title: Gene flow between two thick-billed grasswren subspecies with low dispersal creates a genomic pattern of isolation-by-distance

abstract:
ContextIn the era of the Anthropocene, habitat loss and environmental change threaten the persistence of many species. Genotyping-By-Sequencing (GBS) is a useful molecular tool for understanding how patterns of gene flow are associated with contemporary habitat distributions that may be affected by environmental change. Two parapatric subspecies of the threatened thick-billed grasswren (TBGW; Amytornis modestus) more frequently occur in different plant communities. As such, a preference for plant community type could reduce subspecific introgression and increase genetic diversity at the parapatric boundary.

AimsWe aimed to measure gene flow within and among two TBGW subspecies and tested whether divergent genomic markers were associated with plant community type.

MethodsWe sequenced 118 individuals from either of the two TBGW subspecies or in the region of parapatry and identified 7583 SNPs through ddRADseq.

Key resultsWe found evidence of asymmetric gene flow and a genomic pattern of isolation-by-distance. There were sixteen genomic outliers correlated with plant community type (regardless of location).

ConclusionsThese findings show that plant community type does not prevent introgression in one subspecies (A. m. raglessi), but low dispersal and habitat heterogeneity could contribute to the maintenance of distinct subspecific morphotypes. Local adaptation in different plant community types could also provide a mechanism for future divergence.

ImplicationsWe suggest subspecific introgression could increase genetic variation and the adaptive potential of the species, facilitating species persistence under conditions of climate change.

Introgression between grasswren subspeciesCharacterising gene flow facilitates conservation management. This study used genomic markers to measure gene flow between thick-billed grasswren subspecies and found results that support taxonomic identification of the two subspecies and suggests grasswrens have low dispersal and may benefit from increased genetic diversity. Recognition of models of divergence with gene flow will be necessary for future conservation management.


title: AF-vapeR: A multivariate genome scan for detecting parallel evolution using allele frequency change vectors

abstract:
O_LIThe repeatability of evolution at the genetic level has been demonstrated to vary along a continuum from complete parallelism to divergence. In order to better understand why this continuum exists within and among systems, hypotheses must be tested using high confidence sets of candidate loci for repeatability. Despite this, few methods have been developed to scan SNP data for signatures specifically associated with repeatability, as opposed to local adaptation.
C_LIO_LIHere we present AF-vapeR (Allele Frequency Vector Analysis of Parallel Evolutionary Responses), an approach designed to identify genome regions exhibiting highly correlated allele frequency changes within haplotypes and among replicated allele frequency change vectors. The method divides the genome into windows of an equivalent number of SNPs, and within each window performs eigen decomposition over normalised allele frequency change vectors (AFV), each derived from a replicated pair of populations/species. Properties of the resulting eigenvalue distribution can be used to compare regions of the genome for those exhibiting strong parallelism, and can also be compared against a null distribution derived from randomly permuted AFV. Further, the shape of the eigenvalue distribution can reveal multiple axes of parallelism within datasets.
C_LIO_LIWe demonstrate the utility of this approach to detect different modes of parallel evolution using simulations, and also demonstrate a reduction in error rate compared with intersecting FST outliers. Lastly, we apply AF-vapeR to three previously published datasets (stickleback, guppies, and Galapagos finches) which comprise a range of sampling and sequencing strategies, and lineage ages. We detect known parallel regions whilst also identifying novel candidates.
C_LIO_LIThe main benefits of this approach include a reduced false-negative rate under many conditions, an emphasis on signals associated specifically with repeatable evolution as opposed to local adaptation, and an opportunity to identify different modes of parallel evolution at the first instance.
C_LI

