title: Leveraging eDNA metabarcoding to characterize nearshore fish communities in Southeast Alaska: Do habitat and tide matter?

abstract: Nearshore marine habitats are critical for a variety of commercially important fish species, but assessing fish communities in these habitats is costly and time-intensive. Here, we leverage eDNA metabarcoding to characterize nearshore fish communities near Juneau, Alaska, USA, a high-latitude environment with large tidal swings, strong currents, and significant freshwater input. We investigated whether species richness and community composition differed across three habitat types (sand beaches, eelgrass beds, and rocky shorelines) and between high and low tides. Additionally, we tested whether replication of field samples and PCR reactions influenced either species richness or composition. We amplified a 12S mitochondrial locus in our samples and identified 188 fish amplicon sequence variants (ASVs), corresponding to 21 unique taxa, with approximately half of these resolved to single species. Species richness and composition inferred from eDNA differed substantially among habitats, with rock habitats containing fewer taxa and fewer overall detections than sand and eelgrass habitats. The effect of tide was more subtle and suggested a habitat-tide interaction, with differences in taxa between tides largely isolated to sand habitats. Power analyses indicated that additional field sampling is useful to detect subtle changes in species richness such as those due to tide. PCR replicates typically identified a small number of additional taxa. The most notable result from our study was that shore morphology appeared to substantially influence community structure. Rocky shorelines sloped quickly into deep water, while sand and eelgrass habitats descended much more gradually. We hypothesize that differences in taxa observed among habitats were largely due to lack of mixing between bottom and surface water, providing further evidence that eDNA transport is minimal and that many marine eDNA detections are derived from highly localized sampling locations. We suggest that future studies could explore the extent to which habitat and nearshore physical processes influence eDNA detections.


title: Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines

abstract: Beta cells intrinsically contribute to the pathogenesis of type 1 diabetes (T1D), but the genes and molecular processes that mediate beta cell survival in T1D remain largely unknown. We combined high throughput functional genomics and human genetics to identify T1D risk loci regulating genes affecting beta cell survival in response to the proinflammatory cytokines IL-1{beta}, IFN{gamma}, and TNF. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) active in beta cells using ATAC-seq and single nuclear ATAC-seq (snATAC-seq), and linked cytokine-responsive beta cell cCREs to putative target genes using single cell co-accessibility and HiChIP. We performed a genome-wide pooled CRISPR loss-of-function screen in EndoC-{beta}H1 cells, which identified 867 genes affecting cytokine-induced beta cell loss. Genes that promoted beta cell survival and had up-regulated expression in cytokine exposure were specifically enriched at T1D loci, and these genes were preferentially involved in inhibiting inflammatory response, ubiquitin-mediated proteolysis, mitophagy and autophagy. We identified 2,229 variants in cytokine-responsive beta cell cCREs altering transcription factor (TF) binding using high-throughput SNP-SELEX, and variants altering binding of TF families regulating stress, inflammation and apoptosis were broadly enriched for T1D association. Finally, through integration with genetic fine mapping, we annotated T1D loci regulating beta cell survival in cytokine exposure. At the 16p13 locus, a T1D variant affected TF binding in a cytokine-induced beta cell cCRE that physically interacted with the SOCS1 promoter, and increased SOCS1 activity promoted beta cell survival in cytokine exposure. Together our findings reveal processes and genes acting in beta cells during cytokine exposure that intrinsically modulate risk of T1D.

category: genomics


title: Plasma donation induces a protein expression profile shift in circulating human blood

abstract:
Commercial plasma donation yields a change in protein concentration similar to that observed in therapeutic plasma exchange (TPE) in humans. The post-donation expression profile shows an increase in many proteins after even a single donation, and the effect is enhanced with additional donations. Unlike TPE, human plasma donation returns saline without albumin to the donor, thus eliminating supplemental albumin as a contributing factor. The observed fold change falls outside the variation expected by natural circadian expression changes.

N=6 humans (four donors, one monthly control and one circadian test). Seventeen antibody tests were performed, measuring the concentration of 507 proteins for each test.

category: biochemistry


title: A simple tool extends TIMSTOF compatibility with historic data processing tools and enables ion mobility-enhanced spectral libraries

abstract: Trapped ion mobility mass spectrometry is proving to be a disruptive technology in LCMS based proteomics. One primary drawback of this hardware is the lack of compatibility with the hundreds of data processing pipelines historically in use. This study describes a simple data conversion tool that "folds" the TIMSTOF ion mobility data into the MS2 fragmentation spectra allowing simple downstream processing. Little to no detriment in the assignment of peptide spectral matches is observed when "folding" the 1/k0 value into the low mass region. To demonstrate one utility of TIMS Folding, spectral libraries are provided in multiple common formats that were constructed from the same files both with and without folded ion mobility data. When new data is acquired and folded using the same parameters prior to data processing the folded ion mobility data can be used as an additional metric for peptide match confidence against folded spectral libraries.


title: Extracellular Vesicles Deliver Mitochondria and HSP27 Protein to Protect the Blood-Brain Barrier

abstract:
Ischemic stroke causes brain endothelial cell (BEC) death and damages tight junction integrity of the blood-brain barrier (BBB). We harnessed the innate mitochondrial load of endothelial cell-derived extracellular vesicles (EVs) and utilized mixtures of EV/exogenous heat shock protein 27 (HSP27) as a one-two punch strategy to increase BEC survival (via EV mitochondria) and preserve their tight junction integrity (via HSP27 effects). We demonstrated that the medium-to-large (m/lEV) but not small EVs (sEV) transferred their mitochondrial load, which subsequently colocalized with the mitochondrial network of the recipient primary human BECs. BECs treated with m/lEVs increased relative ATP levels and displayed superior mitochondrial function. m/lEVs isolated from rotenone (mitochondrial complex I inhibitor) exposed BECs (RTN-m/lEVs) did not increase BECs ATP levels compared to naive m/lEVs. In contrast, RTN-sEVs functionality was minimally affected compared to naive sEVs. Compared to EV/HSP27 mixtures, PEG-DET/EV/HSP27 ternary mixtures increased HSP27 protein loading. (PEG-DET/HSP27)/EV ternary and EV/HSP27 binary mixtures decreased the paracellular permeability of small and large molecular mass fluorescent tracers in oxygen glucose-deprived primary human BECs. This one-two punch approach to increase BEC metabolic function and tight junction integrity is a promising strategy for BBB protection and prevention of long-term neurological dysfunction post-ischemic stroke.

Highlights[tpltrtarr] Medium-to-large extracellular vesicles (m/lEVs), not small EVs contain mitochondria
[tpltrtarr]m/lEVs increased ATP and mitochondrial function in brain endothelial cells (BECs)
[tpltrtarr]Donor m/lEV mitochondria colocalized with host mitochondria in recipient BECs
[tpltrtarr]m/lEVs from rotenone-exposed BECs did not increase recipient BEC ATP levels
[tpltrtarr]PEG-DET/EV/HSP27 ternary mixtures increase exogenous HSP27 protein loading

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/466491v4_ufig1.gif" ALT="Figure 1">
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category: bioengineering


title: Extracellular Vesicle (EV) Mitochondria and EV/HSP27 Mixtures Protect the Ischemic Brain Endothelium


title: Genotyping of structural variation using PacBio high-fidelity sequencing

abstract:
BackgroundStructural variations (SVs) pervade the genome and contribute substantially to the phenotypic diversity of species. However, most SVs were ineffectively assayed because of the complexity of plant genomes and the limitations of sequencing technologies. Recent advancement of third-generation sequencing technologies, particularly the PacBio high-fidelity (HiFi) sequencing, which generates both long and highly accurate reads, offers an unprecedented opportunity to characterize SVs and reveal their functionality. Since HiFi sequencing is new, it is crucial to evaluate HiFi reads in SV detection before applying the technology at scale.

ResultsWe sequenced wheat genomes using HiFi, then conducted a comprehensive evaluation of SV detection using mainstream long-read aligners and SV callers. The results showed the accuracy of SV discovery depends more on aligners rather than callers. For aligners, pbmm2 and NGMLR provided the most accurate results while detecting deletion and insertion, respectively. Likewise, cuteSV and SVIM achieved the best performance across all SV callers. We demonstrated that the combination of the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the impact of sequencing depth on the accuracy of SV detection. The results showed that low-coverage HiFi sequencing is capable of generating high-quality SV genotyping.

ConclusionsThis study provides a robust benchmark of SV discovery with HiFi reads, showing the remarkable potential of long-read sequencing to investigate structural variations in plant genomes. The high accuracy SV discovery from low-coverage HiFi sequencing indicates that skim HiFi sequencing is an ideal approach to study structural variations at the population level.

category: bioinformatics


title: Systems-based approach for optimization of a scalable bacterial ST mapping assembly-free algorithm

abstract: Epidemiological surveillance of bacterial pathogens requires real-time data analysis with a fast turn-around, while aiming at generating two main outcomes: 1) Species level identification; and 2) Variant mapping at different levels of genotypic resolution for population-based tracking, in addition to predicting traits such as antimicrobial resistance (AMR). With the recent advances and continual dissemination of whole-genome sequencing technologies, large-scale population-based genotyping of bacterial pathogens has become possible. Since bacterial populations often present a high degree of clonality in the genomic backbone (i.e., low genetic diversity), the choice of genotyping scheme can even facilitate the understanding of ancestral relationships and can be used for prediction of co-inherited traits such as AMR. Multi-locus sequence typing (MLST) fits that purpose and can identify sequence types (ST) based on seven ubiquitous genome-scattered loci that aid in genotyping isolates beneath the species level. ST-based mapping also standardizes genotyping across laboratories and is used by laboratories worldwide. However, algorithms for inferring ST from Illumina paired-end sequencing data typically rely on genome assembly prior to classification. Genome assembly is computationally intensive and is a bottleneck for speed and scalability, which are important aspects of genomic epidemiology. The stringMLST program uses an assembly-free, kmer-based algorithm for inferring STs, which can overcome the speed and scalability bottlenecks. Here we have systematically studied the accuracy and scalability of stringMLST relative to the standard MLST program across a wide array of phylogenetically divergent Public Health-relevant bacterial pathogens. Our data shows that optimal kmer length for stringMLST is species-specific and that genome-intrinsic and -extrinsic features can affect performance and accuracy of the program. While suitable parameters could be identified for most organisms, there were a few instances where this program may not be directly deployable in its current format. More importantly, we integrated stringMLST into our freely available and scalable hierarchical-based population genomics platform, ProkEvo, and further demonstrated how the implementation facilitates automated, reproducible bacterial population analysis. The ProkEvo implementation provides a rapidly deployable genomic epidemiology tool for ST mapping along with other pan-genomic data mining strategies, while providing specific guidance on how to optimize stringMLST performance for a wide variety of bacterial pathogens.


