title: Perceptual Weighting of V1 Spikes Revealed by Optogenetic White Noise Stimulation

abstract:
During visually guided behaviors, mere hundreds of milliseconds can elapse between a sensory input and its associated behavioral response. How spikes occurring at different times are integrated to drive perception and action remains poorly understood. We delivered random trains of optogenetic stimulation (white noise) to excite inhibitory interneurons in V1 of mice while they performed a visual detection task. We then performed a reverse correlation analysis on the optogenetic stimuli to generate a neuronal-behavioral kernel: an unbiased, temporally-precise estimate of how suppression of V1 spiking at different moments around the onset of a visual stimulus affects detection of that stimulus. Electrophysiological recordings enabled us to capture the effects of optogenetic stimuli on V1 responsivity and revealed that the earliest stimulus-evoked spikes are preferentially weighted for guiding behavior. These data demonstrate that white noise optogenetic stimulation is a powerful tool for understanding how patterns of spiking in neuronal populations are decoded in generating perception and action.

Significance StatementHow the brain decodes dynamic neuronal responses to generate perception and behavior remains uncertain. A critical challenge is determining the relative contribution of spikes that occur at different times on the timescale of brain computations (tens of ms). Optogenetic tools permit causal investigations into neuronal-behavioral relationships, but are generally impractical for obtaining millisecond resolution. We circumvented this by delivering random (white noise) patterns of optogenetic inhibition to the primary visual cortex of behaving mice during visual tasks. Aligning optogenetic stimuli to task outcomes (hit, miss) yielded a neuronal-behavioral kernel - a temporal weighting that describes how inhibition at different moments impacts perception of visual stimuli. Thus, this method is a powerful tool for linking neuronal spiking, perception, and behavior.


title: Predicting the current and future distribution of four original plants of Gentianae Macrophyllae Radix in China under climate change scenarios

abstract: The wild resources of the four original plants (Gentiana crasicaulis Duthie ex Burk, Gentiana daurica Fisch, Gentiana straminea Maxim, and Gentiana macrophylla Pall) of Gentianae Macrophyllae Radix are becoming exhausted. Predicting the distribution under current and future climate scenarios is of significance for the sustainable utilization of resources and ecological protection. In this study, we constructed four species distribution models (SDMs) combining species distribution informations, 19 bioclimatic variables, and the maximum entropy (MaxEnt) model. The results showed that these 4 plants prefer a cool and humid climate. Under the future climate scenarios, the areas of the highly suitable habitats for Gentiana crasicaulis Duthie ex Burk and Gentiana daurica Fisch were likely to decrease, while Gentiana straminea Maxim was likely to expand, and Gentiana macrophylla Pall was less affected. In addition, the centroids of the highly suitable habitats for the four species shifted north or west. Most notably, most of the highly suitable habitats for the four species remained unchanged, which would be the preferred area for semi-artificial cultivation. The above information in this study would contribute to the development of reasonable strategies to reduce the impact of climate change on the four original plants.

category: ecology


title: Local adaptation and archaic introgression shape global diversity at human structural variant loci

abstract: Large genomic insertions, deletions, and inversions are a potent source of functional and fitness-altering variation, but are challenging to resolve with short-read DNA sequencing alone. While recent long-read sequencing technologies have greatly expanded the catalog of structural variants (SVs), their costs have so far precluded their application at population scales. Given these limitations, the role of SVs in human adaptation remains poorly characterized. Here, we used a graph-based approach to genotype 107,866 long-read-discovered SVs in short-read sequencing data from diverse human populations. We then applied an admixture-aware method to scan these SVs for patterns of population-specific frequency differentiation--a signature of local adaptation. We identified 220 SVs exhibiting extreme frequency differentiation, including several SVs that were among the lead variants at their corresponding loci. The top two signatures traced to separate insertion and deletion polymorphisms at the immunoglobulin heavy chain locus, together tagging a 325 Kbp haplotype that swept to high frequency and was subsequently fragmented by recombination. Alleles defining this haplotype are nearly fixed (60-95%) in certain Southeast Asian populations, but are rare or absent from other global populations composing the 1000 Genomes Project. Further investigation revealed that the haplotype closely matches with sequences observed in two of three high-coverage Neanderthal genomes, providing strong evidence of a Neanderthal-introgressed origin. This extraordinary episode of positive selection, which we infer to have occurred between 1700 and 8400 years ago, corroborates the role of immune-related genes as prominent targets of adaptive archaic introgression. Our study demonstrates how combining recent advances in genome sequencing, genotyping algorithms, and population genetic methods can reveal signatures of key evolutionary events that remained hidden within poorly resolved regions of the genome.

category: evolutionary biology


title: Comprehensive analysis of male-free reproduction in Monomorium triviale (Formicidae: Myrmicinae)

abstract: We report comprehensive evidence for obligatory thelytokous parthenogenesis in an ant Monomorium triviale. This species is characterized by distinct queen-worker dimorphism with strict reproductive division of labor: queens produce both workers and new queens without mating, whereas workers are completely sterile. We collected 333 nests of this species from 14 localities and three laboratory-reared populations in Japan. All wild queens dissected had no sperm in their spermathecae. Laboratory observation confirmed that virgin queens produced workers without mating. Furthermore, microsatellite genotyping showed identical heterozygous genotypes between mothers and their respective daughters, suggesting an extremely low probability of sexual reproduction. Microbial analysis detected no bacterial genera that are known to induce thelytokous parthenogenesis in Hymenoptera. Finally, the lack of variation in partial sequences of mitochondrial DNA among individuals sampled from across Japan suggests recent rapid spread or selective sweep. M. triviale would be a promising model system of superorganism-like adaptation through comparative analysis with well-studied sexual congeners, including the pharaoh ant M. pharaonis.

category: zoology


title: High-order areas and auditory cortex both represent the high-level event structure of music

abstract:
Recent fMRI studies of event segmentation have found that default mode regions represent high-level event structure during movie watching. In these regions, neural patterns are relatively stable during events and shift at event boundaries. Music, like narratives, contains hierarchical event structure (e.g., sections are composed of phrases). Here, we tested the hypothesis that brain activity patterns in default mode regions reflect the high-level event structure of music. We used fMRI to record brain activity from 25 participants (male and female) as they listened to a continuous playlist of 16 musical excerpts, and additionally collected annotations for these excerpts by asking a separate group of participants to mark when meaningful changes occurred in each one. We then identified temporal boundaries between stable patterns of brain activity using a hidden Markov model and compared the location of the model boundaries to the location of the human annotations. We identified multiple brain regions with significant matches to the observer-identified boundaries, including auditory cortex, medial prefrontal cortex, parietal cortex, and angular gyrus. From these results, we conclude that both higher-order and sensory areas contain information relating to the high-level event structure of music. Moreover, the higher-order areas in this study overlap with areas found in previous studies of event perception in movies and audio narratives, including regions in the default mode network.

Significance StatementListening to music requires the brain to track dynamics at multiple hierarchical timescales. In our study, we had fMRI participants listen to real-world music (classical and jazz pieces) and then used an unsupervised learning algorithm (a hidden Markov model) to model the high-level event structure of music within participants brain data. This approach revealed that default mode brain regions involved in representing the high-level event structure of narratives are also involved in representing the high-level event structure of music. These findings provide converging support for the hypothesis that these regions play a domain-general role in processing events occurring over long timescales.

category: neuroscience


title: Comparison of mouse models reveals the molecular bases for psychotic illness in Prader-Willi syndrome

abstract: Prader-Willi Syndrome (PWS) is a neurodevelopmental disorder caused by mutations affecting paternal chromosome 15q11-q13, and characterized by hypotonia, hyperphagia, impaired cognition and behavioural problems. Psychotic illness is a challenging problem for individuals with PWS and has different rates of prevalence in distinct PWS genotypes. Previously, we demonstrated behavioural and cognitive endophenotypes of relevance to psychiatric illness in a mouse model for one of the associated PWS genotypes, namely PWS-IC, in which deletion of the imprinting centre leads to loss of paternal imprinted gene expression and over-expression of Ube3a. Here we examine the broader gene expression changes that are specific to the psychiatric endophenotypes seen in this model. To do this we compared the brain transcriptomic profile of the PWS-IC mouse to the PWS-cr model that carries a deletion of the PWS minimal critical interval spanning the snoRNA Snord116 and Ipw. Firstly, we examined the same behavioural and cognitive endophenotypes of relevance to psychiatric illness in the PWS-cr mice. Unlike the PWS-IC mice, PWS-cr exhibit no differences in locomotor activity, sensory-motor gating, and attention. RNA-seq analysis of neonatal whole brain tissue revealed a greater number of transcriptional changes between PWS-IC and wild-type littermates, than between PWS-cr and wild-type littermates. Moreover, the differentially expressed genes in the PWS-IC brain were enriched for GWAS variants of episodes of psychotic illness but, interestingly, not schizophrenia. These data illustrate the molecular pathways that may underpin psychotic illness in PWS and have implication for potential therapeutic interventions.


title: Comparison of mouse models reveals a molecular distinction between psychotic illness in PWS and schizophrenia


title: Dendritic membrane resistance modulates activity-induced Ca2+ influx in oxytocinergic magnocellular neurons of mouse PVN

abstract:
Hypothalamic oxytocinergic magnocellular neurons have a fascinating ability to release peptide from both their axon terminals and from their dendrites. Existing data indicates there is a flexible relationship between somatic activity and dendritic release, but the mechanisms governing this relationship are not completely understood. Here we use a combination of electrical and optical recording techniques to quantify activity-dependent calcium influx in proximal vs. distal dendrites of oxytocinergic magnocellular neurons located in the paraventricular nucleus of the hypothalamus (OT-MCNs). Results reveal that the dendrites of OT-MCNs are weak conductors of somatic voltage changes, and yet activity-induced dendritic calcium influx can be robustly regulated by a diverse set of stimuli that open or close ionophores located along the dendritic membrane. Overall, this study reveals that dendritic membrane resistance is a dynamic and endogenously regulated feature of OT-MCNs that is likely to have substantial functional impact on central oxytocin release.

