities against ara-C and idarubicin in primary blood monocytes from healthy donors as well as primary cancer isolates from ~50% of AML patients.
C_LIO_LINear-median expression of PARP1 mRNA is associated with a 50% increase in survival time (HR = 0.66, p = 0.01) of AML patients following chemotherapy with ara-C and idarubicin.
C_LI

GRAPHICAL ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=118 HEIGHT=200 SRC="FIGDIR/small/445484v1_ufig1.gif" ALT="Figure 1">
View larger version (42K):
org.highwire.dtl.DTLVardef@af2a33org.highwire.dtl.DTLVardef@1fb8e1corg.highwire.dtl.DTLVardef@2eebf4org.highwire.dtl.DTLVardef@84eb8c_HPS_FORMAT_FIGEXP  M_FIG C_FIG


title: Extremely potent human monoclonal antibodies for the prophylaxis and therapy of Tetanus

abstract: Human monoclonal antibodies were used here to study the mechanism of neuron intoxication by tetanus neurotoxin protein toxins and as a safe preventive and therapeutic substitute of hyperimmune sera. By screening memory B cells of immune donors, we selected two monoclonal antibodies specific for tetanus neurotoxin with exceptionally high neutralizing activities, which have been extensively characterized both structurally and functionally. We found that these antibodies interfere with the binding and translocation of the neurotoxin into neurons by interacting with two epitopes, whose definition pinpoints crucial events in the cellular pathogenesis of tetanus. Some mechanistic aspects of tetanus neurotoxin intoxication were revealed, explaining at the same time, the unprecedented neutralization ability of these antibodies. Importantly, these antibodies are exceptionally efficient in preventing experimental tetanus when injected in mice long before the neurotoxin. Moreover, their Fab derivatives neutralize tetanus neurotoxin in post-exposure experiments, suggesting their potential therapeutic use upon intrathecal injection. As such, these human monoclonal antibodies, as well as their Fab derivatives, meet all requirements for being considered for prophylaxis and therapy of human tetanus and are ready for clinical trials.

category: pathology


title: Effect of water temperature on the behavior of Neptunea cumingii and the histology, immune enzyme activity, and transcriptome of its gills and kidneys

abstract: The behavior of the marine snail Neptunea cumingii cultured at different temperatures (0, 4, 8, 12, 16 (control), 20, 24, and 28{degrees}C) and the histology, immune enzyme activity, and transcriptome of its gills and kidneys were studied using ecological and molecular methods. At 0{degrees}C, most of the snails shrank in size and did not eat during the first 6 h. At 28{degrees}C, snails also did not eat, death began to occur at 24 h. when the temperature was 8 {degrees}C and 12 {degrees}C, there was no significant difference in the mean feed intake of N. cumingii (P>0.05). And it was higher than the average conch intake under other temperature conditions. However, the histology of the gills and kidneys differed among test temperatures. At 0{degrees}C, the morphology of the gill pieces was difficult to judge. At 24{degrees}C, edema was present in the small gills, and at 28{degrees}C the small gills were severely deformed, the distance between the gill capillaries and the surrounding area was enlarged, and the gill tissue was severely damaged. Temperature increase or decrease from 16{degrees}C caused the columnar cells of the kidney to become shorter and more numerous. The total antioxidant capacity (T-AOC), catalase (CAT) and superoxide dismutase activities (SOD) of the gill and kidney differed significantly among the temperature conditions (p < 0.05). Transcriptome results showed that temperature change resulted in up-regulation of 2339 genes and down-regulation of 2058 genes in the gills, and in up-regulation of 2300 genes and down-regulation of 2060 genes in the kidneys of N. cumingii. Furthermore, the DEGs were subject to GO and KEGG enrichment analysis, and which showed that most of the DEGs in gill were involved in protein folding, defolding, translation, ribosome, and most of the DEGs in kidney were involved in DNA recombination, nuclear euchromatin, RNA-directed DNA polymerase activity. Finally, the results from this study show that N. cumingii prefers the temperature range was 8 to 16, temperature increase or decrease from that range, many aspects of N. cumingii biology could be significantly affected.

category: physiology


title: Homeostasis Equation: An Approach to Theoretical Medicine

abstract: Homeostasis is kind of force that makes living organism to live. In this study, we suggest an integral equation that models homeostasis in living organism. We also showed that various situations can be modeled by homeostasis, and give mathematical interpretation of mechanism of living organism. With our proposed integral equation, one can handle homeostasis quantitatively, and this approach is expected to unveil various hidden properties of living organism.


title: Integrative functional analysis uncovers metabolic differences between Candida species

abstract: Candida species are a dominant constituent of the human mycobiome and a better understanding of their metabolism from a fungal perspective can provide key insights into their ability to cause pathogenesis. Here, we have developed the BioFung database - a fungal specific tool for functional annotation using the KEGG database that provides an efficient method for annotation of protein-encoding gene. Analysis of carbohydrate-active enzyme (CAZymes) and BioFung, uncovered core and accessory features across Candida species demonstrating plasticity, adaptation to the environment and acquired features. Integerative functional analysis revealed that all Candida species can employ amino acid metabolism. However, metabolomics revealed that only a specific cluster of species (AGAu species - C. albicans, C. glabrata and C. auris) utilised amino acid metabolism. We identified critical metabolic pathways in the AGAu clusters with biomarkers and anti-fungal target potential in the CAZyme profile, polyamine, choline and fatty acid biosynthesis pathways. This study, combining genomic analysis, metabolomics and gene expression validation, highlights the metabolic diversity within AGAu species that underlies their remarkable ability to dominate the mycobiome and cause disease.

