title: Bioimage postprocessing based on discrete wavelet transform and Lucy-Richardson deconvolution methods

abstract: Accompanied with the increasing requirements of probing micro/nanoscopic structures of biological samples, a variety of image processing algorithms have been developed for visualization or to facilitate data analysis. However, it remains challenging to enhance both the signal-to-noise ratio and image resolution using a single algorithm. In this investigation, we propose an approach utilizing discrete wavelet transform (DWT) in combination with Lucy-Richardson (LR) deconvolution (DWDC). Our results demonstrate that the signal-to-noise ratio and resolution of live cells microtubule network are considerably improved, allowing recognition of features as small as 120 nm. Notably, the approach is independent of imaging system and shows robustness in processing fibrous structures, e.g. the cytoskeleton networks.


title: Tissue Specific Age Dependence of the Cell Receptors Involved in the SARS-CoV-2 Infection

abstract: The coronavirus disease 2019 (COVID-19) pandemic has affected tens of millions of individuals and caused hundreds of thousands of deaths worldwide. Due to its rapid surge, there is a shortage of information on viral behavior and host response after SARS-CoV-2 infection. Here we present a comprehensive, multiscale network analysis of the transcriptional response to the virus. We particularly focus on key-regulators, cell-receptors, and host-processes that are hijacked by the virus for its advantage. ACE2-controlled processes involve a key-regulator CD300e (a TYROBP receptor) and the activation of IL-2 pro-inflammatory cytokine signaling. We further investigate the age-dependency of such receptors and identify the adipose and the brain as potentially contributing tissues for the diseases severity in old patients. In contrast, several other tissues in the young population are more susceptible to SARS-CoV-2 infection. In summary, this present study provides novel insights into the gene regulatory organization during the SARS-CoV-2 infection and the tissue-specific age dependence of the cell receptors involved in COVID-19.

category: systems biology


title: Balanced release of neuropeptide FF and gonadotropin-releasing hormone 3 modulates male sexual behavior

abstract: Animals properly perform sexual behaviors by using multiple sensory cues. However, neural mechanisms integrating multiple sensory cues and regulating motivation for sexual behaviors remain unclear. Here, we focused on peptidergic neurons, terminal nerve gonadotropin-releasing hormone (TN-GnRH) neurons, which receive inputs from various sensory systems and co-express neuropeptide FF (NPFF) in addition to GnRH. Our behavioral analyses using knockout medaka of GnRH (gnrh3) and/or NPFF (npff) demonstrated that some sexual behavioral repertories were  delayed, not disrupted, in gnrh3-/- and npff-/- males, while the double knockout showed normal behaviors. We also found anatomical evidence to show that both neuropeptides modulate the sexual behavior-controlling brain areas. Furthermore, we demonstrated that NPFF activates neurons in the preoptic area via indirect pathway, which is considered to induce the increase in the motivation for male sexual behaviors. Considering these results, we propose a novel mechanism by which balanced release of co-existing peptides is important for the neuromodulatory function of TN-GnRH neurons in the control of behavioral motivation. Our results may go a long way toward understanding the functional significance of peptidergic neuromodulation in response to external environments.

category: neuroscience


title: Human placental villi immune cells help maintain homeostasis in utero

abstract: Maintenance of healthy pregnancy is reliant on successful balance between the fetal and maternal immune systems. Although maternal mechanisms responsible have been well studied, those used by the fetal immune system remain poorly understood. Using suspension mass cytometry and various imaging modalities, we report a complex immune system within the mid-gestation (17-23 weeks) human placental villi (PV). Further, we identified immunosuppressive signatures in innate immune cells and antigen presenting cells that potentially maintain immune homeostasis in utero. Consistent with recent reports in other fetal organs, T cells with memory phenotypes were detected within the PV tissue and vasculature. Moreover, we determined PV T cells could be activated to upregulate CD69 and proliferate after T cell receptor (TCR) stimulation and when exposed to maternal uterine antigens. Finally, we report that cytokine production by PV T cells is sensitive to TCR stimulation and varies between mid-gestation, preterm (26-35 weeks) and term deliveries (37-40 weeks). Collectively, we elucidated the complexity and functional maturity of fetal immune cells within the PV and highlighted their immunosuppressive potential.

category: immunology


title: Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and related humans in the Netherlands

abstract: In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and related humans on farms. High number of farm infections (68/126) in minks and farm related personnel (>50% of farms) were detected, with limited spread to the general human population. Three of five initial introductions of SARS-CoV-2 lead to subsequent spread between mink farms until November 2020. The largest cluster acquired a mutation in the receptor binding domain of the Spike protein (position 486), evolved faster and spread more widely and longer. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combing genetic information with epidemiological information at the animal-human interface.

category: microbiology


title: hnRNPA1 regulates early translation to replication switch in SARS-CoV-2 life cycle

abstract:
Our study suggests that methylation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is essential for its optimal replication in the target cells. Heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1, an RNA-binding protein) was shown to mediate deposition of N6-methyladenosine (m6A) in internal SARS-CoV-2 RNA. The levels of hNRNPA1 expression and extent of methylation varied, depending on the course of SARS-CoV-2 life cycle. The recruitment of eIF4E (translational initiation factor) facilitated viral RNA translation at 1 hour post infection (1 hpi). However, at 2 hpi, methylation of internal SARS-CoV-2 RNA recruited hNRNPA1 which facilitated viral RNA transcription but resulted in translational repression, a phenomenon contributing in understanding the early translation to replication switch in the viral life cycle. Besides, the abrogation of methylation also produced a defective 5 cap of viral RNA which failed to interact with eIF4E, thereby resulting in a decreased synthesis of viral proteins. To conclude, methylation of the internal and 5 cap of SARS-CoV-2 RNA was shown to regulate transcription and translation of SARS-CoV-2 in a time dependent manner.

IMPORTANCERNA modifications are found in all life forms and have been linked to development, health and diseases. Our study reveals that internal SARS-CoV-2 RNA methylation (m6A) is essential for interaction with hNRNPA1 to effectively synthesize viral genome. Besides, m6A-marked RNA and hRNPA1 interaction was also shown to regulate early translation to replication switch in SARS-CoV-2 life cycle. Blocking SARS-CoV-2 RNA methylation resulted in reduced virus yield, suggesting epitranscriptomic machinery (methylation) facilitates SARS-CoV-2 replication and might represent potential target for new antiviral drugs against COVID-19.


title: Induction of human trophoblast stem-like cells from primed pluripotent stem cells

abstract:
The placenta is a transient but important multifunctional organ crucial for healthy pregnancy for both mother and fetus. Nevertheless, limited access to human placenta samples and the paucity of a proper in vitro model system has hampered our understanding of the mechanisms underlying early human placental development and placenta-associated pregnancy complications. To overcome these constraints, we established a simple procedure with a short-term treatment of bone morphogenetic protein 4 (BMP4) in trophoblast stem cell culture medium (TSCM) to convert human primed pluripotent stem cells (PSCs) to trophoblast stem-like cells (TSLCs). These TSLCs show not only comparable morphology and global gene expression profiles to bona fide human trophoblast stem cells (TSCs) but also long-term self-renewal capacity with bipotency that allows the cells to differentiate into functional extravillous trophoblasts (EVT) and syncytiotrophoblasts (ST). These indicate that TSLCs are equivalent to genuine human TSCs. Our data suggest a straightforward approach to make human TSCs directly from pre-existing primed PSCs and provide a valuable opportunity to study human placenta development and pathology even from patients with placenta-related diseases.

HIGHLIGHTSShort-term treatment of BMP4 in TSCM induces human primed PSCs into TSLCs

TSLCs possess similar self-renewal and bipotency as bona fide TSCs

Global gene expression profiling shows high similarity between TSLCs and TSCs

TSLC-derived EVT and ST possess characteristics shown in TSC-derived counterparts

category: cell biology


title: ECM dimensionality tunes actin tension to modulate the endoplasmic reticulum and spheroid phenotype

abstract: Primary tissue organoids and cell spheroids recapitulate tissue physiology with remarkable fidelity. We investigated how engagement with a three dimensional laminin-rich extracellular matrix supports the polarized, stress resilient spheroid phenotype of mammary epithelial cells. Cells within a three dimensional laminin-rich extracellular matrix decreased and redistributed the actin crosslinker filamin to reduce their cortical actin tension. Cells with low cortical actin tension had increased plasma membrane protrusions that promoted negative plasma membrane curvature and fostered protein associations with the plasma membrane, consistent with efficient protein secretion. By contrast, cells engaging a laminin-rich extracellular matrix in two dimensions had high filamin-dependent cortical actin tension, exhibited compromised endoplasmic reticulum function including increased expression of PKR-like Endoplasmic Reticulum Kinase signaling effectors, and had compromised protein secretion. Cells with low filamin-mediated cortical actin tension and reduced endoplasmic reticulum stress response signaling secreted, and assembled, a polarized endogenous basement membrane and survived better, and their spheroids were more resistant to exogenous stress. The findings implicate filamin-dependent cortical actin tension in endoplasmic reticulum function and highlight a role for mechanics in organoid homeostasis.


title: Biological Action at a Distance: Correlated pattern formation in adjacent tessellation domains without communication

abstract: Tessellations emerge in many natural systems, and the constituent domains often contain regular patterns, raising the intriguing possibility that pattern formation within adjacent domains might be correlated by the geometry, without the direct exchange of information between parts comprising either domain. We confirm this paradoxical effect, by simulating pattern formation via reaction-diffusion in domains whose boundary shapes tessellate, and showing that correlations between adjacent patterns are strong compared to controls that self-organise in domains with equivalent sizes but unrelated shapes. The effect holds in systems with linear and non-linear diffusive terms, and for boundary shapes derived from regular and irregular tessellations. Based on the prediction that correlations between adjacent patterns should be bimodally distributed, we develop methods for testing whether a given set of domain boundaries constrained pattern formation within those domains. We then confirm such a prediction by analysing the development of  subbarrel patterns, which are thought to emerge via reaction-diffusion, and whose enclosing borders form a Voronoi tessellation on the surface of the rodent somatosensory cortex. In more general terms, this result demonstrates how causal links can be established between the dynamical processes through which biological patterns emerge and the constraints that shape them.