category: evolutionary biology


title: The evolutionary pathways for local adaptation in mountain hares

abstract: Understanding the evolution of local adaptations is a central aim of evolutionary biology and key for the identification of unique populations and lineages of conservation relevance. By combining RAD sequencing and whole-genome sequencing, we identify genetic signatures of local adaptation in mountain hares (Lepus timidus) from isolated and distinctive habitats of its wide distribution: Ireland, the Alps and Fennoscandia. Demographic modelling suggested that the split of these mountain hares occurred around 20 thousand years ago, providing the opportunity to study adaptive evolution over a short timescale. Using genome-wide scans, we identified signatures of extreme differentiation among hares from distinct geographic areas that overlap with area-specific selective sweeps, suggesting targets for local adaptation. Several identified candidate genes are associated with traits related to the uniqueness of the different environments inhabited by the three groups of mountain hares, including coat colour, ability to live at high altitudes and variation in body size. In Irish mountain hares, a variant of ASIP, a gene previously implicated in introgression-driven winter coat colour variation in mountain and snowshoe hares (L. americanus), may underlie brown winter coats, reinforcing the repeated nature of evolution at ASIP moulding adaptive seasonal colouration. Comparative genomic analyses across several hare species suggested that mountain hares adaptive variants appear predominantly species-specific. However, using coalescent simulations we also show instances where the candidate adaptive variants have been introduced via introgressive hybridization. Our work shows that standing adaptive variation, including that introgressed from other species, was a crucial component of the post-glacial dynamics of species.


title: APPRIS principal isoforms and MANE Select transcripts in clinical variant interpretation

abstract:
Most coding genes are able to generate multiple alternatively spliced transcripts. Determining which of these transcript variants produces the main protein isoform, and which of a genes multiple splice variants are functionally important, is crucial in comparative genomics and essential for clinical variant interpretation.

Here we show that the principal isoforms chosen by APPRIS and the MANE Select variants provide the best approximations of the main cellular protein isoforms. Principal isoforms are predicted from conservation and from protein features, and MANE transcripts are chosen from the consensus between teams of expert manual curators. APPRIS principal isoforms coincide in over 94% of coding genes with MANE Select transcripts and the two methods are particularly discriminating when they agree on the main splice variant. Where the two methods agree, the splice variants coincide with the main isoform detected in proteomics experiments in 98.2% of genes with multiple protein isoforms.

We also find that almost all ClinVar pathogenic mutations map to MANE Select or APPRIS principal isoforms. Where APPRIS and MANE agree on the main isoform, 99.93% of validated pathogenic variants map to principal rather than alternative exons. MANE Plus Clinical transcripts cover most validated pathogenic mutations in alternative coding exons. TRIFID functional importance scores are particularly useful for distinguishing clinically important alternative isoforms: the highest scoring TRIFID isoforms are more than 300 times more likely to have validated pathogenic mutations.

We find that APPRIS, MANE and TRIFID are important for determining the biological relevance of splice isoforms and should be an essential part of clinical variant interpretation.

category: genomics


title: In search of a core cellular network in single cell transcriptome data

abstract: Along with specialized functions, cells of multicellular organisms also perform essential functions. Whether diverse cells do this by using the same set of genes, interacting in a fixed coordinated fashion, remains a central question in biology. Single-cell RNA-sequencing (scRNA-seq) measures gene expression of individual cells, enabling researchers to discover gene expression patterns that contribute to the diversity of cell functions. Current efforts focus primarily on identifying differentially expressed genes. However, patterns of co-expression between genes are more indicative of biological processes than are the expression of individual genes. Here, we constructed cell type-specific gene co-expression networks using the fly brain transcriptome atlas to search for a core cellular network. We detected a set of highly coordinated genes preserved across cell types and defined this set as the core network. This network was further validated through two additional datasets profiling fly brains or heads. This core has a small size and shows dense connectivity. Modules within this core are enriched for basic cellular functions and gene members of these modules have distinct evolutionary signatures. Overall, we demonstrated that a core cellular network exists in diverse cell types of fly brains and this core exhibits unique topological, structural, functional and evolutionary properties.


title: In search of a core cellular network with single cell transcriptome data in the fruit fly


title: Does endogenous variation in stress modulate risk and time preferences?