category: systems biology


title: Hydrodynamics of gliding penguin flipper suggests the adjustment of sweepback with swimming speeds

abstract: Hydrodynamic performance of a gliding penguin flipper (wing) considering the backward sweep was estimated with computational fluid dynamics (CFD) simulation. A flipper of a gentoo penguin (Pygoscelis papua) was 3D scanned, smoothed, and a numerical fluid mesh was generated. For accurate yet resource-saving computation, an embedded large-eddy simulation (ELES) methods was employed, where the flow near the flipper was solved with large-eddy simulation (LES) and flow far away from the flipper was solved with Reynolds-averaged Navier-Stokes (RANS). The relative flow speed was fixed at 2 m s-1, close to the typical foraging speed for the penguin species. The sweep angle was set to be 0{degrees}, 30{degrees}, and 60{degrees}, while the angle of attack was varied between -40{degrees} and 40{degrees}, both are within the realistic ranges in the wing kinematics measurement of penguins in an aquarium. It was revealed that a higher sweep angle reduces the lift slope, but the lift coefficient is unchanged at a high angle of attack. Drag coefficient was reduced across the angles of attack with increasing the sweep angles. The drag polars suggest the sweep angle may be adjusted with the change in swimming speed and anhedral (negative dihedral) angle to minimise drag while maintaining the vertical force balance to counteract the positive buoyancy. This will effectively expand the swimming envelope of the gliding penguin, similar to a flying counterpart such as swift.

category: zoology


title: GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging

abstract: Optical imaging of calcium signals in the brain has enabled researchers to observe the activity of hundreds-to-thousands of individual neurons simultaneously. Current methods predominantly focus on matrix factorization and aim at detecting neurons in the imaged field-of-view, and then inferring the corresponding time-traces. The explicit locality constraints on the cell shapes additionally limits the applicability to optical imaging at different scales (i.e., dendritic or widefield data). Here we present a new method that frames the problem of isolating independent fluorescing components as a dictionary learning problem. Specifically, we focus on the time-traces, which are the main quantity used in scientific discovery, and learn the dictionary of time traces with the spatial maps acting as the presence coefficients encoding which pixels the time traces are active in. Furthermore, we present a novel graph filtering model which redefines connectivity between pixels in terms of their shared temporal activity, rather than spatial proximity. This model greatly eases the ability of our method to handle data with complex non-local spatial structure, such as dendritic imaging. We demonstrate important properties of our method, such as robustness to initialization, implicitly inferring number of neurons and simultaneously detecting different neuronal types, on both synthetic data and real data examples. Specifically, we demonstrate applications of our method to calcium imaging both at the dendritic, somatic, and widefield scales.


title: Precise visuomotor transformations underlying collective behavior in larval zebrafish

abstract: Complex schooling behaviors result from local interactions among individuals. Yet, how sensory signals from neighbors are analyzed in the visuomotor stream of animals is poorly understood. Here, we studied aggregation behavior in larval zebrafish and found that over development larvae transition from overdispersed groups to tight shoals. Using a virtual reality assay, we characterized the algorithms fish use to transform visual inputs from neighbors into movement decisions. We found that young larvae turn away from retinal "clutter" by integrating and averaging retina-wide visual inputs within each eye, and by using a winner-take-all strategy for binocular integration. As fish mature, their responses expand to include attraction to low retinal clutter, that is based on similar algorithms of visual integration. Using model simulations, we show that the observed algorithms accurately predict group structure over development. These findings allow us to make testable predictions regarding the neuronal circuits underlying collective behavior in zebrafish.


title: Undivided attention: The temporal effects of attention dissociated from decision, memory, and expectation

abstract: Selective attention prioritises relevant information amongst competing sensory input. Time-resolved electrophysiological studies have shown stronger representation of attended compared to unattended stimuli, which has been interpreted as an effect of attention on information coding. However, because attention is often manipulated by making only the attended stimulus a target to be remembered and/or responded to, many reported attention effects have been confounded with target-related processes such as visual short-term memory or decision-making. In addition, the effects of attention could be influenced by temporal expectation. The aim of this study was to investigate the dynamic effect of attention on visual processing using multivariate pattern analysis of electroencephalography (EEG) data, while 1) controlling for target-related confounds, and 2) directly investigating the influence of temporal expectation. Participants viewed rapid sequences of overlaid oriented grating pairs at fixation while detecting a "target" grating of a particular orientation. We manipulated attention, one grating was attended and the other ignored, and temporal expectation, with stimulus onset timing either predictable or not. We controlled for target-related processing confounds by only analysing non-target trials. Both attended and ignored gratings were initially coded equally in the pattern of responses across EEG sensors. An effect of attention, with preferential coding of the attended stimulus, emerged approximately 230ms after stimulus onset. This attention effect occurred even when controlling for target-related processing confounds, and regardless of stimulus onset predictability. These results provide insight into the effect of attention on the dynamic processing of competing visual information, presented at the same time and location.


title: Overexpression of Reticulon 3 enhances CNS axon regeneration and functional recovery after injury

abstract: CNS neurons are generally incapable of regenerating their axons after injury due to several intrinsic and extrinsic factors, including the presence of axon growth inhibitory molecules. One such potent inhibitor of CNS axon regeneration is Reticulon (RTN) 4 or Nogo-66. Here, we focused on RTN3 as its contribution in CNS axon regeneration is currently unknown. We found that RTN3 expression correlated with an axon regenerative phenotype in dorsal root ganglion neurons (DRGN) after injury to the dorsal columns, a model of spinal cord injury. Overexpression of RTN3 promoted disinhibited DRGN neurite outgrowth in vitro and dorsal column axon regeneration/sprouting and electrophysiological, sensory and locomotor functional recovery after injury in vivo. Knockdown of protrudin however, ablated RTN3-enhanced neurite outgrowth/axon regeneration in vitro and in vivo. Moreover, overexpression of RTN3 in a second model of CNS injury, the optic nerve crush injury model, enhanced retinal ganglion cell (RGC) survival, disinhibited neurite outgrowth in vitro and survival and axon regeneration in vivo, an effect that was also dependent on protrudin. These results demonstrate that RTN3 enhances neurite outgrowth/axon regeneration in a protrudin-dependent manner after both spinal cord and optic nerve injury.