category: developmental biology


title: An exon-intron split framework to prioritize transcriptional and post-transcriptional regulatory signals and its application to study energy homeostasis in pigs

abstract: The contribution of microRNAs (miRNAs) to mRNA regulation has often been explored by post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes of mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Gottingen minipigs. Exon-intron split analysis (EISA) of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of upregulated miRNAs also in the fed state. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, EISA provides a valuable view about the regulation of gene expression, complementary to canonical differential expression analyses.

category: genomics


title: An exon-intron split framework to prioritize miRNA-driven post-transcriptional regulatory signals and its application to study energy homeostasis in pigs


title: Modeling miRNA-driven post-transcriptional regulatory signals by using exon-intron split analysis (EISA) in pigs


title: Modeling miRNA-driven post-transcriptional regulation by using exon-intron split analysis (EISA) in pigs


title: Modeling microRNA-driven post-transcriptional regulation by using exon-intron split analysis (EISA) in pigs


title: A Gradient-based Spectral Explainability Method for EEG Deep Learning Classifiers

abstract: The automated feature extraction capabilities of deep learning classifiers have promoted their broader application to EEG analysis. In contrast to earlier machine learning studies that used extracted features and traditional explainability approaches, explainability for classifiers trained on raw data is particularly challenging. As such, studies have begun to present methods that provide insight into the spectral features learned by deep learning classifiers trained on raw EEG. These approaches have two key shortcomings. (1) They involve perturbation, which can create out-of-distribution samples that cause inaccurate explanations. (2) They are global, not local. Local explainability approaches can be used to examine how demographic and clinical variables affected the patterns learned by the classifier. In our study, we present a novel local spectral explainability approach. We apply it to a convolutional neural network trained for automated sleep stage classification. We apply layer-wise relevance propagation to identify the relative importance of the features in the raw EEG and subsequently examine the frequency domain of the explanations to determine the importance of each canonical frequency band locally and globally. We then perform a statistical analysis to determine whether age and sex affected the patterns learned by the classifier for each frequency band and sleep stage. Results showed that {delta}, {beta}, and {gamma} were the overall most important frequency bands. In addition, age and sex significantly affected the patterns learned by the classifier for most sleep stages and frequency bands. Our study presents a novel spectral explainability approach that could substantially increase the level of insight into classifiers trained on raw EEG.

category: bioinformatics


title: DeeReCT-TSS: A novel meta-learning-based method annotates TSS in multiple cell types based on DNA sequences and RNA-seq data

abstract: The accurate annotation of transcription start sites (TSSs) and their usage is critical for the mechanistic understanding of gene regulation under different biological contexts. To fulfill this, on one hand, specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner. On the other hand, various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences. Most of these computational tools cast the problem as a binary classification task on a balanced dataset and thus result in drastic false positive predictions when applied on the genome-scale. To address these issues, we present DeeReCT-TSS, a deep-learning-based method that is capable of TSSs identification across the whole genome based on both DNA sequences and conventional RNA-seq data. We show that by effectively incorporating these two sources of information, DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types. Furthermore, we develop a meta-learning-based extension for simultaneous transcription start site (TSS) annotation on 10 cell types, which enables the identification of cell-type-specific TSS. Finally, we demonstrate the high precision of DeeReCT-TSS on two independent datasets from the ENCODE project by correlating our predicted TSSs with experimentally defined TSS chromatin states. Our application, pre-trained models and data are available at https://github.com/JoshuaChou2018/DeeReCT-TSS_release.


title: Comethyl: A network-based methylome approach to investigate the multivariate nature of health and disease

abstract:
Health outcomes are frequently shaped by difficult to dissect inter-relationships between biological, behavioral, social, and environmental factors. DNA methylation patterns reflect such multi-variate intersections, providing a rich source of novel biomarkers and insight into disease etiologies. Recent advances in whole-genome bisulfite sequencing (WGBS) enable investigation of DNA methylation over all genomic CpGs, but existing bioinformatic approaches lack accessible system-level tools. Here, we develop the R package Comethyl, for weighted gene correlation network analysis (WGCNA) of user-defined genomic regions that generates modules of comethylated regions, which are then tested for correlations with sample traits. First, regions are defined by CpG genomic location or regulatory annotation and filtered based on CpG count, sequencing depth, and variability. Next, correlation networks are used to find modules of interconnected nodes using methylation values within the selected regions. Each module containing multiple comethylated regions is reduced in complexity to a single eigennode value, which is then tested for correlations with experimental metadata. Comethyl has the ability to cover the noncoding regulatory regions of the genome with high relevance to interpretation of genome-wide association studies and integration with other types of epigenomic data. We demonstrate the utility of Comethyl on a dataset of male cord blood samples from newborns later diagnosed with autism spectrum disorder (ASD) versus typical development. Comethyl successfully identified an ASD-associated module containing gene regions with brain glial functions. Comethyl is expected to be useful in uncovering the multi-variate nature of health disparities for a variety of common disorders. Comethyl is available at github.com/cemordaunt/comethyl.

Description of the AuthorsCharles E. Mordaunt, Ph.D. developed Comethyl while a postdoctoral fellow in the department of Medical Microbiology and Immunology at UC Davis. He is currently a Computational Biologist at GSK.

Julia S. Mouat is a doctoral student in the Integrative Genetics and Genomics graduate group at UC Davis with interests in health disparities and intergenerational epigenetic risk factors for autism spectrum disorders.

Rebecca J. Schmidt, Ph.D. is an Associate Professor of Public Health Sciences at UC Davis, with expertise in the use of epigenetics in epidemiology and neurodevelopmental disorders.

Janine M. LaSalle, Ph.D. is a Professor of Medical Microbiology and Immunology, Co-Director of the Perinatal Origins of Disparities Center, and Deputy Director of the Environmental Health Sciences Center at UC Davis, with expertise in epigenomics and neurodevelopmental disorders.


title: Cloud-based DIA data analysis module for signal refinement improves accuracy and throughput of large datasets.

abstract: Data-independent acquisition (DIA) is a powerful mass spectrometry method that promises higher coverage, reproducibility, and throughput than traditional quantitative proteomics approaches. However, the complexity of DIA data caused by fragmentation of co-isolating peptides presents significant challenges for confident assignment of identity and quantity, information that is essential for deriving meaningful biological insight from the data. To overcome this problem, we previously developed Avant-garde, a tool for automated signal refinement of DIA and other targeted mass spectrometry data. AvG is designed to work alongside existing tools for peptide detection to address the reliability and quantitative suitability of signals extracted for the identified peptides. While its use is straightforward and offers efficient refinement for small datasets, the execution of AvG for large DIA datasets is time-consuming, especially if run with limited computational resources. To overcome these limitations, we present here an improved, cloud-based implementation of the AvG algorithm deployed on Terra, a user-friendly cloud-based platform for large-scale data analysis and sharing, as an accessible and standardized resource to the wider community.


title: Mining divergent and conserved signals in 5' splicing site sequences

abstract:
The main steps of the splicing process are similar across eukaryotes. However differences in splicing factors, gene architecture and sequence divergences suggest clade-specific features of splicing and its regulation. In each organism the ensemble of 5 splicing sequences reflects the balance between natural nucleotidic variability and minimal molecular constraints to assure splicing fidelity. This compromise shapes the underlying statistical patterns in donor sequences composition.

In this work we aimed to mine conserved and divergent signals in splicing donor sequences. As 5 donor sequences are a major cue for proper recognition of splicing sites we reasoned that statistical regularities of their sequence composition might reflect biological functionality and evolutionary history associated to splicing mechanisms.

We considered a regularized maximum entropy modeling framework to mine for non-trivial two-site correlations in donor sequences of 30 different eukaryote organisms. Our approach allowed us to accommodate and extend within a unified framework many of the regularities observed in previous works, like the negative epistatic effects between exonic and intronic consensus sites. In addition, for each analyzed organism, we could identify minimal sets of two-site coupling patterns that could generate, at a given regularization level, observed one-site and two-site frequencies in donor sequences. Noticeably, performing a systematic and comparative analysis of 5ss we showed that lineage information could be traced from joint di-nucleotide probabilities. Specifically, we could identify characteristic two-site coupling patterns for plants and for animals and argue that they could echo differences in splicing regulation previously reported between these groups.

Author summaryThe sequence composition of 5 splicing sites of eukaryote organisms reflect a complex scenario. Nucleotide variability has to coexist with the need to correctly define exon/intron boundaries and the fidelity of splicing seems to depend on a pattern of trade-offs between substitutions at different positions of the splicing site. Better understanding of these patterns may help to gain insight into the details underlying the splicing process and its evolution.

