title: Evidence of individual differences in motives for nicotine seeking in classical nicotine self-administration and associated outcomes of varenicline administration

abstract:
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSSmokers vary in their motives for tobacco seeking, suggesting that they could benefit from personalized treatments. However, these variations have received little attention in animal models for the study of tobacco dependence. In the most classically used model, ie. intravenous self-administration of nicotine in the rat, seeking behaviour is reinforced by the combination of intravenous nicotine with a discrete stimulus (eg. discrete cue light). In both human and animals, two types of psychopharmacological interactions between nicotine and environmental stimuli have been evidenced. Whether these two types of interactions contribute equally to nicotine seeking in all individuals is unknown.

MethodsWe combined behavioural pharmacology and clustering analysis. In an outbred male rat population, we tested whether nicotine and the discrete nicotine-associated cue light contributed equally to self-administration in all individuals. Two clusters of rats were identified, in which we further studied the nature of the psychopharmacological interaction between nicotine and the cue, as well as the response to the cessation aid varenicline when nicotine was withdrawn.

ResultsNotably, withdrawing nicotine produced drastic opposed effects on seeking behavior in the two identified clusters of rats; a 50% increase vs a 18% decrease, respectively. The first cluster of rats sought for the primary reinforcing effects of nicotine and the discrete cue light that has gained nicotine-like secondary reinforcing properties. The second cluster sought nicotine for its ability to enhance the primary reinforcing effects of the discrete cue light. Critically, the approved cessation aid Varenicline counteracted the absence of nicotine in both, but eventually decreasing seeking in the former but increasing it in the latter.

ConclusionsClassical rodent models for the study of the reinforcing and addictive effects of nicotine hide individual variations in the psychopharmacological motives supporting seeking behavior. These variations may be a decisive asset for improving their predictive validity in the perspective of precision medicine for smoking cessation.


title: Multifunctional Cre-dependent transgenic mice for high-precision all-optical interrogation of neural circuits

abstract: Determining which features of the neural code drive perception and behavior requires the ability to simultaneous read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two photon (2p) calcium imaging and targeted 2p photostimulation enable the activation of specific, functionally defined groups of neurons in behaving animals. However, these techniques do not yet have the ability to reveal how the specific distribution of firing rates across a relevant neural population mediates neural computation and behavior. The key technical obstacle is the inability to transform single-cell calcium signals into accurate estimates of firing rate changes and then write in these cell-specific firing rate changes to each individual neuron in a targeted population. To overcome this challenge, we made two advances: first we introduce a new genetic line of mice for robust Cre-dependent co-expression of a high-performance calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we developed a pipeline that enables the read-out and write-in of precise population vectors of neural activity across a targeted group of neurons. The combination of the new multifunctional transgenic line and the photostimulation paradigm offer a powerful and convenient platform for investigating the neural codes of computation and behavior. It may prove particularly useful for probing causal features of the geometry of neural representations where the ability to directly control the topology of population activity is essential.

category: neuroscience


title: All-optical recreation of naturalistic neural activity with a multifunctional transgenic reporter mouse


title: Fronto-parietal Network Segregation Predicts Maintained Cognition in the Cognitively Healthy Oldest-old (85+): evidence for dedifferentiation

abstract: Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics vary with age and how these variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brains organization, and the cognitive effects of aging may relate to this large-scale organization. We investigated functional network properties in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry. We found that the segregation of both the cortical association system and the segregation of the fronto-parietal network (FPN) were strong predictors of cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked with cognitive performance. In particular, segregation of the FPN plays an important role in supporting overall cognition and processing speed in this aging cohort. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating that cognitive ability is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.


title: Fronto-Parietal Network Segregation Predicts Maintained Processing Speed in the Cognitively Healthy Oldest-old


title: Neural networks implicated in autobiographical memory training

abstract: Training of autobiographical memory has been proposed as intervention to improve cognitive functions. The neural substrates for such improvements are poorly understood. Several brain networks have been previously linked to autobiographical recollections, including the default mode network (DMN) and the sensorimotor network. Here we tested the hypothesis that different neural networks support distinct aspects of memory improvement in response to training on a group of 59 subjects. We found that memory training increases DMN connectivity, and this associates with improved recollection of cue-specific memories. On the contrary, training decreased connectivity in the sensorimotor network, a decrease that correlated with improved ability for voluntary recall. Moreover, only decreased sensorimotor connectivity associated with training-induced decrease in the TNF immunological factor, which has been previously linked to improved cognitive performance. We identified functional and biochemical factors that associate with distinct memory processes improved by autobiographical training. Pathways which connect autobiographical memory to both high level cognition and somatic physiology are discussed.


title: A Minimum Perturbation Theory of Deep Perceptual Learning

abstract: Perceptual learning (PL) involves long-lasting improvement in perceptual tasks following extensive training. Such improvement has been found to correlate with modifications in neuronal response properties in early as well as late sensory cortical areas. A major challenge is to dissect the causal relation between modification of the neural circuits and the behavioral changes. Previous theoretical and computational studies of PL have largely focused on single-layer model networks, and thus did not address salient characteristics of PL arising from the multiple-staged "deep" structure of the perceptual system. Here we develop a theory of PL in a deep neuronal network architecture, addressing the questions of how changes induced by PL are distributed across the multiple stages of cortex, and how do the respective changes determine the performance in fine discrimination tasks. We prove that in such tasks, modifications of synaptic weights of early sensory areas are both sufficient and necessary for PL. In addition, optimal synaptic weights in the deep network are not unique but span a large space of solutions. We postulate that, in the brain, plasticity throughout the deep network is distributed such that the resultant perturbation on prior circuit structures is minimized. In contrast to most previous models of PL, the minimum perturbation (MP) learning does not change the network readout weights. Our results provide mechanistic and normative explanations for several important physiological features of PL and reconcile apparently contradictory psychophysical findings.


title: Power dynamics of theta oscillations during goal-directed navigation in freely moving humans: A mobile EEG-virtual reality T-maze study

abstract: Theta oscillations ([~]4-12 Hz) are dynamically modulated by speed and direction in freely moving animals. However, due to the paucity of electrophysiological recordings of freely moving humans, this mechanism remains poorly understood. Here, we combined mobile-EEG with fully immersive virtual-reality to investigate theta dynamics in twenty-two healthy adults (aged 18-29 years old) freely navigating a T-maze to find rewards. Our results revealed three dynamic periods of theta modulation: 1) theta power increases coincided with the participants decision-making period; 2) theta power increased for fast and leftward trials as subjects approached the goal location; and 3) feedback onset evoked two phase-locked theta bursts over the right temporal and frontal-midline channels. These results suggest that recording scalp EEG in freely moving humans navigating a simple virtual T-maze can be utilized as a powerful translational model by which to map theta dynamics during "real-life" goal-directed behavior in both health and disease.


title: A persistent behavioral state enables sustained predation of humans by mosquitoes

abstract: Predatory animals pursue prey in a noisy sensory landscape, deciding when to continue or abandon their chase. The mosquito Aedes aegypti is a micropredator that first detects humans at a distance through sensory cues such as carbon dioxide. As a mosquito nears its target it senses more proximal cues such as body heat that guides it to a meal of blood. How long the search for blood continues after initial detection of a human is not known. Here we show that a 5-second optogenetic pulse of fictive carbon dioxide induced a persistent behavioral state in female mosquitoes that lasted for more than 10 minutes. This state is highly specific to females searching for a blood meal and was not induced in recently blood-fed females or in males, who do not feed on blood. In males that lack the gene fruitless, which controls persistent social behaviors in other insects, fictive carbon dioxide induced a long-lasting behavior response resembling the predatory state of females. Finally, we show that the persistent state triggered by detection of fictive carbon dioxide enabled females to engorge on a blood meal mimic offered up to 14 minutes after the initial 5-second stimulus. Our results demonstrate that a persistent internal state allows female mosquitoes to integrate multiple human sensory cues over long timescales, an ability that is key to their success as an apex micropredator of humans.


title: A Novel and Functionally Diverse Class of Acetylcholine-gated Ion Channels

abstract: Fast cholinergic neurotransmission is mediated by acetylcholine-gated ion channels; in particular, excitatory nicotinic acetylcholine receptors play well established roles in virtually all nervous systems. Acetylcholine-gated inhibitory channels have also been identified in some invertebrate phyla, yet their roles in the nervous system are less well understood. We report the existence of multiple new inhibitory acetylcholine-gated ion channels with diverse ligand binding properties in C. elegans. We identify three channels, LGC-40, LGC-57 and LGC-58, whose primary ligand is choline rather than acetylcholine, as well as the first evidence of a truly polymodal channel, LGC-39, which is activated by both cholinergic and aminergic ligands. Using our newly deorphanised channel evidence we uncover the surprising extent to which a single neuron expresses both excitatory and inhibitory channels, not only for acetylcholine but also the other major neurotransmitters. The results presented in this study offer a new insight into the potential evolutionary benefit of a vast and diverse repertoire of LGICs to generate complexity in an anatomically compact nervous system.