title: Disc Large Homolog 1 is critical for early microcluster formation and activation in human T cells

abstract: T cell activation by antigen involves multiple sequential steps, including TCR-microcluster (MC) formation, immunological synapse formation and phosphorylation of mediators downstream of the TCR. The adaptor protein Disc Large Homolog 1 (DLG1) is known to regulate proximal TCR signaling and, in turn, T cell activation, acting as a molecular chaperone that organizes specific kinases downstream of antigen recognition. Here, we report using knockdown and knockout studies in human T cells that DLG1 functions even earlier to regulate T cell activation by promoting TCR-MC formation. Moreover, we found that DLG1 can act as a bridge between the TCR-{zeta} chain and ZAP70 while inhibiting binding of the phosphatase SHP1 to TCR-{zeta}. Together, these effects drive dysregulation of T cell activation in DLG1-deficient T cells.


title: SCARF1-induced efferocytosis plays an immunomodulatory role in humans, and autoantibodies targeting SCARF1 are produced in patients with systemic lupus erythematosus

abstract: Deficiency in the clearance of cellular debris is a major pathogenic factor in the emergence of autoimmune diseases. We previously demonstrated that mice deficient for scavenger receptor class F member 1 (SCARF1) develop a lupus-like autoimmune disease with symptoms similar to human systemic lupus erythematosus (SLE), including a pronounced accumulation of apoptotic cells (ACs). Therefore, we hypothesized that SCARF1 will be important for clearance of ACs and maintenance of self-tolerance in humans, and that dysregulation of this process could contribute to SLE. Here, we show that SCARF1 is highly expressed on phagocytic cells, where it functions as an efferocytosis receptor. In healthy individuals, we discovered that engagement of SCARF1 by ACs on BDCA1+ dendritic cells (DCs) initiates an interleukin-10 (IL-10) anti-inflammatory response mediated by the phosphorylation of signal transducer and activator of transcription 1 (STAT1). Unexpectedly, there was no significant difference in SCARF1 expression in SLE patient samples compared to healthy donor samples. However, we detected anti-SCARF1 autoantibodies in 26% of SLE patients, which was associated with dsDNA antibody positivity. Furthermore, our data shows a direct correlation of the levels of anti-SCARF1 in the serum and defects in the removal of ACs. Depletion of immunoglobulin restores efferocytosis in SLE serum, suggesting that defects in the removal of ACs is partially mediated by SCARF1 pathogenic autoantibodies. Our data demonstrate that human SCARF1 is an AC receptor in DCs and plays a role in maintaining tolerance and homeostasis.


title: Effect of salinity and water dilution on environmental DNA degradation in freshwater environments

abstract: Environmental DNA (eDNA) analysis methods have been developed to detect the distribution and abundance/biomass of organisms in various environments. eDNA generally degrades quickly, thus the study of eDNA degradation is critical for eDNA evaluation. However, there have only been a few studies of eDNA degradation experiments in which the salt concentration and water dilution were controlled. In this study, the effects of degradation were experimentally evaluated by controlling the salinity and water dilution of pond water. An experiment was conducted to evaluate the effects of salinity and dilution on eDNA detection with fragmental eDNA and free cell-derived eDNA using pond water, diluted pond water, and saline pond water. We quantified the eDNA copies of free cells, fragmental DNA, and the eDNA from Cyprinus carpio. In both the diluted and saline pond water, we found that the degradation rate of eDNA was much slower than that in pond water. Furthermore, the DNA concentration did not exponentially decrease in both the saline purified water and purified water samples. For the lower degradation rate in salt water, we interpreted that salts may affect DNA degradation factors such as microbe compositions and activities. The effect of salinity and dilution on eDNA detection provides fundamental information about the degradation process of eDNA, which is essential to understand the behavior of eDNA in natural environments.


title: Genomic Selection for End-Use Quality and Processing Traits in Soft White Winter Wheat Breeding Program with Machine and Deep Learning Models

abstract: Breeding for grain yield, biotic and abiotic stress resistance, and end-use quality are important goals of wheat breeding programs. Screening for end-use quality traits is usually secondary to grain yield due to high labor needs, cost of testing, and large seed requirements for phenotyping. Hence, testing is delayed until later stages in the breeding program. Delayed phenotyping results in advancement of inferior end-use quality lines into the program. Genomic selection provides an alternative to predict performance using genome-wide markers. Due to large datasets in breeding programs, we explored the potential of the machine and deep learning models to predict fourteen end-use quality traits in a winter wheat breeding program. The population used consisted of 666 wheat genotypes screened for five years (2015-19) at two locations (Pullman and Lind, WA, USA). Nine different models, including two machine learning (random forest and support vector machine) and two deep learning models (convolutional neural network and multilayer perceptron), were explored for cross-validation, forward, and across locations predictions. The prediction accuracies for different traits varied from 0.45-0.81, 0.29-0.55, and 0.27-0.50 under cross-validation, forward, and across location predictions. In general, forward prediction accuracies kept increasing over time due to increments in training data size and was more evident for machine and deep learning models. Deep learning models performed superior over the traditional ridge regression best linear unbiased prediction (RRBLUP) and Bayesian models under all prediction scenarios. The high accuracy observed for end-use quality traits in this study support predicting them in early generations, leading to the advancement of superior genotypes to more extensive grain yield trailing. Furthermore, the superior performance of machine and deep learning models strengthen the idea to include them in large scale breeding programs for predicting complex traits.