In this work we aimed to study conserved and divergent signatures embedded in the sequence composition of eukaryotic 5 splicing sites. We developed generative probabilistic models that allowed us to analyze sequence composition of donor sequences for several eukaryote organisms. Our regularized models served to incrementally disentangle the minimal set of coupling parameters needed to accurately reproduced observed 1-site and 2-site nucleotide frequencies. Focusing our study on di-nucelotide probabilities we found that they actually carried phylogenetic signal. In particular, our comparative analysis allowed us to identify differential two-site coupling patterns for animal and plants that might be related to specific differences in splicing regulation.


title: Mining divergent and conserved signals in 5' splicing site sequences across fungi, metazoa and plants


title: Autocrine signaling explains the emergence of Allee effects in cancer cell populations

abstract: In many human cancers, the rate of cell growth depends crucially on the size of the tumour cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations of brain tumor cells grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy.

category: cancer biology


title: Reciprocal changes in voltage-gated potassium and subthreshold inward currents help maintain firing dynamics of AVPV kisspeptin neurons during the estrous cycle.

abstract:
Kisspeptin-expressing neurons in the anteroventral-periventricular nucleus (AVPV) are part of a neural circuit generating the gonadotropin-releasing hormone (GnRH) surge. This process is estradiol-dependent and occurs on the afternoon of proestrus in female mice. On proestrus, AVPV kisspeptin neurons express more kisspeptin and exhibit higher frequency action potentials and burst firing compared to diestrus, which is characterized by a pulsatile rather than a prolonged surge of GnRH secretion. We hypothesized changes in voltage-gated potassium conductances shape activity profiles of these cells in a cycle-dependent manner. Whole-cell voltage-clamp recordings of GFP-identified AVPV kisspeptin neurons in brain slices from diestrous and proestrous mice revealed three subcomponents of the voltage-sensitive K+ current: fast-inactivating, slow-inactivating, and residual. During proestrus, the V50 of inactivation of the fast-inactivating current was depolarized and the amplitude of the slow-inactivating component was reduced compared to diestrus; the residual component was consistent across both stages. Computational models were fit to experimental data, including published estrous-cycle effects on other voltage-gated currents. Computer simulations suggest proestrus-typical K+ currents are suppressive compared to diestrus. Interestingly, larger T-type, persistent-sodium, and hyperpolarization-activated currents during proestrus compensate for this suppressive effect while also enabling post-inhibitory rebound bursting. These findings suggest modulation of voltage-gated K+ and multiple subthreshold depolarizing currents across the negative to positive feedback transition maintain AVPV kisspeptin neuron excitability in response to depolarizing stimuli. These changes also enable firing in response to hyperpolarization, providing a net increase in neuronal excitability, which may contribute to activation of this population leading up to the preovulatory GnRH surge.

Significance StatementGnRH neurons provide the central signal to initiate ovulation by releasing a surge of hormone. GnRH neurons are regulated by other cells including those expressing kisspeptin, a potent stimulator of GnRH secretion. Kisspeptin neurons in the anteroventral-periventricular nucleus (AVPV) express more kisspeptin and become more active during the afternoon of proestrus, the phase of the rodent estrous (reproductive) cycle when the GnRH surge occurs. We found voltage-dependent potassium currents in AVPV kisspeptin neurons change with phase of the estrous cycle. Firing simulations indicated these changes are suppressive if occurring in isolation. But proestrous-typical increases in subthreshold depolarizing currents overcome this suppression and promote greater excitability by increasing rebound firing, possibly contributing to the preovulatory activation of this system.

category: physiology


title: Spinal ganglia control nociceptive input to the central nervous system

abstract: Accumulating observations suggest that peripheral somatosensory ganglia may regulate pain transmission, yet direct evidence is sparse. Here we show that the peripheral afferent nociceptive information undergoes dynamic filtering within dorsal root ganglia (DRG) and suggest that this filtering occurs at the axonal bifurcations (t-junctions). Using synchronous in vivo electrophysiological recordings in the peripheral (spinal nerve) and central (dorsal root) processes of the sensory nerve, ganglionic transplantation of GABAergic progenitor cells, and optogenetics we demonstrate tonic and dynamic filtering of action potentials traveling through the DRG. Filtering induced by focal application of GABA or optogenetic GABA release from the DRG-transplanted GABAergic progenitor cells was specific to nociceptive fibers. Light-sheet imaging and computer modeling demonstrated that, compared to other somatosensory fiber types, nociceptors have shorter stem axons, making somatic control over t-junctional filtering more efficient. Optogenetically-induced GABA release within DRG from the transplanted GABAergic cells enhanced filtering and reduced both acute and chronic inflammatory and neuropathic pain in vivo. These findings support  gating of pain information by spinal ganglia and suggest new therapeutic approaches for pain relief.


title: Transcriptional regulation of neural stem cell expansion in adult hippocampus

abstract: Experience governs neurogenesis from radial-glial neural stem cells (RGLs) in the adult hippocampus to support memory. Transcription factors in RGLs integrate physiological signals to dictate self-renewal division mode. Whereas asymmetric RGL divisions drive neurogenesis during favorable conditions, symmetric divisions prevent premature neurogenesis while amplifying RGLs to anticipate future neurogenic demands. The identities of transcription factors regulating RGL symmetric self-renewal, unlike those that regulate RGL asymmetric self-renewal, are not known. Here, we show that the transcription factor Kruppel-like factor 9 (Klf9) is elevated in quiescent RGLs and inducible, deletion of Klf9 promotes RGL activation state. Clonal analysis and longitudinal intravital 2-photon imaging directly demonstrate that Klf9 functions as a brake on RGL symmetric self-renewal. In vivo translational profiling of RGLs lacking Klf9 generated a blueprint of RGL symmetric self-renewal for stem cell community. Together, these observations identify Klf9 as a transcriptional regulator of neural stem cell expansion in the adult hippocampus.


title: Spike-based symbolic computations on bit strings and numbers

abstract: The brain uses recurrent spiking neural networks for higher cognitive functions such as symbolic computations, in particular, mathematical computations. We review the current state of research on spike-based symbolic computations of this type. In addition, we present new results which show that surprisingly small spiking neural networks can perform symbolic computations on bit sequences and numbers and even learn such computations using a biologically plausible learning rule. The resulting networks operate in a rather low firing rate regime, where they could not simply emulate artificial neural networks by encoding continuous values through firing rates. Thus, we propose here a new paradigm for symbolic computation in neural networks that provides concrete hypotheses about the organization of symbolic computations in the brain. The employed spike-based network models are the basis for drastically more energy-efficient computer hardware - neuromorphic hardware. Hence, our results can be seen as creating a bridge from symbolic artificial intelligence to energy-efficient implementation in spike-based neuromorphic hardware.


title: A conditioned place preference for heroin is signaled by increased dopamine and direct pathway activity and decreased indirect pathway activity in the nucleus accumbens

abstract:
Initial drug use promotes the development of conditioned reinforcement, whereby the reinforcing properties of a drug become attributed to drug-associated stimuli, such as cues and contexts. A principal role for the nucleus accumbens (NAc) in the response to drug-associated stimuli has been well-documented. In particular, direct and indirect pathway medium spiny neurons (dMSNs and iMSNs) have been shown to bidirectionally regulate cue-induced heroin-seeking in rats expressing addiction-like phenotypes, and a shift in NAc activity towards the direct pathway has been shown in mice following cocaine conditioned place preference (CPP). However, how NAc signaling guides heroin CPP, and whether heroin alters the balance of signaling between dMSNs and iMSNs remains unknown. Moreover, the role of NAc dopamine signaling in heroin reinforcement remains unclear. Here, we integrate fiber photometry for in vivo monitoring of dopamine and dMSN/iMSN calcium activity with a heroin CPP procedure in rats to address these outstanding questions. We identify a sensitization-like response to heroin in the NAc, with prominent iMSN activity during initial heroin exposure and prominent dMSN activity following repeated heroin exposure. We demonstrate a ramp in dopamine activity, dMSN activation, and iMSN inactivation preceding entry into a heroin-paired context, and a decrease in dopamine activity, dMSN inactivation, and iMSN activation preceding exit from a heroin-paired context. Finally, we show that buprenorphine is sufficient to prevent the development of heroin CPP and activation of the NAc post-conditioning. Together, these data support the hypothesis that an imbalance in NAc activity contributes to the development of addiction.

SIGNIFICANCE STATEMENTThe attribution of the reinforcing effects of drugs to neutral stimuli (e.g., cues and contexts) contributes to the maintenance of addiction, as re-exposure to drug-associated stimuli can reinstate drug seeking and taking even after long periods of abstinence. The nucleus accumbens (NAc) has an established role in encoding the value of drug-associated stimuli, and dopamine release into the NAc is known to modulate the reinforcing effects of drugs, including heroin. Using fiber photometry, we show that entering a heroin-paired context is driven by dopamine signaling and NAc direct pathway activation, whereas exiting a heroin-paired context is driven by NAc indirect pathway activation. This study provides further insight into the role of NAc microcircuitry in encoding the reinforcing properties of heroin.


title: A modular protein subunit vaccine candidate produced in yeast confers protection against SARS-CoV-2 in non-human primates

abstract: Vaccines against SARS-CoV-2 have been distributed at massive scale in developed countries, and have been effective at preventing COVID-19. Access to vaccines is limited, however, in low- and middle-income countries (LMICs) due to insufficient supply, high costs, and cold storage requirements. New vaccines that can be produced in existing manufacturing facilities in LMICs, can be manufactured at low cost, and use widely available, proven, safe adjuvants like alum, would improve global immunity against SARS-CoV-2. One such protein subunit vaccine is produced by the Serum Institute of India Pvt. Ltd. and is currently in clinical testing. Two protein components, the SARS-CoV-2 receptor binding domain (RBD) and hepatitis B surface antigen virus-like particles (VLPs), are each produced in yeast, which would enable a low-cost, high-volume manufacturing process. Here, we describe the design and preclinical testing of the RBD-VLP vaccine in cynomolgus macaques. We observed titers of neutralizing antibodies (>104) above the range of protection for other licensed vaccines in non-human primates. Interestingly, addition of a second adjuvant (CpG1018) appeared to improve the cellular response while reducing the humoral response. We challenged animals with SARS-CoV-2, and observed a ~3.4 and ~2.9 log10 reduction in median viral loads in bronchoalveolar lavage and nasal mucosa, respectively, compared to sham controls. These results inform the design and formulation of current clinical COVID-19 vaccine candidates like the one described here, and future designs of RBD-based vaccines against variants of SARS-CoV-2 or other betacoronaviruses.