IMPACT STATEMENTActivity-induced dendritic calcium influx in oxytocinergic magnocellular neurons can be robustly modulated by a highly diverse set of stimuli acting on distinct types of ionophores expressed along the dendritic membrane.


title: Imagined speech can be decoded from low- and cross-frequency features in perceptual space

abstract: Reconstructing intended speech from neural activity using brain-computer interfaces (BCIs) holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech have met limited success, mainly because the associated neural signals are weak and variable hence difficult to decode by learning algorithms. Using three electrocorticography datasets totalizing 1444 electrodes from 13 patients who performed overt and imagined speech production tasks, and based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future BCIs, and assessed their performance to discriminate speech items in articulatory, phonetic, vocalic, and semantic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to successful imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings demonstrate that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding, and that exploring perceptual spaces offers a promising avenue for future imagined speech BCIs.


title: Modulation of the spontaneous brain activity and functional connectivity in the triple resting-state networks following the visual oddball paradigm

abstract: The default mode network (DMN), the salience network (SN), and the central executive network (CEN) could be considered as the core resting-state brain networks (RSN) due to their involvement in a wide range of cognitive tasks. Despite the large body of knowledge relating to their regional spontaneous activity (RSA) and functional connectivity (FC) of these networks, less is known about the influence of task-associated activity on these parameters and on the interaction between these three networks. We have investigated the effects of the visual-oddball paradigm on three fMRI measures (amplitude of low-frequency fluctuations for RSA, regional homogeneity for local FC, and degree centrality for global FC) in these three core RSN networks. A rest-task-rest paradigm was used and the RSNs were identified using independent component analysis (ICA) on the resting-state data. We found that the task-related brain activity induced different patterns of significant changes within the three RS networks. Most changes were strongly associated with the task performance. Furthermore, the task-activity significantly increased the inter-network correlations between the SN and CEN as well as between the DMN and CEN, but not between the DMN and SN. A significant dynamical change in RSA, alongside local and global FC within the three core resting-state networks following a simple cognitive activity may be an expression of the distinct involvement of these networks in the performance of the task and their various outcomes.


title: Modeling by artificial neural networks of silver carp (Hypophthalmichthys molitrixi) with sous vide processing on the effects of storage and processing temperatures on the microbiological status

abstract: To evaluate and anticipate the microbial changes of silver carp (Hypophthalmichthys molitrixi) during cold storage (0, 5, 10, 15 & 21 day) at different sous vide processing temperatures (60, 65, 70, and 75 {degrees}C), changes in microbial load of Enterobacteriaceae, Lactic Acid bacteria (LAB), Pseudomonas, Psychrotrophs, and total viable count (TVC) were considered. A radial basis function neural network (RBFNN) model was established to predict the changes in the microbial content of silver carp. The critical temperature for inactivation of Enterobacteriaceae and lactic acid bacteria was 65 {degrees}C and for Pseudomonas and Psychrotrophs was 70 {degrees}C and the highest value (75 {degrees}C) was observed for the total viable count. In samples processed at 75 {degrees}C, the presence of Enterobacteriaceae, Pseudomonas and Psychrotrophs were not detectable up to 15 days of storage and lactic acid bacteria were not detectable even at the end of the storage period. The optimal ANN topology for modeling Enterobacteriaceae, Pseudomonas, and Psychrotroph contained 9 neurons in the hidden layer, but for TVC and LAB, it was 14 neurons.

category: microbiology


title: Local protein synthesis of mtIF3 regulates mitochondrial translation for axonal development

abstract: Mitochondrial initiation factor 3 (mtIF3) binds to and dissociates mitochondrial ribosomes. The mtIF3-small subunit complex then recruits mtIF2, mRNA, and N-formylmethionine-tRNA to initiate mitochondrial translation. Intriguingly, transcripts of the nuclear-encoded mtIF3 gene have been shown present in axonal growth cones; however, the biological function of this compartmentalization remains largely unknown. Here, we demonstrate that brain-derived neurotrophic factor (BDNF) induces local translation of mtIF3 mRNA in axonal growth cones. Subsequently, mtIF3 protein is translocated into axonal mitochondria and promotes mitochondrial translation as assessed by our newly developed bimolecular fluorescence complementation sensor for the assembly of mitochondrial ribosomes. We further show that BDNF-induced axonal growth requires mtIF3-dependent mitochondrial translation in axons. These findings provide new insight into how neurons adaptively control mitochondrial physiology and axonal development via local mtIF3 translation.

category: cell biology


title: Population structure limits parallel evolution

abstract: Population genetic theory predicts that small effective population sizes (Ne) and restricted gene flow limit the potential for local adaptation. In particular, the probability of evolving similar phenotypes based on shared genetic mechanisms (i.e. parallel evolution), is expected to be reduced. We tested these predictions in a comparative genomic study of two ecologically similar and geographically co-distributed stickleback species (viz. Gasterosteus aculeatus and Pungitius pungitius). We found that P. pungitius harbours less genetic diversity and exhibits higher levels of genetic differentiation and isolation-by-distance than G. aculeatus. Conversely, G. aculeatus exhibits a stronger degree of genetic parallelism across freshwater populations than P. pungitius: 2996 vs. 379 SNPs located within 26 vs nine genomic regions show evidence of selection in multiple freshwater populations of G. aculeatus and P. pungitius, respectively. Most regions involved in parallel evolution in G. aculeatus showed increased levels of divergence, suggestive of selection on ancient haplotypes. In contrast, regions involved in freshwater adaptation in P. pungitius were younger, and often associated with reduced diversity. In accordance with theory, the results suggest that connectivity and genetic drift play crucial roles in determining the levels and geographic distribution of standing genetic variation, providing evidence that population subdivision limits local adaptation and therefore also the likelihood of parallel evolution.


title: Proteomic characterization of GSK3β knockout shows altered cell adhesion and metabolic pathway utilisation in colorectal cancer cells

abstract: Glycogen-specific kinase (GSK3{beta}) is an integral regulator of the Wnt signalling pathway as well as many other diverse signalling pathways and processes. Dys-regulation of GSK3{beta} is implicated in many different pathologies, including neurodegenerative disorders as well as many different tumour types. In the context of tumour development, GSK3{beta} has been shown to play both oncogenic and tumour suppressor roles, depending upon tissue, signalling environment or disease progression. Although multiple substrates of the GSK3{beta} kinase have been identified, the wider protein networks within which GSK3{beta} participates are not well known, and the consequences of these interactions not well understood. In this study, LC-MS/MS expression analysis was performed using knockout GSK3{beta} colorectal cancer cells and isogenic controls in colorectal cancer cell lines carrying dominant stabilizing mutations of {beta}-Catenin. Consistent with the role GSK3{beta}, we found that {beta}-Catenin levels and canonical Wnt activity are unaffected by knockout of GSK3{beta} and therefore use this knockout cell model to identify other processes in which GSK3{beta} is implicated. Quantitative proteomic analysis revealed perturbation of proteins involved in cell-cell adhesion, and we characterize the phenotype and altered proteomic profiles associated with this. We also characterize the perturbation of metabolic pathways resulting from GSK3{beta} knockout and identify defects in glycogen metabolism. In summary, using a precision colorectal cancer cell-line knockout model with constitutively activated {beta}-Catenin we are able to identify several of the diverse pathways and processes associated with GSK3{beta} function.

category: cancer biology


title: Human stem cell model of HNF1A deficiency shows uncoupled insulin to C-peptide secretion with accumulation of abnormal insulin granules

abstract:
Mutations in HNF1A cause Maturity Onset Diabetes of the Young type 3 (MODY3), the most prevalent form of monogenic diabetes. We generated stem cell-derived pancreatic endocrine cells from human embryonic stem cells (hESCs) with induced hypomorphic mutations in HNF1A. Using these cells, we show that HNF1A orchestrates a transcriptional program required for distinct aspects of {beta}-cell fate and function. During islet cell differentiation, HNF1A deficiency biases islet endocrine cells towards an -cell fate associated with PAX4 down-regulation. HNF1A- deficient {beta}-cells display impaired basal and glucose stimulated-insulin secretion in association with a reduction in CACNA1A and intracellular calcium levels, and impaired insulin granule exocytosis in association with SYT13 down-regulation. Knockout of PAX4, CACNA1A and SYT13 reproduce the relevant phenotypes. Reduction of insulin secretion is associated with accumulation of enlarged secretory granules, and altered stoichiometry of secreted insulin to C-peptide. In HNF1A deficient {beta}-cells, glibenclamide, a sulfonylurea drug used in the treatment of MODY3 patients, increases intracellular calcium to levels beyond those achieved by glucose, and restores C-peptide and insulin secretion to a normal stoichiometric ratio. To study HNF1A deficiency in the context of a human disease model, we also generated stem cell-derived pancreatic endocrine cells from two MODY3 patients induced pluripotent stem cells (iPSCs). While insulin secretion defects are constitutive in cells with complete HNF1A loss of function, {beta}-cells heterozygous for hypomorphic HNF1A mutations are initially normal, but lose the ability to secrete insulin and acquire abnormal stoichiometric secretion ratios. Importantly, the defects observed in these stem cell models are also seen in circulating proportions of insulin:C-peptide in nine MODY3 patients.