abstract: It has been argued that one dimension of the cycle of poverty is that poverty is a state of chronic stress and that chronic stress impairs decision-making. These poor decisions, made under chronic stress, might include carrying high-interest loans, failure to buy health insurance, gambling or drug use. As such, these decisions can contribute to the cycle of poverty. More specifically, a few studies suggest that increased stress may lead to more risk-aversion and steeper delay-discounting. While the deleterious effects of chronic stress on brain function are well established, much less is known about how chronic stress influences financial decision making specifically. Here, in a longitudinal design within six weeks period we aimed to incorporate biological mechanisms to improve our understanding of how stress influences economic decisions. We used a combination of decision-making tasks, questionnaires, saliva and hair samples within-subject (N=41). We assessed time and risk preferences using hierarchical Bayesian techniques to both pool data and allow heterogeneity in decision making and compared those to cortisol levels and self-reported stress. We found only weak links between endogenous variation in stress and model-based estimates of risk and time preferences. In particular, we found that fluctuations in the stress level measured via hair sample were not only positively correlated with time preferences in the short delay task and risk preferences, but also the decision noise in the risk task. However, relationships for the risk task disappeared when an outlier was removed. Also, we found model-free task measures in the short delay task to be moderately related to both hair cortisol as well as the stressful life events questionnaire measure. For example, we observed that endogenous stress fluctuations and the life change units were negatively correlated with the proportion of later choices. Finally, we established that for the reaction times the curvilinear relationship was preferred to the linear one for those with increase in biological stress level compared to the baseline: when cortisol level increased slightly, participants decided slower, but when stress increased to higher levels, they decided quicker.

category: animal behavior and cognition


title: Pitfalls and recommended strategies and metrics for suppressing motion artifacts in functional MRI

abstract: In resting-state functional magnetic resonance imaging (rs-fMRI), artefactual signals arising from subject motion can dwarf and obfuscate the neuronal activity signal. Typical motion correction approaches involve the generation of nuisance regressors, which are timeseries of non-brain signals regressed out of the fMRI timeseries to yield putatively artifact-free data. Recent work suggests that concatenating all regressors into a single regression model is more effective than the sequential application of individual regressors, which may reintroduce previously removed artifacts. This work compares 18 motion correction pipelines consisting of head motion, independent components analysis, and non-neuronal physiological signal regressors in sequential or concatenated combinations. The pipelines are evaluated on a dataset of cognitively normal individuals with repeat imaging and on datasets of studies of Autism Spectrum Disorder, Major Depressive Disorder, and Parkinsons Disease. Extensive metrics of motion artifact removal are measured, including resting state network recovery, Quality Control-Functional Connectivity (QC-FC) correlation, distance-dependent artifact, network modularity, and test-retest reliability of multiple rs-fMRI analyses. The results reveal limitations in previously proposed metrics, including the QC-FC correlation and modularity quality, and identify more robust motion correction metrics. The results also reveal limitations in the concatenated regression approach, which is outperformed by the sequential regression approach in the test-retest reliability metrics. Finally, pipelines are recommended that perform well based on quantitative and qualitative comparisons across multiple datasets and robust metrics. These new insights and recommendations help address the need for effective motion artifact correction to reduce noise and confounds in rs-fMRI.

category: bioengineering


title: Directing multicellular organization by varying the aspect ratio of soft hydrogel microwells

abstract: Multicellular organization with precise spatial definition is an essential step in a wide range of biological processes, including morphogenesis, development, and healing. Gradients and patterns of chemoattractants are well-described guides of multicellular organization, but the influences of three-dimensional geometry of soft hydrogels on multicellular organization are less well defined. Here, we report the discovery of a new mode of self-organization of endothelial cells in ring-like patterns on the perimeters of hydrogel microwells that is independent of protein or chemical patterning and is driven only by geometry and substrate stiffness. We observe quantitatively striking influences of both the microwell aspect ratio ({varepsilon} = perimeter/depth) and the hydrogel modulus. We systematically investigate the physical factors of cells and substrates that drive this multicellular behavior and present a mathematical model that explains the multicellular organization based upon balancing extracellular and cytoskeletal forces. These forces are determined in part by substrate stiffness, geometry, and cell density. The force balance model predicts the direction and distance of translational cell migration based on the dynamic interaction between tangential cytoskeletal tension and cell-cell and cell-substrate adhesion. We further show that the experimental observations can be leveraged to drive customized multicellular self-organization. Our observation of this multicellular behavior demonstrates the importance of the combinatorial effects of geometry and stiffness in complex biological processes. It also provides a new methodology for direction of cell organization that may facilitate the engineering of bionics and integrated model organoid systems.