title: Xeno-nucleic Acid (XNA) 2'-Fluoro-Arabino Nucleic Acid (FANA) Aptamers to the Receptor Binding Domain of SARS-CoV-2 S Protein Block ACE2 Binding

abstract: The causative agent of COVID-19, SARS-CoV-2, gains access to cells through interactions of the receptor binding domain (RBD) on the viral S protein with angiotensin converting enzyme 2 (ACE2) on the surface of human host cells. Systematic Evolution of Ligands by Exponential Enrichment (SELEX) was used to generate aptamers (nucleic acids selected for high binding affinity to a target) to the RBD made from 2-fluoroarabinonucleic acid (FANA). The best selected ~ 79 nucleotide aptamers bound the RBD (Arg319-Phe541) and the larger S1 domain (Val16-Arg685) of the 1272 amino acid S protein with equilibrium dissociation constants (KD,app) of ~ 10-20 nM and a binding half-life for the RBD of 53 {+/-} 18 minutes. Aptamers inhibited the binding of the RBD to ACE2 in an ELISA assay. Inhibition, on a per weight basis, was similar to neutralizing antibodies that were specific for RBD. Aptamers demonstrated high specificity, binding with about 10-fold lower affinity to the related S1 domain from the original SARS virus, which also binds to ACE2. Overall, FANA aptamers show affinities comparable to previous DNA aptamers to RBD and S protein and directly block receptor interactions while using an alternative Xeno-nucleic acid (XNA) platform.


title: Repurposing screen highlights broad-spectrum coronavirus antivirals and their host targets

abstract: Libraries composed of licensed drugs represent a vast repertoire of molecules modulating physiologic processes in humans, thus providing unique opportunities for discovery of host targeting antivirals. We interrogated the ReFRAME repurposing library with 12,993 molecules for broad-spectrum coronavirus antivirals and discovered 134 compounds inhibiting an alphacoronavirus, mapping to 59 molecular target categories. Dominant targets included the 5-hydroxytryptamine receptor and dopamine receptor and cyclin-dependent kinase inhibitors. Counter-screening with SARS-CoV-2 and validation in primary cells identified Phortress, an aryl hydrocarbon receptor (AHR) ligand, Bardoxolone and Omaveloxolone, two nuclear factor, erythroid 2 like 2 (NFE2L2) activators as inhibitors of both alpha- and betacoronaviruses. The landscape of coronavirus targeting molecules provides important information for the development of broad-spectrum antivirals reinforcing pandemic preparedness.


title: Water-soluble tocopherol derivatives inhibit SARS-CoV-2 RNA-dependent RNA polymerase

abstract: The recent emergence of a novel coronavirus, SARS-CoV-2, has led to the global pandemic of the severe disease COVID-19 in humans. While efforts to quickly identify effective antiviral therapies have focused largely on repurposing existing drugs1-4, the current standard of care, remdesivir, remains the only authorized antiviral intervention of COVID-19 and provides only modest clinical benefits5. Here we show that water-soluble derivatives of -tocopherol have potent antiviral activity and synergize with remdesivir as inhibitors of the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). Through an artificial-intelligence-driven in silico screen and in vitro viral inhibition assay, we identified D--tocopherol polyethylene glycol succinate (TPGS) as an effective antiviral against SARS-CoV-2 and {beta}-coronaviruses more broadly that also displays strong synergy with remdesivir. We subsequently determined that TPGS and other water-soluble derivatives of -tocopherol inhibit the transcriptional activity of purified SARS-CoV-2 RdRp and identified affinity binding sites for these compounds within a conserved, hydrophobic interface between SARS-CoV-2 nonstructural protein 7 and nonstructural protein 8 that is functionally implicated in the assembly of the SARS-CoV-2 RdRp6. In summary, we conclude that solubilizing modifications to -tocopherol allow it to interact with the SARS-CoV-2 RdRp, making it an effective antiviral molecule alone and even more so in combination with remdesivir. These findings are significant given that many tocopherol derivatives, including TPGS, are considered safe for humans, orally bioavailable, and dramatically enhance the activity of the only approved antiviral for SARS-CoV-2 infection7-9.


title: Mapping Human Transient Transcriptomes Using Single Nucleotide Resolution 4sU Sequencing (SNU-Seq)

abstract:
Genomes are pervasively transcribed leading to stable and unstable transcripts that define functional regions of genomes and contribute to cellular phenotypes. Defining comprehensive nascent transcriptomes is pivotal to understand gene regulation, disease processes, and the impact of extracellular signals on cells. However, currently employed methods are laborious, technically challenging and costly. We developed single-nucleotide resolution 4sU-sequencing (SNU-Seq), involving pulse labelling, biotinylation and direct isolation of nascent transcripts. Artificial poly-(A)-tailing of the 3 most nucleotide of nascent transcripts ensures oligo-d(T) primer-based library preparation and sequencing using commercial 3 RNA-Seq kits. We show that SNU-Seq is a cost-effective new method generating even read profiles across transcription units. We used SNU-Seq to identify transcription elongation parameters, to map usage of polyadenylation (PAS) sites and novel enhancers. Remarkably, 4sU labelled nascent RNA accumulates short [~]100nt transcripts that map to the 5 end of genes. We show that isolation of these short nascent RNA and sequencing the 5 and 3 ends using size-selected SNU-Seq (ssSNU-Seq) provides highly sensitive annotations of mapped and novel TSSs, promoter-proximal pause/termination sites. Thus, SNU-seq and ssSNU-seq combined yield comprehensive transcriptomics data at low cost with high spatial and temporal resolution.

Highlights- SNU-Seq maps nascent transcripts at base-pair resolution, with high sensitivity and low cost
- SNU-Seq detects comprehensive polyadenylation sites.
- SNU-Seq maps the promoter proximal pause 60-80 nt from the TSS.
- Size-selected SNU-Seq yields highly sensitive and novel TSS annotations

category: molecular biology


title: Conversion rate to the secondary conformation state in the binding mode of SARS-CoV-2 spike protein to human ACE2 may predict infectivity efficacy of the underlying virus mutant

abstract: Since its outbreak in 2019 SARS-CoV-2 has spread with high transmission efficiency across the world, putting health care as well as economic systems under pressure [1, 2]. During the course of the pandemic, the originally identified SARS-CoV-2 variant has been widely replaced by various mutant versions, which showed enhanced fitness due to increased infection and transmission rates [3, 4]. In order to find an explanation, why SARS-CoV-2 and its emerging mutated versions showed enhanced transfection efficiency as compared to SARS-CoV 2002, an improved binding affinity of the spike protein to human ACE has been proposed by crystal structure analysis and was identified in cell culture models [5-7]. Kinetic analysis of the interaction of various spike protein constructs with the human ACE2 was considered to be best described by a Langmuir based 1:1 stoichiometric interaction. However, we demonstrate in this report that the SARS-CoV-2 spike protein interaction with ACE2 is best described by a two-step interaction, which is defined by an initial binding event followed by a slower secondary rate transition that enhances the stability of the complex by a factor of [~]190 with an overall KD of 0.20 nM. In addition, we show that the secondary rate transition is not only present in SARS-CoV-2 wt but is also found in B.1.1.7 where its transition rate is five-fold increased.


title: Autoimmune regulator act in synergism with thymocyte adhesion in the control of lncRNAs in medullary thymic epithelial cells

abstract: The autoimmune regulator (Aire) gene in medullary thymic epithelial cells (mTECs) encodes the AIRE protein, which interacts with its partners within the nucleus. This "Aire complex" induces stalled RNA Pol II on chromatin to proceed with transcription elongation of a large set of messenger RNAs and microRNAs. Considering that RNA Pol II also transcribes long noncoding RNAs (lncRNAs), we hypothesized that Aire might be implicated in the upstream control of this RNA species. To test this, we employed a loss-of-function approach in which Aire knockout mTECs were compared to Aire wild-type mTECs for lncRNA transcriptional profiling both in vitro and in vivo model systems. RNA sequencing enables the differential expression profiling of lncRNAs when these cells adhere in vitro to thymocytes or do not adhere to them as a way to test the effect of cell adhesion. Sets of lncRNAs that are unique and that are shared in vitro and in vivo were identified. Among these, we found the Aire-dependent lncRNAs as for example, Platr28, Ifi30, Morrbid, Malat1, and Xist. This finding represents the first evidence that Aire mediates the transcription of lncRNAs in mTECs. Microarray hybridizations enabled us to observe that temporal thymocyte adhesion modulates the expression levels of such lncRNAs as Morrbid, Xist, and Fbxl12o after 36h of adhesion. This finding shows the existence of a synergistic mechanism involving a link between thymocyte adhesion, Aire, and lncRNAs in mTECs that might be important for immune self-representation.


title: Emergence of a geometric pattern of cell fates from tissue-scale mechanics in the Drosophila eye

abstract: Pattern formation of biological structures involves the arrangement of different types of cells in an ordered spatial configuration. In this study, we investigate the mechanism of patterning the Drosophila eye into a precise triangular grid of photoreceptor clusters called ommatidia. Previous studies had led to a long-standing biochemical model whereby a reaction-diffusion process is templated by recently formed ommatidia to propagate a molecular prepattern across the eye epithelium. Here, we find that the templating mechanism is instead, mechanical in origin; newly born columns of ommatidia serve as a template to spatially pattern cell flows that move the cells in the epithelium into position to form each new column of ommatidia. Cell flow is generated by a pressure gradient that is caused by a narrow zone of cell dilation precisely positioned behind the growing wavefront of ommatidia. The newly formed lattice grid of ommatidia cells are immobile, deflecting and focusing the flow of other cells. Thus, the self-organization of a regular pattern of cell fates in an epithelium is mechanically driven.