title: Immunodominant and neutralizing linear B cell epitopes spanning the spike and membrane proteins of Porcine Epidemic Diarrhea Virus

abstract: Porcine Epidemic Diarrhea Virus (PEDV) is the causative agent of PED, an enteric disease that causes high mortality rates in piglets. PEDV is an alphacoronavirus that has high genetic diversity. Insights into neutralizing B cell epitopes of all genetically diverse PEDV strains are of importance, particularly for designing a vaccine that can provide broad protection against PEDV. In this work, we aimed to explore the landscape of linear B cell epitopes on the spike (S) and membrane (M) proteins of global PEDV strains. All amino acid sequences of the PEDV S and M proteins were retrieved from the NCBI database and grouped. Immunoinformatics-based methods were next developed and used to identify putative linear B cell epitopes from 14 and 5 consensus sequences generated from distinct groups of the S and M proteins, respectively. ELISA testing predicted peptides with PEDV-positive sera revealed 9 novel immunodominant epitopes on the S protein. Importantly, 7 of these novel immunodominant epitopes and other subdominant epitopes were demonstrated to be neutralizing epitopes by neutralization-inhibition assay. Additionally, our study shows the first time that M protein is also the target of neutralizing antibodies as 7 neutralizing epitopes in the M protein were identified. Conservancy analysis revealed that epitopes in the S1 subunit are more variable than those in the S2 subunit and M protein. In this study, we offer the immunoinformatics approach for linear B cell epitope identification and a more complete profile of linear B cell epitopes across the PEDV S and M proteins, which may contribute to the development of a greater PEDV vaccine as well as peptide-based immunoassays.

category: immunology


title: Transcript accumulation rates in the early  C. elegans  embryo

abstract: Dynamic changes in transcription are widespread in the developing embryo, where cell cycles are rapid and cell fate decisions sometimes need to be made quickly, before the next cell division. In the early Caenorhabditis elegans embryo, specification of the intestine relies on high absolute levels of transcription factors that are a part of the gut gene regulatory network. These absolute levels are likely achieved by controlled transcript accumulation rates. However, accumulation rates have not been measured globally in the worm embryo. We used single cell RNA-seq data from the early C. elegans embryo to estimate the accumulation rates of zygotic genes up to the 24-cell stage. We find that rapid transcript accumulation is a characteristic feature of transcription factors across different cell types and lineages. We identified genomic features associated with high transcription rates and core promoter motifs that might drive these rates. For one Very High-rate gene ceh-51, which is required for mesoderm development, we measured the contributions of core promoter elements to rate. We find that each of these motifs contribute modestly to the accumulation rate of ceh-51, suggesting a complex relationship between promoter motifs and gene structure in controlling transcript accumulation rates. These results are a step towards understanding the regulation of transcript accumulation rates during embryonic cell fate specification.

category: developmental biology


title: Transcriptomic, epigenetic and metabolic characterization of the pluripotency continuum in rabbit preimplantation embryos

abstract:
Despite the growing interest in the rabbit model for developmental and stem cell biology, the characterization of embryos at the molecular level is still poorly documented. We conducted a transcriptome analysis of rabbit pre-implantation embryos from E2.7 (morula stage) to E6.6 (early primitive streak stage) using bulk and single-cell RNA-sequencing. In parallel, we studied oxidative phosphorylation and glycolysis and analysed active and repressive epigenetic modifications during blastocyst formation and expansion. We generated a transcriptomic, epigenetic, and metabolic map of the pluripotency continuum in rabbit preimplantation embryos and identified novel markers of naive pluripotency that might be instrumental for deriving naive pluripotent stem cell lines. Although the rabbit is evolutionarily closer to mice than to primates, we found that the transcriptome of rabbit epiblast cells shares common features with that of humans and non-human primates.

Summary StatementRabbit preimplantation embryos share characteristics with human and monkey embryos with respect to timing of early lineage segregation and expression of marker genes for naive and primed pluripotency.


title: Major transcriptomic, epigenetic and metabolic changes underly the pluripotency continuum in rabbit preimplantation embryos


title: Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features

abstract: Tumor tissue of origin (TOO) is an important factor for guiding treatment decisions. However, TOO cannot be determined for ~3% of metastatic cancer patients and are categorized as cancers of unknown primary (CUP). As whole genome sequencing (WGS) of tumors is now transitioning from the research domain to diagnostic practice in order to address the increasing demand for biomarker detection, its use for detection of TOO in routine diagnostics also starts becoming within reach. While proof of concept for the use of genome-wide features has been demonstrated before, more complex WGS mutation features, including structural variant (SV) driver and passenger events, have never been integrated into TOO-classifiers even though they bear highly characteristic links with tumor TOO. Using a uniformly processed dataset containing 6820 whole-genome sequenced primary and metastatic tumors, we have developed Cancer of Unknown Primary Location Resolver (CUPLR), a random forest based TOO classifier that employs 502 features based on simple and complex somatic driver and passenger mutations. Our model is able to distinguish 33 cancer (sub)types with an overall accuracy of 91% and 89% based on cross-validation (n=6139) and hold out set (n=681) predictions respectively. We found that SV derived features increase the accuracy and utility of TOO classification for specific cancer types. To ensure that predictions are human-interpretable and suited for use in routine diagnostics, CUPLR reports the top contributing features and their values compared to cohort averages. The comprehensive output of CUPLR is complementary to existing histopathological procedures and may thus improve diagnostics for patients with CUP.

category: genomics


title: DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of enhancers

abstract: Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood and enhancer de novo design is considered impossible. Here we built a deep learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence in Drosophila melanogaster S2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally non-equivalent instances of the same TF motif that are determined by motif-flanking sequence and inter-motif distances. We validated these rules experimentally and demonstrated their conservation in human by testing more than 40,000 wildtype and mutant Drosophila and human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activities de novo.


title: Silencing XIST on the future active X: Searching human and bovine preimplantation embryos for the repressor

abstract: X inactivation is the means of equalizing the dosage of X chromosomal genes in male and female eutherian mammals, so that only one X is active in each cell. The XIST locus (in cis) on each additional X chromosome initiates the transcriptional silencing of that chromosome, making it an inactive X. How the active X in both males and females is protected from inactivation by its own XIST locus is not well understood in any mammal. Previous studies of autosomal duplications suggest that gene(s) on the short arm of human chromosome 19 repress XIST function on the active X. Here, we examine the time of transcription of some candidate genes in preimplantation embryos using single-cell RNA sequencing data from human embryos and qRT-PCR from bovine embryos. The candidate genes assayed are those transcribed from 19p13.3-13.2, which are widely expressed and can remodel chromatin. Our results confirm that XIST is expressed at low levels from the future active X in embryos of both sexes; they also show that the XIST locus is repressed in both sexes when pluripotency factors are being upregulated, during the 4-8 cell and morula stages in human and bovine embryos - well before the early blastocyst (E5) when XIST on the inactive X in females begins to be upregulated. Our data suggest a role for DNMT1, UHRF1, SAFB and SAFB2 in XIST repression; they also exclude XACT and other 19p candidate genes and provide the transcriptional timing for some genes not previously assayed in human or bovine preimplantation embryos.


title: At a snail's pace: the influence of habitat disturbance on terrestrial snail movement using experimentally manipulated mesocosms

abstract: The Anthropocene marks great changes to environments and the animals that inhabit them. Changes, such as disturbance, can affect the manner in which animals interact with their environments, such as moving and selecting habitats. To test how animals might respond to changing disturbance regimes, we employ an experimental approach to movement ecology. We used integrated step selection analysis (iSSA) to test the behavioural responses of individually-marked grove snails (Cepaea nemoralis) exposed to a gradient of physical disturbance in their habitat. We used a before-after control-impact (BACI) experimental design within semi-controlled mesocosms to manipulate edge and disturbance variables by altering the area of the mesocosm covered by bricks. We showed that grove snails perceive edges of enclosures and edges of bricks as risks, and responded to such risks by altering their movement. Grove snails displayed a bimodal response to risk by taking shelter in place or moving faster to be farther from the disturbance. Furthermore, individuals tended to modulate their behavioural response to the degree of risk. Our study highlights the usefulness of experimental mesocosms in movement ecology and in determining the effects of habitat alteration and human-imposed risk on movement behaviour.

category: animal behavior and cognition


title: The effects of age, sex, weight and breed on canid methylomes

abstract: Unlike genomes, which are static throughout the lifespan of an organism, DNA methylomes are dynamic. To study these dynamics we developed quantitative models that measure the effect of multiple factors on DNA methylomes including, age, sex, weight and genetics. We conducted our study in canids, which prove to be an ideal species to assess epigenetic moderators due to their extreme variability in size and well-characterized genetic structure. We collected buccal swabs from 217 canids (207 domestic dogs and 10 gray wolves) and used targeted bisulfite sequencing to measure methylomes. We also measured genotypes at over one thousand single nucleotide polymorphisms (SNPs). We found that DNA methylomes are strongly associated with age, enabling the construction of epigenetic clocks. We also show that methylomes are strongly impacted by sex, weight and sterilization status, leading to accurate predators of these factors. Methylomes are also affected by genetics and we observe multiple associations between SNP loci and methylated CpGs. Finally, we show that several factors moderate the relationship between epigenetic ages and real ages, such as body weight, which increases epigenetic aging. In conclusion, we demonstrate that the plasticity of DNA methylomes is impacted by myriad genetic and physiological factors, and that DNA methylation biomarkers are accurate predictors of age, sex and sterilization status.

category: bioinformatics


title: Memory mapped parallel BAM file access API for high throughput sequence analysis informatics

abstract: In precision medicine, genomic data needs to be processed as fast as possible to arrive at treatment decisions in a timely fashion. We developed mmbam, a library to allow sequence analysis informatics software to access raw sequencing data stored in BAM files extremely fast. Taking advantage of memory mapped file access and parallel data processing, we demonstrate that analysis software ported to mmbam consistently outperforms their stock versions. Open source and freely available, we envision that mmbam will enable a new generation of high-performance informatics tools for precision medicine.