title: Electronic Mapping of a Bacterial Genome with Dual Solid-State Nanopores and Active Single-Molecule Control

abstract: We present the first electronic mapping of a bacterial genome using solid-state nanopore technology. A dual-nanopore architecture and active control logic are used to produce single-molecule data that enables estimation of distances between physical tags installed at sequence motifs within double-stranded DNA (dsDNA). Previously developed dual-pore "DNA flossing" control generates multiple scans of tagged regions of each captured DNA. The control logic was extended here in two ways: first, to automate "zooming out" on each molecule to progressively increase the number of tags scanned during DNA flossing; and second, to automate recapture of a molecule that exited flossing to enable interrogation of the same and/or different regions of the molecule. New analysis methods were developed to produce consensus alignments from each multi-scan event. The combined multi-scanning and multi-capture method was applied to the challenge of mapping from a heterogeneous mixture of single-molecule fragments that make up the Escherichia coli (E. coli) chromosome. Coverage of 3.1x across 2,355 resolvable sites (68% of reference sites) of the E. coli genome was achieved after 5.6 hours of recording time. The recapture method showed a 38% increase in the merged-event alignment length compared to single-scan alignments. The observed inter-tag resolution was 150 bp in engineered DNA molecules and 166 bp natively within fragments of E. coli DNA, with detection of 133 inter-site intervals shorter than 200 bp in the E. coli reference map. Proof of concept results on estimating distances in repetitive regions of the E. coli genome are also provided. With an appropriately designed array and future refinements to the control logic, higher throughput implementations can enable human-sized genome and epigenome mapping applications.

category: biophysics


title: Examining the Ensembles of Amyloid-β Monomer Variants and their Propensities to Form Fibers Using an Energy Landscape Visualization Method

abstract: The amyloid-{beta} (A{beta}) monomer, an intrinsically disordered peptide, is produced by the cleavage of the amyloid precursor protein, leading to A{beta}40 and A{beta}42 as major products. These two isoforms generate pathological aggregates, whose accumulation correlates with Alzheimers disease (AD). Experiments have shown that even though the natural abundance of A{beta}42 is smaller than that for A{beta}40, the A{beta}42 is more aggregation-prone compared to A{beta}40. Moreover, several single-point mutations are associated with early-onset forms of AD. This work analyzes coarse-grained AWSEM simulations of normal A{beta}40 and A{beta}42 monomers, along with six single-point mutations associated with early on set disease. We analyzed the simulations using the Energy Landscape Visualization Method (ELViM), a reaction coordinate-free approach suited to explore the frustrated energy landscapes of intrinsically disordered proteins. ELViM is shown to distinguish the monomer ensembles of variants that rapidly form fibers from those that do not form fibers as readily. It also delineates the amino-acid contacts characterizing each ensemble. The results shed light on the potential of ELViM to probe intrinsically disordered proteins.


title: Solvation dynamics-powered structure and function of multi-molecular cellular systems exemplified by non-equilibrium cereblon-degrader-CK1α ternary complex formation

abstract:
Cellular functions are executed via a form of analog computing that is based on the switchable covalent and non-covalent states of multi-molecular fluxes (i.e., time-dependent species/state concentrations) operating in the non-linear dynamics regime. We and others have proposed that the non-covalent states and state transitions of aqueous fluxes are powered principally by the storage and release of potential energy to/from the anisotropic H-bond network of solvating water (which we refer to as the "solvation field"), which is a key tenet of a first principles theory on cellular structure and function (called Biodynamics) that we outlined previously. This energy is reflected in water occupancy as a function of solute surface position, which can be probed computationally using WATMD software. In our previous work, we used this approach to deduce the structural dynamics of the COVID main protease, including substrate binding-induced enzyme activation and dimerization, and product release-induced dimer dissociation. Here, we examine: 1) The general relationships between surface composition/topology and solvation field properties for both high and low molecular weight (HMW and LMW) solutes.
2) The general means by which structural dynamics are powered by solvation free energy, which we exemplify via binding between the E3 ligase CUL4A/RBX1/DDB1/CRBN, LMW degraders, and substrates. We propose that degraders organize the substrate binding surface of cereblon toward complementarity with native and neo substrates, thereby speeding the association rate constant and incrementally slowing the dissociation rate constant.
3) Structure-activity relationships (SAR) based on complementarity between the solvation fields of cognate protein-ligand partners exemplified via LMW degraders.

category: pharmacology and toxicology


title: Characterization of γ-Glutamyl Peptidases and γ-Glutamyl Cyclotransferases for Glutathione Degradation in Arabidopsis

abstract:
O_LIOrganic sulfur is stored as glutathione (GSH) in plants. In Arabidopsis, {gamma}-glutamyl cyclotransferases (GGCT2;1, GGCT2;2, and GGCT2;3) degrade cytosolic GSH, but they do not fully explain the rapid GSH turnover. Here, we demonstrate that {gamma}-glutamyl peptidases, GGP1 and GGP3, play a substantial role in degrading GSH in the cytosol.
C_LIO_LIWe conducted yeast complementation assay and activity assay of recombinant proteins to identify the novel GSH degradation enzymes. The expression patterns were investigated by RT-qPCR. GSH concentrations in the mutants were also analyzed.
C_LIO_LIGGP1 complemented the yeast phenotype. Recombinant GGP1 and GGP3 showed reasonable Km values considering cytosolic GSH concentration, and their activity was comparable to that of GGCTs. The GGP1 transcript was highly abundant in mature organs such as rosette leaves. The expression of GGCT2;1 was conspicuously enhanced under sulfur deficiency. GSH concentration was higher in ggp1 knockout mutants regardless of nutritional conditions; the concentration was higher in ggct2;1 knockout mutants under sulfur-deficient conditions.
C_LIO_LIWe propose a model wherein cytosolic GSH is degraded fundamentally by GGP1. The degradation is accelerated by GGCT2;1 under sulfur deficiency. Given the energy cost throughout the reactions, GGPs could render a more efficient route for GSH degradation than GGCTs.
C_LI

category: plant biology


title: Intestinal GCN2 controls Drosophila systemic growth upon AA imbalance in response to Lactiplantibacillus plantarum symbiotic cues encoded by r/tRNAoperons

abstract: Symbiotic bacteria interact with their host through the release of symbiotic cues. Here, we took advantage of the mutualism between Drosophila and Lactiplantibacillus plantarum (Lp) to investigate a novel mechanism of host-symbiont interaction. Using chemically-defined holidic diets, we found that association with Lp improves the growth of larvae fed on amino acid-imbalanced diets, even though Lp cannot produce the limiting amino acid. We show that in this context Lp supports its hosts growth through a molecular dialog that requires functional operons encoding ribosomal and transfer RNAs (r/tRNAs) in Lp and the GCN2 kinase in Drosophilas enterocytes. Our data indicate that products of Lp r/tRNAs loci activate GCN2 in a subset of larval enterocytes, a mechanism necessary to remodel the intestinal transcriptome and ultimately to support anabolic growth. Our findings unravel a novel beneficial molecular dialog between host and microbes, which relies on a non-canonical role of GCN2 as a mediator of non-nutritional symbiotic cues encoded by r/tRNA operons.

category: microbiology


title: Intestinal GCN2 controls Drosophila systemic growth in response to Lactiplantibacillus plantarum symbiotic cues encoded by r/tRNA operons


title: Autologous mitochondria transport via transzonal filopodia rejuvenates aged oocytes by UC-MSCs derived granulosa cells-oocyte aggregation

abstract: Mitochondria transfer can rescue oocyte aging-related infertility. However, heterologous techniques are suspended due to heteroplasmy. Regarding autologous approaches, the donor source and manipulating procedures require further optimization. Here we propose a strategy using umbilical cord mesenchymal stem cells (UC-MSCs) as mitochondria donor cells and employing intercellular mitochondria transport as the transfer method. We cryopreserved UC-MSCs of the female pup. When the female aged, its UC-MSCs were induced into granulosa cells (iGCs). The zona-weakened GV oocytes were aggregated with autologous iGCs into iGC-oocyte complexes. After cultivation in GDF9-containing media, mitochondria migrated from iGCs into the GV oocyte via transzonal filopodia. The maturation rate, quality, and developmental potential of these oocytes were substantially increased. Furthermore, the birth rate after embryo transfer has been improved. This approach utilized noninvasive procedures to collect mitochondria donor cells and optimized mitochondria transfer manipulations, so may represent a promising advance towards the improvement of aging-related infertility.

category: developmental biology


title: Acoustic Censusing and Individual Identification of Birds in the Wild

abstract: Avian vocal individuality carries information that can be utilized as an alternative to physical tagging of individuals. However, it is rarely used in conservation tasks despite rapidly-expanding use of passive acoustic monitoring techniques. Reliable acoustic individual recognizers and accurate quantifiers of population size remain elusive, which discourages the use of vocal individuality for monitoring, wildlife management, and ecological research. We propose a neuro-fuzzy framework that allows discrimination of individuals by their calls, the discovery of unexpected individuals in a set of recordings, and estimation of population size using solely sound. Our method, tested using data collected in the wild, allows rapid individual identification and even acoustic censusing without prior information from the recorded individuals. We achieve this by integrating a fuzzy classification and clustering methodology (LAMDA) into a Convolutional Deep Clustering Neural Network (CDCN). Our approach will benefit monitoring for conservation, and paves the way towards robust individual acoustic identification in species whose handling is time-consuming, culturally or ethically problematic, or logistically difficult.

category: ecology


title: MFN2 Influences Amyotrophic Lateral Sclerosis Pathology

abstract:
ObjectiveTo better understand the pathology of amyotrophic lateral sclerosis, we used sequence data from patients seen at the University of Utah to identify novel disease-associated loci. We utilized both in vitro and in vivo studies to determine the biological effect of patient mutations in MFN2.