title: Epigenetically Inherited Mutation Rates Predicted to Maximize Adaptation Rates

abstract: The mutation rate is an important determinant of evolutionary dynamics. Because the mutation rate determines the rate of appearance of beneficial and deleterious mutations, it is subject to second-order selection. The mutation rate varies between and within species and populations, increases under stress, and is genetically controlled by mutator alleles. The mutation rate may also vary among genetically identical individuals: empirical evidence from bacteria suggests that the mutation rate may be affected by translation errors and expression noise in various proteins (1). Importantly, this non-genetic variation may be heritable via transgenerational epigenetic inheritance. Here we investigate how the inheritance mode of the mutation rate affects the rate of adaptive evolution on rugged fitness landscapes. We model an asexual population with two mutation rate phenotypes, non-mutator and mutator. An offspring may switch from its parental phenotype to the other phenotype. The rate of switching between the mutation rate phenotypes is allowed to span a range of values. Thus, the mutation rate can be interpreted as a genetically inherited trait when the switching rate is low, as an epigenetically inherited trait when the switching rate is intermediate, or as a randomly determined trait when the switching rate is high. We find that epigenetically inherited mutation rates result in the highest rates of adaptation on rugged fitness landscapes for most realistic parameter sets. This is because an intermediate switching rate can maintain the association between a mutator phenotype and pre-existing mutations, which facilitates the crossing of fitness valleys. Our results provide a rationale for the evolution of epigenetic inheritance of the mutation rate, suggesting that it could have been selected because it facilitates adaptive evolution.

category: evolutionary biology


title: The (non) accuracy of mitochondrial genomes for family level phylogenetics: the case of erebid moths (Lepidoptera; Erebidae)

abstract: The use of molecular data to study evolutionary history of different organisms, revolutionized the field of systematics. Now with the appearance of high throughput sequencing (HTS) technologies more and more genetic sequence data is available. One of the important sources of genetic data for phylogenetic analyses has been mitochondrial DNA. The limitations of mitochondrial DNA for the study of phylogenetic relationships have been thoroughly explored in the age of single locus phylogenies. Now with the appearance of genomic scale data, more and more mitochondrial genomes are available. Here we assemble 47 mitochondrial genomes using whole genome Illumina short reads of representatives of the family Erebidae (Lepidoptera), in order to evaluate the accuracy of mitochondrial genome application in resolving deep phylogenetic relationships. We find that mitogenomes are inadequate for resolving subfamily level relationships in Erebidae, but given good taxon sampling, we see its potential in resolving lower level phylogenetic relationships.


title: Allele-resolved single-cell multi-omics uncovers the dynamics and transcriptional kinetics of X-chromosome upregulation

abstract: X-chromosome inactivation (XCI) and upregulation (XCU) are the major opposing chromosome-wide modes of gene regulation that collectively achieve dosage compensation in mammals, but the regulatory link between the two remains elusive. Here, we use allele-resolved single-cell RNA-seq combined with chromatin accessibility profiling to finely dissect the separate effects of XCI and XCU on RNA levels during mouse development. We uncover that balanced X dosage is flexibly attained through expression tuning by XCU in a sex- and lineage-specific manner along varying degrees of XCI and across developmental and cellular states. Male blastomeres achieve XCU upon zygotic genome activation while females experience two distinct waves of XCU, upon imprinted- and random XCI, and ablation of Xist impedes female XCU. Contrary to widely established models of mammalian dosage compensation, naive female embryonic cells carrying two active X chromosomes do not exhibit upregulation but express both alleles at basal level, yet collectively exceeding the RNA output of a single hyperactive allele. We show, in vivo and in vitro, that XCU is kinetically driven by X-specific modulation of transcriptional burst frequency, coinciding with increased compartmentalization of the hyperactive allele. Altogether, our data provide unprecedented insights into the dynamics of mammalian XCU, prompting a revised model of the chain in events of allelic regulation by XCU and XCI in unitedly achieving stable cellular levels of X-chromosome transcripts.


title: Comparing the appetitive learning performance of six European honeybee subspecies in a common apiary

abstract:
The Western honeybee (Apis mellifera L.) is one of the most widespread insects with numerous subspecies in its native range. In how far adaptation to local habitats has affected the cognitive skills of the different subspecies is an intriguing question which we investigate in this study. Naturally mated queens of the following five subspecies from different parts of Europe were transferred to Southern Germany: A. m. iberiensis from Portugal, A. m. mellifera from Belgium, A. m. macedonica from Greece, A.m. ligustica from Italy and A. m. ruttneri from Malta. We also included the local subspecies A.m. carnica in our study. New colonies were built up in a common apiary where the respective queens were introduced. Worker offspring from the different subspecies was compared in classical olfactory learning performance using the proboscis extension response. Prior to conditioning we measured individual sucrose responsiveness to investigate whether possible differences in learning performances were due to a differential responsiveness to the sugar water reward. Most subspecies did not differ in their appetitive learning performance. However, foragers of the Iberian honeybee, A. m. iberiensis, performed significantly more poorly, despite having a similar sucrose responsiveness. We discuss possible causes for the low cognitive performance of the Iberian honeybees, which may have been shaped by adaptation to local habitat.

Summary statementThis study is the first to compare the associative learning performance of six honeybee subspecies from different European regions in a common apiary.

category: animal behavior and cognition


title: Polyacrylamide co-N,N'-methylene bisacrylamide monoliths for high peak capacity HILIC-HRMS of intact proteins at low trifluoroacetic acid content

abstract:
In this study, we optimized a polymerization mixture to synthesize polyacrylamide-co-N,N-methylene bisacrylamide monolithic stationary phases for hydrophilic-interaction chromatography (HILIC) of intact proteins. Thermal polymerization was performed, and the effects of varying the amount of crosslinker and the porogen composition on the separation performance of the resulting columns were studied.

The homogeneity of the structure and the different porosities were examined through scanning electron microscopy. Further characterization of the monolithic structure revealed a permeable (Kf between 2.5 x 10-15 and 1.40 x 10-13 m2) and polar stationary phase suitable for HILIC. The HILIC separation performance of the different columns was assessed using gradient separation of a sample containing four intact proteins, with the best performing stationary phase exhibiting a peak capacity of 51 in a gradient of 25 min.

Polyacrylamide-based materials were compared with a silica-based particulate amide phase (2.7 m core-shell particles). The monolith has no residual silanol sites and, therefore, fewer sites for ion-exchange interactions with proteins. Thus, it required lower concentrations of ion-pair reagent in HILIC of intact proteins. When using 0.1% of trifluoroacetic acid (TFA) the peak capacities of the two columns were similar (31 and 36 for the monolithic and packed column, respectively). However, when decreasing the concentration of TFA to 0.005%, the monolithic column maintained its separation performance and selectivity (peak capacity 26), whereas the packed column showed greatly reduced performance (peak capacity 7), lower selectivity, and inability to elute all four reference proteins. Finally, using a mobile phase containing 0.1% formic acid and 0.005% TFA the HILIC separation on the monolithic column was successfully hyphenated with high-resolution mass spectrometry. Detection sensitivity for protein and glycoproteins was increased and the amount of adducts formed was decreased in comparison with separations performed at 0.1% TFA.

category: biochemistry


title: PyLipID: A Python package for analysis of protein-lipid interactions from MD simulations

abstract:
Lipids play important modulatory and structural roles for membrane proteins. Molecular dynamics simulations are frequently used to provide insights into the nature of these proteinlipid interactions. Systematic comparative analysis requires tools that provide algorithms for objective assessment of such interactions. We introduce PyLipID, a python package for the identification and characterization of specific lipid interactions and binding sites on membrane proteins from molecular dynamics simulations. PyLipID uses a community analysis approach for binding site detection, calculating lipid residence times for both the individual protein residues and the detected binding sites. To assist structural analysis, PyLipID produces representative bound lipid poses from simulation data, using a density-based scoring function. To estimate residue contacts robustly, PyLipID uses a dual-cutoff scheme to differentiate between lipid conformational rearrangements whilst bound from full dissociation events. In addition to the characterization of protein-lipid interactions, PyLipID is applicable to analysis of the interactions of membrane proteins with other ligands. By combining automated analysis, efficient algorithms, and open-source distribution, PyLipID facilitates the systematic analysis of lipid interactions from large simulation datasets of multiple species of membrane proteins.