One sentence of summaryDeficiency of the transcription factor HNF1A biases islet endocrine cell fate towards -cells, impairs intracellular calcium homeostasis and insulin exocytosis, alters the stoichiometry of insulin to C-peptide release, and leads to an accumulation of abnormal insulin secretory granules in {beta}-cells.


title: Fibroblast State Reversal By MBNL1-Dependent Transcriptome Modification Regulates Cardiac Repair

abstract: Dynamic fibroblast state transitions are responsible for the hearts fibrotic response to injury, raising the possibility that tactical control of these transitions could alter maladaptive fibrotic outcomes. Transcriptome maturation by the RNA binding protein Muscleblind Like 1 (MBNL1) has emerged as a potential driver of differentiated cell states. Here genetic lineage tracing of myofibroblasts in the injured heart demonstrated that gains in MBNL1 function corresponded to profibrotic fibroblast states. Similarly, in mice cardiac fibroblast specific MBNL1 overexpression induced a transcriptional myofibroblast profile in healthy cardiac fibroblasts that prevented the fibroproliferative phase of cardiac wound healing. By contrast loss of MBNL1 reverted cardiac fibroblasts to a pro-proliferative epicardial progenitor state that limited cardiac fibrosis following myocardial infarction. This progenitor state transition was associated with an MBNL1-dependent destabilization of the mesenchymal transition gene, Sox9. These findings suggest that MBNL1 regulation of the fibroblast transcriptome drives state transitions underlying cardiac fibrosis and repair.


title: Baseline cell proliferation rates and response to UV differ in Lymphoblastoid Cell Lines derived from healthy individuals of extreme constitution types

abstract: Differences in human phenotypes and susceptibility to complex diseases are an outcome of genetic and environmental interactions. This is evident in diseases that progress through a common set of intermediate patho-endophenotypes. Precision medicine aims to delineate the molecular players for individualized and early interventions. Functional studies in Lymphoblastoid Cell Line (LCL) model of phenotypically well characterized healthy individuals can help deconvolute and validate these molecular mechanisms. We developed LCLs from eight healthy individuals belonging to three extreme constitution types, deep phenotyped on the basis of Ayurveda. LCLs were characterized by karyotyping and immunophenotyping. Growth characteristics and response to UV was studied in these LCLs. We observed significant differences in cell proliferation rates between the contrasting groups such that one type (Kapha) proliferates significantly slower than the other two (Vata, Pitta). In response to UV, one fast growing group (Vata) shows higher cell death but recovers its numbers due to inherent higher rates of proliferation. The baseline differences in cell proliferation are key to understanding the survival of cells in UV stress. Variability in baseline cellular phenotypes not only explains the cellular basis of different constitutions types but can also help set priors during designing an individualized therapy with DNA damaging agents. This is the first study of its kind that shows variability of intermediate patho-phenotypes amongst healthy individuals that have implications in precision medicine.


title: Endometrial Gap Junction Expression - Early Indicators of Endometriosis and Integral to Invasiveness

abstract: Endometriosis is an invasive disease, and a leading cause of pain, infertility and disability among women, with an incidence 10 fold that of cancer. A more complete understanding of disease pathogenesis is essential for the development of non-surgical diagnostic assays and non-hormonal therapeutics. Avoidance of immune clearance and implantation of endometrial tissue on peritoneal surfaces are features of endometriosis lesion formation that overlap with cancer metastasis. Connexins, and the gap junctions they form, have been implicated in cancer progression, and may be associated endometriosis pathophysiology. Single cell transcriptomic profiling of endometrial epithelial and stromal cells from women with endometriosis reveals a striking and progressive shift in expression of connexins and related regulatory and junctional genes. We demonstrate that gap junction coupling between endometrial cells and the peritoneal mesothelium is dramatically induced, specifically in endometriosis patients, and is required for invasion by inducing breakdown of the mesothelial barrier function.


title: Detour learning ability and the effect of novel sensory cues on learning in Australian bull ants, Myrmecia midas

abstract:
Many animals navigate in a structurally complex environment which requires them to detour around physical barriers that they encounter. While many studies in animal cognition suggest that they are able to adeptly avoid obstacles, it is unclear whether a new route is learned to navigate around these barriers and, if so, what sensory information may be used to do so. We investigated detour learning ability in the Australian bull ant, Myrmecia midas, which primarily uses visual landmarks to navigate. We first placed a barrier on the ants natural path of their foraging tree. Initially, 46% of foragers were unsuccessful in detouring the obstacle. In subsequent trips, the ants became more successful and established a new route. We observed up to eight successful foraging trips detouring around the barrier. When we subsequently changed the position of the barrier, made a new gap in the middle of the obstacle, or removed the barrier altogether, ants mostly maintained their learned motor routine, detouring with a similar path as before, suggesting that foragers were not relying on barrier cues and therefore learned a new route around the obstacle. In additional trials, when foragers encountered new olfactory or tactile cues, or the visual environment was blocked, their navigation was profoundly disrupted. These results suggest that changing sensory information, even in modalities that foragers do not usually need for navigation, drastically affects the foragers ability to successful navigate.

Subject CategoryNeuroscience and Cognition

category: animal behavior and cognition


title: The urea cycle is transcriptionally controlled by hypoxia-inducible factors

abstract: Here, we demonstrate transcriptional regulation of urea cycle genes CPS1 and ARG1 by hypoxia-inducible factors (HIFs) and demonstrate a hepatic HIF dependent increase in urea cycle activity.

category: biochemistry


title: Can we put Humpty Dumpty back together again? What does protein quantification mean in bottom-up proteomics?

abstract: Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. In bottom-up proteomics, protein parsimony and protein inference derived from these measured peptides are important for determining which protein coding genes are present. However, given the complexity of RNA splicing processes, and how proteins can be modified post-translationally, it is overly simplistic to assume that all peptides that map to a singular protein coding gene will demonstrate the same quantitative response. Accordingly, by assuming all peptides from a protein coding sequence are representative of the same protein we may be missing out on detecting important biological differences. To better account for the complexity of the proteome we need to think of new or better ways of handling peptide data.


title: LanceOtron: a deep learning peak caller for ATAC-seq, ChIP-seq, and DNase-seq

abstract: ATAC-seq, ChIP-seq, and DNase-seq have revolutionized molecular biology by allowing researchers to identify important DNA-encoded elements genome-wide. Regions where these elements are found appear as peaks in the analog signal of an assays coverage track, and despite the ease with which humans can visually categorize these regions, meaningful peak calls from whole genome datasets require complex analytical techniques. Current methods focus on statistical tests to classify peaks, reducing the information-dense peak shapes to simply maximum height, and discounting that background signals do not completely follow any known probability distribution for significance testing. Deep learning has been shown to be highly accurate for image recognition, on par or exceeding human ability, providing an opportunity to reimagine and improve peak calling. We present the peak calling framework LanceOtron, which combines multifaceted enrichment measurements with deep learning image recognition techniques for assessing peak shape. In benchmarking transcription factor binding, chromatin modification, and open chromatin datasets, LanceOtron outperforms the long-standing, gold-standard peak caller MACS2 through its improved selectivity and near perfect sensitivity. In addition to command line accessibility, a graphical web application was designed to give any researcher the ability to generate optimal peak calls and interactive visualizations in a single step.

category: bioinformatics


title: Unsupervised discovery of dynamic cell phenotypic states from transmitted light movies

abstract:
Identification of cell phenotypic states within heterogeneous populations, along with elucidation of their switching dynamics, is a central challenge in modern biology. Conventional single-cell analysis methods typically provide only indirect, static phenotypic readouts. Transmitted light images, on the other hand, provide direct morphological readouts and can be acquired over time to provide a rich data source for dynamic cell phenotypic state identification. Here, we describe an end-to-end deep learning platform, UPSIDE (for Unsupervised Phenotypic State IDEntification), for discovering cell states and their dynamics from transmitted light movies.

UPSIDE uses the variational auto-encoder architecture to learn latent cell representations, that are then clustered for state identification, decoded for feature interpretation, and linked across movie frames for transition rate inference. Using UPSIDE, we identified distinct blood cell types in a heterogeneous dataset. From acute myeloid leukemia cell movies, we then identified stem-cell associated morphological states and their inter-conversion rates. UPSIDE opens up use of transmitted light movies for systematic exploration of cell state heterogeneity and dynamics in biology and medicine.


title: Predicting the Specificity-Determining Positions of Paralogous Complexes

abstract: Due to its clinical relevance, modulation of functionally relevant amino acids in protein-protein complexes has attracted a great deal of attention. To this end, many approaches have been proposed to predict partner-selecting, i.e., specificity-determining positions in evolutionarily close complexes. These approaches can be grouped into sequence-based machine learning and structure-based energy-driven methods. In this work, we assessed these methods ability to map the specificity-determining positions of Axl, a receptor tyrosine kinase involved in cancer progression and immune-related diseases. For this, we used three sequence-based predictors - SDPred, Multi-RELIEF, and Sequence Harmony - and a structure-based approach by utilizing HADDOCK and extensive molecular dynamics simulations. As a result, we show that (i) sequence-based methods overpredict the number of specificity-determining positions for Axl complexes and that (ii) combining sequence-based approaches with HADDOCK provides the most coherent set of predictions. Our work lays out a critical study on the comparative performance specificity-determining position predictors. It also presents a combined sequence-structure-based approach, which can guide the development of therapeutic molecules capable of combatting Axl misregulation in different types of diseases.


title: Youthful and age-related matreotypes predict drugs promoting longevity

abstract:
The identification and validation of drugs that promote health during aging ( geroprotectors) is key to the retardation or prevention of chronic age-related diseases. Here we found that most of the established pro-longevity compounds shown to extend lifespan in model organisms also alter extracellular matrix gene expression (i.e., matrisome) in human cell lines. To harness this novel observation, we used age-stratified human transcriptomes to define the age-related matreotype, which represents the matrisome gene expression pattern associated with age. Using a  youthful matreotype, we screened in silico for geroprotective drug candidates. To validate drug candidates, we developed a novel tool using prolonged collagen expression as a non-invasive and in-vivo surrogate marker for C. elegans longevity. With this reporter, we were able to eliminate false positive drug candidates and determine the appropriate dose for extending the lifespan of C. elegans. We improved drug uptake for one of our predicted compounds, genistein, and reconciled previous contradictory reports of its effects on longevity. We identified and validated new compounds, tretinoin, chondroitin sulfate, and hyaluronic acid, for their ability to restore age-related decline of collagen homeostasis and increase lifespan. Thus, our innovative drug screening approach - employing extracellular matrix homeostasis - facilitates the discovery of pharmacological interventions promoting healthy aging.