MethodSequence data for a total of 140 patients were run through VAAST and Phevor to determine genes that were more burdened with rare, nonsynonymous variants compared to control longevity cohort. Variants identified in MFN2 were expressed in Mfn2 knockout cells to determine if mutant MFN2 could rescue mitochondrial morphology defects. We identified additional rare, nonsynonymous variants in MFN2 in ALSdb that were expressed in knockout mouse embryonic fibroblasts (MEFs). Membrane potential was measured to quantify mitochondrial health upon mutant MFN2 expression. mfn2 knockout zebrafish were used to examine movement compared to wildtype and protein aggregation in brain.

ResultsMFN2 mutations identified in ALS patients from our University of Utah cohort and ALSdb were defective in rescuing morphological defects in Mfn2 knockout MEFs. Selected mutants showed decreased membrane potential compared to wildtype MFN2 expression. Zebrafish heterozygous and homozygous for loss of mfn2 showed increased TDP-43 levels in their hindbrain and cerebellum.

ConclusionIn total, 21 rare, deleterious mutations in MFN2 were tested in Mfn2 knockout MEFs. Mutant MFN2 expression was not able to rescue the knockout phenotype, though at differing degrees of severity. Decreased membrane potential also argues for inhibited mitochondrial function. Increased TDP-43 levels in mutant zebrafish illustrates MFN2s function in ALS pathology. MFN2 variants influence ALS pathology and highlight the importance of mitochondria in neurodegeneration.

category: genetics


title: Substrate rigidity modulates traction forces and stoichiometry of cell matrix adhesions.

abstract: In cell matrix adhesions, integrin receptors and associated proteins provide a dynamic coupling of the extracellular matrix (ECM) to the cytoskeleton. This allows bidirectional transmission of forces between the ECM and the cytoskeleton, which tunes intracellular signaling cascades that control survival, proliferation, differentiation, and motility. The quantitative relationships between recruitment of distinct cell matrix adhesion proteins and local cellular traction forces are not known. Here, we applied quantitative superresolution microscopy to cell matrix adhesions formed on fibronectin-stamped elastomeric pillars and developed an approach to relate the number of talin, vinculin, paxillin, and focal adhesion kinase (FAK) molecules to the local cellular traction force. We find that FAK recruitment does not show an association with traction-force application whereas a ~60 pN force increase is associated with the recruitment of one talin, two vinculin, and two paxillin molecules on a substrate of effective stiffness of 47 kPa. On a substrate with a four-fold lower effective stiffness the stoichiometry of talin:vinculin:paxillin changes to 2:12:6 for the same ~60 pN traction force. The relative change in force-related vinculin recruitment indicates a stiffness-dependent switch in vinculin function in cell matrix adhesions. Our results reveal a substrate-stiffness-dependent modulation of the relation between cellular traction-force and the molecular stoichiometry of cell-matrix adhesions.


title: Global transcriptome analysis reveals partial estrogen-like effects of karanjin in MCF-7 breast cancer cells

abstract: Karanjin, an abundantly occurring furanoflavonoid in edible and non-edible legumes, exerts diverse biological effects in vivo, and in vitro. Its potential as an anticancer agent is also gaining traction following recent demonstrations of its anti-proliferative, cell cycle inhibitory, and pro-apoptotic effects. However, the universality of its anticancer potential is yet to be scrutinized, particularly so because flavonoids can act as selective estrogen receptor modulators (SERMs). Even the genomic correlates of its biological activities are yet to be examined in hormone responsive cells. This paper presents the early and direct transcriptomic footprint of 10 M karanjin in MCF-7 breast cancer cells, using next generation sequencing technology (RNA-seq). We show that karanjin-modulated gene-expression repertoire is enriched in several hallmark gene sets, which include early estrogen-response, and G2/M checkpoint genes. Genes modulated by karanjin overlapped with those modulated by 1 nM 17{beta}-estradiol (E2), or 1 M tamoxifen. Karanjin altered the expression of selected estrogen-regulated genes in a cell-type, and concentration dependent manner. It downmodulated the expression of ER protein in MCF-7 cells. Furthermore, ER knockdown negatively impacted karanjins ability to modulate the expression of selected E2 target genes. Our data suggest that karanjin exerts its effects on ER-positive breast cancer cells, at least in part, via ER. The apparent SERM-like effects of karanjin pose a caveat to the anticancer potential of karanjin. In-depth studies on cell-type and concentration-dependent effects of karanjin may bring out its true potential in endocrine therapies.


title: Genome-wide association study reveals complex genetic architecture of cadmium and mercury accumulation and tolerance traits in Medicago truncatula

abstract: Heavy metals are an increasing problem due to contamination from human sources that and can enter the food chain by being taken up by plants. Understanding the genetic basis of accumulation and tolerance in plants is important for reducing the uptake of toxic metals in crops and crop relatives, as well as for removing heavy metals from soils by means of phytoremediation. Following exposure of Medicago truncatula seedlings to cadmium (Cd) and mercury (Hg), we conducted a genome-wide association study using relative root growth (RRG) and leaf accumulation measurements. Cd and Hg accumulation and RRG had heritability ranging 0.44 - 0.72 indicating high genetic diversity for these traits. The Cd and Hg trait associations were broadly distributed throughout the genome, indicated the traits are polygenic and involve several quantitative loci. For all traits, candidate genes included several membrane associated ATP-binding cassette transporters, P-type ATPase transporters, several oxidative stress response genes and stress related UDP-glycosyltransferases. The P-type ATPase transporters and ATP-binding cassette protein-families have roles in vacuole transport of heavy metals, and our findings support their wide use in physiological plant responses to heavy metals and abiotic stresses. We also found associations between Cd RRG with the genes CAX3 and PDR3, two linked adjacent genes, and leaf accumulation of Hg associated with the genes NRAMP6 and CAX9. When plant genotypes with the most extreme phenotypes were compared, we found significant divergence in genomic regions using population genomics methods that contained metal transport and stress response gene ontologies. Several of these genomic regions show high linkage disequilibrium (LD) among candidate genes suggesting they have evolved together. Minor allele frequency (MAF) and effect size of the most significant SNPs was negatively correlated with large effect alleles being most rare. This is consistent with purifying selection against alleles that increase toxicity and abiotic stress. Conversely, the alleles with large affect that had higher frequencies that were associated with the exclusion of Cd and Hg. Overall, macroevolutionary conservation of heavy metal and stress response genes is important for improvement of forage crops by harnessing wild genetic variants in gene banks such as the Medicago HapMap collection.


title: Early transcriptomic response of Alnus glutinosa to Frankia alni symbiont, an upregulated nsLTP (non-specific Lipid Transfer Protein) is implicated in early and late stages of symbiosis

abstract:
Alnus glutinosa response to Frankia alni is driven by several sequential physiological modifications that include calcium spiking, root hair deformation, penetration, induction of primordium, formation and growth of nodule. Here, we have conducted a transcriptomic study to analyse plant responses to Frankia alni at early stages of symbiosis establishment.

Forty-two genes were significantly activated by either with a Frankia culture supernatant or with living cells separated from the roots by a dialysis membrane permitted to identify plant genes which expression changes upon early contact with Frankia. Most of these genes encode biological processes, including oxidative stress and response to stimuli. The most upregulated gene is the non-specific lipid transfer protein (nsLTP) encoding gene with a fold change of 141. Physiological experiments showed that nsLTP increases Frankia nitrogen fixation at sub-lethal concentration. Immunohistochemistry experiments conducted at an early infection stage indicated that nsLTP protein is localized at the deformed root hair region after Frankia inoculation and later in nodules, precisely around bacterial vesicles. Taken together, these results suggest that nsLTP acts at early and late stages of symbiosis, probably by increasing nitrogen uptake by Frankia.


title: The non-specific Lipid Transfer Protein (nsLTP) is involved at early and late stages of symbiosis between Alnus glutinosa and Frankia alni.


title: Synthetic periphyton as a model community to examine species dynamics in complex microbial consortia

abstract: Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation.

category: synthetic biology


title: Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities


title: Coordinate regulation of liver ferroportin degradation and de novo synthesis determines serum iron levels in mice

abstract: The iron hormone hepcidin is transcriptionally activated by iron or inflammation via distinct, partially overlapping pathways. We addressed how iron affects inflammatory hepcidin levels and the ensuing hypoferremic response. Dietary iron overload did not mitigate hepcidin induction in LPS-treated wt mice but prevented effective inflammatory hypoferremia. Likewise, LPS modestly decreased serum iron in hepcidin-deficient Hjv-/- mice, model of hemochromatosis. Synthetic hepcidin triggered hypoferremia only in control but not iron-loaded wt animals. Furthermore, it dramatically decreased hepatic and splenic ferroportin in Hjv-/- mice on standard or iron-deficient diet, but only triggered hypoferremia in the latter. Mechanistically, iron induced liver ferroportin mRNA translation, thereby antagonizing hepcidin-mediated hypoferremia. Conversely, iron depletion suppressed de novo ferroportin synthesis in Hjv-/- livers, allowing exogenous hepcidin to cause hypoferremia. Consequently, prolonged LPS treatment eliminating ferroportin mRNA permitted hepcidin-mediated hypoferremia in iron-loaded mice. Thus, liver ferroportin mRNA translation is critical determinant of serum iron and finetunes hepcidin-dependent functional outcomes. Our data indicate a crosstalk between hepcidin/ferroportin and IRE/IRP systems. Moreover, they suggest that hepcidin supplementation therapy is more efficient combined with iron depletion.