title: Distinct mechanoreceptor pezo-1 isoforms modulate food intake in the nematode Caenorhabditis elegans

abstract: Two PIEZO mechanosensitive cation channels, PIEZO1 and PIEZO2, have been identified in mammals, where they are involved in numerous sensory processes. While structurally similar, PIEZO channels are expressed in distinct tissues and exhibit unique properties. How different PIEZOs transduce force, how their transduction mechanism varies, and how their unique properties match the functional needs of the tissues they are expressed in remain all-important unanswered questions. The nematode Caenorhabditis elegans has a single PIEZO ortholog (pezo-1) predicted to have twelve isoforms. These isoforms share many transmembrane domains but differ in those that distinguish PIEZO1 and PIEZO2 in mammals. We used transcriptional and translational reporters to show that putative promoter sequences immediately upstream of the start codon of long pezo-1 isoforms predominantly drive GFP expression in mesodermally derived tissues (such as muscle and glands). In contrast, sequences upstream of shorter pezo-1 isoforms resulted in GFP expression primarily in neurons. Putative promoters upstream of different isoforms drove GFP expression in different cells of the same organs of the digestive system. The observed unique pattern of complementary expression suggests that different isoforms could possess distinct functions within these organs. We used mutant analysis to show that pharyngeal muscles and glands require long pezo-1 isoforms to respond appropriately to the presence of food. The number of pezo-1 isoforms in C. elegans, their putative differential pattern of expression, and roles in experimentally tractable processes make this an attractive system to investigate the molecular basis for functional differences between members of the PIEZO family of mechanoreceptors.


title: An approach to gene-based testing accounting for dependence of tests among nearby genes

abstract: In genome-wide association studies (GWAS), it has become commonplace to test millions of SNPs for phenotypic association. Gene-based testing can improve power to detect weak signal by reducing multiple testing and pooling signal strength. While such tests account for linkage disequilibrium (LD) structure of SNP alleles within each gene, current approaches do not capture LD of SNPs falling in different nearby genes, which can induce correlation of gene-based test statistics. We introduce an algorithm to account for this correlation. When a genes test statistic is independent of others, it is assessed separately; when test statistics for nearby genes are strongly correlated, their SNPs are agglomerated and tested as a locus. To provide insight into SNPs and genes driving association within loci, we develop an interactive visualization tool to explore localized signal. We demonstrate our approach in the context of weakly powered GWAS for autism spectrum disorder, which is contrasted to more highly powered GWAS for schizophrenia and educational attainment. To increase power for these analyses, especially those for autism, we use adaptive p-value thresholding (AdaPT), guided by high-dimensional metadata modeled with gradient boosted trees, highlighting when and how it can be most useful. Notably our workflow is based on summary statistics.


title: Chromatin forms nanoscale three-dimensional packing domains with fractal-like scaling behavior in vitro

abstract: Chromatin organization over a wide range of length scales plays a critical role in the regulation of transcription and deciphering the interplay of these processes requires high-resolution, three-dimensional, quantitative imaging of chromatin structure in vitro. Herein, we introduce ChromSTEM, a method that utilizes high angle annular dark-field imaging and tomography in scanning transmission electron microscopy combined with DNA-specific staining for electron microscopy. We utilized ChromSTEM to quantify chromatin structure in cultured cells and the statistical packing behavior of the chromatin polymer. Using chromatin mass and density analysis, we observed that chromatin forms spatially well-defined higher-order domains which are around 100 nm in radius, with a radially decreasing mass-density from the center to the periphery. Although the morphological properties of the domains vary within the same cell line, they seem to exhibit greater heterogeneity across cell lines, underlying a potential role of statistical chromatin packing in regulating cell-type-specific gene expression.

category: genomics


title: Statistical Analysis of Three-Dimensional Chromatin Packing Domains Determined by Chromatin Scanning Transmission Electron Microscopy (ChromSTEM)


title: Old data and friends improve with age: Advancements with the updated tools of GeneNetwork

abstract:
Understanding gene-by-environment interactions is important across biology, particularly behaviour. Families of isogenic strains are excellently placed, as the same genome can be tested in multiple environments. The BXDs recent expansion to 140 strains makes them the largest family of murine isogenic genomes, and therefore give great power to detect QTL. Indefinite reproducible genometypes can be leveraged; old data can be reanalysed with emerging tools to produce novel biological insights.

To highlight the importance of reanalyses, we obtained drug- and behavioural-phenotypes from Philip et al. 2010, and reanalysed their data with new genotypes from sequencing, and new models (GEMMA and R/qtl2). We discover QTL on chromosomes 3, 5, 9, 11, and 14, not found in the original study.

We narrowed down the candidate genes based on their ability to alter gene expression and/or protein function, using cis-eQTL analysis, and variants predicted to be deleterious. Co-expression analysis ( gene friends) and human PheWAS were used to further narrow candidates.

Prominent candidate genes include: Slitrk6 in a Chr 14 QTL for locomotion in the center of an open field, we show to be part of a coexpression network involved in voluntary movement, and association with neuropsychiatric phenotypes in PheWAS; and Cdk14, one of only 3 genes in a Chr 5 QTL for handling induced convulsions after ethanol treatment, that is regulated by the anticonvulsant drug valproic acid.

By using families of isogenic strains, we can reuse and reanalyse data to discover novel and highly plausible candidate genes involved in response to the environment.


title: The Telomere Length Landscape of Localized Prostate Cancer

abstract: Replicative immortality is a hallmark of cancer, and can be achieved through telomere lengthening and maintenance. We report telomere lengths (TLs) of 392 localized prostate cancer tumours and characterize their relationship to genomic, transcriptomic and proteomic features. Shorter tumour TLs were associated with elevated genomic instability, including single-nucleotide variants, indels and structural variants. Genes involved in cell proliferation and signaling were correlated with tumour TL at all levels of the central dogma. TL was also associated with multiple clinical features of a tumour. Longer TLs in non-tumour samples were associated with a lower rate of biochemical relapse after definitive local therapy. Our analysis integrates multi-omics data to illuminate the relationship of specific genomic alterations in a tumour and TL in prostate cancer. Although the role of telomere length in cancer has been well studied, its association to genomic features is less well known. We describe the multi-level integration of telomere length, genomics, transcriptomics and proteomics in localized prostate cancer. Patient Summary We examined the association between telomere length and multiple omics-level data in prostate cancer. We observed that traditional telomere mutations are rare in prostate cancer and that telomere length is associated with multiple measure of genomic instability.