ToC Graphic

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/452312v1_ufig1.gif" ALT="Figure 1">
View larger version (53K):
org.highwire.dtl.DTLVardef@1f6530corg.highwire.dtl.DTLVardef@c639d5org.highwire.dtl.DTLVardef@1fef967org.highwire.dtl.DTLVardef@a80446_HPS_FORMAT_FIGEXP  M_FIG C_FIG

category: biophysics


title: Hypoxia induces early neurogenesis in human fetal neural stem cells by activating the WNT pathway.

abstract: Fetal neural stem cells (FNSCs) are present in the brain of human fetuses that differentiate into cells of neuronal and glial lineages. Difference in oxygen concentration between maternal and fetal circulation indicates that the developing fetus may be exposed to lower oxygen concentrations compared to adults. This physiological hypoxia may influence the growth and differentiation of the FNSCs. This study aimed to evaluate the effect of hypoxia on the differentiation potential of human FNSCs isolated from the sub-ventricular zone of aborted fetal brains (n=5). FNSCs were isolated, expanded, and characterized by Nestin and Sox2 expression, using immunocytochemistry and flowcytometry respectively. These FNSCs were exposed to 20% oxygen (normoxia) and 0.2% oxygen (hypoxia) concentrations for 48 hours, and hypoxia exposure (n=5) was evaluated by a panel of markers (CA9, PGK1 and VEGF). Whole human genome transcriptomic analyses (Genespring GX13) of FNSCs exposed to hypoxia (Agilent 4x44K human array slides), highlighted that genes associated with neurogenesis were getting enriched. The pathway analysis of these enriched genes (using Metacore) showed that WNT signaling played a role in determining the cell fate of FNSCs exposed to hypoxic environment. Microarray analyses was validated using neuronal and glial lineage commitment markers such as Ngn1, Ngn2, ASCL1, DCX, GFAP, Olig2 and Nkx2.2 using qPCR (n=9). This demonstrated upregulation of the neuronal commitment markers on hypoxia exposure, while no change was observed in astrocytic and oligodendrocyte lineage commitment markers. Increased expression of downstream targets of the WNT signaling pathway, TCF4 and ID2, by qPCR (n=9), indicated its involvement in mediating neuronal differentiation on exposure to hypoxia.


title: Enhancer-promoter interactions and transcription are maintained upon acute loss of CTCF, cohesin, WAPL, and YY1

abstract: It remains unclear why acute depletion of CTCF and cohesin only marginally affects expression of most genes despite substantially perturbing 3D genome folding at the level of domains and structural loops. To address this conundrum, we used high-resolution Micro-C and nascent transcript profiling to find that enhancer-promoter (E-P) interactions are largely insensitive to acute (3-hour) depletion of CTCF, cohesin, and WAPL. YY1 has been proposed to be a structural regulator of E-P loops, but acute YY1 depletion also had minimal effects on E-P loops, transcription, and 3D genome folding. Strikingly, live-cell single-molecule imaging revealed that cohesin depletion reduced transcription factor binding to chromatin. Thus, although neither CTCF, cohesin, WAPL, nor YY1 are required for the short-term maintenance of most E-P interactions and gene expression, we propose that cohesin may serve as a "transcription factor binding platform" that facilitates transcription factor binding to chromatin.


title: Structural heterogeneity of the microtubule lattice

abstract:
Microtubules are polymers assembled from {beta}-tubulin heterodimers. They typically display lateral - and {beta}-{beta} homotypic interactions, except at one region, called the seam, where heterotypic -{beta} and {beta}- interactions occur. Here, we decorated microtubules assembled in vitro or in cytoplasmic Xenopus egg extracts with kinesin-motor domains, and analyzed their lattice organization using dual axis cryo-electron tomography followed by segmented sub-tomogram averaging. In both conditions, microtubules incorporated variable protofilament and/or tubulin subunit helix start numbers. While microtubules assembled in vitro displayed variable numbers of seams, those assembled in extracts displayed preferentially one seam. The seam location varied within individual microtubules implying the presence of lattice holes. Thus, the formation of discontinuous microtubule lattices is an intrinsic property of tubulin assembly, a process that is controlled in cells.

One-Sentence SummaryMicrotubules assembled from purified tubulin form discontinuous lattices, an intrinsic property strictly controlled in cytoplasmic Xenopus egg extracts.


title: The importance of environmentally-acquired bacterial symbionts for the squash bug (Anasa tristis), a significant agricultural pest

abstract: Most insects maintain associations with microbes that shape their ecology and evolution. Such symbioses have important applied implications when the associated insects are pests or vectors of disease. The squash bug, Anasa tristis (Coreoidea: Coreidae), is a significant pest of human agriculture in its own right and also causes damage to crops due to its capacity to transmit a bacterial plant pathogen. Here, we demonstrate that complete understanding of these insects requires consideration of their association with bacterial symbionts in the family Burkholderiaceae. Isolation and sequencing of bacteria housed in midgut crypts in these insects indicates that these bacteria are consistent and dominant members of the crypt-associated bacterial communities. These symbionts are closely related to Caballeronia spp. associated other true bugs in the superfamiles Lygaeoidea and Coreoidea. Fitness assays with representative Burkholderiaceae strains indicate that the association can significantly increase survival and decrease development time, though strains do vary in the benefits that they confer to their hosts, with Caballeronia spp. providing the greatest benefit. Experiments designed to assess transmission mode indicate that unlike many other beneficial insect symbionts, the bacteria are not acquired from parents before or after hatching but are instead acquired from the environment after molting to a later development stage. The bacteria do, however, have the capacity to escape adults to be transmitted to later generations, leaving the possibility for a combination of indirect vertical and horizontal transmission.

category: ecology


title: When the whole is less than the sum of its parts: maximum object category information and behavioral prediction in multiscale activation patterns

abstract: Neural codes are reflected in complex, temporally and spatially specific patterns of activation. One popular approach to decode neural codes in electroencephalography (EEG) is multivariate decoding. This approach examines the discriminability of activity patterns across experimental conditions to test if EEG contains information about those conditions. However, conventional decoding analyses ignore aspects of neural activity which are informative. Specifically, EEG data can be decomposed into a large number of mathematically distinct features (e.g., entropy, Fourier and Wavelet coefficients) which can reflect different aspects of neural activity. We previously compared 30 such features of EEG data, and found that visual category, and participant behavior, can be more accurately predicted using multiscale spatiotemporally sensitive Wavelet coefficients than mean amplitude (Karimi-Rouzbahani et al., 2021b). Here, we considered that even this larger set of features may only partially capture the underlying neural code, because the brain could use a combination of encoding protocols within a single trial which is not reflected in any one mathematical feature alone. To check, we combined those mathematical features using state-of-the-art supervised and unsupervised feature selection procedures (n = 17). Across 3 datasets, we compared decoding of visual object category between these 17 sets of combined features, and between combined and individual features. Object category could be robustly decoded using the combined features from all of the 17 algorithms. However, the combination of features, which were equalized in dimension to the individual features, were outperformed in most of the time points by the most informative individual feature (Wavelet coefficients). Moreover, the Wavelet coefficients also explained the behavioral performance more accurately than the combined features. These results suggest that a single but multiscale encoding protocol may capture the neural code better than any combination of features. Our findings put new constraints on the models of neural information encoding in EEG.


title: The Janus-like role of neuraminidase isoenzymes in inflammation

abstract: The processes of activation, extravasation, and migration of immune cells to a site are early and essential steps in the induction of an acute inflammatory response. These events are part of the inflammatory cascade which involves multiple regulatory steps. Using a murine air-pouch model of inflammation with LPS as an inflammation inducer we demonstrate that isoenzymes of the neuraminidase family (NEU1, 3, and 4) play essential roles in this process acting as positive or negative regulators of leukocyte infiltration. Genetically knocked-out (KO) mice for different NEU genes (Neu1 KO, Neu3 KO, Neu4 KO, and Neu3/4 double KO mice) were induced with LPS, leukocytes at the site of inflammation were counted, and the inflamed tissue was analyzed using immunohistochemistry. Our data show that leukocyte recruitment was decreased in NEU1 and NEU3-deficient mice, while it was increased in NEU4-deficient animals. Consistent with these results, systemic levels of pro-inflammatory cytokines and those in pouch exudate were reduced in Neu1 and increased in Neu4 KO mice. We found that pharmacological inhibitors specific for NEU1, NEU3, and NEU4 isoforms also affected leukocyte recruitment. We conclude that NEU isoenzymes have distinct - and even opposing - effects on leukocyte recruitment, and therefore warrant further investigation to determine their mechanisms and importance as regulators of the inflammatory cascade.


title: Retinal ganglion cell-specific genetic regulation in primary open angle glaucoma

abstract: To assess the transcriptomic profile of disease-specific cell populations, fibroblasts from patients with primary open-angle glaucoma (POAG) were reprogrammed into induced pluripotent stem cells (iPSCs) before being differentiated into retinal organoids and compared to those from healthy individuals. We performed single-cell RNA-sequencing of a total of 330,569 cells and identified cluster-specific molecular signatures. Comparing the gene expression profile between cases and controls, we identified novel genetic associations for this blinding disease. Expression quantitative trait mapping identified a total of 2,235 significant loci across all cell types, 58 of which are specific to the retinal ganglion cell subpopulations, which ultimately degenerate in POAG. Transcriptome-wide association analysis identified genes at loci previously associated with POAG, and analysis, conditional on disease status, implicated 54 statistically significant retinal ganglion cell-specific expression quantitative trait loci. This work highlights the power of large-scale iPSC studies to uncover context-specific profiles for a genetically complex disease.

category: genetics


title: Evolutionary repair reveals an unexpected role of the tRNA modification m1G37 in aminoacylation

abstract: The tRNA modification m1G37, which is introduced by the tRNA methyltransferase TrmD, is thought to be essential for growth in bacteria due to its role in suppressing translational frameshift errors at proline codons. However, because bacteria can tolerate high levels of mistranslation, it is unclear why loss of m1G37 is not tolerated. Here, we addressed this question by performing experimental evolution of trmD mutant strains of E. coli. Surprisingly, trmD mutant strains were viable even if the m1G37 modification was completely abolished, and showed rapid recovery of growth rate, mainly via tandem duplication or coding mutations in the proline-tRNA ligase gene proS. Growth assays and in vitro aminoacylation assays showed that G37-unmodified tRNAPro is aminoacylated less efficiently than m1G37-modified tRNAPro, and that growth of trmD mutant strains can be largely restored by single mutations in proS that restore aminoacylation of G37-unmodified tRNAPro. These results show that inefficient aminoacylation of tRNAPro is the main reason for growth defects observed in trmD mutant strains and that the ProRS enzyme may act as a gatekeeper of translational accuracy, preventing the use of error-prone unmodified tRNAPro in protein translation. Our work shows the utility of experimental evolution for uncovering the hidden functions of essential genes and has implications for the development of antibiotics targeting TrmD.