category: immunology


title: Comparing single cell datasets using DensityMorph

abstract: 1The proliferation of single cell datasets has brought a wealth of information, but also great challenges in data analysis. Obtaining a cohesive overview of multiple single cell samples is difficult and requires consideration of cell population structure - which may or may not be well defined - along with subtle shifts in expression within cell populations across samples, and changes in population frequency across samples. Ideally, all this would be integrated with the experimental design, e.g. time point, genotype, treatment etc. Data visualisation is the most effective way of communicating analysis but often this takes the form of a plethora of TSNE plots, colour coded according to marker and sample. In this manuscript, I introduce a novel exploratory data analysis and visualisation method that is centred around a novel quasi-distance (DensityMorph) between single cell samples. DensityMorph makes it possible to plot single cell samples in a manner analogous to performing principal component analysis on microarray samples. Biological interpretation is ensured by the introduction of Explanatory Components, which show how marker expression and coexpression drive the differences between samples. This method is a breakthrough in terms of displaying the most pertinent biological changes across single cell samples in a compact plot. Finally, it can be used either as a stand-alone method or to structure other types of analysis such as manual flow cytometry gating or cell population clustering.


title: Biological Insights Knowledge Graph: an integrated knowledge graph to support drug development

abstract: The use of knowledge graphs as a data source for machine learning methods to solve complex problems in life sciences has rapidly become popular in recent years. Our Biological Insights Knowledge Graph (BIKG) combines relevant data for drug development from public as well as internal data sources to provide insights for a range of tasks: from identifying new targets to repurposing existing drugs. Besides the common requirements to organisational knowledge graphs such as being able to capture the domain precisely and give the users the ability to search and query the data, the focus on handling multiple use cases and supporting use case-specific machine learning models presents additional challenges: the data models must also be streamlined for the performance of downstream tasks; graph content must be easily customisable for different use cases; different projections of the graph content are required to support a wider range of different consumption modes. In this paper we describe our main design choices in implementation of the BIKG graph and discuss different aspects of its life cycle: from graph construction to exploitation.

category: systems biology


title: Variations in EEG predicts the individual differences in social tasks

abstract: People experience events and form an impression of others in a way that is affected by social influence every day. In the present study, we designed a series of tasks centered on social influence to investigate peoples bias in following others opinions and its underlying neural predictors. Our results showed social conformity and proved that social influence-induced change can be predicted by the amount of inter-trial electroencephalogram (EEG) variations when people view others faces. This prediction effect is robust in the alpha-band over the right frontal and left occipital electrodes for negative influence. Inter-trial EEG variations can also predict the subsequent trust difference between negatively and positively influenced faces. Our findings suggest that higher Inter-trial EEG variations in the pre-influence task may serve as a predictor of high vulnerability to social influence. The present study provides a novel approach that considers both the stability of ones endogenous EEG and the variations in external task components to predict human social behaviors.

category: neuroscience


title: Variations in EEG predict the individual differences in social tasks


title: Inter-trial Variations in EEG predict the individual differences in social tasks


title: Inter-trial variations in EEG predict the individual differences in social tasks


title: Mean field approximation of network of biophysical neurons driven by conductance-based ion exchange dynamics

abstract:
Numerous network and whole brain modeling approaches make use of mean-field models. Their relative simplicity allows studying network dynamics at a large scale. They correspond to lumped descriptions of neuronal assemblies connected via synapses. mean-field models do not consider the ionic composition of the extracellular space, which can change in physiological and pathological conditions, with strong effects on neuron activity. Here we derive a mean-field model of a population of Hodgkin-Huxley type neurons, which links the neuronal intra- and extra-cellular ion concentrations to the mean membrane potential and the mean synaptic input in terms of the synaptic conductance. The model can generate various physiological brain activities including multi-stability at resting states, as well as pathological spiking and bursting behaviors, and depolarization block. The results from the analytical solution of the mean-field model agree with the mean behavior of numerical simulations of large-scale networks of neurons. The mean-field model is analytically exact for non-autonomous ion concentration variables and provides a mean-field approximation in the thermodynamic limit, for locally homogeneous mesoscopic networks of biophysical neurons driven by an ion-exchange mechanism. These results may provide the missing link between high-level neural mass approaches which are used in the brain network modeling and physiological parameters that drive the neuronal dynamics.

Significance StatementIn this study, we applied mathematical formalism to estimate the mean-field behaviors of a large neuronal ensemble taking into account the ion-exchange between the intracellular and extracellular space. The model demonstrates different brain activities including resting state, spiking behavior, and seizure, as a function of the extracellular ion concentration. The relevant parameter regime for different brain activities is extracted mainly in terms of ion concentration and heterogeneity of individual neurons in the network. This neural mass model enables studying the influence of changes in extracellular ionic conditions on whole brain dynamics in health and disease. The effect of external stimulus current and conductance-based coupling of neural masses are also analyzed.


title: Mean-field approximation of network of biophysical neurons driven by conductance-based ion exchange


title: Finger representations in primary somatosensory cortex are modulated during vibrotactile working memory

abstract:
It is well-established that several cortical areas represent vibrotactile stimuli in somatotopic maps. However, whether such somatotopic representations remain active during the delay period of working memory (WM) tasks, i.e. in the absence of any tactile stimulation, is unknown. In our experiment, participants had to compare two tactile stimuli with different vibration frequencies that were separated by a delay period (memory condition) or they were exposed to identical stimuli but did not have to solve a WM task (no memory condition). Importantly, both vibrotactile stimuli were either applied to the right index or little finger. Analyzing the delay period, we identified a well-known fronto-parietal network of brain regions involved in WM but we did not find WM specific activity in S1. However, using multi-voxel pattern analysis (MVPA) and representational similarity analysis (RSA), we found that S1 finger representations were more dissimilar during the delay period of the WM condition than during the control condition. These results indicate that WM processes modulate the representational geometry of S1 suggesting that some aspects of the tactile WM content are represented in a somatotopic fashion.

HIGHLIGHTSO_LIMultivariate approaches were used to identify finger specific representational changes during vibrotactile frequency discrimination.
C_LIO_LIVibrotactile working memory modulates somatotopic finger representations in contralateral S1 during the delay period, i.e. in the absence of any tactile stimuli
C_LI


title: Finger representations in primary somatosensory cortex are modulated during vibrotactile working memory task


title: Co-allocation to overlapping dendritic branches in the retrosplenial cortex integrates contextual memories across time

abstract:
Events occurring close in time are often linked in memory, providing an episodic timeline and a framework for those memories. Recent studies suggest that memories acquired close in time are encoded by overlapping neuronal ensembles, but whether dendritic plasticity plays a role in linking memories is unknown. Using activity-dependent labeling and manipulation, as well as longitudinal one- and two-photon imaging of RSC somatic and dendritic compartments, we show that memory linking is not only dependent on ensemble overlap in the retrosplenial cortex, but also on branch-specific dendritic allocation mechanisms. These results demonstrate a causal role for dendritic mechanisms in memory integration and reveal a novel set of rules that govern how linked, and independent memories are allocated to dendritic compartments.

One-Sentence SummaryDendritic allocation mechanisms link distinct memories across time


title: A retrograde mechanism coordinates memory allocation across brain regions

abstract: Memories engage ensembles of neurons across different brain regions within a memory system. However, it is unclear whether the allocation of a memory to these ensembles is coordinated across brain regions. To address this question, we used CREB expression to bias memory allocation in one brain region, and rabies retrograde tracing to test memory allocation in connected presynaptic neurons in the other brain regions. We find that biasing allocation of CTA memory in the basolateral amygdala (BLA) also biases memory allocation in presynaptic neurons of the insular cortex (IC). By manipulating the allocation of CTA memory to specific neurons in both BLA and IC, we found that we increased their connectivity and enhanced CTA memory performance. These results - which are corroborated by mathematical simulations, and by studies with auditory fear conditioning - demonstrate that a retrograde mechanism coordinates the allocation of memories across different brain regions.


title: Analysis of cellular and synaptic mechanisms behind spontaneous cortical activity in vitro: Insights from optimization of spiking neuronal network models

abstract:
Spontaneous network bursts, the intervals of intense network-wide activity interleaved with longer periods of sparse activity, are a hallmark phenomenon observed in cortical networks at postnatal developmental stages. Generation, propagation and termination of network bursts depend on a combination of synaptic, cellular and network mechanisms; however, the interplay between these mechanisms is not fully understood. We study this interplay in silico, using a new data-driven framework for generating spiking neuronal networks fitted to the microelectrode array recordings. We recorded the network bursting activity from rat postnatal cortical networks under several pharmacological conditions. In each condition, the function of specific excitatory and inhibitory synaptic receptors was reduced in order to examine their impact on global network dynamics. The obtained data was used to develop two complementary model fitting protocols for automatic model generation. These protocols allowed us to disentangle systematically the modeled cellular and synaptic mechanisms that affect the observed network bursts. We confirmed that the change in excitatory and inhibitory synaptic transmission in silico, consistent with pharmacological conditions, can account for the changes in network bursts relative to the control data. Reproducing the exact recorded network bursts statistics required adapting both the synaptic transmission and the cellular excitability separately for each pharmacological condition. Our results bring new understanding of the complex interplay between cellular, synaptic and network mechanisms supporting the burst dynamics. While here we focused on analysis of in vitro data, our approach can be applied ex vivo and in vivo given that the appropriate experimental data is available.