title: The Telomere Length Landscape of Prostate Cancer


title: Strong attraction of male mosquitoes (Aedes aegypti) to humans

abstract: Female Aedes aegypti mosquitoes integrate multiple sensory cues to locate human hosts for blood meals. While male mosquitoes do not blood feed, male Ae. aegypti swarm around and land on humans in nature. Basrur et al. (2020) generated male Ae. aegypti lacking the fruitless gene and discovered that they gained strong attraction to humans, similar to female mosquitoes. The authors assume that host-seeking is a female-specific trait. However, all experiments were performed under confined laboratory conditions which are unable to detect long-range attraction. We used semi-field experiments to demonstrate robust attraction of male Ae. aegypti to humans. Our observations refute a key assumption of Basrur et al. (2020) and raise questions around conditions under which fruitless prevents male host-seeking. Male mosquito attraction to humans is likely to be important for mating success in wild populations and its basis should be further explored.


title: Intra-dorsal striatal acetylcholine M1 but not dopaminergic D1 or glutamatergic NMDA receptor antagonists inhibit the consolidation of duration memory in interval timing

abstract: The striatal beat frequency (SBF) model assumes that striatal medium spiny neurons encode duration via synaptic plasticity. Muscarinic 1 (M1) cholinergic receptors, as well as dopamine and glutamate receptors, are important for neural plasticity in the dorsal striatum. Therefore, we investigated the effect of inhibiting these receptors on the formation of duration memory. After sufficient training in a Peak interval (PI)-20 s procedure, rats were given a single or mixed infusion of a selective antagonist for the dopamine D1 receptor (SCH23390, 0.5 g per side), the NMDA-type glutamate receptor (D-AP5, 3 g), or the M1 receptor (pirenzepine, 10 g) bilaterally in the dorsal striatum, immediately before starting a PI 40 s session (shift session). On the next day, the rats were tested for new duration memory (40 s) in a session in which no lever presses were reinforced (probe session). In the shift session, performance was tie, irrespective of the drug injected. However, in the probe session, the mean peak time (an index of duration memory) of the M1 + NMDA co-blockade group, but not of the D1 + NMDA co-blockade group, was lower than that of the control group (Exp. 1 and 2). In Exp. 3, the effect of the co-blockade of M1 and NMDA receptors was replicated. Moreover, sole blockade of M1 receptors induced the same effect as M1 and NMDA blockade. These results suggest that in the dorsal striatum, the M1 receptor, but not the D1 or NMDA receptors, are involved in the consolidation of duration memory.


title: Distinct movement patterns generate stages of spider web-building

abstract:
The geometric complexity and stereotypy of spider webs have long generated interest in their algorithmic origin. Like other examples of animal architecture, web construction is the result of several assembly phases that are driven by distinct behavioral stages coordinated to build a successful structure. Manual observations have revealed a range of sensory cues and movement patterns used during web construction, but methods to systematically quantify the dynamics of these sensorimotor patterns are lacking. Here, we apply an analytical pipeline to quantify web-making behavior of the orb-weaver Uloborus diversus. Position tracking revealed stereotyped stages of construction that could occur in typical or atypical progressions across individuals. Using an unsupervised clustering approach, we identified general and stage-specific leg movements. A Hierarchical Hidden Markov Model revealed that stages of web-building are characterized by stereotyped sequences of actions largely shared across individuals, regardless of whether these stages progress in a typical or atypical fashion. Web stages could be predicted based on action-sequences alone, revealing that web-stages are a physical manifestation of underlying behavioral phases.

HighlightsO_LISpider centroid trajectories indicate stereotyped progression of web-building stages.
C_LIO_LIUnsupervised movement clustering reveals a shared set of movements which correspond to previously defined behaviors that define web-making across individuals.
C_LIO_LIStages of web-building use both stage-specific and non-specific behaviors.
C_LIO_LIStereotyped and distinct action sequences are predictive of stages of web-building.
C_LI


title: Temporary prey storage along swarm columns of army ants: an adaptive strategy for successful raiding?

abstract: While pillaging the brood of other ant colonies, Eciton army ants accumulate prey in piles, or caches, along their foraging trails. Widely documented, these structures have historically been considered as byproducts of heavy traffic or aborted relocations of the ants temporary nest, or bivouac. However, we recently observed that caches of the hook-jawed army ant, Eciton hamatum, appeared independently from heavy traffic or bivouac relocations. In addition, the flow of prey through caches varied based on the quantity of prey items workers transported. As this suggested a potential adaptive function, we developed agent-based simulations to compare raids of caching and non-caching virtual army ants. We found that caches increased the amount of prey that relatively low numbers of raiders were able to retrieve. However, this advantage became less conspicuous - and generally disappeared - as the number of raiders increased. Based on these results, we hypothesize that caches maximize the amount of prey that limited amounts of raiders can retrieve, especially as prey colonies coordinately evacuate their brood. In principle, caches also allow workers to safely collect multiple prey items and efficiently transport them to the bivouac. Further field observations are needed to test this and other hypotheses emerging from our study.


title: Vimentin binds to G-quadruplex repeats found at telomeres and gene promoters

abstract:
G-quadruplex (G4) structures that can form at guanine-rich genomic sites, including telomeres and gene promoters, are actively involved in genome maintenance, replication, and transcription, through finely tuned interactions with protein networks. In the present study, we identified the intermediate filament protein Vimentin as a binder with nanomolar affinity for those G-rich sequences that give rise to at least two adjacent G4 units, named G4 repeats. This interaction is supported by the N-terminal domains of soluble Vimentin tetramers. The selectivity of Vimentin for G4 repeats vs individual G4s provides an unprecedented result. Based on GO enrichment analysis performed on genes having putative G4 repeats within their core promoters, we suggest that Vimentin recruitment at these sites may contribute to the regulation of gene expression during cell development and migration, possibly by reshaping the local higher-order genome topology, as already reported for lamin B.

Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

category: biochemistry


title: Cryptic genetic variations of alanine:glyoxylate aminotransferase shape its fitness and dynamics

abstract:
Genetic variations expand the conformational landscape of proteins and may underlie cryptic properties that promote environmental adaptability. However, they can also represent modifying factors for disease susceptibility, by changing frustrated regions that in turn affect protein overall intracellular fitness. In this dichotomy between conservation and innovation, understanding at structural level how genetic variations keep the balance to maintain protein fitness represents an unmet need.

Herein, we took advantage of known genetic variations of human alanine:glyoxylate aminotransferase (AGT1), which is present as a common major allelic form (AGT-Ma) and a minor polymorphic form (AGT-Mi) expressed in 20% of Caucasian population. By crystallographic studies and molecular dynamics simulations we showed that the polymorphic amino acid substitutions shape the conformational flexibility of AGT1 so that three surface regions that are structured in AGT-Ma become disordered in AGT-Mi, thanks to plasticity effects propagated from the mutation site(s) to the whole structure. In-depth biochemical characterisation of variants from a library encompassing the three regions correlate this plasticity to a fitness window between AGT-Ma and AGT-Mi, and suggest the existence of cryptic functions related to protein-protein interactions. These results establish that naturally-occurring genetic variations tip the balance between stability and frustration to expand the potential innovability of the protein.


title: Towards a Mechanical Model for anisotropic Glioma Spread using Darcy's law

abstract:
The growth of a tumor within a finite domain (skull) generates mechanical forces that alter the physical interactions among cells. The relationship between these forces and the tumor architecture remains an open problem subjected to extensive research. Recently, it has been determined that those regions of high mechanical compression can accelerate and intensify the invasive capacity of the malignant cells, forming an irregular tumor whose full extent and edges are difficult to identify.

In the present paper, we propose a one-dimensional mathematical model that describes the process of proliferation and diffusion of glioma cells taking into account the mechanical compression generated during its expansion. Supported on the mixture theory, we model the brain-tumor system as a multiphase mixture of cancer cells, healthy cells, biological fluids and extracellular matrix whose densities determine the mechanical loads generated during the volumetric growth. Our model provides a detailed understanding of the pressure distribution on the interface boundary between healthy and cancer cells. It validates the hypothesis that the conferred ability of cancer cells to proliferate depends strongly on the mechanical pressure sensed. Through the analysis of the mechanical pressure, we determine that the anisotropic loads promote cancer cells to grow preferentially in the directions of low mechanical compression.


title: Structural basis for DNA targeting by the Tn7 transposon

abstract: Tn7 transposable elements are unique for their highly specific, and sometimes programmable, target-site selection mechanisms and precise insertions. All the elements in the Tn7-family utilize a AAA+ adaptor (TnsC) to coordinates target-site selection with transposase activation and prevent insertions at sites already containing a Tn7 element. Due to its multiple functions, TnsC is considered the linchpin in the Tn7 element. Here we present the high-resolution cryo-EM structure of TnsC bound to DNA using a gain-of-function variant of the protein and a DNA substrate that together recapitulate the recruitment to a specific DNA target site. We find that TnsC forms an asymmetric ring on target DNA that segregates target-site selection and transposase recruitment to opposite faces of the ring. Unlike most AAA+ ATPases, TnsC uses a DNA distortion to find the target site but does not remodel DNA to activate transposition. By recognizing pre-distorted substrates, TnsC creates a built-in regulatory mechanism where ATP-hydrolysis abolishes ring formation proximal to an existing element. This work unveils how Tn7 and Tn7-like elements determine the strict spacing between the target and integration sites.


title: Role of molecular polymorphism in defining tau filament structures in neurodegenerative diseases

abstract: Misfolding and aggregation of tau protein is implicated in many neurodegenerative diseases that are typified by the presence of large, filamentous tau inclusions. The aggregation of tau in human brain is disease-specific with characteristic filaments defining the neuropathology. An understanding of how identical tau isoforms aggregate into disparate filament morphologies in phenotypically distinct tau-related diseases remains elusive. Here, we determine the structure of a brain-derived twisted tau filament in progressive supranuclear palsy and compare it to a dissimilar tau fold found in corticobasal degeneration. While the tau filament core in both diseases is comprised of residues 274 to 380, molecular-level polymorphism exists. Potential origins of the molecular polymorphism, such as noncovalent cofactor binding, are identified and predicted to modulate tau filament structures in the brain.


title: Stability of a Nonequilibrium Biochemical Cycle Revealed by Single-Molecule Spectroscopy

abstract: Biological machinery relies on nonequilibrium dynamics to maintain stable directional fluxes through complex reaction cycles. In stabilizing the reaction cycle, the role of microscopic irreversibility of elementary transitions, and the accompanying entropy production, is of central interest. Here, we use multidimensional single-molecule spectroscopy to demonstrate that the reaction cycle of bacteriorhodopsin is coupled through both reversible and irreversible transitions, with directionality of trans-membrane H+ transport being ensured by the entropy production of irreversible transitions. We observe that thermal destabilization of the process is the result of diminishing thermodynamic driving force for irreversible transitions, leading to an exponentially increasing variance of flux through the transitions. We show that the thermal stability of the reaction cycle can be predicted from the Gibbs-Helmholtz relation.


title: Cholesterol Oxidation Modulates the Formation of Liquid-Ordered Domains in Model Membranes

abstract:
7-ketocholesterol (KChol) is one of the most cytotoxic oxysterols found in the plasma membrane, and increased levels of KChol are associated with numerous pathologies. It is thought to induce apoptosis via inactivation of the phosphatidylinositol 3-kinase/Akt signaling pathway -- a pathway that depends on lipid-rafts as signaling platforms. By means of coarse-grained molecular dynamics simulations, we demonstrate that KChol disrupts the liquid-liquid phase separation seen in an equimolar mixture of (dipalmitoylphosphatidylcholine) DPPC, (dioleoylphosphatidylcholine) DOPC, and Cholesterol (Chol). This disruption occurs via two mechanisms: i) KChol adopts a wider range of orientations with the membrane, which disrupts the packing of neigh-boring lipids and ii) KChol has no preference for DPPC over DOPC, which is the main driving force for lateral demixing in DPPC/DOPC/Chol membranes. This provides a molecular description of the means by which KChol induces apoptosis, and illustrates that a single chemical substitution to cholesterol can have a profound impact on the lateral organization of lipid membranes.