title: Palmitoylation targets the Calcineurin phosphatase to the Phosphatidylinositol 4-kinase complex at the plasma membrane

abstract: Calcineurin, the conserved protein phosphatase and target of immunosuppressants, is a critical mediator of Ca2+ signaling. To discover novel calcineurin-regulated processes we examined an understudied isoform, CNA{beta}1. We show that unlike canonical cytosolic calcineurin, CNA{beta}1 localizes to the plasma membrane and Golgi due to palmitoylation of its divergent C-terminal tail, which is reversed by the ABHD17A depalmitoylase. Palmitoylation targets CNA{beta}1 to a distinct set of membrane-associated interactors including the phosphatidylinositol 4-kinase (PI4KA) complex containing EFR3B, PI4KA, TTC7B and FAM126A. Hydrogen-deuterium exchange reveals multiple calcineurin-PI4KA complex contacts, including a calcineurin-binding peptide motif in the disordered tail of FAM126A, which we establish as a calcineurin substrate. Calcineurin inhibitors decrease PI4P production during Gq-coupled GPCR signaling, suggesting that calcineurin dephosphorylates and promotes PI4KA complex activity. In sum, this work discovers a new calcineurin-regulated signaling pathway highlighting the PI4KA complex as a regulatory target and revealing that dynamic palmitoylation confers unique localization, substrate specificity and regulation to CNA{beta}1.


title: Scalable Fabrication of 3D Structured Microparticles Using Induced Phase Separation

abstract: Microparticles with defined shapes and spatial chemical modification can enable new opportunities to interface with cells and tissues at the cellular scale. However, conventional methods to fabricate shaped microparticles have trade-offs between the throughput of manufacture and precision of particle shape and chemical functionalization. Here, we achieved scalable production of hydrogel microparticles at rates of greater than 40 million/hour with localized surface chemistry using a parallelized step emulsification device and temperature-induced phase-separation. The approach harnesses a polymerizable polyethylene glycol (PEG) and gelatin aqueous-two phase system (ATPS) which conditionally phase separates within microfluidically-generated droplets. Following droplet formation, phase separation is induced and phase separated droplets are subsequently crosslinked to form uniform crescent and hollow shell particles with gelatin functionalization on the boundary of the cavity. The gelatin localization enabled deterministic cell loading in sub nanoliter-size crescent-shaped particles, which we refer to as nanovials, with cavity dimensions tuned to the size of cells. Loading on nanovials also imparted improved cell viability during analysis and sorting using standard fluorescence activated cell sorters, presumably by protecting cells from shear stress. This localization effect was further exploited to selectively functionalize capture antibodies to nanovial cavities enabling single-cell secretion assays with reduced cross-talk in a simplified format.

category: bioengineering


title: Distribution-based comprehensive evaluation ofmethods for differential expression analysis inmetatranscriptomics

abstract:
BackgroundMeasuring and understanding the function of the human microbiome is key for several aspects of health; however, the development of statistical methods specifically for the analysis of microbial gene expression (i.e., metatranscriptomics) is in its infancy. Many currently employed differential expression analysis methods have been designed for different data types and have not been evaluated in metatranscriptomics settings. To address this knowledge gap, we undertook a comprehensive evaluation and benchmarking of eight differential analysis methods for metatranscriptomics data.

ResultsWe used a combination of real and simulated metatranscriptomics data to evaluate the performance (i.e., model fit, Type-I error, and statistical power) of eight methods: log-normal (LN), logistic-beta (LB), MAST, Kruskal-Wallis, two-part Kruskal-Wallis, DESeq2, ANCOM-BC, and metagenomeSeq. The simulation was informed by supragingival biofilm microbiome data from 300 preschool-age children enrolled in a study of early childhood caries (ECC), whereas validations were sought in two additional datasets, including an ECC and an inflammatory bowel disease one. The LB test showed the highest power in both small and large sample sizes and reasonably controlled Type-I error. Contrarily, MAST was hampered by inflated Type-I error. Using LN and LB tests, we found that genes C8PHV7 and C8PEV7, harbored by the lactate-producing Campylobacter gracilis, had the strongest association with ECC.

ConclusionThis comprehensive model evaluation findings offer practical guidance for the selection of appropriate methods for rigorous analyses of differential expression in metatranscriptomics data. Selection of an optimal method is likely to increase the possibility of detecting true signals while minimizing the chance of claiming false ones.


title: Twisting DNA by Salt

abstract: The structure and properties of DNA depend on the environment, in particular the ion atmosphere. Here, we investigate how DNA twist -one of the central properties of DNA- changes with concentration and identity of the surrounding ions. To resolve how cations influence the helical twist, we combine single-molecule magnetic tweezer experiments and extensive all- atom molecular dynamics simulations. Two interconnected trends are observed for monovalent alkali and divalent alkaline earth cations. First, DNA twist increases monotonously with increasing concentration for all ions investigated. Second, for a given salt concentration, DNA twist strongly depends on cation identity. At 100 mM concentration, DNA twist increases as Ba2+ < Na+ < K+ < Rb+ < Li+ {approx} Cs+ < Sr2+ < Mg2+ < Ca2+. Our molecular dynamics simulations reveal that preferential binding of the cations to the DNA backbone or the nucleobases has opposing effects on DNA twist and provides the microscopic explanation of the observed ion specificity. However, the simulations also reveal shortcomings of existing force field parameters for Cs+ and Sr2+. The comprehensive view gained from our combined approach provides a foundation for understanding and predicting cation-induced structural changes both in nature and in DNA nanotechnology.


title: Recording Temporal Signals with Minutes Resolution Using Enzymatic DNA Synthesis

abstract: Employing DNA as a high-density data storage medium has paved the way for next-generation digital storage and biosensing technologies. However, the multipart architecture of current DNA-based recording techniques renders them inherently slow and incapable of recording fluctuating signals with sub-hour frequencies. To address this limitation, we developed a simplified system employing a single enzyme, terminal deoxynucleotidyl transferase (TdT), to transduce environmental signals into DNA. TdT adds nucleotides to the 3 ends of single-stranded DNA (ssDNA) in a template-independent manner, selecting bases according to inherent preferences and environmental conditions. By characterizing TdT nucleotide selectivity under different conditions, we show that TdT can encode various physiologically relevant signals like Co2+, Ca2+, Zn2+ concentrations and temperature changes in vitro. Further, by considering the average rate of nucleotide incorporation, we show that the resulting ssDNA functions as a molecular ticker tape. With this method we accurately encode a temporal record of fluctuations in Co2+ concentration to within 1 minute over a 60-minute period. Finally, we engineer TdT to allosterically turn off in the presence of physiologically relevant concentration of calcium. We use this engineered TdT in concert with a reference TdT to develop a two-polymerase system capable of recording a single step change in Ca2+ signal to within 1 minute over a 60-minute period. This work expands the repertoire of DNA-based recording techniques by developing a novel DNA synthesis-based system that can record temporal environmental signals into DNA with minutes resolution.

category: synthetic biology


title: Task-related hemodynamic responses in human early visual cortex are modulated by task difficulty and behavioral performance

abstract: Early visual cortex exhibits widespread hemodynamic responses in the absence of visual stimulation, which are entrained to the timing of a task and not predicted by local spiking or local field potential (LFP). Such task-related responses ("TRRs") covary with reward magnitude and physiological signatures of arousal. It is unknown, however, if TRRs change on a trial-to-trial basis according to behavioral performance and task difficulty. If so, this would suggest that TRRs reflect arousal on a trial-to-trial timescale and covary with critical task and behavioral variables. We measured fMRI-BOLD responses in the early visual cortex of human observers performing an orientation discrimination task consisting of separate easy and hard runs of trials. Stimuli were presented in a small portion of one hemifield, but the fMRI response was measured in the ipsilateral hemisphere, far from the stimulus representation and focus of spatial attention. TRRs scaled in amplitude with task difficulty, behavioral accuracy, reaction time, and lapses across trials. These modulations were not explained by the influence of respiration, cardiac activity, or head movement on the fMRI signal. Similar modulations with task difficulty and behavior were observed in pupil size. These results suggest that TRRs reflect arousal and behavior on the timescale of individual trials.

category: neuroscience


title: The 4.4 A structure of the giant Melbournevirus virion belonging to the Marseilleviridae family

abstract: Members of Marseilleviridae, one family of icosahedral giant viruses classified in 2012 have been identified worldwide in all types of environments. The virion shows a characteristic internal membrane extrusion at the five-fold vertices of the capsid, but its structural details need to be elucidated. We now report the 4.4 [A] cryo-electron microscopy structure of the Melbournevirus capsid. An atomic model of the major capsid protein (MCP) shows a unique cup structure on the trimer that accommodates additional proteins. A polyalanine model of the penton base protein shows internally extended N- and C-terminals, which indirectly connect to the internal membrane extrusion. The Marseilleviruses share the same orientational organisation of the MCPs as PBCV-1 and CroV, but do not appear to possess a protein akin to the "tape measure" of these viruses. Minor capsid proteins named PC-{beta}, zipper, and scaffold are proposed to control the dimensions of the capsid during assembly.

category: microbiology


title: Automatic inference of cell neighborhood in 2D and 3D using nuclear markers

abstract:
SignificanceEstimating neighboring cells by using only nuclear markers is crucial in many biological applications. Although several strategies have been used for this purpose, most published methods lack a rigorous characterization of their efficiencies. Remarkably, previously described methods are not automatic and depend only on cell-cell distance, neglecting the importance of pair-neighborhood interaction.