title: Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data

abstract: Many disease-associated genomic variants disrupt gene function through abnormal splicing. With the advancement of genomic medicine, identifying disease-associated splicing associated variants has become more important than ever. Most bioinformatics approaches to detect splicing associated variants require both genome and transcriptomic data. However, there are not many datasets where both of them are available. In this study, we developed a methodology to detect genomic variants that cause splicing changes (more specifically, intron retention), using transcriptome sequencing data alone. After demonstrating its high sensitivity and precision, we have applied it to 230,988 transcriptome sequencing data from the publicly available repository and identified 27,937 intron retention associated variants (IRAVs). In addition, by exploring positional relationships with variants registered in existing disease databases, we extracted 3,077 putative disease-associated IRAVs, which range from cancer drivers to variants linked with autosomal recessive disorders. The new in-silico screening framework proposed here provides a foundation for a platform that can automatically acquire medical knowledge making the most of massively accumulated publicly available sequencing data. Collections of IRAVs identified in this study are available through IRAVDB (https://iravdb.io/).


title: A Probabilistic Approach For Registration Of Multi-Modal Spatial Transcriptomics Data

abstract: Observing the spatial characteristics of gene expression by image-based spatial transcriptomics technology allows studying gene activity across different cells and intracellular structures. We present a probabilistic approach for the registration and analysis of transcriptome images and immunostaining images. The method is based on particle filters and jointly exploits intensity information and image features. We applied our approach to synthetic data as well as real transcriptome images and immunostaining microscopy images of the mouse brain. It turns out that our approach accurately registers the multi-modal images and yields better results than a state-of-the-art method.


title: Fast and compact matching statistics analytics

abstract:
MotivationFast, lightweight methods for comparing the sequence of ever larger assembled genomes from ever growing databases are increasingly needed in the era of accurate long reads and pan-genome initiatives. Matching statistics is a popular method for computing whole-genome phylogenies and for detecting structural rearrangements between two genomes, since it is amenable to fast implementations that require a minimal setup of data structures. However, current implementations use a single core, take too much memory to represent the result, and do not provide efficient ways to analyze the output in order to explore local similarities between the sequences.

ResultsWe develop practical tools for computing matching statistics between large-scale strings, and for analyzing its values, faster and using less memory than the state of the art. Specifically, we design a parallel algorithm for shared-memory machines that computes matching statistics 30 times faster with 48 cores in the cases that are most difficult to parallelize. We design a lossy compression scheme that shrinks the matching statistics array to a bitvector that takes from 0.8 to 0.2 bits per character, depending on the dataset and on the value of a threshold, and that achieves 0.04 bits per character in some variants. And we provide efficient implementations of range-maximum and range-sum queries that take a few tens of milliseconds while operating on our compact representations, and that allow computing key local statistics about the similarity between two strings. Our toolkit makes construction, storage, and analysis of matching statistics arrays practical for multiple pairs of the largest genomes available today, possibly enabling new applications in comparative genomics.

Availability ad implementationOur C/C++ code is available at https://github.com/odenas/indexed_ms under GPL-3.0.


title: A model for the intrinsic limit of cancer therapy: duality of treatment-induced cell death and treatment-induced stemness

abstract: AO_SCPLOWBSTRACTC_SCPLOWIntratumor cellular heterogeneity and non-genetic cell plasticity in tumors pose a recently recognized challenge to cancer treatment. Because of the dispersion of initial cell states within a clonal tumor cell population, a perturbation imparted by a cytocidal drug only kills a fraction of cells. Due to dynamic instability of cellular states the cells not killed are pushed by the treatment into a variety of functional states, including a "stem-like state" that confers resistance to treatment and regenerative capacity. This immanent stress-induced stemness competes against cell death in response to the same perturbation and may explain the near-inevitable recurrence after any treatment. This double-edged-sword mechanism of treatment complements the selection of preexisting resistant cells in explaining post-treatment progression. Unlike selection, the induction of a resistant state has not been systematically analyzed as an immanent cause of relapse. Here, we present a generic elementary model and analytical examination of this intrinsic limitation to therapy. We show how the relative proclivity towards cell death versus transition into a stem-like state, as a function of drug dose, establishes either a window of opportunity for containing tumors or the inevitability of progression following therapy. The model considers measurable cell behaviors independent of specific molecular pathways and provides a new theoretical framework for optimizing therapy dosing and scheduling as cancer treatment paradigms move from "maximal tolerated dose," which may promote therapy induced-stemness, to repeated "minimally effective doses" (as in adaptive therapies), which contain the tumor and avoid therapy-induced progression.

category: cancer biology


title: Metabolic regulation inferred from Jacobian and Hessian matrices of metabolic functions

abstract: Quantitative analysis of experimental metabolic data is frequently challenged by non-intuitive, complex patterns which emerge from regulatory networks. Quantitative output of metabolic regulation can be summarised by metabolic functions which comprise information about dynamics of metabolite concentrations. They reflect the sum of biochemical reactions which affect a metabolite concentration. Derivatives of metabolic functions provide essential information about system dynamics. The Jacobian matrix of a reaction network summarises first-order partial derivatives of metabolic functions with respect to metabolite concentrations while Hessian matrices summarise second-order partial derivatives. Here, a simple model of invertase-driven sucrose hydrolysis is simulated and both Jacobian and Hessian matrices of metabolic functions are derived for quantitative analysis of kinetic regulation of sucrose metabolism. Based on previous experimental observations, metabolite dynamics are quantitatively explained in context of underlying metabolic functions. Their potential regulatory role during plant cold acclimation is derived from Jacobian and Hessian matrices.

category: systems biology


title: Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain

abstract:
Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole-brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultrahigh field fMRI performed at 10.5 Tesla to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we extended existing electrophysiological hierarchies to whole brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Further, with these results in hand, we were able to show that one facet of the high-dimensional functional connectivity topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match functional connectivity gradient topographies across the whole brain. We conclude that intrinsic timescales are a unifying organizational principle of neural processing across the whole brain.

Declaration of InterestsThe authors declare no competing interests.


title: Antiviral CD19+CD27+ Memory B Cells Are Associated with Protection from Recurrent Asymptomatic Ocular Herpes Infection

abstract:
Reactivation of herpes simplex virus 1 (HSV-1) from latently infected neurons of the trigeminal ganglia (TG) leads to blinding recurrent herpetic disease in symptomatic (SYMP) individuals. Although the role of T cells in herpes immunity seen in asymptomatic (ASYMP) individuals is heavily explored, the role of B cells is less investigated. In the present study, we evaluated whether B cells are associated with protective immunity against recurrent ocular herpes. The frequencies of circulating HSV-specific memory B cells and of memory follicular helper T cells (CD4+ Tfh cells), that help B cells produce antibodies, were compared between HSV-1 infected SYMP and ASYMP individuals. The levels of IgG/IgA and neutralizing antibodies were compared in SYMP and ASYMP individuals. We found that: (i) the ASYMP individuals had increased frequencies of HSV-specific CD19+CD27+ memory B cells; and (ii) high frequencies of HSV-specific switched IgG+CD19+CD27+ memory B cells detected in ASYMP individuals were directly proportional to high frequencies of CD45R0+CXCR5+CD4+ memory Tfh cells. However, no differences were detected in the level of HSV-specific IgG/IgA antibodies in SYMP and ASYMP individuals. Using the UV-B-induced HSV-1 reactivation mouse model, we found increased frequencies of HSV-specific antibody-secreting plasma HSV-1 gD+CD138+ B cells within the TG and circulation of ASYMP mice compared to SYMP mice. In contrast, no significant differences in the frequencies of B cells were found in the cornea, spleen, and bone-marrow. Our findings suggest that circulating antibody-producing HSV-specific memory B cells recruited locally to the TG may contribute to protection from symptomatic recurrent ocular herpes.

IMPORTANCEReactivation of herpes simplex virus 1 (HSV-1) from latently infected neurons of the trigeminal ganglia (TG) leads to blinding recurrent herpetic disease in symptomatic (SYMP) individuals. Although the role of T cells in herpes immunity against blinding recurrent herpetic disease is heavily explored, the role of B cells is less investigated. In the present study, we found that in both asymptomatic (ASYMP) individuals and ASYMP mice there was increased frequencies of HSV-specific memory B cells that were directly proportional to high frequencies of memory Tfh cells. Moreover, following UV-B induce reactivation, we found increased frequencies of HSV-specific antibody-secreting plasma B cells within the TG and circulation of ASYMP mice, compared to SYMP mice. Our findings suggest that circulating antibody-producing HSV-specific memory B cells recruited locally to the TG may contribute to protection from recurrent ocular herpes.


title: The Evolution of Larger Size in High Altitude Drosophila melanogaster has a Polymorphic Genetic Architecture

abstract:
Important uncertainties persist regarding the genetic architecture of adaptive trait evolution in natural populations, including the number of genetic variants involved, whether they are drawn from standing genetic variation, and whether directional selection drives them to complete fixation. Here, we take advantage of a unique natural population of Drosophila melanogaster from the Ethiopian highlands, which has evolved larger body size than any other known population of this species. We apply a bulk segregant quantitative trait locus (QTL) mapping approach to four unique crosses between highland Ethiopian and lowland Zambian populations for both thorax length and wing length. Results indicated a persistently variable genetic basis for these evolved traits (with largely distinct sets of QTLs for each cross), and at least a moderately polygenic architecture with relatively strong effects present. We complemented these mapping experiments with population genetic analyses of QTL regions and gene ontology enrichment analysis, generating strong hypotheses for specific genes and functional processes that may have contributed to these adaptive trait changes.