New & NoteworthyWe studied the role of synaptic mechanisms in shaping the neural population activity by proposing a new method to combine experimental data and data-driven computational modeling based on spiking neuronal networks. We analyze a dataset recorded from postnatal rat cortical cultures in vitro under the pharmacological influence of excitatory and inhibitory synaptic receptor antagonists. Our computational model identifies neurobiological mechanisms necessary to reproduce the changes in population activity seen across pharmacological conditions.


title: Overdominant and partially dominant mutations drive short-term adaptation in diploid yeast

abstract: Identification of adaptive targets in experimental evolution typically relies on extensive replication and allele reconstructions. An alternative approach is to directly assay all mutations in an evolved clone by generating pools of segregants that contain random combinations of the evolved mutations. Here, we apply this method to 6 clones isolated from 4 diploid populations that were clonally evolved for 2,000 generations in rich glucose medium. Each clone contains [~]20-25 mutations relative to the ancestor. We derived intermediate genotypes between the founder and the evolved clones by bulk mating sporulated cultures of each evolved clone to a barcoded haploid version of the founder. We competed the barcoded segregants en masse and quantified the fitness of each barcode. We estimated average fitness effects of evolved mutations using barcode fitness and whole genome sequencing for a subset of segregants or time-course whole population whole genome sequencing. In contrast to our previous work in haploid populations, we find that diploids carry fewer evolved mutations with a detectable fitness effect (6%), contributing a modest fitness advantage (up to 5.4%). In agreement with theoretical expectations, reconstruction experiments show that all adaptive mutations manifest some degree of dominance over the ancestral allele, and most are overdominant. Competition assays under conditions that deviated from the evolutionary environment show that adaptive mutations are often pleiotropic.

category: evolutionary biology


title: Comparative transcriptomics identifies the transcription factors BRANCHED1 and TCP4, as well as the microRNA miR166 as candidate genes involved in the evolutionary transition from dehiscent to indehiscent fruits in Lepidium (Brassicaceae)

abstract:
BackgroundFruits are the seed-bearing structures of flowering plants and are highly diverse in terms of morphology, texture and maturation. Dehiscent fruits split open upon maturation to discharge their seeds while indehiscent fruits are dispersed as a whole. Indehiscent fruits evolved from dehiscent fruits several times independently in the crucifer family (Brassicaceae). The fruits of Lepidium appelianum, for example, are indehiscent while the fruits of the closely related L. campestre are dehiscent. Here, we investigate the molecular and genetic mechanisms underlying the evolutionary transition from dehiscent to indehiscent fruits using these two Lepidium species as model system.

ResultsWe have sequenced the transcriptomes and small RNAs of floral buds, flowers and fruits of L. appelianum and L. campestre and analyzed differentially expressed genes (DEGs) and differently differentially expressed genes (DDEGs). DEGs are genes that show significantly different transcript levels in the same structures (buds, flowers and fruits) in different species, or in different structures in the same species. DDEGs are genes for which the change in expression level between two structures is significantly different in one species than in the other. Comparing the two species, the highest number of DEGs was found in flowers, followed by fruits and floral buds while the highest number of DDEGs was found in fruits versus flowers followed by flowers versus floral buds. Several gene ontology terms related to cell wall synthesis and degradation were overrepresented in different sets of DEGs highlighting the importance of these processes for fruit opening. Furthermore, the fruit valve identity genes FRUITFUL and YABBY3 were among the DEGs identified. Finally, the microRNA miR166 as well as the TCP transcription factors BRANCHED1 (BRC1) and TCP FAMILY TRANSCRIPTION FACTOR 4 (TCP4) were found to be DDEGs.

ConclusionsOur study reveals differences in gene expression between dehiscent and indehiscent fruits and uncovers miR166, BRC1 and TCP4 as possible causes for the evolutionary transition from dehiscent to indehiscent fruits in Lepidium.


title: Identifying Lethal Dependencies with HUGE Predictive Power from Large-Scale Functional Genomic Screens

abstract: Recent functional genomic screens -such as CRISPR-Cas9 or RNAi screening-have fostered a new wave of targeted treatments based on the concept of synthetic lethality. These approaches identified LEthal Dependencies (LEDs) by estimating the effect of genetic events on cell viability. The multiple-hypothesis problem related to the large number of gene knockouts limits the statistical power of these studies. Here, we show that predictions of LEDs from functional screens can be dramatically improved by incorporating the "HUb effect in Genetic Essentiality" (HUGE) of gene alterations. We analyze three recent genome-wide loss-of-function screens - Project Score, CERES score and DEMETER score-identifying LEDs with 75 times larger statistical power than using state-of-the-art methods. HUGE shows an increased enrichment in a recent harmonized knowledgebase of clinical interpretations of somatic genomic variants in cancer (with an AUROC up to 0.87). Our approach is effective even in tumors with large genetic heterogeneity such as acute myeloid leukemia, where we identified LEDs not recalled by previous pipelines, including FLT3-mutant genotypes sensitive to FLT3 inhibitors. Interestingly, in-vitro validations confirm lethal dependencies of either NRAS or PTPN11 depending on the NRAS mutational status. HUGE will hopefully help discover novel genetic dependencies amenable for precision-targeted therapies in cancer.


title: Anisotropic interaction and motion states of locusts in a hopper band

abstract: Swarming locusts present a quintessential example of animal collective motion. Juvenile locusts march and hop across the ground in coordinated groups called hopper bands. Composed of up to millions of insects, hopper bands exhibit coordinated motion and various collective structures. These groups are well-documented in the field, but the individual insects themselves are typically studied in much smaller groups in laboratory experiments. We present the first trajectory data that detail the movement of individual locusts within a hopper band in a natural setting. Using automated video tracking, we derive our data from footage of four distinct hopper bands of the Australian plague locust, Chortoicetes terminifera. We reconstruct nearly twentythousand individual trajectories composed of over 3.3 million locust positions. We classify these data into three motion states: stationary, walking, and hopping. Distributions of relative neighbor positions reveal anisotropies that depend on motion state. Stationary locusts have high-density areas distributed around them apparently at random. Walking locusts have a low-density area in front of them. Hopping locusts have low-density areas in front and behind them. Our results suggest novel interactions, namely that locusts change their motion to avoid colliding with neighbors in front of them.

category: animal behavior and cognition


title: Comprehensive analysis of behavioral dynamics in the protochordate Ciona intestinalis

abstract:
Vertebrate nervous systems can generate a remarkable diversity of behaviors. However, our understanding of how behaviors may have evolved in the chordate lineage is limited by the lack of neuroethological studies leveraging our closest invertebrate relatives.

Here we combine high-throughput video acquisition with pharmacological perturbations of bioamine signaling to systematically reveal the global structure of the motor behavioral repertoire in the Ciona intestinalis larvae. Most of Cionas postural variance can be captured by six basic shapes, which we term "Eigencionas". Motif analysis of postural time series further demonstrated that bioamines influence numerous stereotyped behavioral maneuvers including "startle-like" and "beat-and-glide". Employing computational modeling of swimming dynamics and spatio-temporal embedding of postural features revealed that subtle behavioural differences are generated at the levels of motor modules and the transitions between, both modulated by bioamines. Finally, we show that flexible motor module usage gives rise to diverse behaviors in response to different light stimuli.


title: Particle interactions and their effect on magnetic particle imaging and spectroscopy

abstract: Tracer and thus signal stability is crucial for an accurate diagnosis via magnetic particle imaging (MPI). However, MPI-tracer nanoparticles frequently agglomerate during their in vivo applications leading to particle interactions. Here, we investigate the influence of such magnetic coupling phenomena on the MPI signal. We prepared and characterized Zn0.4Fe2.6O4 nanoparticles and controlled their interparticle distance by variying SiO2 coating thickness. The silica shell affected the magnetic properties indicating stronger particle interactions for a smaller interparticle distance. The SiO2-coated Zn0.4Fe2.6O4 outperformed the bare sample in magnetic particle spectroscopy (MPS) in terms of signal/noise, however, the shell thickness itself only weakly influenced the MPS signal. To investigate the importance of magnetic coupling effects in more detail, we benchmarked the MPS signal of the bare and SiO2-coated Zn-ferrites against commercially available PVP-coated Fe3O4 nanoparticles in water and PBS. PBS is known to destabilize nanoparticles mimicking an agglomeration in vivo. The bare and coated Zn-ferrites showed excellent signal stability, despite their agglomeration in PBS. We attribute this to their aggregated morphology formed during their flame-synthesis. On the other hand, the MPS signal of commercial PVP-coated Fe3O4 strongly decreased in PBS compared to water, indicating strongly changed particle interactions. The relevance of this effect was further investigated in a mammalian cell model. For PVP-coated Fe3O4, we could detect a strong discrepancy between the particle concentration obtained from the MPS signal and the actual concentration determined via ICP-MS. The same trend was observed during their MPI analysis; while SiO2-coated Zn-ferrites could be precisely located in water and PBS, PVP-coated Fe3O4 could not be detected in PBS at all. This drastically limits the sensitivity and also general applicability of MPI using such standard commercial tracers and highlights the advantages of our flame-made Zn-ferrites concerning signal stability and ultimately diagnostic accuracy.