HighlightsO_LIMany geroprotective drugs alter extracellular matrix gene expression
C_LIO_LIDefined young and old human matreotype signatures can identify novel potential geroprotective compounds
C_LIO_LIProlonged collagen homeostasis as a surrogate marker for longevity
C_LI

category: pharmacology and toxicology


title: Efficient Precision Dosing Under Estimated Uncertainties via Koopman Expectations of Bayesian Posteriors with Pumas

abstract: Personalized precision dosing is about mathematically determining effective dosing strategies that optimize the probability of containing a patients outcome within a therapeutic window. However, the common Monte Carlo approach for generating patient statistics is computationally expensive because thousands of simulations need to be computed. In this manuscript we describe a new method which utilizes the Koopman operator to perform a direct computation of expected patient outcomes with respect to quantified uncertainties of Bayesian posteriors in a nonlinear mixed effect model framework. We detail how quantities such as the probability of being within the therapeutic window can be calculated with a choice of loss function on the Koopman expectation. We demonstrate a high performance parallelized implementation of this methodology in Pumas(R) and showcase the ability to accelerate the computation of these expectations by 50x-200x over Monte Carlo. We showcase how dosing can be optimized with respect to probabilistic statements respecting variable uncertainties using the Koopman operator. We end by demonstrating an end-to-end workflow, from estimating variable uncertainties via Bayesian estimation to optimizing a dose with respect to parametric uncertainty.


title: Induction of antioxidant and detoxifying enzymes by oriental bezoar

abstract: Oriental bezoar, a gallstone formed in the gall sac of Bos taurus Linne var. domesticus Gmelin (Bovidae), has been used as an antipyretic, sedative, antispasmodic, and detoxifying drug in oriental medicine. It reportedly has an antioxidative effect; however, its underlying mechanism remains unclear. Therefore, we investigated the effects of oriental bezoar and its main components on the nuclear factor erythroid 2-related factor 2 (Nrf2)-antioxidant response element (ARE) pathway, which transcriptionally regulates the gene encoding an antioxidant enzyme, heme oxygenase-1 (HO-1), and detoxifying enzymes glutathione-S-transferase alpha 1 (GSTA1) and quinone oxidoreductase 1 (NQO1) in vitro. Using a dual-luciferase reporter assay and real-time PCR, oriental bezoar and its main constituent bilirubin were shown to induce ARE activity and up-regulate the expression of HO-1, GSTA1, and NQO1 in HepG2 cells in a dose-dependent manner. These results suggest that activation of the Nrf2-ARE pathway is partially involved in the antioxidative effect of oriental bezoar, thus providing a scientific basis for oriental bezoars traditional use for detoxification.


title: Microstructure Aware Modeling Of Biochemical Transport In Arterial Blood Clots

abstract: Flow-mediated transport of biochemical species is central to thrombotic phenomena. Comprehensive three-dimensional modeling of flow-mediated transport around realistic macroscale thrombi poses challenges owing to their arbitrary heterogeneous microstructure. Here, we develop a microstructure aware model for species transport within and around a macroscale thrombus by devising a custom preconditioned fictitious domain formulation for thrombus-hemodynamics interactions, and coupling it with a fictitious domain advection-diffusion formulation for transport. Microstructural heterogeneities are accounted through a hybrid discrete particle-continuum approach for the thrombus interior. We present systematic numerical investigations on unsteady arterial flow within and around a three-dimensional macroscale thrombus; demonstrate the formation of coherent flow structures around the thrombus which organize advective transport; illustrate the role of the permeation processes at the thrombus boundary and subsequent intra-thrombus transport; and characterize species transport from bulk flow to the thrombus boundary and vice versa.

category: physiology


title: Evaluation of a Recessive Male Floret Color in Cultivated Northern Wild Rice (Zizania palustris L.) for Pollen-Mediated Gene Flow Studies

abstract: Northern wild rice (NWR; Zizania palustris L.) is a wind-pollinated, annual, aquatic grass that grows naturally in the Great Lakes Region (GLR) of the United States and Canada, and is also cultivated in flooded paddies, predominantly in California and Minnesota. A better understanding of pollen-mediated gene flow is needed within the species for both conservation and breeding efforts as cultivation occurs within the species natural range and spatially-isolated, paddy structures are limited within breeding programs. Widely cited pollen travel research in NWR demonstrated that pollen could travel at least 3200m. However, a population segregating for male sterility was used as the pollen recipient in the study and was determined to not be adequate for NWR pollen travel studies. Here, we present the characterization of a recessive white male floret (WMF) population in contrast to the dominant, purple male floret (PMF) color of cultivated NWR along with estimates of pollen-mediated gene flow in a cultivated paddy setting. Studies conducted in 2018 and 2019 revealed that the primary amount of pollen-mediated gene flow occurred within the first 7m from the PMF donor source with no gene flow detected past 63m. These results suggest that the likelihood of pollen-mediated gene flow between cultivated NWR and natural stands remains low. We also identified a strong linkage between male floret, auricle, and culm color. This study demonstrates that the WMF trait is an excellent candidate for use in pollen-mediated gene flow studies in NWR.

category: plant biology


title: Do examinations prepare students for higher education? A lesson from the Covid-19 lockdown.

abstract: The COVID-19 pandemic caused severe disruption to education in the UK in 2020, with most of the school teaching moving online and national school examinations being cancelled. This was particularly disruptive for those taking end of school examinations in preparation for higher education. Biological science courses require students to absorb a lot of new vocabulary and concepts, with examinations traditionally focusing on content recall rather than reasoning. Students who had entered university in September 2019 were compared with those arriving in September 2020 with respect to their knowledge of bioscience vocabulary and understanding of key concepts. Results showed no significant difference between those who had gone through the examination process in 2019 relative to those who had not, in 2020. This suggests the cramming of information for examinations has no detectable effect on the knowledge and understanding of biology that students take with them to university.

category: scientific communication and education


title: Revisiting the role of synaptic plasticity and network dynamics for fast learning in spiking neural networks

abstract:
Spike-based neural network models have so far not been able to reproduce the capability of the brain to learn from very few, often even from just a single example. We show that this deficiency of models disappears if one allows synaptic weights to store priors and other information that optimize the learning process, while using the network state to quickly absorb information from new examples. For that, it suffices to include biologically realistic neurons with spike frequency adaptation in the neural network model, and to optimize the learning process through meta-learning. We demonstrate this on a variety of tasks, including fast learning and deletion of attractors, adaptation of motor control to changes in the body, and solving the Morris water maze task - a paradigm for fast learning of navigation to a new goal.

Significance StatementIt has often been conjectured that STDP or other rules for synaptic plasticity can only explain some of the learning capabilities of brains. In particular, learning a new task from few trials is likely to engage additional mechanisms. Results from machine learning show that artificial neural networks can learn from few trials by storing information about them in their network state, rather than encoding them in synaptic weights. But these machine learning methods require neural networks with biologically unrealistic LSTM (Long Short Term Memory) units. We show that biologically quite realistic models for neural networks of the brain can exhibit similar capabilities. In particular, these networks are able to store priors that enable learning from very few examples.


title: Genetic depletion of BDNF impairs both context-dependent and context-independent extinction learning of a spatial appetitive task

abstract: Brain derived neurotropic factor (BDNF) supports neuronal survival, growth, and differentiation and is involved in forms of hippocampus-dependent learning, as well as hippocampus-dependent learning. Extinction learning (EL) comprises active inhibition of no-longer relevant learned information, in conjunction with a decreased response of a previously learned behavior. It is highly dependent on context, and evidence exists that it requires hippocampal activation. Concordantly, the participation of BDNF in hippocampus-dependent memory is experience-dependent. BDNF has been associated with synaptic plasticity needed for acquisition and extinction learning of fear conditioning. However, little is known about its influence on the extinction and renewal of spatial appetitive extinction learning (EL). In this study, in BDNF+/--mice we evaluated to what extent BDNF contributes to spatial appetitive EL in the presence (ABA) or absence (AAA) of a context change. Daily training, to reach acquisition criterion in a T-maze, resulted in a similar outcome in BDNF+/--mice or their wildtype (wt) littermates. EL was delayed in the AAA, and significantly impaired in the ABA-context compared to EL in wt littermates. When renewal was tested in the ABA paradigm we detected a significant response in wt controls, but not in BDNF+/--mice. Taken together, these results support an important role for BDNF in EL in AAA and ABA context, as well as renewal of a spatial appetitive task, processes that relate to information updating and retrieval.


title: Structural and immunological identification and antiviral infection experiment of the dominant cytotoxic T lymphocyte epitopes of the oncogenic Marek's disease virus

abstract:
Mareks disease (MD) is a serious cancer caused by MDV in chickens, and it is also the first tumor disease that could be controlled by an attenuated vaccine in the world. However, the attenuated vaccine is able to inhibit only the formation of tumors but cannot prevent the infection of oncogenic viruses; instead, it leads to mutations and the emergence of a number of virulent strains. In this paper, the crystal structures of chicken MHC class I (pBF2*1501) molecules bound with 8-mer and 9-mer MDV peptides were solved. The results showed that the conformations of the 8-mer and 9-mer peptides in the antigen-binding groove (ABG) of pBF2*1501 are different; the ABG-8-mer is flat, and the ABG-9-mer has the "featured" M-type epitope morphology. Based on these results, multiple MDV epitopes were confirmed using the tetramer technique, and the immunoprotective effect of dominant epitope was confirmed using the protein adjuvant HSP108-N333 in BF2*1501-expressing chickens. The results showed that the two epitopes have obvious protective effects after a standard immunization program. After challenge, the mortality rate was only 20%, and the protective index (PI) reached 33% in the epitope group. The results verified that a single epitope could induce extremely strong specific antitumor T lymphocyte immunity. The results show that three key factors are crucial to obtain the best antitumor effect: accurate identification of dominant cytotoxic T lymphocyte (CTL) epitopes, efficient protein adjuvant and MHC matching. Meanwhile, the results also provided obvious advantages for the development of multiple epitope vaccines for tumor diseases.