AimTo develop a robust and automatic method for assessing cell local neighborhood, while analyzing the impact of the physical variables involved in this task.

ApproachWe inferred neighbors from images with nuclei labeling by approximating the cell-cell interaction graph by the Delaunay triangulation of nuclei centroids. Each edge of this graph was filtered by thresholding in cell-cell distance and the maximum angle that each pair subtends with shared neighbors (pair-neighborhood interaction). Thresholds were calculated by maximizing a new robust statistic that measures the communicability efficiency of the cell graph. Using a variety of images of diverse tissues with additional membrane labeling to find the ground truth, we characterized the assessment performance.

ResultsOn average, our method detected 95% of true neighbors, with only 6% of false discoveries. Even though our methods performance and tissue regularity are correlated, it works with performance metrics over 86% in very different organisms, including Drosophila melanogaster, Tribolium castaneum, Arabidopsis thaliana and C. elegans.

ConclusionsWe automatically estimated neighboring relationships between cells in 2D and 3D using only nuclear markers. To achieve this goal, we filtered the Delaunay triangulation of nuclei centroids with a new measure of graph communicability efficiency. In addition, we found that taking pair-neighborhood interactions into account, in contrast to considering only cell-cell distances, leads to significant performance improvements. This becomes more notorious when the number of cells is low or the geometry of the cell graph is highly complex.


title: Circular-Linear Copulae for Animal Movement Data

abstract:
O_LIAnimal movement is often modeled in discrete time, formulated in terms of steps taken between successive locations at regular time intervals. Steps are characterized by the distance between successive locations (step-lengths) and changes in direction (turn angles). Animals commonly exhibit a mix of directed movements with large step lengths and turn angles near 0 when traveling between habitat patches and more wandering movements with small step lengths and uniform turn angles when foraging. Thus, step-lengths and turn angles will typically be cross-correlated.
C_LIO_LIMost models of animal movement assume that step-lengths and turn angles are independent, likely due to a lack of available alternatives. Here, we show how the method of copulae can be used to fit multivariate distributions that allow for correlated step lengths and turn angles.
C_LIO_LIWe describe several newly developed copulae appropriate for modeling animal movement data and fit these distributions to data collected on fishers (Pekania pennanti). The copulae are able to capture the inherent correlation in the data and provide a better fit than a model that assumes independence. Further, we demonstrate via simulation that this correlation can impact movement patterns (e.g. rates of dispersion overtime).
C_LIO_LIWe see many opportunities to extend this framework (e.g. to consider autocorrelation in step attributes) and to integrate it into existing frameworks for modeling animal movement and habitat selection. For example, copula could be used to more accurately sample available locations when conducting habitat-selection analyses.
C_LI


title: Mathematically and biologically consistent framework for presence-absence pairwise indices of diversity

abstract:
AimA large number of indices that compare two or more assemblages have been proposed or reinvented. The interpretation of the indices varies across the literature, despite efforts for clarification and unification. Most of the effort has focused on interdependence between the indices and the mathematics behind them. At the same time, following issues have been underestimated: (i) the difference between statistical independence of indices and the independence based on their informational value, and (ii) the inferences from the indices about diversity patterns and phenomena. Here we offer an alternative framework for diversity indices.

MethodsWe distinguish different classes of dependence, and show that three indices which are mutually independent in terms of their information content are sufficient for appropriate inferences. This applies regardless of whether the indices are statistically correlated or not. We classify 20 existing indices into three main and four minor mutually independent families, and demonstrate how similarity between assemblages violates the stability of the families, confusing conceptually different patterns. We show what can be inferred about spatial diversity phenomena from different indices, demonstrate problems with most of the indices of nestedness, and show which combinations of indices may be used for meaningful ecological inference.

Results and Main conclusionsWe demonstrate that no single index can properly filter out a single effect of a phenomena because the phenomena inevitably bound each other (e.g. species richness gradient bounds possible values of Jaccard index of community similarity). Consequently, inventing indices which seemingly purify these effect (e.g. pure turnover or pure nestedness) leads to misleading inference. In contrast, a proper inference is obtained by using a combination of classical indices from different, mutually independent families. Our framework provides a practical clue how to compare different indices across the literature.


title: Joint Gene Network Construction by Single-Cell RNA Sequencing Data

abstract: SO_SCPLOWUMMARYC_SCPLOWIn contrast to differential gene expression analysis at single gene level, gene regulatory networks (GRN) analysis depicts complex transcriptomic interactions among genes for better understandings of underlying genetic architectures of human diseases and traits. Recently, single-cell RNA sequencing (scRNA-seq) data has started to be used for constructing GRNs at a much finer resolution than bulk RNA-seq data and microarray data. However, scRNA-seq data are inherently sparse which hinders direct application of the popular Gaussian graphical models (GGMs). Furthermore, most existing approaches for constructing GRNs with scRNA-seq data only consider gene networks under one condition. To better understand GRNs under different but related conditions with single-cell resolution, we propose to construct Joint Gene Networks with scRNA-seq data (JGNsc) using the GGMs framework. To facilitate the use of GGMs, JGNsc first proposes a hybrid imputation procedure that combines a Bayesian zero-inflated Poisson (ZIP) model with an iterative low-rank matrix completion step to efficiently impute zero-inflated counts resulted from technical artifacts. JGNsc then transforms the imputed data via a nonparanormal transformation, based on which joint GGMs are constructed. We demonstrate JGNsc and assess its performance using synthetic data. The application of JGNsc on two cancer clinical studies of medulloblastoma and glioblastoma identifies novel findings in addition to confirming well-known biological results.


title: Partitioning gene-mediated disease heritability without eQTLs

abstract: Unknown SNP-to-gene regulatory architecture complicates efforts to link noncoding GWAS associations with genes implicated by sequencing or functional studies. eQTLs are used to link SNPs to genes, but expression in bulk tissue explains a small fraction of disease heritability. A simple but successful approach has been to link SNPs with nearby genes, but the fraction of heritability mediated by these genes is unclear, and gene-proximal (vs. gene-mediated) heritability enrichments are attenuated accordingly. We propose the Abstract Mediation Model (AMM) to estimate (1) the fraction of heritability mediated by the closest or kth-closest gene to each SNP and (2) the mediated heritability enrichment of a gene set (e.g. genes with rare-variant associations). AMM jointly estimates these quantities by matching the decay in SNP enrichment with distance from genes in the gene set. Across 47 complex traits and diseases, we estimate that the closest gene to each SNP mediates 27% (SE: 6%) of heritability, and that a substantial fraction is mediated by genes outside the ten closest. Mendelian disease genes are strongly enriched for common-variant heritability; for example, just 21 dyslipidemia genes mediate 25% of LDL heritability (211x enrichment, P = 0.01). Among brain-related traits, genes involved in neurodevelopmental disorders are only about 4x enriched, but gene expression patterns are highly informative, with detectable differences in per-gene heritability even among weakly brain-expressed genes.


title: Functional enrichment of alternative splicing events with NEASE reveals insights into tissue identity and diseases

abstract: Alternative splicing (AS) is an important aspect of gene regulation. Nevertheless, its role in molecular processes and pathobiology is far from understood. A roadblock is that tools for the functional analysis of AS-set events are lacking. To mitigate this, we developed NEASE, a tool integrating pathways with protein-protein and domain-domain interactions to functionally characterize AS events. We show in four application cases how NEASE can identify pathways contributing to tissue identity and cell type development, and how it highlights splicing-related biomarkers. With a unique view on AS, NEASE generates unique and meaningful biological insights complementary to classical pathways analysis.


title: Prolonged partner separation erodes nucleus accumbens transcriptional signatures of pair bonding in male prairie voles

abstract: The loss of a spouse is often cited as the most traumatic event in a persons life. However, for most people, the severity of grief and its maladaptive effects subside over time via an understudied adaptive process. Like humans, socially monogamous prairie voles (Microtus ochrogaster) form opposite-sex pair bonds, and upon partner separation, show behavioral and neuroendocrine stress phenotypes that diminish over time. Eventually, they can form a new bond, a key indicator of adapting to the loss of their partner. Thus, prairie voles provide an ethologically-relevant model for examining neuromolecular changes that emerge following partner separation for adapting to loss. Here, we test the hypothesis that extended partner separation diminishes pair bond-associated behaviors (partner preference and selective aggression) and causes pair bond transcriptional signatures to erode. Pairs were cohoused for 2 weeks and then either remained paired or were separated for 48hrs or 4wks before collecting fresh nucleus accumbens tissue for RNAseq. In a separate cohort, we assessed partner preference and selective aggression at these time points. Surprisingly, pair bond-associated behaviors persist despite prolonged separation and are similar between same-sex and opposite-sex paired voles. In contrast, we found that opposite-sex pair bonding, as compared with same-sex pairing, led to changes in accumbal transcription that were stably maintained as long as animals remained paired but eroded following prolonged partner separation. Eroded genes are primarily associated with gliogenesis and myelination, suggesting a previously undescribed role for glia in maintaining pair bonds and adapting to partner loss. We further reasoned that relevant neuronal transcriptional changes may have been masked by the prominent transcriptional signals associated with glia. Thus, we pioneered neuron-specific translating ribosomal affinity purification in voles. Neuronally-enriched transcriptional changes revealed dopaminergic-, mitochondrial-, and steroid hormone signaling-associated gene clusters whose expression patterns are sensitive to acute pair bond disruption and loss adaptation. Together, our results suggest that partner separation results in erosion of transcriptomic signatures of pair bonding despite core behavioral features of the bond remaining intact, revealing potential molecular processes central to priming a vole to be able to form a new bond.