Graphical TOC Entry

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/445501v3_ufig1.gif" ALT="Figure 1">
View larger version (62K):
org.highwire.dtl.DTLVardef@10777a1org.highwire.dtl.DTLVardef@13ef4c9org.highwire.dtl.DTLVardef@38e0c4org.highwire.dtl.DTLVardef@2c7b91_HPS_FORMAT_FIGEXP  M_FIG C_FIG


title: CmP signaling network unveils novel biomarkers for triple negative breast cancer in African American women

abstract: Breast cancer is the most commonly diagnosed cancer worldwide and remains the second leading cause of cancer death. While breast cancer mortality has steadily declined over the past decades through medical advances, an alarming disparity in breast cancer mortality has emerged between African American women (AAW) and Caucasian American women (CAW); and new evidence suggests more aggressive behavior of triple-negative breast cancer (TNBC) in AAW may contribute to racial differences in tumor biology and mortality. Progesterone (PRG) is capable of exerting its cellular effects through either its classic, non-classic or combined responses through binding to either classic nuclear PRG receptors (nPRs) or non-classic membrane PRG receptors (mPRs), warranting both pathways an equally important status in PRG-mediated signaling. In our previous report, we demonstrated that the CCM signaling complex (CSC) consisting of CCM1, CCM2, and CCM3 proteins can couple both nPRs and mPRs signaling cascades to form a CSC-mPRs-PRG-nPRs (CmPn) signaling network in nPR positive(+) breast cancer cells. In this report, we furthered our research by establishing the CSC-mPRs-PRG (CmP) signaling network in nPR(-) breast cancer cells, demonstrating that a common core mechanism exists, regardless of nPR(+/-) cell type. This is the first report stating that inducible expression patterns exist between CCMs and major mPRs in TNBC cells. Furthermore, we firstly show mPRs in TNBC cells are localized in the nucleus and participate in nucleocytoplasmic shuttling in a coordinately synchronized fashion with CCM proteins under steroid actions, following the same cellular distribution as other well-defined steroid hormone receptors. Finally, for the first time, we deconvoluted the CmP signalosome by using multi-omics approaches, which helped us understand key factors within the CmP network, and identify 21 specific biomarkers with potential clinical applications associated with AAW-TNBC tumorigenesis. These novel biomarkers could have immediate clinical implications to dramatically improve health disparities among AAW-TNBCs.


title: Comprehensive Analysis of Spatial Architecture in Primary Liver Cancer

abstract: Heterogeneity is the major challenge for cancer prevention and therapy. Here, we firstly constructed high-resolution spatial transcriptomes of primary liver cancers (PLCs) containing 84,823 spots within 21 tissues from 7 patients. The sequential comparison of spatial tumor microenvironment (TME) characteristics from non-tumor to leading-edge to tumor regions revealed that the tumor capsule potentially affects intratumor spatial cluster continuity, transcriptome diversity and immune cell infiltration. Locally, we found that the bidirectional ligand-receptor interactions at the 100 m wide cluster-cluster boundary contribute to maintaining intratumor architecture. Our study provides novel insights for diverse tumor ecosystem of PLCs and has potential benefits for cancer intervention.


title: miRNA-34c suppresses osteosarcoma progression in vivo by targeting Notch and E2F

abstract: The expression of microRNAs (miRNAs) is dysregulated in many types of cancers including osteosarcoma (OS) due to genetic and epigenetic alterations. Among these, miR-34c, an effector of tumor suppressor P53 and an upstream negative regulator of Notch signaling in osteoblast differentiation, is dysregulated in OS. Here, we demonstrated a tumor suppressive role of miR-34c in OS progression using in vitro assays and in vivo genetic mouse models. We found that miR-34c inhibits the proliferation and the invasion of metastatic OS cells, which resulted in reduction of the tumor burden and increased overall survival in an orthotopic xenograft model. Moreover, the osteoblast specific over expression of miR-34c increased survival in the osteoblast specific p53 mutant OS mouse model. We found that miR-34c regulates the transcription of several genes in Notch signaling (NOTCH1, JAG1 and HEY2) and in p53 mediated cell cycle and apoptosis (CCNE2, E2F5, E2F2 and HDAC1). More interestingly, we found that the metastatic free survival probability was increased among a patient cohort from TARGET OS which has lower expression of direct targets of miR-34c that was identified in our transcriptome analysis such as E2F5 and NOTCH1. In conclusion, we demonstrate that miR-34c is a tumor suppressive miRNA in OS progression in vivo. In addition, we highlight the therapeutic potential of targeting miR-34c in OS.


title: The Phtheirospermum japonicum isopentenyltransferase PjIPT1a regulates host cytokinin responses in Arabidopsis

abstract: The hemiparasitic plant Phtheirospermum japonicum is a nutritional specialist that supplements its nutrient requirements by parasitizing other plants through haustoria. During parasitism, the Phtheirospermum haustorium transfers hypertrophy-inducing cytokinins (CKs) to the infected host root. The CK biosynthesis genes required for haustorium-derived CKs and the induction of hypertrophy are still unknown. We searched for haustorium-expressed isopentenyltransferases (IPTs) that catalyse the first step of CK biosynthesis, confirmed the specific expression by in vivo imaging of a promoter-reporter, and further analysed the subcellular localization, the enzymatic function, and contribution to inducing hypertrophy by studying CRISPR-Cas9 induced Phtheirospermum mutants. PjIPT1a was expressed in intrusive cells of the haustorium close to the host vasculature. PjIPT1a and its closest homolog PjIPT1b located to the cytosol and showed isopentenyltransferases activity in vitro with differences in substrate specificity. Mutating PjIPT1a abolished parasite-induced CK responses in the host. A homolog of PjIPT1a with shared characteristics was also identified in the related weed Striga hermonthica. We propose that PjIPT1a exemplifies how parasitism-related functions evolve through gene duplications and neofunctionalization.