title: Development and Validation of Subject-Specific 3D Human Head Models Based on a Nonlinear Visco-Hyperelastic Constitutive Framework

abstract: Computational models of the human head are promising tools for the study and prediction of traumatic brain injuries (TBIs). Most available head models are developed using inputs (i.e., head geometry, material properties, and boundary conditions) derived from ex-vivo experiments on cadavers or animals and employ linear viscoelasticity (LVE)-based constitutive models, which leads to high uncertainty and poor accuracy in capturing the nonlinear response of brain tissue under impulsive loading conditions. To resolve these issues, a framework for the development of fully subject-specific 3D human head models is proposed, in which model inputs are derived from the same living human subject using a comprehensive in-vivo brain imaging protocol, and the viscous dissipation-based visco-hyperelastic constitutive modeling framework is employed. Specifically, brain tissue material properties are derived from in-vivo magnetic resonance elastography (MRE), and full-field strain-response of brain under rapid rotational acceleration is obtained from tagged MRI, which is used for model validation. The constitutive model comprises the Ogden hyperelastic strain energy density and the Upadhyay-Subhash-Spearot viscous dissipation potential. The simulated strain-response is compared with experimental data and with predictions from subject-specific models employing two commonly used LVE-based constitutive models, using a rigorous validation procedure that evaluates agreement in spatial strain distribution, temporal strain evolution, and differences in maximum values of peak and average strain. Results show that the head model developed in this work reasonably captures 3D brain dynamics, and when compared to LVE-based models, provides improvements in the prediction of peak strains and temporal strain evolution.


title: Essential elements of radical pair magnetosensitivity in Drosophila

abstract: Many animals use the Earths magnetic field (geoMF) for navigation1. The favored mechanism for magnetosensitivity involves a blue-light (BL) activated electron transfer reaction between flavin adenine dinucleotide (FAD) and a chain of tryptophan (Trp) residues within the photoreceptor protein, CRYPTOCHROME (CRY). The spin-state of the resultant radical pair (RP) and hence the concentration of CRY in its active state is influenced by the geoMF2. The canonical CRY-centric radical pair mechanism (RPM) does not, however, explain many physiological and behavioural observations2-8. Here, using electrophysiology and behavioural analyses, we assay magnetic field (MF) responses at single neuron and organismal level. We show that the 52 C-terminal (CT) amino acids of CRY, which are missing the FAD binding domain and the Trp chain, are sufficient to facilitate magnetoreception. We also show that increasing intracellular FAD potentiates both BL-induced and MF-dependent effects on the activity mediated by the CT. Additionally, high levels of FAD alone are sufficient to cause BL neuronal sensitivity and, remarkably, potentiation of this response in the co-presence of a MF. These unexpected results reveal the essential components of a primary magnetoreceptor in flies, providing strong evidence that non-canonical (i.e., non-CRY-dependent) RPs can elicit MF responses in cells.

category: physiology


title: Where is the money? Dynamics in feedback processing and attention during spatial probabilistic learning

abstract: Learned feature-based stimulus-reward-associations can modulate behavior and the underlying neural processing of information. In our study, we investigated the neurocognitive mechanisms underlying learning of spatial stimulus-reward-associations. Participants performed a probabilistic spatial reward-learning task that required participants, within 40 trials, to learn which out of four locations on a computer screen yielded the most gain-feedback when chosen. Our behavioral findings show that participants learned to choose which location was most rewarding. Those findings were paralleled by significant amplitude differences in event-related potentials (ERPs) elicited by the presentation of loss and gain feedback; the amplitude of the feedback-related negativity (FRN) was more negative in response to loss feedback compared to gain feedback, but showed no modulation by trial-number. On the other hand, the late positive component (LPC), became larger in response to losses as the learning-set progressed, but smaller in response to gains. Additionally, immediately following feedback presentation, brain activity in the visual cortex - read out through alpha frequency oscillations measured over occipital sites - was predictive of the amplitude of the N2pc ERP component, a marker of spatial attention orienting, observed on the next trial. Taken together, we elucidated neurocognitive dynamics underlying feedback processing in spatial reward learning, and the subsequent effects that spatial stimulus-reward association learning have on spatial attention.


title: Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience

abstract: Integrating data from multiple experiments is common practice in systems neuroscience but it requires inter-experimental variability to be negligible compared to the biological signal of interest. This requirement is rarely fulfilled; systematic changes between experiments can drastically affect the outcome of complex analysis pipelines. Modern machine learning approaches designed to adapt models across multiple data domains offer flexible ways of removing inter-experimental variability where classical statistical methods often fail. While applications of these methods have been mostly limited to single-cell genomics, in this work, we develop a theoretical framework for domain adaptation in systems neuroscience. We implement this in an adversarial optimization scheme that removes inter-experimental variability while preserving the biological signal. We compare our method to previous approaches on a large-scale dataset of two-photon imaging recordings of retinal bipolar cell responses to visual stimuli. This dataset provides a unique benchmark as it contains biological signal from well-defined cell types that is obscured by large inter-experimental variability. In a supervised setting, we compare the generalization performance of cell type classifiers across experiments, which we validate with anatomical cell type distributions from electron microscopy data. In an unsupervised setting, we remove inter-experimental variability from data which can then be fed into arbitrary downstream analyses. In both settings, we find that our method achieves the best trade-off between removing inter-experimental variability and preserving biological signal. Thus, we offer a flexible approach to remove inter-experimental variability and integrate datasets across experiments in systems neuroscience. Code available at https://github.com/eulerlab/rave.


title: Post-mating Refractoriness in Drosophila melanogaster Depends Upon Ecdysis Triggering Hormone Signaling

abstract: An individuals decision to engage in courtship depends on external cues from potential mates and internal cues related to maturation, health, and experience. Hormones allow such information to be conveyed to distal tissues in a coordinated fashion. Here, we show Ecdysis-Triggering Hormone (ETH) is a regulator of male courtship in Drosophila melanogaster, and critical for mate choice and courtship inhibition after the completion of copulation. Preventing ETH release increases male-male courtship and decreases post-copulation courtship inhibition (PCCI). Such aberrant male courtship behavior in ETH-deficient males appears to be the consequence of inabilityto integrate pheromone cues into decision making. Silencing of ETH receptor (ETHR) in GR32A-expressing neurons leads to reduced ligand sensitivity and elevated male-male courtship. We find OR67D is critical for suppression of courtship after mating, and ETHR silencing in OR67D-expressing neurons, and GR32A-expressing neurons to a lesser degree, elevates post-copulation courtship. Finally, ETHR silencing in the corpus allatum increases post-copulation courtship; treatment of with juvenile hormone analog partially restores normal post-mating behavior. ETH, a stress-sensitive reproductive hormone, appears to coordinate multiple sensory modalities to guide Drosophila male courtship behaviors, especially after mating.


title: Cycles of transcription and local translation consolidate Arc protein at dendritic sites

abstract: Long-term memory requires transcription and translation of activity-regulated genes. Many of these are immediate early genes (IEGs) with short-lived mRNAs and proteins, decaying rapidly after stimulation. It remains unknown how an IEG with rapid mRNA and protein turnover can impact long-lasting changes at the synapses. Using fluorescently tagged endogenous Arc, an IEG important for memory consolidation, we performed high-resolution imaging of transcription and translation in individual neurons to identify the long-term gene dynamics after stimulation. Unexpectedly, once induced, Arc underwent transcriptional reactivation often at the same allele. Cycles of transcription were coordinated with localized translation. This cyclical regulation of an IEG, dependent on protein synthesis, reactivates subsequent transcription for maintaining mRNA supply to dendrites. The ensuing Arc mRNAs were preferentially localized at sites marked by previous Arc protein, thereby consolidating local "hubs" of dendritic Arc. These findings revealed the spatio-temporal dynamics of transcription-translation coupling of an IEG and provide a mechanism by which short-lived synaptic proteins can be sustained over the long-time scales of memory consolidation.


title: Cycles of transcription and local translation support molecular long-term memory in the hippocampus


title: IMPACT OF ADOLESCENT INTERMITTENT ETHANOL EXPOSURE IN MALE AND FEMALE RATS ON SOCIAL DRINKING AND NEUROPEPTIDE GENE EXPRESSION

abstract:
BackgroundAlcohol use during adolescence can alter maturational changes that occur in brain regions associated with social and emotional responding. Our previous studies have shown that adult male, but not female rats demonstrate social anxiety-like alterations and enhanced sensitivity to ethanol-induced social facilitation following adolescent intermittent ethanol (AIE) exposure. These consequences of AIE may influence adult social drinking in a sex-specific manner.

MethodsTo test effects of AIE on social drinking, male and female Sprague-Dawley rats exposed to water or ethanol [0 or 4 g/kg, intragastrically, every other day, between postnatal day (P) 25 and 45] were tested as adults (P72-83) in a social drinking paradigm (30-minute access to a 10% ethanol solution in supersac or supersac alone in groups of three same-sex littermates across two 4-day cycles separated by 4 days off). Social behavior was assessed during the last drinking session, with further assessment of oxytocin (OXT), oxytocin receptor (OXTR), vasopressin (AVP) and vasopressin receptors 1a and 1b (AVPR1a, AVPR1b) in the hypothalamus and lateral septum.

ResultsMales exposed to AIE consumed more ethanol than water-exposed controls during the second drinking cycle, whereas AIE did not affect supersac intake in males. AIE-exposed females consumed less ethanol and more supersac than water-exposed controls. Water-exposed females drinking ethanol showed more social investigation as well as significantly higher hypothalamic OXTR, AVP, and AVPR1b gene expression than their counterparts ingesting supersac and AIE females drinking ethanol. In males, hypothalamic AVPR1b gene expression was affected by drinking solution, with significantly higher expression evident in males drinking ethanol than those consuming supersac.