ImportanceMareks disease (MD) is the first tumor disease that can be controlled by an attenuated vaccine. However, the attenuated vaccine cannot prevent the infection of the oncogenic virus and instead leads to the emergence of a number of mutated virulent strains. First, the mechanism of the chicken BF2*1501 preferentially presents 9-mer peptide was clarified. Based on this result, multiple MDV epitopes were confirmed, and the dominant epitopes were identified. Subsequently, two epitope groups showed obvious protective effects after a standard immunization program, and the protective index (PI) of one of the epitope groups reached over 30%. The results showed that a single epitope could induce strong and efficient antitumor CTL immunity. Overall, three key factors are crucial to obtain the best antitumor effect: accurate identification of dominant epitopes, efficient protein adjuvant and MHC matching. Our results provide an obvious strategy for the development of multiple epitope vaccines in tumor diseases.

category: immunology


title: Infant gut strain persistence is associated with maternal origin, phylogeny, and functional potential including surface adhesion and iron acquisition

abstract: Gut microbiome succession impacts infant development. However, it remains unclear what factors promote persistence of initial bacterial colonists in the developing gut. Here, we performed strain-resolved metagenomic analyses to compare gut colonization of preterm and full-term infants throughout the first year of life and evaluated links between strain persistence and strain origin as well as genetic potential. Analysis of 206 fecal metagenomes collected from full-term and preterm infants and their mothers revealed that infants initially distinct microbial communities converged by age one. Approximately 11% of early colonists, primarily Bacteroides and Bifidobacterium, persisted during the first year of life, and these were more prevalent in full-term compared to preterm infants. Gut-associated strains from mothers were significantly more likely to persist in the infant gut than other strains. Enrichment in genes for surface adhesion, iron acquisition and carbohydrate degradation may explain persistence of some strains through the first year of life.


title: Expression and Manufacturing of Protein Therapeutics in Spirulina

abstract: Arthrospira platensis (commonly known as spirulina) is a photosynthetic cyanobacterium1. It is a highly nutritious food that has been consumed for decades in the US, and even longer by indigenous cultures2. Its widespread use as a safe food source and proven scalability have driven frequent attempts to convert it into a biomanufacturing platform. But these were repeatedly frustrated by spirulinas genetic intractability. We report here efficient and versatile genetic engineering methodology for spirulina that allows stable expression of bioactive protein therapeutics at high levels. We further describe large-scale, indoor cultivation and downstream processing methods appropriate for the manufacturing of biopharmaceuticals in spirulina. The potential of the platform is illustrated by pre-clinical development and human testing of an orally delivered antibody therapeutic against campylobacter, a major cause of infant mortality in the developing world and a growing antibiotic resistance threat3,4. This integrated development and manufacturing platform blends the safety of food-based biotechnology with the ease of genetic manipulation, rapid growth rates and high productivity characteristic of microbial platforms. These features combine for exceptionally low-cost production of biopharmaceuticals to address medical needs that are unfeasible with current biotechnology platforms.

category: molecular biology


title: Does where you live influence what you are made of? Spatial correlates of chemical traits across commonly occurring boreal plants

abstract:
ContextSpatially explicit drivers of foliar chemical traits link plants to ecosystem processes to reveal landscape functionality. Specifically, foliar elemental, stoichiometric, and phytochemical (ESP) compositions represent key indicator traits.

ObjectivesHere, we investigate the spatial drivers of foliar ESP at the species level and across species at the trait level for five commonly occurring boreal forest understory plants.

MethodsOn the island of Newfoundland, Canada, we collected foliar material from four chronosequenced forest grids. Using response variables of foliar elemental (C, N, P, percent and quantity), stoichiometric (C:N, C:P, N:P), and phytochemical (terpenoids) composition, we tested multiple competing hypotheses using spatial predictors of land cover (e.g., coniferous, deciduous, mixedwood), productivity (e.g., enhanced vegetation index), biotic (e.g., stand age/height, canopy closure) and abiotic (e.g., elevation, aspect, slope) factors.

ResultsWe found evidence to support spatial relationships of foliar ESP for most species (mean R2 = 0.22, max = 0.65). Spatial variation in elemental quantity traits of C, N, P were related to land cover along with biotic and abiotic factors for 2 of 5 focal species. Notably, foliar C, C:P, and sesquiterpene traits between different species were related to abiotic factors. Similarly, foliar terpenoid traits between different species were related to a combination of abiotic and biotic factors (mean R2 = 0.26).

ConclusionsSpatial-trait relationships mainly occur at the species level, with some commonalities occurring at the trait level. By linking foliar ESP traits to spatial predictors, we can map plant chemical composition patterns that influence landscape-scale ecosystem processes.


title: New distributional data for the northern forestfly, Lednia borealis Baumann and Kondratieff, 2010 (Plecoptera: Nemouridae), Washington, USA

abstract: The northern forestfly, Lednia borealis (Plecoptera: Nemouridae) is a rare montane stonefly believed to be endemic to Washington. The species, first recognized as a valid taxon in 2010, is the only member of the genus Lednia known from the state. Like other species in its genus, it is found in mid- to high-elevation cold water habitat, including lakes, glacial-fed streams, and rheocrenes (channelized springs). Lednia species in general appear to be rare or at least rarely collected. Because of their reliance on alpine and subalpine habitat, Lednia may be especially vulnerable to threats associated with climate change. However, relatively little is known about this species, and distribution data are scarce. From 2015 to 2019, 94 sites were surveyed in order to document unmapped populations of Lednia borealis to improve range and distributional information from montane areas of Washington State. In this paper, we share locations of L. borealis documented to date, including collections from eight newly documented Lednia sites in the Mt. Baker and Glacier Peak Wildernesses in the Cascade Mountains of Washington, and report recent COI barcoding results. We also provide updated details on the species distribution, highlight a confirmed habitat association with glacial edge meltwater, and provide recommendations for future surveys.


title: A hierarchical Bayesian model to investigate trade-offs between growth and reproduction in a long-lived plant

abstract: 1A trade-off between growth and fecundity, reflecting the inability of simultaneously investing in both functions when resources are limited, is a fundamental feature of life history theory. This particular trade-off is the result of evolutionary and environmental constrains shaping reproductive and growth traits, but it remains difficult to pinpoint in natural populations of long-lived plants. We developed a hierarchical Bayesian model to estimate the inter-individual correlation among growth and reproduction, using observations at individual level over several years combined with resource simulations from an ecophysiological-based model (CASTANEA). In the Bayesian model, the resource, simulated by CASTANEA and incorporated as a latent variable, is allocated to tree growth, reproductive buds initiation and fruit maturation. Then, we used individual random effects correlated among energetic sinks to investigate potential trade-offs. We applied this original approach to a Mediterranean coniferous tree, Atlas Cedar (Cedrus atlantica), at two contrasted levels of competition, high versus low density population. We found that trees initializing many reproductive buds had a higher growth. Moreover, a negative correlation was detected between growth and fruit survival during maturation. Finally, trees investing more resource to maturate fruits initiated less reproductive buds. The level of competition did not impact the sign of these three correlations, but changed the level of resource allocation: low density population favored growth whereas high density favored reproduction. The level of resource have an impact on individual strategies. This new modeling framework allowed us to detect various individual strategies of resource allocation to growth versus late-stage reproduction on the one hand, and to early-versus late-stage reproduction on the other hand. Moreover, the sign of the correlation between growth and reproductive traits depends on the stage of reproduction considered. Hence, we suggest that the investigation of potential trade-offs between growth and reproduction requires to integrate the dynamics of resource and sinks phenology, from initiation to maturation of reproductive organs.


title: Estimating the fundamental niche: accounting for the uneven1availability of existing climates

abstract: Studies that question important conceptual and methodological aspects of the field of ecological niche modeling (and species distribution modeling) have cast doubts on whether it is possible to estimate the fundamental niche of a species using presence-only data. The main limitation in niche estimation is that presence data come from the realized niche, which is only a subset of the fundamental niche. Most of the existing methods lack the ability to overcome this limitation and therefore fit niches that resemble the realized niche. To obtain a more accurate estimate of the fundamental niche, we propose using the geographic region that is accessible to a species (based on its dispersal ability) to determine a sampling distribution, in environmental space, from which we can quantify the likelihood of observing a particular environmental combination in a sample of presence points. We incorporate this sampling distribution into a multivariate normal model (i.e., a Mahalanobis distance model) by creating a weight function that modifies the probabilities of observing different environmental combinations in a sample of presences. This modification accounts for the uneven availability of environmental conditions. We show that the parameters of this weighted-normal model can be approximated with a maximum likelihood estimation approach; and then used to draw ellipsoids (confidence regions) that represent the fundamental niche of the species. We illustrate the application of our model with two worked examples. First, we use presence data for an invasive species and an accessible area that includes only its native range to evaluate whether the fitted model predicts confirmed establishments of the species outside its native range. Second, we use presence data for closely related species with known accessible areas to demonstrate how the different dispersal abilities of the species constrain a classic Mahalanobis distance model. Overall, we show that accounting for the distribution of environmental conditions that are accessible to a species indeed affects the estimation of the ellipsoids used to model its fundamental niche.