title: Estimating anisotropy directly via neural timeseries

abstract: An isotropic dynamical system is one that looks the same in every direction, i.e., if we imagine - standing somewhere within an isotropic system, we would not be able to differentiate between different lines of sight. Conversely, anisotropy is a measure of the extent to which a system deviates from perfect isotropy, with larger values indicating greater discrepancies between the structure of the system along its axes. Here, we derive the form of a generalised scalable (mechanically similar) discretized field theoretic Lagrangian that allows for levels of anisotropy to be directly estimated via timeseries of arbitrary dimensionality. We generate synthetic data for both isotropic and anisotropic systems and, by using Bayesian model inversion and reduction, show that we can discriminate between the two datasets - thereby demonstrating proof of principle. We then apply this methodology to murine calcium imaging data collected in rest and task states, showing that anisotropy can be estimated directly from different brain states and cortical regions in an empirical in vivo biological setting. We hope that this theoretical foundation, together with the methodology and publicly available MATLAB code, will provide an accessible way for researchers to obtain new insight into the structural organization of neural systems in terms of how scalable neural regions grow - both ontogenetically during the development of an individual organism, as well as phylogenetically across species.


title: Fast photoswitchable molecular prosthetics control neuronal activity in the cochlea

abstract: Artificial control of neuronal activity enables studies of neural circuits and restoration of neural function. Direct, rapid, and sustained photocontrol of intact neurons could overcome shortcomings of established electrical stimulation such as poor selectivity. We have developed fast photoswitchable ligands of glutamate receptors to establish such control in the auditory system. The new photoswitchable ligands produced photocurrents in untransfected neurons upon covalently tethering to endogenous glutamate receptors and activating them reversibly with visible light pulses of few milliseconds. As a proof of concept of these molecular prostheses, we apply them to the ultrafast synapses of auditory neurons of the cochlea that encode sound and provide auditory input to the brain. This drug-based method affords kilohertz rate stimulation of auditory neurons of adult gerbils without genetic manipulation that would be required for their optogenetic control. The new photoswitchable ligands are also broadly applicable to spatiotemporally control fast spiking interneurons in the brain.


title: INTEROCEPTIVE INFORMATION OF PHYSICAL VIGOR: OREXIN NEURONS GAUGE CIRCULATING IGF-I FOR MOTIVATIONAL MOTOR OUTPUT

abstract: Brain regulation of bodily functions requires interoceptive feedback signals carrying information about the periphery. As mice with low serum IGF-I levels (LID mice) show reduced spontaneous physical activity, we speculated that body vigor information might be conveyed by circulating IGF-I, a regulator of skeletal muscle and bone mass that enters the brain during physical activity. Since hypothalamic orexin neurons, that are involved in regulating physical activity, express IGF-I receptors (IGF-IR), we hypothesized that these neurons might gauge circulating IGF-I levels. Inactivation of IGF-IR in mouse orexin neurons (Firoc mice) reduced spontaneous activity. Firoc mice maintain normal physical fitness but show anxiety- and depressive-like behaviors that seems to interfere with the rewarding effects of exercise, as they were less sensitive to the rewarding actions of exercise. Further, in response to exercise, Firoc mice showed reduced activation of hypothalamic orexin neurons and ventro-tegmental area (VTA) monoaminergic neurons, as indicated by c-fos staining. Collectively, these results suggest that circulating IGF-I is gauged by orexin neurons to modulate physical activity in part by stimulation of the VTA to motivate motor output. Hence, serum IGF-I may constitute a feedback signal, informing orexin neurons to adapt physical activity to physical vigor.


title: A Promising Chemical Series of Positive Allosteric Modulators of the μ-Opioid Receptor that Enhance the Antinociceptive Efficacy of Opioids but not their Adverse Effects

abstract: Positive allosteric modulators (PAMs) of the {micro}-opioid receptor (MOR) have been proposed to exhibit therapeutic potential by maximizing the analgesic properties of clinically used opioid drugs while limiting their adverse effects or risk of overdose as a result of using lower drug doses. We herein report in vitro and in vivo characterization of two small molecules from a chemical series of MOR PAMs that exhibit: (i) MOR PAM activity and receptor subtype selectivity in vitro, (ii) a differential potentiation of the antinociceptive effect of oxycodone, morphine, and methadone in mouse models of pain that roughly correlates with in vitro activity, and (iii) a lack of potentiation of adverse effects associated with opioid administration, such as somatic withdrawal, respiratory depression, and analgesic tolerance. This series of MOR PAMs holds promise for the development of adjuncts to opioid therapy to mitigate against overdose and opioid use disorders.


title: Composite solid lipid nanoparticles with hydrogel core for delivering small hydrophilic molecules to the retina: an in vitro study using ARPE-19 and 661W cells

abstract: In this study, we developed a novel solid lipid nanoparticle (SLN) formulation for drug delivery of small hydrophilic cargo to the retina. The new formulation, based on a gel core and composite shell, allowed up to two times increase in the encapsulation efficiency. The type of hydrophobic polyester used in the composite shell mixture affects the particle surface charge, colloidal stability, and cell internalization profile. We validated the SLN capability as a drug delivery system by performing encapsulation of a hydrophilic neuroprotective cyclic guanosine monophosphate analogue, previously demonstrated to hold retinoprotective properties, and the best formulation resulted in particles with size of {+/-} 250nm, anionic charge > -20 mV, and an encapsulation efficiency value of {+/-}60%, criteria that are suitable for retinal delivery. In vitro studies using ARPE-19 and 661W retinal cell lines revealed a relatively low SLN toxicity, even when high particle concentration was used. More importantly, SLN could be uptaken by the cells and the release of the hydrophilic cargo in the cytoplasm was visually demonstrated. These findings suggest that the newly developed SLN with a gel core and composite polymer/lipid shell holds all characteristics suitable for drug delivery of small hydrophilic active molecules into retinal cell.