ConclusionsCollectively, these findings provide new evidence regarding sex-specific effects of AIE on social drinking and suggest that the hypothalamic OXT and AVP systems are implicated in the effects of ingested ethanol on social behavior in a sex- and adolescent exposure-dependent manner.


title: Joint modeling of choices and reaction times based on Bayesian contextual behavioral control

abstract: In cognitive neuroscience and psychology, reaction times are an important behavioral measure. However, in instrumental learning and goal-directed decision making experiments, findings often rely only on choice probabilities from a value-based model, instead of reaction times. Recent advancements have shown that it is possible to connect value-based decision models with reaction time models, for example in a joint reinforcement learning and diffusion decision model. We propose a novel joint model of both choices and reaction times by combining a mechanistic account of Bayesian sequential decision making with a sampling procedure. Specifically, we use a recent context-specific Bayesian forward planning model which we extend by an MCMC sampler to obtain both choices and reaction times. We show that we can explain and reproduce a rather wide range of well-known experimental findings in value based-decision making as well as classical inhibition and switching tasks. First, we use the proposed model to explain how instrumental learning and automatized behavior result in decreased reaction times and improved accuracy. Second, we reproduce classical results in the Eriksen flanker task. Third, we reproduce established findings in task switching. These findings show that the proposed joint behavioral model may describe common underlying processes in all these types of decision making paradigms.


title: Synchronization through uncorrelated noise in excitatory-inhibitory networks

abstract: Gamma rhythms play a major role in many different processes in the brain, such as attention, working memory and sensory processing. While typically considered detrimental, counterintuitively noise can sometimes have beneficial effects on communication and information transfer. Recently, Meng and Riecke showed that synchronization of interacting networks of inhibitory neurons in the gamma band increases while synchronization within these networks decreases when neurons are subject to uncorrelated noise. However, experimental and modeling studies point towards an important role of the pyramidal-interneuronal network gamma (PING) mechanism in the cortex. Therefore, we investigated the effect of uncorrelated noise on the communication between excitatory-inhibitory networks producing gamma oscillations via a PING mechanism. Our results suggest that synaptic noise can have a supporting role in facilitating inter-regional communication and that noise-induced synchronization between networks is generated via a different mechanism than when synchronization is mediated by strong synaptic coupling. Noise-induced synchronization is achieved by lowering synchronization within networks which allows the respective other network to impose its own gamma rhythm resulting in synchronization between networks.


title: Invariant neural subspaces maintained by feedback modulation

abstract: Sensory systems reliably process incoming stimuli in spite of changes in context. Most recent models accredit this context invariance to an extraction of increasingly complex sensory features in hierarchical feedforward networks. Here, we study how context-invariant representations can be established by feedback rather than feedforward processing. We show that feedforward neural networks modulated by feedback can dynamically generate invariant sensory representations. The required feedback can be implemented as a slow and spatially diffuse gain modulation. The invariance is not present on the level of individual neurons, but emerges only on the population level. Mechanistically, the feedback modulation dynamically reorients the manifold of neural activity and thereby maintains an invariant neural subspace in spite of contextual variations. Our results highlight the importance of population-level analyses for understanding the role of feedback in flexible sensory processing.


title: Age-related response speed deficits arise from specific impairments in sensory evidence accumulation rate

abstract: Older adults exposed to enriched environments (EE) maintain relatively higher levels of cognitive function, even in the face of compromised markers of brain health. Response speed (RS) is often used as a simple proxy to measure the preservation of global cognitive function in older adults. However, it is unknown which specific sensory, decision, and/or motor processes provide the most specific indices of neurocognitive health. Here, using a simple decision task with electroencephalography (EEG), we found that the efficiency with which an individual accumulates sensory evidence was a critical determinant of the extent to which RS was preserved in older adults. Moreover, the mitigating influence of EE on age-related RS declines was most pronounced when evidence accumulation rates were shallowest. Our results suggest that EEG metrics of evidence accumulation may index neurocognitive vulnerability of the ageing brain.


title: Intragenomic variation in mutation biases causes underestimation of selection on synonymous codon usage

abstract: Patterns of non-uniform usage of synonymous codons (codon bias) varies across genes in an organism and across species from all domains of life. The bias in codon usage is due to a combination of both non-adaptive (e.g. mutation biases) and adaptive (e.g. natural selection for translation efficiency/accuracy) evolutionary forces. Most population genetics models quantify the effects of mutation bias and selection on shaping codon usage patterns assuming a uniform mutation bias across the genome. However, mutation biases can vary both along and across chromosomes due to processes such as biased gene conversion, potentially obfuscating signals of translational selection. Moreover, estimates of variation in genomic mutation biases are often lacking for non-model organisms. Here, we combine an unsupervised learning method with a population genetics model of synonymous codon bias evolution to assess the impact of intragenomic variation in mutation bias on the strength and direction of natural selection on synonymous codon usage across 49 Saccharomycotina budding yeasts. We find that in the absence of a priori information, unsupervised learning approaches can be used to identify regions evolving under different mutation biases. We find that the impact of intragenomic variation in mutation bias varies widely, even among closely-related species. We show that the overall strength and direction of selection on codon usage can be underestimated by failing to account for intragenomic variation in mutation biases. Interestingly, genes falling into clusters identified by machine learning are also often physically clustered across chromosomes, consistent with processes such as biased gene conversion. Our results indicate the need for more nuanced models of sequence evolution that systematically incorporate the effects of variable mutation biases on codon frequencies.


title: Sex and Estrous Cycle in Memory for Sequences of Events in Rats

abstract: The ability to remember sequences of events is fundamental to episodic memory. While rodent studies have examined sex and estrous cycle in episodic-like spatial memory tasks, little is known about these biological variables in memory for sequences of events that depend on representations of temporal context. We investigated the role of sex and estrous cycle in rats during all training and testing stages of a cross-species validated sequence memory task (Jayachandran et al., 2019). Rats were trained on a task composed of two sequences, each with four unique odors delivered on opposite ends of a linear track. Training occurred in six successive stages starting with learning to poke in a nose port for [≥]1.2s; eventually demonstrating sequence memory by holding their nose in the port for [≥]1s for in-sequence odors and <1s for out-of-sequence odors in order to receive a water reward. Performance was analyzed across sex and estrous cycle (proestrus, estrus, metestrus, and diestrus), the latter being determined by the cellular composition of a daily vaginal lavage. We found no evidence of sex differences in asymptotic sequence memory performance, similar to published data in humans performing the analogous task (Reeders et al., 2021). Likewise, we found no differences in performance across the estrous cycle. One minor difference was that female rats tended to have slightly longer poke times, while males had slightly more short poke times but this did not affect their decisions. These results suggest sex and estrous cycle are not major factors in sequence memory capacities.


title: Epigenomic and transcriptomic prioritization of candidate obesity-risk regulatory GWAS SNPs

abstract: Concern about rising rates of obesity has prompted searches for its genetic risk determinants in genome-wide association studies (GWAS). Most genetic variants that contribute to the increased risk of a given trait are probably regulatory single nucleotide polymorphisms (SNPs). However, identifying plausible regulatory SNPs is difficult because of their varied locations relative to their target gene and linkage disequilibrium, which makes most GWAS-derived SNPs only proxies for many fewer functional SNPs. We developed a systematic approach to prioritizing GWAS-derived obesity SNPs using detailed epigenomic and transcriptomic analysis in adipose tissue vs. heterologous tissues. From 50 obesity-related GWAS and 121,064 expanded SNPs, we prioritized 47 potential causal regulatory SNPs (Tier-1 SNPs) for 14 gene loci. A detailed examination of seven of these genes revealed that four (CABLES1, PC, PEMT, and FAM13A) had Tier-1 SNPs that might regulate alternative use of transcription start sites resulting in different polypeptides being generated or different amounts of an intronic microRNA gene being expressed. HOXA11 and long noncoding RNA gene RP11-392O17.1 had Tier-1 SNPs in their 3 or promoter region, respectively, and strong preferences for expression in subcutaneous vs. visceral adipose tissue. ZBED3-AS1 had two intragenic Tier-1 SNPs, each of which might contribute to mediating obesity risk through modulating long-distance chromatin interactions. We conclude that prioritization of regulatory SNP candidates should focus on their surrounding epigenetic features in a trait-relevant tissue. Our approach not only revealed especially credible novel regulatory SNPs, but also helped evaluate previously highlighted obesity GWAS SNPs that were candidates for transcription regulation.


title: Oral Lichen Planus and its relation with Oral Squamous Cell Carcinoma: new insights into the potential for malignant transformation

abstract: Oral Lichen Planus (OLP) is a chronic inflammatory disorder of unknown etiology. However, evidence suggests that it consists of an immunological process that leads to degeneration of the keratinocytes in the basal layer of the oral mucosa. Despite being recognized by WHO as a potentially malignant disorder with progression to oral squamous cell carcinoma (OSCC), the relationship between both pathologies is still controversial. Different studies have investigated factors associated with the potential for malignant transformation of OLP but it remains unclear. Through a bioinformatics approach, we investigated similarities in gene expression profiles of OLP and OSCC in early and advanced stages. Our results revealed gene expression patterns related to processes of keratinization, keratinocyte differentiation, cell proliferation and immune response in common between OLP and early and advanced OSCC, with the cornified envelope formation and antigen processing cross-presentation pathways in common between OLP and early OSCC. Together, these results reveal that key genes such as PI3, SPRR1B and KRT17, in addition to genes associated with different immune processes such as CXCL-13, HIF1A and IL1B may be involved in this oncogenic process. In addition, we performed an analysis of differentially and co-expressed genes and proposed putative therapeutic targets and associated drugs.


title: LNCRNA expression landscape and specificity between brain regions

abstract: Long noncoding RNAs (lncRNAs) are transcribed into low potential protein coding RNA molecules, which account for over 70% of mammalian transcriptional products. The role of lncRNAs and their expression is still largely unknown, and the subject of recent investigations. Here, we used bulk RNA sequencing data from the Genotype-Tissue Expression (GTEx) project to reveal the occurrence and identify the specificity of lncRNAs in 13 brain regions (1000 samples). We observed that these highly specific lncRNA were co-expressed with previously known mRNA markers for the 13 study regions of the brain. Further investigation revealed that splicing could influence the divergent biogenesis and enrichment of specific lncRNA alleles in different brain regions. Overall, we demonstrate the use of lncRNA as an independent tool for deconvolving brain regions and further highlights its use for cell-type identification from bulk transcriptome data.