Finally, we find that the genetic architectures our QTL mapping results for size traits mirror those from similar experiments on other recently-evolved traits in this species. Collectively, these studies suggest a recurring pattern of polygenic adaptation in this species, in which causative variants do not approach fixation and moderately strong effect loci are present.

category: evolutionary biology


title: The role of evolutionary modes for trait-based cascades in mutualistic networks

abstract: The erosion of functional diversity may foster the collapse of ecological systems. Functional diversity is ultimately defined by the distribution of species traits and, as species traits are a legacy of species evolutionary history, one might expect that the mode of trait evolution influence community resistance under the loss of functional diversity. In this paper, we investigate the role of trait evolutionary dynamics on the robustness of mutualistic networks undergoing the following scenarios of species loss: i) random extinctions, ii) loss of functional distinctiveness and iii) biased towards larger trait values. We simulated networks defined by models of single trait complementary and evolutionary modes where traits can arise in recent diversification events with weak phylogenetic signal, in early diversification events with strong phylogenetic signal, or as a random walk through evolutionary time. Our simulations show that mutualistic networks are especially vulnerable to extinctions based on trait distinctiveness and more robust to random extinction dynamics. The networks show intermediate level of robustness against size-based extinctions. Despite the small range of variation in network robustness, our results show that the mode of trait evolution matters for network robustness in all three scenarios. Networks with low phylogenetic signal are more robust than networks with high phylogenetic signal across all scenarios. As a consequence, our results predict that mutualistic networks based upon current adaptations are more likely to cope with extinction dynamics than those networks that are based upon conserved traits.

category: ecology


title: Green fluorescent protein-like pigments optimize the internal light environment in symbiotic reef building corals

abstract: Pigments homologous to the Green Fluorescent Protein (GFP) have been proposed to fine-tune the internal light microclimate of corals, facilitating photoacclimation of photosynthetic coral symbionts (Symbiodiniaceae) to life in different reef habitats and environmental conditions. However, direct measurements of the in vivo light conditions inside the coral tissue supporting this conclusion are lacking. Here, we quantified the intra-tissue spectral light environment of corals expressing GFP-like proteins from widely different light regimes. We focus on (1) photoconvertible red fluorescent proteins (pcRFPs), thought to enhance photosynthesis in mesophotic habitats via wavelength conversion, and (2) chromoproteins (CPs), which provide photoprotection to the symbionts in shallow water via light absorption. Optical microsensor measurements indicated that both pigment groups strongly alter the coral tissue light environment. Estimates derived from light spectra measured in pcRFP-containing corals showed that fluorescence emission can contribute to >50% of orange-red light available to the photosynthetic symbionts at mesophotic depths. We further show that upregulation of pink CPs in shallow-water corals during bleaching leads to a reduction of orange light by 10-20% compared to low-CP tissue. Thus, screening by CPs has an important role in mitigating the light-enhancing effect of coral tissue scattering during bleaching. Our results provide the first experimental quantification of the importance of GFP-like proteins in fine-tuning the light microclimate of corals during photoacclimation.


title: Genetic determinants of antibiotic resistance and the evolution of trade-offs during adaptation in a single patient

abstract: The processes by which pathogens evolve within single hosts dictate the efficacy of treatment strategies designed to slow antibiotic resistance evolution and influence the population-wide resistance levels. The aim of this study is to describe the underlying genetic and phenotypic changes leading to antibiotic resistance within a single patient who died as resistance evolved to available antibiotics. We assess whether robust patterns of collateral sensitivity and response to combinations exist that might have been leveraged to improve therapy. Whole-genome sequencing was completed for nine isolates taken from this patient over 279 days of chronic infection with Enterobacter hormaechei, along with systematic measurements of changes in resistance against five of the most relevant drugs considered for treatment. The entirety of the genetic change is consistent with de novo mutations and plasmid loss events, without the acquisition of foreign genetic material via horizontal gene transfer. The isolates formed three genetically distinct lineages, with early evolutionary trajectories being supplanted by previously unobserved multi-step evolutionary trajectories. Importantly, no single isolate evolved resistance to all of the antibiotics considered for treatment against E. hormaechei (i.e., none was pan-resistant). Patterns of collateral sensitivity and response to combination therapy revealed contrasting patterns across this diversifying population. Translating antibiotic resistance management strategies from theoretical and laboratory data to clinical situations, such as this, may require managing diverse populations with unpredictable resistance trajectories.


title: The protein folding rate and the geometry and topology of the native state

abstract: Proteins fold in 3-dimensional conformations which are important for their function. Characterizing the global conformation of proteins rigorously and separating secondary structure effects from topological effects is a challenge. New developments in Applied Knot Theory allow to characterize the topological characteristics of proteins (knotted or not). By analyzing a small set of two-state and multi-state proteins with no knots or slipknots, our results show that 95.4% of the analyzed proteins have non-trivial topological characteristics, as reflected by the second Vassiliev measure, and that the logarithm of the experimental protein folding rate depends on both the local geometry and the topology of the proteins native state.


title: Tracking the fates of iron-labeled tumor cells in vivo using Magnetic Particle Imaging

abstract: The use of imaging to detect and monitor the movement and accumulation of cells in living subjects can provide significant insights that can improve our understanding of metastasis and guide therapeutic development. For cell tracking using Magnetic Resonance Imaging (MRI), cells are labeled with iron oxides and the effects of the iron on water provides contrast. However, due to low specificity and difficulties in quantification with MRI, other modalities and approaches need to be developed. Magnetic Particle Imaging (MPI) is an emerging imaging technique which directly detects magnetic iron, allowing for a specific, quantitative and sensitive readout. Here, we use MPI to image iron-labeled tumor cells longitudinally, from implantation and growth at a primary site to movement to distant anatomic sites. In vivo bioluminescent imaging (BLI) was used to localize tumor metastases and computed tomography (CT) allowed for correlation of these signals to anatomic locations. These three imaging modalities provide information on immune escape and metastasis of iron-labeled, and unlabeled, tumor cells, and the accumulation of cell-free iron contrast over time. We identified iron signals by MPI and tumor cells via BLI, and correlated these positive contrast images with CT scans to reveal the anatomic sites with cancer cells; histologic analysis confirmed the presence of iron-labeled tumor cells in the tissues, suggesting that the metastatic cells retained enough iron for MPI detection. The use of multi-modality cell tracking reveals the movement, accumulation and fates of labeled cells that will be helpful understanding cancer progression and guiding the development of targeted therapies.

category: biophysics


title: Global Dynamics as Communication Sensors in Peptide Synthetase Cyclization Domains.

abstract: Structural biology is the foundation for deriving molecular mechanisms, where snapshots of macromolecules and binding partners inform on mutations that test or modify function. However, frequently, the impact of mutations violates the underpinnings of structural models, and mechanisms become cryptic. This conundrum applies to multidomain enzymatic systems called nonribosomal peptide synthetases (NRPSs), which assemble simple substrates into complex metabolites often with pharmaceutical properties. Engineering NRPSs can generate new pharmaceuticals1-3 but a dynamic domain organization challenges rational design.4-8 Using nuclear magnetic resonance (NMR), we determined the solution structure of a 52 kDa cyclization domain and demonstrate that global intra-domain dynamics enable sensing of substrates tethered to partner domains and draw an allosteric response encompassing the enzymes buried active site and two binding sites 40 [A] apart. We show that a point-site mutation that impedes the domain dynamics globally hampers the allosteric response. We demonstrate this mechanism through NMR experiments that provide atomic-level read-outs of allosteric responses during biochemical transformations in situ. Our results establish global structural dynamics as sensors of molecular events that can remodel domain interactions and illustrate the need for integrating structural dynamics explicitly when deriving molecular mechanisms through mutagenesis and structural biology.


title: Uncovering expression signatures of synergistic drug response using an ensemble of explainable AI models

abstract: Complex machine learning models are poised to revolutionize the treatment of diseases like acute myeloid leukemia (AML) by helping physicians choose optimal combinations of anti-cancer drugs based on molecular features. While accurate predictions are important, it is equally important to be able to learn about the underlying molecular basis of anti-cancer drug synergy. Explainable AI (XAI) offers a promising new route for data-driven cancer pharmacology, combining highly accurate models with interpretable insights into model decisions. Due to the highly correlated, high-dimensional nature of cancer transcriptomic data, however, we find that existing XAI approaches are suboptimal when applied naively to large transcriptomic datasets. We show how a novel approach based on model ensembling helps to increase the quality of explanations. We then use our method to demonstrate that a hematopoietic differentiation signature underlies synergy for a variety of anti-AML drug combinations.


title: Differential geometry methods for constructing manifold-targeted recurrent neural networks.

abstract: Neural computations can be framed as dynamical processes, whereby the structure of the dynamics within a neural network are a direct reflection of the computations that the network performs. A key step in generating mechanistic interpretations within this computation through dynamics framework is to establish the link between network connectivity, dynamics and computation. This link is only partly understood. Recent work has focused on producing algorithms for engineering artificial recurrent neural networks (RNN) with dynamics targeted to a specific goal manifold. Some of these algorithms only require a set of vectors tangent to the target manifold to be computed, and thus provide a general method that can be applied to a diverse set of problems. Nevertheless, computing such vectors for an arbitrary manifold in a high dimensional state space remains highly challenging, which in practice limits the applicability of this approach. Here we demonstrate how topology and differential geometry can be leveraged to simplify this task, by first computing tangent vectors on a low-dimensional topological manifold and then embedding these in state space. The simplicity of this procedure greatly facilitates the creation of manifold-targeted RNNs, as well as the process of designing task-solving on-manifold dynamics. This new method should enable the application of network engineering-based approaches to a wide set of problems in neuroscience and machine learning. Furthermore, our description of how fundamental concepts from differential geometry can be mapped onto different aspects of neural dynamics is a further demonstration of how the language of differential geometry can enrich the conceptual framework for describing neural dynamics and computation.