title: Self-healing of hyaluronic acid to improve in vivo retention and function

abstract: Convergent advances in the field of soft matter, macromolecular chemistry, and engineering have led to the development of biomaterials that possess autonomous, adaptive, and self-healing characteristics similar to living systems. These rationally designed biomaterials could surpass the capabilities of their parent material. Herein, we describe the modification of hyaluronic acid (HA) molecules to exhibit self-healing properties and studied its physical and biological function both in vitro and in vivo. Our in vitro findings showed that self-healing HA designed to undergo autonomous repair improved lubrication, enhanced free radical scavenging, and resisted enzymatic degradation compared to unmodified HA. Longitudinal imaging following intra-articular injection of self-healing HA showed improved in vivo retention despite the low molecular weight. Concomitant with these functions, intra-articular injection of self-healing HA mitigated anterior cruciate ligament injury-mediated cartilage degeneration in rodents. This proof-of-concept study shows how incorporation of functional properties like self-healing can be used to surpass the existing capabilities of biolubricants.


title: Blood flow modeling reveals improved collateral artery performance during mammalian heart regeneration

abstract: Collateral arteries are a vessel subtype that bridges two artery branches, forming a natural bypass that can deliver blood flow downstream of an occlusion. These bridges in the human heart are associated with better outcomes during coronary artery disease. We recently found that their rapid development in neonates supports heart regeneration, while the non-regenerative adult heart displays slow and minimal collateralization. Thus, inducing robust collateral artery networks could serve as viable treatment for cardiac ischemia, but reaching this goal requires more knowledge on their developmental mechanisms and functional capabilities. Here, we use whole-organ imaging and 3D computational fluid dynamics (CFD) modeling to identify the spatial architecture of and predict blood flow through collaterals in neonate and adult hearts. We found that neonate collaterals are more numerous, larger in diameter, and, even when similar in size/number, are predicted to more effectively re-perfuse an occluded coronary network when compared to adults. CFD analysis revealed that collaterals perform better in neonates because of decreased differential pressures along their coronary artery tree. Furthermore, testing of various collateral configurations indicated that larger, more proximal collaterals are more beneficial than many smaller ones, identifying a target architecture for therapeutic interventions. Morphometric analysis revealed how the coronary artery network expands during postnatal growth. Vessel diameters do not scale with cardiac muscle growth. Instead, the coronary tree expands solely by adding additional branches of a set length, a burst of which occurs during murine puberty. Finally, we compared mouse structural and functional data to human hearts. Surprisingly, fetal human hearts possessed a very large number of small, but mature, smooth muscle cell covered collaterals while angiogram data indicated adult patients with chronic coronary occlusions contained at least two. Comparing size ratios with modeled mouse data suggested low re-perfusion capabilities of the embryonic collaterals but higher functional benefits of those in diseased adults. Our unique interdisciplinary approach allowed us to quantify the functional significance of collateral arteries during heart regeneration and repair-a critical step towards realizing their therapeutic potential.


title: SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural source

abstract:
Proteins isolated from natural source can be composed of a mixture of isoforms with similar physicochemical properties that coexists in final steps of purification, toxins being prominent examples. Sequence composition is enforced throughout structural studies even when unsubstantiated. Herein, we propose a novel perspective to address the usually neglected heterogeneity of natural products by integrating biophysical, genetic and structural data in our program SEQUENCE SLIDER.

The aim is to assess the evidence supporting chemical composition in structure determination. Locally, we interrogate the experimental map to establish which side chains are supported by the structural data and the genetic information relating sequence conservation is integrated in this statistic. Hence, we build a constrained peptide database, containing most probable sequences to interpret mass spectrometry data (MS). In parallel, we perform MS de novo sequencing with genomic-based algorithms that foresee point mutations.

We calibrated SLIDER with Gallus gallus lysozyme, for which sequence is unequivocally established and numerous natural isoforms are reported. We used SLIDER to characterise a metalloproteinase and a phospholipase A2-like protein from the venom of Bothrops moojeni and a crotoxin from Crotalus durissus collilineatus. This integrated approach offers a more realistic structural descriptor to characterize macromolecules isolated from natural source.