title: Estimating the fundamental niche: accounting for the uneven availability of existing climates


title: Estimating the fundamental niche: accounting for the uneven availability of existing environmental conditions in the calibration area


title: Age, Origin, and Biogeography: Unveiling the Factors Behind the Diversification of Dung Beetles

abstract: The remarkable diversity and global distribution of dung beetles has long attracted the interest of researchers. However, there is still an ongoing debate on their origin, the reasons behind their diversity, and their path to global distribution. The two most prominent hypotheses regarding their origin and biogeographic history involve either vicariance events after the breakup of Gondwana, or an African origin and subsequent dispersal. One of the key reasons why the question is still disputed is a dependence on knowing the age of the dung beetles - a Mesozoic origin would favor the scenario of Gondwanan vicariance, a Cenozoic origin would suggest the out-of-Africa scenario. To help settle this longstanding question, we provide a taxonomically expanded phylogeny, with divergence times estimated under two calibration schemes suggesting an older or younger origin respectively. Using model-based inference, we estimate the ancestral area of the group and test for the influence of ranges on diversification rates. Our results support the hypothesis of an old age for Scarabaeinae and Gondwanan origin but remain ambiguous about the exact relation of range on lineage diversification.


title: Phenotypic plasticity is aligned with phenological adaptation on micro- and macroevolutionary timescales

abstract: In seasonally-variable environments, phenotypic plasticity in phenology may be critical for adaptation to fluctuating environmental (temperature) conditions. Using an 18-generation longitudinal dataset from natural insect (damselfly) populations, we show that phenology has strongly advanced. Individual fitness data suggest this is likely an adaptive response towards a thermally-dependent fitness optimum. A laboratory experiment revealed that developmental plasticity qualitatively matches environmental-dependence of selection, partially explaining observed phenological advance. Expanding our analysis to the macroevolutionary level, we use a database of over 1-million occurrence records and spatiotemporally-matched temperature data from 49 Swedish Odonate species to infer macroevolutionary dynamics of phenology. Phenological plasticity was more closely aligned with adaptation for species that have recently colonized northern latitudes, with more phenological mismatch at lower latitudes. Our results show that phenological plasticity plays a key role in microevolutionary dynamics within a single species, and such plasticity may have facilitated post-Pleistocene range expansion in this insect clade.


title: Phenotypic plasticity is aligned with phenological adaptation on both micro- and macroevolutionary timescales


title: Correlated Evolution in the Small Parsimony Framework

abstract:
When studying the evolutionary relationships among a set of species, the principle of parsimony states that a relationship involving the fewest number of evolutionary events is likely the correct one. Due to its simplicity, this principle was formalized in the context of computational evolutionary biology decades ago by, e.g., Fitch and Sankoff. Because the parsimony framework does not require a model of evolution, unlike maximum likelihood or Bayesian approaches, it is often a good starting point when no reasonable estimate of such a model is available.

In this work, we devise a method for determining if pairs of discrete characters are significantly correlated across all most parsimonious reconstructions, given a set of species on these characters, and an evolutionary tree. The first step of this method is to use Sankoffs algorithm to compute all most parsimonious assignments of ancestral states (of each character) to the internal nodes of the phylogeny. Correlation between a pair of evolutionary events (e.g., absent to present) for a pair of characters is then determined by the (co-) occurrence patterns between the sets of their respective ancestral assignments. The probability of obtaining a correlation this extreme (or more) under a null hypothesis where the events happen randomly on the evolutionary tree is then used to assess the significance of this correlation. We implement this method: parcours (PARsimonious CO-occURrenceS) and use it to identify significantly correlated evolution among vocalizations and morphological characters in the Felidae family.

The parcours tool is freely available at https://github.com/murraypatterson/parcours


title: Determining significant correlation between pairs of extant characters in a small parsimony framework


title: Evidence of Chelonid Herpesvirus 5 (ChHV5) in Green Turtles (Chelonia mydas) from Sabah, Borneo

abstract: Fibropapillomatosis (FP) is characterized by cutaneous tumours and is associated with Chelonid herpesvirus 5 (ChHV5), an alphaherpesvirus from the family Herpesviridae. Here, we provide the first evidence of ChHV5-associated FP in endangered Green turtles (Chelonia mydas) from Sabah, which is located at the northern region of Malaysian Borneo. The aims of this study were firstly, to determine the presence of ChHV5 in both tumour exhibiting and tumour-free turtles using molecular techniques and secondly, to determine the phylogeography of ChHV5 in Sabah. We also aim to provide evidence of ChHV5 infection through histopathological examinations. A total of 115 Green turtles were sampled from Mabul Island, Sabah. We observed three Green turtles that exhibited FP tumours and were positive for ChHV5.In addition, six clinically healthy turtles were also positive for the virus based on Polymerase Chain Reaction of three viral genes (Capsid protein gene UL18, Glycoprotein H gene UL22 and Glycoprotein B gene UL27). The prevalence of the ChHV5 was 5.22% in asymptomatic Green turtles. Epidermal intranuclear inclusions were identified in tumour lesions upon histopathological examination. Thus, the emergence of ChHV5 in Green turtle in the waters of Sabah could indicate a possible threat to sea turtle populations in the future and requires further monitoring of the populations along the Bornean coast.

category: genetics


title: Network-based analysis of allele frequency distribution among multiple populations identifies adaptive genomic structural variants

abstract: Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a network-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 577 structural variants that show high population distribution. We further showed that 39 and 20 of these putatively adaptive structural variants overlap with coding sequences or are significantly associated with GWAS traits, respectively. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to (i) population differentiation of rapidly evolving multi-allelic variants, (ii) incomplete sweeps, and (iii) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.

category: genomics


title: Note: Updating the metadata of four misidentified samples in the DrosRTEC dataset

abstract: This note details the consortiums rationale behind its decision to modify the metadata for putatively misidentified European samples in the DrosRTEC dataset. In brief, we use PCA on published datasets from North America and Europe to generate phylogeographic clusters reflective of worldwide D. melanogaster demography. We used this PCA to train a DAPC model in order the predict the group membership. Our results indicate that 4 out of 73 samples were misclassified and the metadata was updated accordingly. These samples are a spring-fall pair from Spain and Austria.


title: Targeted RNA-seq improves efficiency, resolution, and accuracy of allele specific expression for human term placentas

abstract: Genomic imprinting is an epigenetic mechanism that results in allele specific expression (ASE) based on parent of origin. It is known to play a role in the prenatal and postnatal allocation of maternal resources in mammals. ASE detected by whole transcriptome RNA-seq (wht-RNAseq) has been widely used to analyze imprinted genes using reciprocal crosses in mice to generate large numbers of informative SNPs. Studies in humans are more challenging due to the paucity of SNPs and the poor preservation of RNA in term placentas and other tissues. Targeted RNA-seq (tar-RNAseq) can potentially mitigate these challenges by focusing sequencing resources on the regions of interest in the transcriptome. Here we compared tar-RNAseq and wht-RNAseq in a study of ASE in known imprinted genes in placental tissue collected from a healthy human cohort in Mali, West Africa. As expected, tar-RNAseq substantially improved the coverage of SNPs. Compared to wht-RNAseq, tar-RNAseq produced on average four times more SNPs in twice as many genes per sample and read depth at the SNPs increased 4-fold. In previous research on humans, discordant ASE values for SNPs of the same gene have limited the ability to accurately quantify ASE. We show that tar-RNAseq reduces this limitation as it unexpectedly increased the concordance of ASE between SNPs of the same gene, even in cases of degraded RNA. Studies aimed at discovering associations between individual variation in ASE and phenotypes in mammals and flowering plants will benefit from the improved power and accuracy of tar-RNAseq.


title: Somatic mutations reveal widespread mosaicism and mutagenesis in human placentas

abstract: Clinical investigations of human fetuses have revealed that placentas occasionally harbour chromosomal aberrations that are absent from the fetus1. The basis of this genetic segregation of the placenta, termed confined placental mosaicism, remains unknown. Here, we investigated the phylogeny of human placentas reconstructed from somatic mutations, using whole genome sequencing of 86 placental biopsies and of 106 microdissections. We found that every placental biopsy represented a clonal expansion that is genetically distinct. Biopsies exhibited a genomic landscape akin to childhood cancer, in terms of mutation burden and mutational imprints. Furthermore, unlike any other human normal tissue studied to date, placental genomes commonly harboured copy number changes. Reconstructing phylogenetic relationships between tissues from the same pregnancy, revealed that developmental bottlenecks confined placental tissues, by separating trophectodermal from inner cell mass-derived lineages. Of particular note were cases in which inner cell mass-derived and placental lineages fully segregated within a few cell divisions of the zygote. Such early embryonic bottlenecks may enable the normalisation of zygotic aneuploidy. We observed direct evidence for this in a case of mosaic trisomic rescue. Our findings reveal cancer-like mutagenesis in placental tissues and portray confined mosaicism as the normal outcome of placental development.