title: Geosmin suppresses defensive behaviour and elicits unusual neural responses in honey bees.

abstract: Geosmin is an odorant produced by bacteria in moist soil. It has been found to be extraordinarily relevant to some insects, but the reasons for this are not yet fully understood. Here we report the first tests of the effect of geosmin on honey bees. A stinging assay showed that the defensive behaviour elicited by the bees alarm pheromone is strongly suppressed by geosmin. Surprisingly, the suppression is, however, only present at very low geosmin concentrations, and completely disappears at higher concentrations. We investigated the underlying mechanisms of the behavioural change at the level of the olfactory receptor neurons by means of electroantennography and at the level of the antennal lobe output via calcium imaging. Unusual effects were observed at both levels. The responses of the olfactory receptor neurons to mixtures of geosmin and the alarm pheromone component isoamyl acetate (IAA) were lower than to pure IAA, suggesting an interaction of both compounds at the olfactory receptor level. In the antennal lobe, the neuronal representation of geosmin showed a glomerular activation that decreased with increasing concentration, correlating well with the concentration dependence of the behaviour. Computational modelling of odour transduction and odour coding in the antennal lobe suggests that a broader than usual activation of different olfactory receptor types by geosmin in combination with lateral inhibition in the antennal lobe could lead to the observed non-monotonic increasing-decreasing responses to geosmin and thus underlie the specificity of the behavioural response to low geosmin concentrations.


title: NFkB-signaling suppresses Müller glia-mediated neuron regeneration in the mammalian retina

abstract: Muller glia (MG) in mammalian retinas are incapable of regenerating neurons after damage, whereas the MG in lower vertebrates regenerate functional neurons. Identification networks that regulate MG-mediated regeneration is key to harnessing the regenerative potential of MG. Here we study how NFkB-signaling influences glial responses to damage and reprogramming of MG into neurons in the rodent retina. We find activation of NFkB and dynamic expression of NFkB-associated genes in MG after damage, however NFkB activity is inhibited by microglia ablation. Knockout of NFkB in MG suppressed the accumulation of immune cells after damage. Inhibition of NFkB following NMDA-damage significantly enhanced the reprogramming of Ascl1-overexpressing MG into neuron-like cells. scRNA-seq of retinal glia following inhibition of NFkB reveals coordination with signaling via TGF{beta}2 and suppression of NFI and Id transcription factors. Inhibition of Smad3 or Id transcription factors increased numbers of neuron-like cells produced by Ascl1-overexpressing MG. We conclude that NFkB is a key signaling hub that is activated in MG after damage, mediates the accumulation of immune cells, and suppresses the neurogenic potential of MG.


title: Developmental cell death of cortical projection neurons is controlled by a Bcl11a/Bcl6-dependent pathway

abstract: Developmental neuron death plays a pivotal role in refining organization and wiring during neocortex formation. Aberrant regulation of this process results in neurodevelopmental disorders including impaired learning and memory. Underlying molecular pathways are incompletely determined. Loss of Bcl11a in cortical projection neurons induces pronounced cell death in upper-layer cortical projection neurons during postnatal corticogenesis. We used this genetic model to explore genetic mechanisms by which developmental neuron death is controlled. Unexpectedly, we found Bcl6, previously shown to be involved in transition of cortical neurons from progenitor to postmitotic differentiation state to provide a major check point regulating neuron survival during late cortical development. We show that Bcl11a is a direct transcriptional regulator of Bcl6. Deletion of Bcl6 exerts death of cortical projection neurons. In turn, reintroduction of Bcl6 into Bcl11a mutants prevents induction of cell death in these neurons. Together, our data identify a novel Bcl11a/Bcl6-dependent molecular pathway in regulation of developmental cell death during corticogenesis.


title: Comprehensive characterization of the antibody responses to SARS-CoV-2 Spike protein after infection and/or vaccination

abstract:
BackgroundControl of the COVID-19 pandemic will rely on SARS-CoV-2 vaccine-elicited antibodies to protect against emerging and future variants; an understanding of the unique features of the humoral responses to infection and vaccination, including different vaccine platforms, is needed to achieve this goal.

MethodsThe epitopes and pathways of escape for Spike-specific antibodies in individuals with diverse infection and vaccination history were profiled using Phage-DMS. Principal component analysis was performed to identify regions of antibody binding along the Spike protein that differentiate the samples from one another. Within these epitope regions we determined potential escape mutations by comparing antibody binding of peptides containing wildtype residues versus peptides containing a mutant residue.

ResultsIndividuals with mild infection had antibodies that bound to epitopes in the S2 subunit within the fusion peptide and heptad-repeat regions, whereas vaccinated individuals had antibodies that additionally bound to epitopes in the N- and C-terminal domains of the S1 subunit, a pattern that was also observed in individuals with severe disease due to infection. Epitope binding appeared to change over time after vaccination, but other covariates such as mRNA vaccine dose, mRNA vaccine type, and age did not affect antibody binding to these epitopes. Vaccination induced a relatively uniform escape profile across individuals for some epitopes, whereas there was much more variation in escape pathways in in mildly infected individuals. In the case of antibodies targeting the fusion peptide region, which was a common response to both infection and vaccination, the escape profile after infection was not altered by subsequent vaccination.

ConclusionsThe finding that SARS-CoV-2 mRNA vaccination resulted in binding to additional epitopes beyond what was seen after infection suggests protection could vary depending on the route of exposure to Spike antigen. The relatively conserved escape pathways to vaccine-induced antibodies relative to infection-induced antibodies suggests that if escape variants emerge, they may be readily selected for across vaccinated individuals. Given that the majority of people will be first exposed to Spike via vaccination and not infection, this work has implications for predicting the selection of immune escape variants at a population level.

FundingThis work was supported by NIH grants AI138709 (PI Overbaugh) and AI146028 (PI Matsen). Julie Overbaugh received support as the Endowed Chair for Graduate Education (FHCRC). The research of Frederick Matsen was supported in part by a Faculty Scholar grant from the Howard Hughes Medical Institute and the Simons Foundation. Scientific Computing Infrastructure at Fred Hutch was funded by ORIP grant S10OD028685.


title: Evaluation of flow cytometry for cell count and detection of bacteria in biological fluids.

abstract: The analysis of biological fluids is crucial for the diagnosis and monitoring of diseases causing effusions and helps in the diagnosis of infectious diseases. The gold standard method for cell count in biological fluids is the manual method using counting chambers. The microbiological routine procedures consist of Direct Gram staining and culture on solid or liquid media. We evaluate the analytical performance of SYSMEX UF4000 (Sysmex, Kobe, Japan) and Sysmex XN10 (Sysmex, Kobe, Japan) in comparison with cytological and microbiological routine procedures. A total of 526 biological fluid samples were included in this study (42 ascitic, 31 pleural, 31 peritoneal, 125 cerebrospinal, 281 synovial, and 16 peritoneal dialysis fluids). All samples were analysed by flow cytometry and subsequently processed following cytological and/or microbiological routine procedures. With regards to cell counts, UF4000 (Sysmex, Kobe, Japan) showed a performance which was at least equivalent to those of the reference methods and superior to those of XN10 (Sysmex, Kobe, Japan). Moreover, the bacterial count obtained with UF4000 (Sysmex, Kobe, Japan) was significantly higher among culture or Direct Gram stain positive samples. We established 3 optimal cut-off points to predict Direct Gram stain positive samples for peritoneal (465.0 bacteria/L), synovial (1200.0 bacteria/L), and cerebrospinal fluids (17.2 bacteria/L) with maximum sensitivity and negative predictive values. Cell count and detection of bacteria by flow cytometry could be used upstream cytological and microbiological routine procedures to improve and accelerate the diagnosis of infection of biological fluid samples.

category: microbiology


title: Ligands with poly-fluorophenyl moieties promote a local structural rearrangement in the Spinach2 and Broccoli aptamers that increases ligand affinities

abstract: The interaction of nucleic acids with their molecular targets often involves structural reorganization that may traverse a complex folding landscape. With the more recent recognition that many RNAs, both coding and noncoding, may regulate cellular activities by interacting with target molecules, it becomes increasingly important to understand the means by which nucleic acids interact with their targets and how drugs might be developed that can influence critical folding transitions. We have extensively investigated the interaction of the Spinach2 and Broccoli aptamers with a library of small molecule ligands modified by various extensions from the imido nitrogen of DFHBI (3,5-difluoro-4-hydroxybenzylidene imidazolinone) that reach out from the Spinach2 ligand binding pocket. Studies of the interaction of these compounds with the aptamers revealed that poly-fluorophenyl-modified ligands initiate a slow change in aptamer affinity that takes an extended time (half-life of ~40 min) to achieve. The change in affinity appears to involve an initial disruption of the entrance to the ligand binding pocket followed by a gradual lockdown for which the most likely driving force is an interaction of the gateway adenine with a nearby 2OH group. These results suggest that poly-fluorophenyl modifications might increase the ability of small molecule drugs to disrupt local structure and promote RNA remodeling.

category: molecular biology


title: Proteome-wide landscape of solubility limits in a bacterial cell

abstract: Proteins are prone to aggregate when they are expressed above their solubility limits, a phenomenon termed supersaturation. Aggregation may occur as proteins emerge from the ribosome or after they fold and accumulate in the cell, but the relative importance of these two routes remain poorly known. Here, we systematically probed the solubility limits of each Escherichia coli protein upon overexpression using an image-based screen coupled with machine learning. The analysis suggests that competition between folding and aggregation from the unfolded state governs the two aggregation routes. Remarkably, the majority (70%) of insoluble proteins have low supersaturation risks in their unfolded states and rather aggregate after folding. Furthermore, a substantial fraction ([~]35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our proteome-wide study provides empirical insights into the molecular determinants of protein aggregation routes in a bacterial cell.


title: Fluorescence exclusion: a rapid, accurate and powerful method for measuring yeast cell volume

abstract:
Cells exist in an astonishing range of volumes across and within species. However, our understanding of cell size control remains limited, due in large part to the challenges associated with accurate determination of cell volume. Much of our comprehension of size regulation derives from models such as budding and fission yeast, but even for these morphologically stereotypical cells, assessment of cell volume has relied on proxies and extrapolations from two-dimensional measurements. Recently, the fluorescence exclusion method (FXm) was developed to evaluate the size of mammalian cells, but whether it could be applied to smaller cells remained unknown. Using specifically designed microfluidic chips and an improved data analysis pipeline, we show here that FXm reliably detects subtle difference in the volume of fission yeast cells, even for those with altered shapes. Moreover, it allows for the monitoring of dynamic volume changes at the single-cell level with high time resolution. Collectively, our work reveals how coupling FXm with yeast genetics will bring new insights into the complex biology of cell growth.