Key pointsO_LIThe method SEQUENCE SLIDER integrates biophysical, genetic and structural data to assign sequence.
C_LIO_LIIt joins crystallography, mass spectrometry and phylogenetic data to characterize isoforms.
C_LIO_LISequence heterogeneity of four proteins purified directly from snake venom was established.
C_LI

category: bioinformatics


title: Deciphering PD1 activation mechanism from molecular docking and molecular dynamic simulations

abstract: The activation of T cells is normally accompanied by inhibitory mechanisms within which the PD1 receptor stands out. Upon binding the ligands PDL1 and PDL2, PD1 drives T cells to an unresponsive state called exhaustion characterized by a markedly decreased capacity to exert effector functions. For this reason, PD1 has become one of the most important targets in cancer immunotherapy. Despite the numerous studies about PD1 signaling modulation, how the PD1 signaling is activated upon the ligands binding remains an open question. Several experimental facts suggest that the activation of the PD1-PLD1 pathway depends on the interaction with an unknown partner at the cellular membrane. In this work, we investigate the possibility that the target of PD1-PDL1 is the same PD1-PDL1 complex. We combined molecular docking to explore different binding modes with molecular dynamics and umbrella sampling simulations to assess the complexes stability. We found a high molecular weight complex that explains the activation of PD1 upon PDL1 binding. This complex has an affinity comparable to the PD1-PDL1 interaction and resembles the form of a linear lattice.


title: SMAP: A pipeline for sample matching in proteogenomics

abstract: Integration of genomics and proteomics (proteogenomics) offers unprecedented promise for in-depth understanding of human diseases. However, sample mix-up is a pervasive, recurring problem, due to complex sample processing in proteogenomics. Here we present a pipeline for Sample Matching in Proteogenomics (SMAP) for verifying sample identity to ensure data integrity. SMAP infers sample-dependent protein-coding variants from quantitative mass spectrometry (MS), and aligns the MS-based proteomic samples with genomic samples by two discriminant scores. Theoretical analysis with simulation data indicates that SMAP is capable of uniquely match proteomic and genomic samples, when [≥]20% genotypes of individual samples are available. When SMAP was applied to a large-scale proteomics dataset from 288 biological samples generated by the PsychENCODE BrainGVEX project, we identified and corrected 18.8% (54/288) mismatched samples. The correction was further confirmed by ribosome profiling and assay for transposase-accessible chromatin sequencing data from the same set of samples. Thus our results demonstrate that SMAP is an effective tool for sample verification in a large-scale MS-based proteogenomics study. The source code, manual, and sample data of the SMAP are publicly available at https://github.com/UND-Wanglab/SMAP, and a web-based SMAP can be accessed at https://smap.shinyapps.io/smap/.


title: Group size planning of breedings of gene-modified animals

abstract: Animal breeding is time-consuming, costly, and affected by stochastic events related to Mendelian genetics, fertility, and litter size. Careful planning is mandatory to ensure a successful outcome using the least number of animals, hence adhering to the 3Rs of animal welfare. We have developed an R package, accessible also through an interactive website, that optimizes breeding design and provides a comprehensive report suitable for any breeder of genetically defined traits.


title: Towards Compilation of Balanced Protein Stability Datasets: Flattening the ΔΔG Curve through Systematic Under-sampling

abstract: Protein stability datasets contain neutral mutations that are highly concentrated in a much narrower {Delta}{Delta}G range than destabilizing and stabilizing mutations. Notwith-standing their high density, often studies analyzing stability datasets and/or predictors ignore the neutral mutations and use a binary classification scheme labeling only destabilizing and stabilizing mutations. Recognizing that highly concentrated neutral mutations would affect the quality of stability datasets, we have explored three protein stability datasets; S2648, PON-tstab and the symmetric Ssym that differ in size and quality. A characteristic leptokurtic shape in the {Delta}{Delta}G distributions of all three datasets including the curated and symmetric ones were reported due to concentrated neutral mutations. To further investigate the impact of neutral mutations on {Delta}{Delta}G predictions, we have comprehensively assessed the performance of eleven predictors on the PON-tstab dataset. Correlation and error analyses showed that all of the predictors performed the best on the neutral mutations while their performance became gradually worse as the {Delta}{Delta}G of the mutations departed further from the neutral zone regardless of the direction, implying a bias towards dense mutations. To this end, after unraveling the role of concentrated neutral mutations in biases of stability datasets, we described a systematic under-sampling approach to balance the {Delta}{Delta}G distributions. Before under-sampling, mutations were clustered based on their biochemical and/or structural features and then three mutations were systematically selected from every 2 kcal/mol of each cluster. Upon implementation of this approach by distinct clustering schemes, we generated five subsets varying in size and {Delta}{Delta}G distributions. All subsets notably showed amelioration of not only the shape of {Delta}{Delta}G distributions but also other pre-existing imbalances in the frequency distributions. We also reported differences in the performance of the predictors between the parent and under-sampled subsets due to the enrichment of previously under-represented mutations in the subsets. Altogether, this study not only elaborated the pivotal role of concentrated mutations in the dataset biases but also contemplated and realized a rational strategy to tackle this and other forms of biases. Under-sampling code is available on GitHub (https://github.com/narodkebabci/gRoR).