title: Multi-attribute Glycan Identification and FDR Control for Glycoproteomics

abstract: Rapidly improving methods for glycoproteomics have enabled increasingly large-scale analyses of complex glycopeptide samples, but annotating the resulting mass spectrometry data with high confidence remains a major bottleneck. We recently introduced a fast and sensitive glycoproteomics search method in our MSFragger search engine, which reports glycopeptides as a combination of a peptide sequence and the mass of the attached glycan. In samples with complex glycosylation patterns, converting this mass to a specific glycan composition is not straightforward, however, as many glycans have similar or identical masses. Here, we have developed a new method for determining the glycan composition of N-linked glycopeptides fragmented by collision or hybrid activation that uses multiple sources of information from the spectrum, including observed glycan B- (oxonium) and Y-type ions and mass and precursor monoisotopic selection errors to discriminate between possible glycan candidates. Combined with false discovery rate estimation for the glycan assignment, we show this method is capable of specifically and sensitively identifying glycans in complex glycopeptide analyses and effectively controls the rate of false glycan assignments. The new method has been incorporated into the PTM-Shepherd modification analysis tool to work directly with the MSFragger glyco search in the FragPipe graphical user interface, providing a complete computational pipeline for annotation of N-glycopeptide spectra with FDR control of both peptide and glycan components that is both sensitive and robust against false identifications.


title: Development of a QSAR model to predict molecular inhibition of human STAT3

abstract: Herein is described a method to develop a QSAR model to predict the molecular inhibition of human STAT3. The model was built using machine learning using Python 3.3. A random forest machine learning algorithm was deployed. The model produced a R2 value of 0.86, indicating that our QSAR model is effective at predicting inhibitory compounds of STAT3.


title: Assessing Motivations and Barriers to Science Outreach within Academia: A Mixed-Methods Survey

abstract: The practice of science outreach is more necessary than ever. However, a disconnect exists between the stated goals for science outreach and its actual impact. In order to examine one potential source of this disconnect, we undertook a survey-based study to explore whether barriers to participation (either intrinsic or extrinsic) in science outreach exist within the academic community. We received responses to our survey from 530 individuals, the vast majority of whom engage in some type of science outreach activity on an annual basis. Those who engage in outreach report doing so for both personal and altruistic reasons, and having high (yet varied) levels of comfort with performing outreach activities. Respondents also report the existence of several significant yet surmountable barriers to participation, including lack of time and funding. Our findings demonstrate that both levels of participation in, and attitudes toward, science outreach within the academic community are generally favorable, suggesting that the general ineffectiveness of science outreach is due to other causes. We place our findings within the context of the broader science outreach, science communication and public engagement literature. We make recommendations on how existing approaches and infrastructure can, and must, be changed in order to improve the practice.

category: scientific communication and education


title: Fragmented Spatial Maps: State Abstraction and Efficient Planning from Surprisal

abstract: When animals explore spatial environments, their representations often fragment into multiple maps. What determines these map fragmentations, and can we predict where they will occur with simple principles? We pose the problem of fragmentation of an environment as one of (online) spatial clustering. Taking inspiration from the notion of a contiguous region in robotics, we develop a theory in which fragmentation decisions are driven by surprisal. When this criterion is implemented with boundary, grid, and place cells in various environments, it produces map fragmentations from the first exploration of each space. Augmented with a long-term spatial memory and a rule similar to the distance-dependent Chinese Restaurant Process for selecting among relevant memories, the theory predicts the reuse of map fragments in environments with repeating substructures. Our model provides a simple rule for generating spatial state abstractions and predicts map fragmentations observed in electrophysiological recordings. It further predicts that there should be "fragmentation decision" or "fracture" cells, which in multicompartment environments could be called "doorway" cells. Finally, we show that the resulting abstractions can lead to large (orders of magnitude) improvements in the ability to plan and navigate through complex environments.


title: Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human

abstract: Tetraplegia from spinal cord injury leaves many patients paralyzed below the neck, leaving them unable to perform most activities of daily living. Brain-machine interfaces (BMIs) could give tetraplegic patients more independence by directly utilizing brain signals to control external devices such as robotic arms or hands. The cortical grasp network has been of particular interest because of its potential to facilitate the restoration of dexterous object manipulation. However, a network that involves such high-level cortical areas may also provide additional information, such as the encoding of speech. Towards understanding the role of different brain areas in the human cortical grasp network, neural activity related to motor intentions for grasping and performing speech was recorded in a tetraplegic patient in the supramarginal gyrus (SMG), the ventral premotor cortex (PMv), and the somatosensory cortex (S1). We found that in high-level brain areas SMG and PMv, grasps were well represented by firing rates of neuronal populations already at visual cue presentation. During motor imagery, grasps could be significantly decoded from all brain areas. At identical neuronal population sizes, SMG and PMv achieved similar highly-significant decoding abilities, demonstrating their potential for grasp BMIs. During speech, SMG encoded both spoken grasps and colors, in contrast to PMv and S1, which were not able to significantly decode speech.These findings suggest that grasp signals can robustly be decoded at a single unit level from the cortical grasping circuit in human. Data from PMv suggests a specialized role in grasping, while SMGs role is broader and extends to speech. Together, these results indicate that brain signals from high-level areas of the human cortex can be exploited for a variety of different BMI applications.


title: Predictions and experimental tests of a new biophysical model of the mammalian respiratory oscillator

abstract: Previously our computational modeling studies (Phillips et al., 2019) proposed that neuronal persistent sodium current (INaP) and calcium-activated non-selective cation current (ICAN) are key biophysical factors that, respectively, generate inspiratory rhythm and burst pattern in the mammalian preBotzinger complex (preBotC) respiratory oscillator. Here, we experimentally tested and confirmed three predictions of the model from new simulations concerning the roles of INaP and ICAN: (1) INaP and ICAN blockade have opposite effects on the relationship between network excitability and preBotC rhythmic activity; (2) INaP is essential for preBotC rhythmogenesis; (3) ICAN is essential for generating the amplitude of rhythmic output but not rhythm generation. These predictions were confirmed via optogenetic manipulations of preBotC network excitability during graded INaP or ICAN blockade by pharmacological manipulations in neonatal mouse slices in vitro. Our results support and advance the hypothesis that INaP and ICAN mechanistically underlie rhythm and inspiratory burst pattern generation, respectively, in the isolated preBotC.


title: mTOR-neuropeptide Y signaling sensitizes nociceptors to drive neuropathic pain

abstract: Neuropathic pain is a refractory condition that involves de novo protein synthesis in the nociceptive pathway. The mechanistic target of rapamycin (mTOR) is a master regulator of protein translation; however, mechanisms underlying its role in neuropathic pain remain elusive. Using spared nerve injury-induced neuropathic pain model, we found that mTOR is preferentially activated in large-diameter dorsal root ganglion (DRG) neurons and spinal microglia. However, selective ablation of mTOR in DRG neurons, rather than microglia, alleviated neuropathic pain. We show that injury- induced mTOR activation promoted transcriptional induction of NPY likely via signal transducer and activator of transcription 3 (STAT3) phosphorylation. NPY further acted primarily on Y2 receptors (Y2R) to enhance nociceptor excitability. Peripheral replenishment of NPY reversed pain alleviation upon mTOR removal, whereas Y2R antagonists prevented pain restoration. Our findings reveal an unexpected link between mTOR and NPY in promoting nociceptor sensitization and neuropathic pain, through NPY/Y2R signaling-mediated intra-ganglionic transmission.


title: Evolutionary history limits species' ability to match color sensitivity to available habitat light

abstract: The spectrum of light that an animal sees - from ultraviolet to far red light - is governed by the number and wavelength sensitivity of a family of retinal proteins called opsins. It has been hypothesized that the spectrum of light available in an environment influences the range of colors that a species has evolved to see. However, invertebrates and vertebrates use phylogenetically distinct opsins in their retinae, and it remains unclear whether these distinct opsins influence what animals see, or how they adapt to their light environments. Systematically utilizing published visual sensitivity data from across animal phyla, we found that terrestrial animals are more sensitive to shorter and longer wavelengths of light than aquatic animals, and that invertebrates are more sensitive to shorter wavelengths of light than vertebrates. Controlling for phylogeny removes the effects of habitat and lineage on visual sensitivity. Closed and open habitat terrestrial species have similar spectral sensitivities when comparing across the Metazoa, and deep water animals are more sensitive to shorter wavelengths of light than shallow water animals. Our results suggest that animals do adapt to their light environment, however the invertebrate-vertebrate evolutionary divergence has limited the degree to which animals can perform visual tuning.


title: Blood pressure and the kidney cortex transcriptome response to high sodium diet challenge in female nonhuman primates

abstract:
Blood pressure (BP) is influenced by genetic variation and sodium intake. Ninety percent of Americans consume more than the AHA recommended amount of sodium. Studies on the impact of genetic variation and sodium intake on BP in nonhuman primates (NHP) to date have focused on males. We hypothesized that variation in renal transcriptional networks correlate with BP response to high dietary sodium in female baboons. Sodium-naive female baboons (n=7) were fed a low-sodium (LS) diet for 6 weeks followed by a high sodium (HS) diet for 6 weeks. Sodium intake, serum 17 betaestradiol, and ultrasound-guided kidney biopsies for RNA-Seq BP were collected at the end of each diet. BP was continuously measured for 64-hour periods throughout the study by implantable telemetry devices. On the LS diet, Na+ intake and serum 17 beta-estradiol concentration correlated with BP.

Kidney transcriptomes differed by diet; analysis by unbiased weighted gene co-expression network analysis revealed modules of genes correlated with BP on the HS diet. Cell type composition of renal biopsies was consistent among all animals for both diets. Network analysis of module genes showed causal networks linking hormone receptors, proliferation and differentiation, methylation, hypoxia, insulin and lipid regulation, and inflammation as regulators underlying variation in BP on the HS diet. Our results show variation in BP correlated with novel kidney gene networks with master regulators PPARG and MYC in female baboons on a HS diet. Identification of mechanisms underlying regulators that influence BP will inform better therapies towards greater precision medicine for women.

category: genomics