SUMMARY STATEMENTFluorescence exclusion provides a unique method to accurately measure the volume of yeast cells at both the population and single-cell levels.

category: cell biology


title: Structure of the stress-related LHCSR1 complex determined by an integrated computational strategy

abstract: Light-harvesting complexes (LHCs) are pigment-protein complexes whose main function is to capture sunlight and transfer the energy to reaction centers of photosystems. In response to varying light conditions, LH complexes also play photoregulation and photoprotection roles. In algae and mosses, a sub-family of LHCs, Light-Harvesting complex stress related (LHCSR), is responsible for photoprotective quenching. Despite their functional and evolutionary importance, no direct structural information on LHCSRs is available that can explain their unique properties. In this work we propose a structural model of LHCSR1 from the moss P. Patens, obtained through an integrated computational strategy that combines homology modeling, molecular dynamics, and multiscale quantum chemical calculations. The model is validated by reproducing the spectral properties of LHCSR1. Our model reveals the structural specificity of LHCSR1, as compared with the CP29 LH complex, and poses the basis for understanding photoprotective quenching in mosses.


title: scatterHatch: an R/Bioconductor package for colorblind accessible visualization of single-cell data

abstract:
SummaryColor is often used as a primary differentiating factor in visualization of single-cell and multi-omics analyses. However, color-based visualizations are extremely limiting and require additional considerations to account for the wide range of color perceptions in the population. The scatterHatch package provides software for accessible single-cell visualizations that use patterns in conjunction with colors to amplify the distinction between different cell types, states, and groups.

AvailabilityscatterHatch is available on Github at https://github.com/FertigLab/scatterHatch.

Contactadeshpande@jhu.edu.

Supplementary informationSupplementary figures are available in the attached document.


title: Tonic inhibition of the chloride/proton antiporter ClC-7 by PI(3,5)P2 is crucial for lysosomal pH maintenance

abstract: The acidic luminal pH of lysosomes, maintained within a narrow range, is essential for proper degrative function of the organelle and is generated by the action of a V-type H+ ATPase, but other pathways for ion movement are required to dissipate the voltage generated by this process. ClC-7, a Cl-/H+ antiporter responsible for lysosomal Cl- permeability, is a candidate to contribute to the acidification process as part of this "counterion pathway". The signaling lipid PI(3,5)P2 modulates lysosomal dynamics, including by regulating lysosomal ion channels, raising the possibility that it could contribute to lysosomal pH regulation. Here we demonstrate that depleting PI(3,5)P2 by inhibiting the PIKfyve kinase causes lysosomal hyperacidification, primarily via an effect on ClC-7. We further show that PI(3,5)P2 directly inhibits ClC-7 transport and that this inhibition is eliminated in a disease-causing gain-of-function ClC-7 mutation. Together these observations suggest an intimate role for ClC-7 in lysosomal pH regulation.


title: The Endosomal pH Regulator NHE9 is a Driver of Stemness in Glioblastoma

abstract:
A small population of self-renewing stem cells initiate tumors and maintain therapeutic resistance in glioblastoma. Given the limited treatment options and dismal prognosis for this disease there is urgent need to identify drivers of stem cells that could be druggable targets. Previous work showed that the endosomal pH regulator NHE9 is upregulated in glioblastoma and correlates with worse survival prognosis. Here, we probed for aberrant signaling pathways in patient-derived glioblastoma cells and found that NHE9 increases cell surface expression and phosphorylation of multiple receptor tyrosine kinases by promoting their escape from lysosomal degradation. Downstream of NHE9-mediated receptor activation, oncogenic signaling pathways converged on the JAK2-STAT3 transduction axis to induce pluripotency genes Oct4 and Nanog and suppress markers of glial differentiation. We used both genetic and chemical approaches to query the role of endosomal pH in glioblastoma phenotypes. Loss-of-function mutations in NHE9 that failed to alkalinize endosomal lumen did not increase self-renewal capacity of gliomaspheres in vitro. However, monensin, a chemical mimetic of Na+/H+ exchanger activity, and the H+ pump inhibitor bafilomycin bypassed NHE9 to directly alkalinize the endosomal lumen resulting in stabilization of receptor tyrosine kinases and induction of Oct4 and Nanog. Using orthotopic models of primary glioblastoma cells we found that NHE9 increased tumor initiation in vivo. We propose that NHE9 initiates inside-out signaling from the endosomal lumen, distinct from the established effects of cytoplasmic and extracellular pH on tumorigenesis. Endosomal pH may be an attractive therapeutic target that diminishes stemness in glioblastoma, agnostic of specific receptor subtype.

SignificanceA well-known hallmark of cancer is excessive acidification of tumor microenvironment, caused by upregulation of Na+/H+ exchanger activity on the cancer cell membrane. However, the role of organellar pH in tumor biology has not been established. This study identifies a mechanistic link between upregulation of the endosomal Na+/H+ exchanger NHE9 and stemness properties in glioblastoma, the most malignant and common brain tumor in adults. By increasing pH of the recycling endosome, NHE9 exerts a broad effect on post-translational stability and activation of multiple receptor tyrosine kinases, leading to increased stem cell-like properties of self-renewal and tumor initiation in glioblastoma models. Our findings suggest that targeting NHE9 or endosomal pH could be an effective strategy for receptor agnostic glioblastoma treatment.


title: Frequency band coupling with high-frequency activities during seizures shifts from θ band in tonic phase to δ band in clonic phase

abstract:
ObjectiveTo clarify variations in the relationship between high-frequency activities (HFAs) and low-frequency bands from the tonic to the clonic phase in focal to bilateral tonic-clonic seizures (FBTCS), using phase-amplitude coupling.

MethodsThis retrospective study enrolled six patients with drug-resistant focal epilepsy who underwent intracranial electrode placement for presurgical invasive electroencephalography at Osaka University Hospital (July 2018-July 2019). We used intracranial electrodes to record seizures in focal epilepsy (11 FBTCS). The magnitude of synchronization index (SIm) and receiver-operating characteristic (ROC) analysis were used to analyze the coupling between HFA amplitude (80-250 Hz) and lower frequencies phase.

ResultsThe {theta} (4-8 Hz)-HFA SIm peaked in the tonic phase, whereas the {delta} (2-4 Hz)-HFA SIm peaked in the clonic phase. ROC analysis indicated that the {delta}-HFA SIm discriminated well the clonic from the tonic phase.

ConclusionsThe main low-frequency band modulating the HFA shifted from the {theta} band in the tonic phase to the {delta} band in the clonic phase.

SignificanceIn FBTCS, low-frequency band coupling with HFA amplitude varies temporally. Especially, the {delta} band is specific to the clonic phase. These results suggest dynamically neurophysiological changes in the thalamus or basal ganglia throughout FBTCS.

HighlightsO_LIThe {theta} band (4-8 Hz) was mainly coupled with high-frequency activity (HFA) in the tonic phase of focal to bilateral tonic-clonic seizures (FBTCS).
C_LIO_LIThe {delta} band (2-4 Hz) was mainly coupled with HFA in the clonic phase of FBTCS.
C_LIO_LIThe magnitude of the synchronization index related to {delta}-HFA phase-amplitude coupling discriminated well the clonic from the tonic phase.
C_LI

category: physiology


title: CHD8-associated gastrointestinal complaints are caused by impaired vagal neural crest development and intestinal homeostatic imbalance

abstract: Gastrointestinal complaints in autism are common and impact the quality of life of affected individuals, yet the underlying mechanisms are understudied. We have found that individuals with mutations in CHD8 present with gastrointestinal disturbances. We have shown that loss of chd8, the sole ortholog of CHD8 in zebrafish, leads to reduced number of enteric neurons and decreased intestinal mobility. However, it remains unclear how chd8 acts during the development of the enteric nervous system and whether CHD8-associated gastrointestinal complaints are solely due to impaired neuronal function in the intestine. Here, utilizing a stable chd8 mutant zebrafish model, we found that the loss of chd8 leads to reduced number of vagal neural crest cells (NCCs), enteric neural progenitors, emigrating from the neural tube and their early migration capability was altered. At later stages, although the intestinal colonization by the NCCs was complete, we found decreased numbers of both NCC-derived serotonergic neurons and serotonin-producing enterochromaffin cells, suggesting an intestinal hyposerotonemia in absence of chd8. Moreover, transcriptomic analyses revealed altered expression of key receptors and enzymes in serotonin and acetylcholine signaling pathways. Next, tissue examination of chd8 mutants revealed thinner intestinal epithelium accompanied by accumulation of neutrophils and decreased numbers of goblet cells and eosinophils. Last, single-cell sequencing of whole mid- and posterior intestines showed a global disruption of the immune balance with perturbed expression of inflammatory interleukins and changes in immune cell clusters. Our findings propose a causal developmental link between chd8, NCC development, intestinal homeostasis, and autism-associated gastrointestinal complaints.