title: Reagent-free Raman and quantitative phase imaging offer a unique morpho-molecular platform for recognition of malignancy and stages of B-cell acute lymphoblastic leukemia

abstract: Acute lymphoblastic leukemia (ALL) is one of the most common malignancies which account for nearly one-third of all pediatric cancers. The current diagnostic assays are time-consuming, labor-intensive, and require expensive reagents. Here, we report a label-free approach featuring diffraction phase imaging and Raman microscopy that can retrieve both morphological and molecular attributes for label-free optical phenotyping of individual B cells. By investigating leukemia cell lines of early and late stages along with the healthy B cells, we show that phase image can capture subtle morphological differences among the healthy, early, and late stages of leukemic cells. By exploiting its biomolecular specificity, we demonstrate that Raman microscopy is capable of accurately identifying not only different stages of leukemia cells, but also individual cell lines at each stage. Overall, our study provides a rationale for employing this hybrid modality to screen leukemia cells using the widefield QPI and using Raman microscopy for accurate differentiation of early and late-stage phenotypes. This contrast-free and rapid diagnostic tool exhibits great promise for clinical diagnosis and staging of leukemia in the near future.

category: bioengineering


title: Axial-circular magnetic levitation assisted biofabrication and manipulation of cellular structures

abstract: Diamagnetic levitation is an emerging technology for remote manipulation of cells in cell and tissue level applications. Low-cost magnetic levitation configurations using permanent magnets are commonly composed of a culture chamber physically sandwiched between two block magnets that limit working volume and applicability. This work describes a single ring magnet-based magnetic levitation system to eliminate physical limitations for biofabrication. Developed configuration utilizes sample culture volume for construct size manipulation and long-term maintenance. Furthermore, our configuration enables convenient transfer of liquid or solid phases during the levitation. Prior to biofabrication, we first calibrated the platform for levitation with polymeric beads, considering the single cell density range of viable cells. By taking advantage of magnetic focusing and cellular self-assembly, millimeter-sized 3D structures were formed and maintained in the system allowing easy and on-site intervention in cell culture with an open operational space. We demonstrated that the levitation protocol could be adapted for levitation of various cell types (i.e., stem cell, adipocyte and cancer cell) representing cells of different densities by modifying the paramagnetic ion concentration that could be also reduced by manipulating the density of the medium. This technique allowed the manipulation and merging of separately formed 3D biological units, as well as the hybrid biofabrication with biopolymers. In conclusion, we believe that this platform will serve as an important tool in broad fields such as bottom-up tissue engineering, drug discovery and developmental biology.


title: A deep learning framework for real-time detection of novel pathogens during sequencing

abstract: Novel pathogens evolve quickly and may emerge rapidly, causing dangerous outbreaks or even global pandemics. Next-generation sequencing is the state-of-the-art in open-view pathogen detection, and one of the few methods available at the earliest stages of an epidemic, even when the biological threat is unknown. Analyzing the samples as the sequencer is running can greatly reduce the turnaround time, but existing tools rely on close matches to lists of known pathogens and perform poorly on novel species. Machine learning approaches can predict if single reads originate from more distant, unknown pathogens, but require relatively long input sequences and processed data from a finished sequencing run. Incomplete sequences contain less information, leading to a trade-off between sequencing time and detection accuracy. Using a workflow for real-time pathogenic potential prediction, we investigate which subsequences already allow accurate inference. We train deep neural networks to classify Illumina and Nanopore reads and integrate the models with HiLive2, a real-time Illumina mapper. This approach outperforms alternatives based on machine learning and sequence alignment on simulated and real data, including SARS-CoV-2 sequencing runs. After just 50 Illumina cycles, we observe an 80-fold sensitivity increase compared to real-time mapping. The first 250bp of Nanopore reads, corresponding to 0.5s of sequencing time, are enough to yield predictions more accurate than mapping the finished long reads. The approach could also be used for screening synthetic sequences against biosecurity threats.


title: Deep learning-based real-time detection of novel pathogens during sequencing


title: The competition dynamics of resistant and sensitive infections

abstract:
Antimicrobial resistance is a major health problem with complex dynamics. Resistance may occur in an area because treated infections mutated and developed resistance, and the proportion of infections in a population may then increase. We developed a novel and flexible model that captures several features of resistance dynamics and competition. The model is able to account for many antimicrobials and thus can generally explore competition dynamics and their impact on pathogens and bacteria.

Unlike simpler models, our nested model allows the population of resistant pathogen to smoothly increase or decrease. Time dependent dynamics are incorporated into difference equations which examines the effects of 12 parameters. This enables us to explicitly include three key competition dynamics: the transmission cost of resistance that occurs between hosts, the fitness cost of resistance that occurs within untreated hosts, and the release of this competition (from the fitness cost) that occurs once a host is treated. For malaria, our results suggest that without competitive release, drug resistance does not emerge. However, once emerged, competitive release has little effect, and the best way to mitigate the spread is to ensure that treatment is very effective.


title: In-silico Structural and Molecular Docking-Based Drug Discovery Against Viral Protein (VP40) of Marburg Virus: A Causative Agent of MAVD

abstract: The Marburg virus (MARV) is reported to induce extreme hemorrhagic fever (MHF) with a high degree of infectivity and lethality in both human and non-human primates. An appropriate vaccination for this viruss treatment is not yet usable, and thus needs intensive attempts on multiple scales. In this study, we employed the Computer-Aided Drug Design (CADD) based approach to identify the drug-like compounds inhibiting the replication of the Viral protein (VP40) of MARV. Our database search using an online database "PubChem" retrieved [~]3000 compounds structure-based similarity. Lipinskis rule was applied to evaluate further the drug-like compounds, followed by molecular docking-based screening, and the selection of screening ligand complex with VP40 based on S-score (lower than reference Favipiravir inhibitor) and root-mean-square-deviation (RMSD) value (probably less than 2) using AutoDock 4.2. Resultantly, [~]100 compounds were identified having strong interaction with VP40 of MARV. After evaluating their binding energy using the AutoDock 4.2 software, four compounds (CID-67534452, CID-72201087, CID-123273976, CID-153708661) were identified that showed strongest binding energy with VP40 of MARV and strong inhibition effect than the Favipiravir. Robust binding energy, useful ADMET parameters and drug-likeness suggest that these candidates "CID-67534452, CID-72201087, CID-123273976, CID-153708661" have tremendous potential to stop the replication of MARV, hence might lead to the cure of MAVD.


title: The relationship between ageing and changes in the human blood and brain methylomes

abstract: Changes in DNA methylation have been found to be strongly correlated with age, enabling the creation of "epigenetic clocks". Previously, studies on the relationship between ageing and DNA methylation have assumed a linear relationship, but no study has shown this always to be the case. We show that the relationships between significant methylation changes and ageing are different in different tissues, and that these changes show variable rates across life. Further, we observe a tendency for saturation as ageing proceeds. We provide a straightforward method of assessing all methylation-age relationships and cluster them according to their relative change rates based on fold change. Less than 13% of the significant markers selected here are used in the most common epigenetic clocks. When the significant markers display largely non-linear relationships, our fold change selection outperforms the most common epigenetic clocks in predicting age. We also show that the saturation observed at older ages explains the earlier observations that the epigenetic clock consistently underestimates the age in older samples. The findings imply that markers selected from linear adjustments or correlations do not represent the most meaningful biological changes.


title: Separate neural dynamics underlying the acquisition of different auditory category structures

abstract:
Current models of auditory category learning argue for a rigid specialization of hierarchically organized regions that are fine-tuned to extracting and mapping acoustic dimensions to categories. We test a competing hypothesis: the neural dynamics of emerging auditory representations are driven by category structures and learning strategies. We designed a category learning experiment where two groups of learners learned novel auditory categories with identical dimensions but differing category structures: rule-based (RB) and information-integration (II) based categories. Despite similar learning accuracies, strategies and cortico-striatal systems processing feedback differed across structures. Emergent neural representations of category information within an auditory frontotemporal pathway exclusively for the II learning task. In contrast, the RB task yielded neural representations within distributed regions involved in cognitive control that emerged at different time-points of learning. Our results demonstrate that learners neural systems are flexible and show distinct spatiotemporal patterns that are not dimension-specific but reflect underlying category structures.

SignificanceWhether it is an alarm signifying danger or the characteristics of background noise, humans are capable of rapid auditory learning. Extant models posit that novel auditory representations emerge in the superior temporal gyrus, a region specialized for extracting behaviorally relevant auditory dimensions and transformed onto decisions via the dorsal auditory stream. Using a computational cognitive neuroscience approach, we offer an alternative viewpoint: emergent auditory representations are highly flexible, showing distinct spatial and temporal trajectories that reflect different category structures.


title: Molecular mechanism of a parasite kinesin motor and implications for its inhibition

abstract: Plasmodium parasites cause malaria and are responsible annually for hundreds of thousands of deaths. They have a complex life cycle in which distinct stages are transmitted between, and reproduce in, human and mosquito hosts. In the light of emerging resistance to current therapies, components of the parasite replicative machinery are potentially important targets for anti-parasite drugs. Members of the superfamily of kinesin motors play important roles in the microtubule-based replicative spindle machinery, and kinesin-5 motors are established anti-mitotic targets in other disease contexts. We therefore studied kinesin-5 from Plasmodium falciparum (PfK5) and characterised the biochemical properties and structure of the PfK5 motor domain. We found that the PfK5 motor domain is an ATPase with microtubule plus-end directed motility. We used cryo-EM to determine the motors microtubule-bound structure in no nucleotide and AMPPNP-bound states. Despite significant sequence divergence in this motor, these structures reveal that this parasite motor exhibits classical kinesin mechanochemistry. This includes ATP-induced neck-linker docking to the motor domain, which is consistent with the motors plus-ended directed motility. Crucially, we also observed that a large insertion in loop5 of the PfK5 motor domain creates a dramatically different chemical environment in the well characterised human kinesin-5 drug-binding site. Our data thereby reveal the possibility for selective inhibition of PfK5 and can be used to inform future exploration of Plasmodium kinesins as anti-parasite targets.