title: Order of arrival promotes coexistence via spatial niche preemption by the weak competitor

abstract: Historical contingency, such as the order of species arrival, can modify competitive outcomes via niche modification or preemption. However, how these mechanisms ultimately modify stabilising niche and average fitness differences remains largely unknown. By experimentally assembling two congeneric spider mite species feeding on tomato plants during two generations, we show that order of arrival affects species competitive ability and changes the outcome of competition. Contrary to expectations, order of arrival did not cause positive frequency dependent priority effects. Instead, coexistence was predicted when the inferior competitor (Tetranychus urticae) arrived first. In that case, T. urticae colonised the preferred feeding stratum (leaves) of T. evansi leading to spatial niche preemption, which equalised fitness and reduced niche differences, driving community assembly to a close-to-neutrality scenario. Our study demonstrates how the order of species arrival and the spatial context of competitive interactions can jointly determine whether species can coexist.


title: Specific sequence of arrival promotes coexistence via spatial niche preemption by the weak competitor


title: Dwarf-shrubs dynamics in Mediterranean high mountain ecosystems

abstract:
QuestionVegetation in the alpine and treeline ecotone faces changes in both climate and land use. Shrub encroachment is considered an effect of these changes, but its still unclear how this effect is mediated by environmental heterogeneity. Our goal is to determine which environmental factors shape the fine-scale spatial distribution and temporal trends of alpine dwarf shrub.

LocationThree sites in the Central Apennine, Italy.

MethodsWe used a comprehensive set of environmental factors across a broad temporal span to model, at a fine-scale, both (1) the current spatial distribution and (2) the change in shrub cover over the past 60 years.

ResultsOur results show that dwarf shrubs have generally increased in our study sites over the past 60 years, yet their distribution is strongly shaped by the joint influence of the fine-scale topography, productivity, land use and micro-climate. In particular, shrubs have been locally favored in areas with harsher alpine environmental constraints and stronger resource limitation. Instead, contrary to expectations, at this fine scale, warmer temperatures and the decline in grazing have not favored shrub encroachment.

ConclusionDwarf shrubs appear as a stress-tolerant, pioneer vegetation that is currently distributed mainly over areas that are otherwise sparsely vegetated. It appears that shrubs exhibit poor competitive ability to invade grasslands and, though they have increased overall, they remain restricted to the least productive areas. Fine-scale environmental heterogeneity may strongly influence future responses of dwarf shrubs in changing alpine ecosystems.


title: The matrisome contributes to the increased rigidity of the bovine ovarian cortex and provides a source of new bioengineering tools to investigate ovarian biology

abstract: The gonadotoxic effects of some cancers significantly increase the risk of developing infertility and cessation of ovary hormones (premature ovarian insufficiency, POI). Fertility preservation in the form of ovarian tissue cryopreservation (OTC) is offered to pediatric and adolescent cancer patients who cannot undergo oocyte retrieval and egg cryopreservation. The cryopreserved ovarian tissue can be transplanted back and has been found to restore fertility in 20 - 40% of transplants and restore hormone function for an average of 3 to 5 years. However, some individuals have primary or metastatic disease within their ovarian tissue and would not be able to transplant it back in its native form. Therefore, there is a need for additional methods for hormone and fertility restoration that would support a safe transplant with increased successful livebirths and long-term hormone restoration. To support these goal, we sought to understand the contribution of the ovarian microenvironment to its physical and biochemical properties to inform bioprosthetic ovary scaffolds that would support isolated follicles. Using atomic force microscopy (AFM), we determined that the bovine ovarian cortex was significantly more rigid than the medulla. To determine if this difference in rigidity was maintained in isolated matrisome proteins from bovine ovarian compartments, we cast and 3D printed hydrogels created from decellularized bovine ovarian cortex and medulla slices. The cast gels and 3D printed bioprosthetic ovary scaffolds from the cortex was still significantly more rigid than the medulla biomaterials. To expand our bioengineering toolbox that will aide in the investigation of how biochemical and physical cues may affect folliculogenesis, we sought to confirm the concentration of matrisome proteins in bovine ovarian compartments. The matrisome proteins, COL1, FN, EMILIN1 and AGRN were more abundant in the bovine ovarian cortex than the medulla. Whereas, VTN was more abundant in the medulla than the cortex and COL4 was present in similar amounts within both compartments. Finally, we removed proteins of interest, EMILIN1 and AGRN, from decellularized bovine ovarian cortex materials and confirmed that this specifically depleted these proteins without affecting the rigidity of cast or 3D printed hydrogels. Taken together our results indicate the existence of a rigidity gradient in the bovine ovary, that this rigidity gradient is maintained in resulting engineered materials strongly implicating a role for matrisome proteins in contributing to the physical properties of the bovine ovary. By establishing additional engineering tools we will continue to explore mechanisms behind matrisome-follicle interactions.

category: bioengineering


title: Mapping the functional interactions at the tumor-immune checkpoint interface

abstract: It is challenging to identify the tumor-immune system interactions that modulate immune states and immunotherapy responses due to the prohibitively complex space of possible interactions. Our statistical analysis framework, ImogiMap quantifies tumor-immune interactions based on their synergistic co-associations with immune-associated phenotypes. ImogiMap-based analyses recapitulated known interactions modulating immunotherapy responses and nominated the CD86/CD70 axis as an immunotherapy target that overlaps with IFNG overexpression and patient survival in endometrial carcinoma.


title: Use of a graph neural network to the weighted gene co-expression network analysis of Korean native cattle

abstract:
In the general framework of the weighted gene co-expression network analysis (WGCNA), a hierarchical clustering algorithm is commonly used to module definition. However, hierarchical clustering depends strongly on the topological overlap measure. In other words, this algorithm may assign two genes with low topological overlap to different modules even though their expression patterns are similar. Here, a novel gene module clustering algorithm for WGCNA is proposed. We develop a gene module clustering network (gmcNet), which simultaneously addresses single-level expression and topological overlap measure. The proposed gmcNet includes a "co-expression pattern recognizer" (CEPR) and "module classifier". The CEPR incorporates expression features of single genes into the topological features of co-expressed ones. Given this CEPR-embedded feature, the module classifier computes module assignment probabilities. We validated gmcNet performance using 4,976 genes from 20 native Korean cattle. We observed that the CEPR generates more robust features than single-level expression or topological overlap measure. Given the CEPR-embedded feature, gmcNet achieved the best performance in terms of modularity (0.261) and the differentially expressed signal (27.739) compared with other clustering methods tested. Furthermore, gmcNet detected some interesting biological functionalities for carcass weight, backfat thickness, intramuscular fat, and beef tenderness of Korean native cattle. Therefore, gmcNet is a useful framework for WGCNA module clustering.

Author summaryA graph neural network is a good alternative algorithm for WGCNA module clustering. Even though the graph-based learning methods have been widely applied in bioinformatics, most studies on WGCNA did not use graph neural network for module clustering. In addition, existing methods depend on topological overlap measure of gene pairs. This can degrade similarity of expression not only between modules, but also within module. On the other hand, the proposed gmcNet, which works similar to message-passing operation of graph neural network, simultaneously addresses single-level expression and topological overlap measure. We observed the higher performance of gmcNet comparing to existing methods for WGCNA module clustering. To adopt gmcNet as clustering algorithm of WGCNA, it remains future research issues to add noise filtering and optimal k search on gmcNet. This further research will extend our proposed method to be a useful module clustering algorithm in WGCNA. Furthermore, our findings will be of interest to computational biologists since the studies using graph neural networks to WGCNA are still rare.


title: High-throughput phenotypic screen identifies a new family of potent anti-amoebic compounds

abstract:
Entamoeba histolytica is a disease-causing parasitic amoeba which affects an estimated 50 million people worldwide, particularly in socioeconomically vulnerable populations experiencing water sanitation issues. Infection with E. histolytica is referred to as amoebiasis, and can cause symptoms such as colitis, dysentery, and even death in extreme cases. Drugs exist that are capable of killing this parasite, but they are hampered by downsides such as significant adverse effects at therapeutic concentrations, issues with patient compliance, the need for additional drugs to kill the transmissible cyst stage, and potential development of resistance. Past screens of small and medium sized chemical libraries have yielded anti-amoebic candidates, thus rendering high-throughput screening a promising direction for new drug discovery in this area. In this study, we screened a curated 80,000-compound library from Janssen pharmaceuticals against E. histolytica trophozoites in vitro, and from it identified a highly potent new inhibitor compound. Further experimentation confirmed the activity of this compound, as well as that of several structurally related compounds, originating from both the Janssen Jump-stARter library, and from chemical vendors, thus highlighting a new structure-activity relationship (SAR). In addition, we confirmed that the compound inhibited E. histolytica survival as rapidly as the current standard of care and inhibited transmissible cysts of the related model organism Entamoeba invadens. Together these results constitute the discovery of a novel class of chemicals with favorable in vitro pharmacological properties which may lead to an improved therapy against this parasite and in all of its life stages.

Author summaryThe parasite Entamoeba histolytica represents a significant challenge in the field of global health. It currently infects and causes disease among millions of people worldwide, particularly those lacking access to clean water. Drugs exist to treat this disease, but nevertheless it persists as a problem, likely at least partly due to problems and downsides inherent to these drugs. Hence the search for new and better ones is needed. We report here our contribution to this search, consisting of testing a large, carefully-curated collection of tens of thousands of chemicals for their ability to kill E. histolytica. This large-scale test resulted in the identification of one of the compounds as potently anti-amoebic, capable of killing the parasite cells at extremely low concentrations. Further experimentation found several chemically-related compounds to also possess this property, and additionally found the first compound capable of killing the infective life stage of another Entamoeba parasite. These results have revealed an entire new family of chemicals with good potential for development as better drugs against this disease.

category: pharmacology and toxicology


title: Dependence Of Heart Rate Variability On Immersion In A Virtual Game And Change Of Visual Content In The Flow Of Virtual Reality

abstract:
A modern person constantly changes the environment of his mental activity, moving real into an immersive environment, for example, from the surrounding reality to the information environment of a smartphone and back. This kind of transition is needed to satisfy many of the cognitive and emotional needs of people. The transition from a real physical environment to virtual reality (VR) with the help of a special headset, for example, the Oculus Rift or HTC vive, occurs less often, causing less frequent emotional state. If at the same time the emotional state of a person is investigated, then, as a rule, the manifestation of heart rate variability (HRV) is used as an indicator. However, there are relatively few studies in the literature on physiological responses using HRV during the perception of VR content. The results of such studies are extrapolated to data evoked in HRV manifestations by stimuli of real and virtual environments. We studied HRV in 55 participants while they were in the flow of VR content of different dynamics. The results were analyzed by statistically testing the hypothesis of the effect of VR immersion and the effect of transitions between realities on HRV manifestations, as well as the effect of VR flow dynamics on HRV. The results showed that the perception of the VR flow and the content transitions made in it determine the change in HRV in the form of such parameters as LF and the Baevsky Index, which can be considered as markers of immersion in VR. An increase in emotional arousal with sequential participation in virtual games in one virtual stream determines the manifestations of HRV - HR, Moda and PAR.

The results contribute to understanding the possibilities of using VR technology to recognize emotions during the transition between the natural environment and VR, as well as to determine the level of emotional arousal when immersed in the changing flow of virtual content. These studies are important for the study of the psychology of emotions in the VR flow paradigm.


title: Integrative analysis identified common and unique molecular signatures in hepatobiliary cancers

abstract: Hepatobiliary cancers (HBCs) are the most aggressive and sixth most diagnosed cancers globally. Biomarkers for timely diagnosis and targeted therapy in HBCs are still limited. Considering the gap, our objective is to identify unique and overlapping molecular signatures associated with HBCs. We analyzed publicly available transcriptomic datasets on Gallbladder cancer (GBC), Hepatocellular carcinoma (HCC), and Intrahepatic cholangiocarcinoma (ICC) to identify potential biomarkers using integrative systems approaches. An effective Common and Unique Molecular Signature Identification (CUMSI) approach has been developed, which contains analysis of differential gene expression (DEG), gene co-expression networks (GCN), and protein-protein interactions (PPIs) networks. Functional analysis of the DEGs unique for GBC, HCC, and ICC indicated that GBC is associated with cellular processes, HCC is associated with immune signaling pathways, and ICC is associated with lipid metabolic pathways. Our findings shows that the hub genes and pathways identified for each individual cancer type of the HBS are related with the primary function of each organ and each cancer exhibit unique expression patterns despite being part of the same organ system.


title: The influence of reproductive stage on cerebellar network connectivity across adulthood

abstract:
Sex-specific differences in the aging cerebellum may be related to hormone changes with menopause. We evaluated the influence of reproductive stage on lobular cerebellar network connectivity using data from the Cambridge Centre for Ageing and Neuroscience repository. We used raw structural and resting state neuroimaging data and information regarding age, sex, and menopause-related variables. Crus I and II and Lobules V and VI were our cerebellar seeds of interest. We characterized reproductive stage using the Stages of Reproductive Aging Workshop criteria. Results show that postmenopausal females have lower cerebello-striatal and cerebello-cortical connectivity, particularly in frontal regions, along with lower connectivity within the cerebellum, compared to reproductive females. Postmenopausal females also exhibit greater connectivity in some brain areas as well. Differences begin to emerge across transitional stages of menopause. Further, results reveal sex-specific differences in connectivity between female reproductive groups and age-matched male control groups. This suggests that menopause may influence cerebellar network connectivity in aging females, and sex differences in the aging brain may be related to this biological process.

HighlightsO_LILobular analysis of cerebellar network connectivity across reproductive stages
C_LIO_LIPostmenopausal females show lower cerebellar connectivity, compared to reproductive
C_LIO_LIConnectivity differences begin to emerge in transitional stages of menopause
C_LIO_LIAge-matched male control groups show distinct patterns of cerebellar connectivity
C_LIO_LIReproductive stage influences cerebellar network connectivity in aging females
C_LI

category: neuroscience


title: Modelling sexual violence in male rats: The sexual aggression test (SxAT)

abstract:
Sexual assault and rape are crimes that impact victims worldwide. Although the psychosocial and eco-evolutionary factors associated with this antisocial behavior have repeatedly been studied, the underlying neurobiological mechanisms are still unknown mainly due to the lack of an appropriate animal model of sexual aggression (SxA). Here, we established a novel paradigm to provoke and subsequently assess SxA in adult male Wistar rats: the sexual aggression test (SxAT). Briefly, male Wistar rats are sexually aroused by a receptive female, which is exchanged by a non-receptive female immediately after the first intromission. This protocol elicits forced mounting (FM) and aggressive behavior (AB) towards the non-receptive female to different degrees, which can be scored. In a series of experiments we can show that SxA behavior is a relatively stable trait in rats and correlates positively with sexual motivation. Rats with innate abnormal anxiety and aggressive behavior also show abnormal SxA behavior. In addition, central infusion of oxytocin moderately inhibits AB, but increases FM. Finally, we identified the agranular insular cortex to be specifically activated by SxA, and inhibition of this region mildly decreased AB during the SxAT.

Altogether, the SxAT is a paradigm that can be readily implemented in behavioral laboratories as a valuable tool to find answers regarding the biological mechanisms underlying SxA in humans, as well as social decision-making in general.


title: Inflammation modulates regeneration in the acute or chronically damaged zebrafish retina

abstract: Unlike mammals, zebrafish regenerate in response to retinal damage. Because microglia are activated by retinal damage, we investigated their role during regeneration following acute or chronic damage. At three weeks-post-fertilization (wpf), fish exhibiting NMDA-induced acute damage or cone photoreceptor-specific chronic degeneration, the gold rush (gosh) mutant, displayed reactive microglia and Muller glia proliferation. Retinas treated to inhibit the immune response lacked reactive microglia and possessed fewer PCNA-positive cells, while LPS treatment increased microglia and PCNA-labeled cells. NMDA-injured retinas upregulated the expression of il-1{beta} and tnf- pro-inflammatory cytokine genes, followed by increased expression of il-10 and arg1 anti-inflammatory/remodeling cytokine genes. An early and transiently TNF- pro-inflammatory microglia population was identified in the NMDA-damaged retina. In contrast, gosh mutant retinas exhibited a mild increase of pro-inflammatory cytokine gene expression concurrently with a greater increased in anti-inflammatory/remodeling cytokine gene expression. Few TNF- pro-inflammatory microglia were observed in the gosh retina. How inflammation regulates regeneration in zebrafish would provide important clues towards improving the therapeutic strategies for repairing injured mammalian tissues.


title: Key Factors in the Cortical Response to Transcranial Electrical Stimulations--A Multi-Scale Modeling Study

abstract: Transcranial electrode stimulation (tES), one of the techniques used to apply non-invasive brain stimulation (NIBS), modulates cortical activities by delivering weak electric currents through scalp-attached electrodes. This emerging technique has gained increasing attention recently; however, the results of tES vary greatly depending upon subjects and the stimulation paradigm, and its cellular mechanism remains uncertain. In particular, there is a controversy over the factors that determine the cortical response to tES. Some studies have reported that the electric fields (EF) orientation is the determining factor, while others have demonstrated that the EF magnitude itself is the crucial factor. In this work, we conducted an in-depth investigation of cortical activity in two types of electrode montages used widely--the conventional (C)-tES and high-definition (HD)-tES--as well as two stimulation waveforms--direct current (DC) and alternating current (AC). To do so, we constructed a multi-scale model by coupling an anatomically realistic human head model and morphologically realistic multi-compartmental models of three types of cortical neurons (layer 2/3 pyramidal neuron, layer 4 basket cell, layer 5 pyramidal neuron). Then, we quantified the neuronal response to the C-/HD-tDCS/tACS and explored the relation between the electric field (EF) and the radial fields (RF: radial component of EF) magnitude and the cortical neurons threshold. The EF tES induced depended upon the electrode montage, and the neuronal responses were correlated with the EF rather than the RFs magnitude. The electrode montages and stimulation waveforms caused a small difference in threshold, but the higher correlation between the EFs magnitude and the threshold was consistent. Further, we observed that the neurons morphological features affected the degree of the correlation highly. Thus, the EF magnitude was a key factor in the responses of neurons with arborized axons. Our results demonstrate that the crucial factor in neuronal excitability depends upon the neuron models morphological and biophysical properties. Hence, to predict the cellular targets of NIBS precisely, it is necessary to adopt more advanced neuron models that mimic realistic morphological and biophysical features of actual human cells.