category: biophysics


title: RNA Pore Translocation with Static and Periodic Forces: Effect of Secondary and Tertiary Elements on Process Activation and Duration

abstract: We use MD simulations to study the pore translocation properties of a pseudoknotted viral RNA. We consider the 71-nucleotide long xrRNA from Zika virus and establish how it responds when driven through a narrow pore by static or periodic forces applied to either one of the two termini. Unlike the case of fluctuating homopolymers, the onset of translocation is significantly delayed with respect to the application of static driving forces. Because of the peculiar xrRNA architecture, activation times can differ by orders of magnitude at the two ends. Instead, translocation duration is much smaller than activation times and occurs on timescales comparable at the two ends. Periodic forces amplify significantly the differences at the two ends, both for activation times and translocation duration. Finally, we use a waiting-times analysis to examine the systematic slowing-downs in xrRNA translocations and associate them to the hindrance of specific secondary and tertiary elements of xrRNA. The findings ought to be useful as a reference to interpret and design future theoretical and experimental studies of RNA translocation.


title: Analyzing cancer gene expression data through the lens of normal tissue-specificity

abstract: The genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.


title: Water and Electrolyte Homeostasis in a Mouse Model with Reduced ENaC Gamma Subunit Expression

abstract: The epithelial Na+ channel (ENaC) promotes the absorption of Na+ in the aldosterone-sensitive distal nephron, colon, and respiratory epithelia. Deletion of genes encoding ENaCs subunits results in early post-natal mortality. We present initial characterization of a mouse with dramatically suppressed expression of the {gamma} subunit. We use this hypomorphic ({gamma}mt) allele to explore the importance of ENaCs {gamma} subunit in homeostasis of electrolytes and body fluid volume. At baseline, {gamma} subunit expression in {gamma}mt/mt mice is markedly suppressed in kidney and lung, while electrolytes resemble those of littermate controls. Challenge with a high K+ diet does not cause significant differences in blood K+, but provokes higher aldosterone in {gamma}mt/mt mice than controls. Quantitative magnetic resonance (QMR) measurement of body composition reveals similar baseline body water, lean tissue mass, and fat tissue mass in {gamma}mt/mt mice and controls. Surprisingly, euvolemia is sustained without significant changes in aldosterone or atrial natriuretic peptide. {gamma}mt/mt mice exhibit a more rapid decline in body water and lean tissue mass in response to a low Na+ diet than controls. Replacement of drinking water with 2% saline induces dramatic increases in body fat in both genotypes, and a selective transient increase in body water and lean tissue mass in {gamma}mt/mt mice. While ENaC in renal tubules and colon work to prevent extracellular fluid volume depletion, our observations suggest that ENaC in non-epithelial tissues may have a role in preventing extracellular fluid volume overload.


title: L-WNK1 is required for BK channel activation in intercalated cells

abstract: BK channels expressed in intercalated cells (ICs) in the aldosterone-sensitive distal nephron (ASDN) mediate flow-induced K+ secretion. In the ASDN of mice and rabbits, IC BK channel expression and activity increase with a high K+ diet. In cell culture, the long isoform of the kinase WNK1 (L-WNK1) increases BK channel expression and activity. Apical L-WNK1 expression is selectively enhanced in ICs in the ASDN of rabbits on a high K+ diet, suggesting that L-WNK1 contributes to BK channel regulation by dietary K+. We examined the role of IC L-WNK1 expression in enhancing BK channel activity in response to a high K+ diet. Mice with an IC-selective deletion of L-WNK1 (IC-L-WNK1-KO) and littermate control mice were placed on a high K+ (5% K+ as KCl) diet for at least 10 days. IC-L-WNK1-KO mice exhibited higher blood K+ concentrations ([K+]) than controls. BK channel-dependent whole-cell currents in ICs from cortical collecting ducts of high K+ fed IC-L-WNK1-KO mice were reduced compared to controls. Six-hour urinary K+ excretion in response a saline load was similar in IC-L-WNK1-KO mice and controls. The observations that IC-L-WNK1-KO mice have higher blood [K+] and reduced IC BK channel currents are consistent with impaired urinary K+ secretion, and suggest that IC L-WNK1 has a role in the renal adaptation to a high K+ diet.


title: AI-driven Deep Visual Proteomics defines cell identity and heterogeneity

abstract: The systems-wide analysis of biomolecules in time and space is key to our understanding of cellular function and heterogeneity in health and disease1. Remarkable technological progress in microscopy and multi-omics technologies enable increasingly data-rich descriptions of tissue heterogeneity2,3,4,5. Single cell sequencing, in particular, now routinely allows the mapping of cell types and states uncovering tremendous complexity6. Yet, an unaddressed challenge is the development of a method that would directly connect the visual dimension with the molecular phenotype and in particular with the unbiased characterization of proteomes, a close proxy for cellular function. Here we introduce Deep Visual Proteomics (DVP), which combines advances in artificial intelligence (AI)-driven image analysis of cellular phenotypes with automated single cell laser microdissection and ultra-high sensitivity mass spectrometry7. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. Individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and novel proteins. AI also discovered rare cells with distinct morphology, whose potential function was revealed by proteomics. Applied to archival tissue of salivary gland carcinoma, our generic workflow characterized proteomic differences between normal-appearing and adjacent cancer cells, without admixture of background from unrelated cells or extracellular matrix. In melanoma, DVP revealed immune system and DNA replication related prognostic markers that appeared only in specific tumor regions. Thus, DVP provides unprecedented molecular insights into cell and disease biology while retaining spatial information.

category: systems biology


title: A Developmental Role for Microglial Presenilin 1 in Memory

abstract: Microglia, the macrophages of the brain, are increasingly recognized to play a key role in synaptic plasticity and function; however, the underlying mechanisms remain elusive. Presenilin 1 (PS1) is an essential protein involved in learning and memory, through neuronal mechanisms. Loss of Presenilin function in neurons impairs synapse plasticity and causes cognitive deficits in mice. Surprisingly, here we show memory enhancement in mice by deleting PS1 selectively in microglia. We further demonstrate increased synapse transmission and in vivo neuronal activity in mice by depleting PS1 during microglial development, but not after microglial maturation. Remarkably, conditional deletion of PS1 in microglia during development increased memory retention in adulthood and was dependent on the NMDA receptor subunit GluN2B. In vivo calcium imaging of freely behaving mice revealed increased amplitude of neuronal Ca2+ transients in the CA1 hippocampus of PS1 cKO mice compared to control mice, suggesting a greater CA1 engagement during novel object exploration. Finally, loss of PS1 in microglia mitigated synaptic and cognitive deficits in a mouse model of Alzheimers disease. Together our results reveal a novel mechanism and function of PS1 in microglia in which modulation can enhance neuronal activity, learning and memory in mice.

category: neuroscience


title: TREM2 is thyroid hormone regulated making the TREM2 pathway druggable with ligands for thyroid hormone receptor

abstract: Triggering receptor expressed on myeloid cells-2 (TREM2) is a cell surface receptor on macrophages and microglia that senses and responds to disease associated signals to regulate the phenotype of these innate immune cells. The TREM2 signaling pathway has been implicated in a variety of diseases ranging from neurodegeneration in the central nervous system to metabolic disease in the periphery. We report here that TREM2 is a thyroid hormone regulated gene and its expression in macrophages and microglia is stimulated by thyroid hormone. Both endogenous thyroid hormone and sobetirome, a synthetic thyroid hormone agonist drug, suppress pro-inflammatory cytokine production from myeloid cells including macrophages that have been treated with the SARS-CoV-2 spike protein which produces a strong, pro-inflammatory phenotype. Thyroid hormone agonism was also found to induce phagocytic behavior in microglia, a phenotype consistent with activation of the TREM2 pathway. The thyroid hormone antagonist NH-3 blocks the anti-inflammatory effects of thyroid hormone agonists and suppresses microglia phagocytosis. Finally, in a murine experimental autoimmune encephalomyelitis (EAE) multiple sclerosis model, treatment with Sob-AM2, a CNS-penetrating sobetirome prodrug, results in increased Trem2 expression in disease lesion resident myeloid cells which correlates with therapeutic benefit in the EAE clinical score and reduced damage to myelin. Our findings represent the first report of endocrine regulation of TREM2 and provide a unique opportunity to drug the TREM2 signaling pathway with orally active small molecule therapeutic agents.


title: Dermal macrophages set pain sensitivity by modulating tissue NGF levels through SNX25-Nrf2 signaling

abstract: Crosstalk between peripheral neurons and immune cells plays important roles in pain sensation. We identified sorting nexin 25 (Snx25) as a pain-modulating gene in a transgenic mouse line with reduced pain behavior. Snx25 conditional-KO (cKO) in monocyte/macrophage-lineage cells but not in the peripheral sensory neurons reduced pain responses in both normal and neuropathic conditions. Cross transplantation experiments of bone marrows between cKO and wild type (WT) mice revealed that cKO macrophages caused dull phenotype in WT mice and WT macrophages in turn increased pain behavior in cKO mice. SNX25 in dermal macrophages enhances NGF (one of the key factors in pain sensation) production by inhibiting ubiquitin-mediated degradation of Nrf2, a transcription factor that activates Ngf mRNA synthesis. We conclude that dermal macrophages set pain sensitivity by producing and secreting NGF into the dermis in addition to their host defense functions.