title: Taxonomy Analysis in Bacteria Kingdom based onProtein Domain: A Comparison Study

abstract:
The taxonomy research on the bacterial kingdom is important and can be usually conducted by the analysis on conserved genes, 16s rRNA, protein domain, and so on. Comparatively, the protein domains maintain a most direct relationship with phenotypes. In this paper, based on the protein domain, we propose a 3-step framework to standardize the classification process of bacteria. Different model candidates are involved and discussed in each step. By comparing the classification results with existing taxonomy, we select the most appropriate candidate to improve the framework, and furthermore, discuss their biological significance. Finally, we put forward taxonomy suggestions based on the best classification results.

Significance StatementWe standardize a 3-step framework to carry out bacterial taxonomy research based on protein domain. Furthermore, we filter out the best solution in each step that can together generate the most appropriate classification result, and at the same time, we discuss the biological significant it indicates. Finally, we propose suggestions on NCBI bacterial taxonomy based on the classification results.


title: Taxonomy Analysis in Bacterial Kingdom based onProtein Domain: A Comparison Study


title: Extensive Chromatin Structure-Function Association Revealed by Accurate Compartmentalization Characterization

abstract: Chromosome conformation capture-based experiments have shown that eukaryotic chromosomes are partitioned into A and B compartments conventionally identified by the first eigenvector (EV1) of dimension reduction methods. However, many genomic regions show marginal EV1 values, indicating the ambiguity of A/B compartment scheme on these regions. We develop MOSAIC (MOdularity and Singular vAlue decomposition-based Identification of Compartments), an accurate compartmental state detection scheme. MOSAIC reveals that those ambiguous regions segregate into two additional compartmental states, which typically correspond to small genomic regions flanked by large canonical A/B compartments with opposite activities. They are denoted as micro-compartments accordingly. In contrast to the canonical A/B compartments, micro-compartments cover ~30% of the genome and are highly dynamic between cell types. More importantly, distinguishing the micro-compartments underpins accurate characterization of chromatin structure-function relationship. By applying MOSAIC to GM12878 and K562 cells, we identify CD86, ILDR1 and GATA2 which show concordance between gene expression and compartmental states beyond the scheme of A/B compartments. Taken together, MOSAIC uncovers fine-scale and dynamic structures underlying canonical A/B compartments. Our results suggest dynamic chromatin compartmentalization is underlying transcriptional regulation and disease.


title: SL-Cloud: A Computational Resource to Support Synthetic Lethal Interaction Discovery

abstract: Synthetic lethal interactions (SLIs), genetic interactions in which the simultaneous inactivation of two genes leads to a lethal phenotype, are promising targets for therapeutic intervention in cancer, as exemplified by the recent success of PARP inhibitors in treating BRCA1/2-deficient tumors. We present SL-Cloud, an integrated resource and framework to facilitate the prediction of context-specific SLIs by using cloud-based technologies. This resource addresses two main challenges related to SLI inference: the need to wrangle and preprocess large multi-omic datasets and the multiple comparable prediction approaches available. We demonstrate the utility of this resource by using a set of DNA damage repair genes as the basis for predicting potential SLI partners, using multiple computational strategies. Context-specific synthetic lethality potential can also be compared using the framework. We demonstrate various use cases for our cloud-based computational resource and the utility of this approach for customizable and extensible computational inference of SLIs.


title: Evaluation of cell segmentation methods without reference segmentations

abstract: Cell segmentation is a cornerstone of many bioimage informatics studies. Inaccurate segmentation introduces computational error in downstream cellular analysis. Evaluating segmentation results is thus a necessary step for developing segmentation methods as well as for choosing the most appropriate method for a particular type of tissue or image. The evaluation process has typically involved comparison of segmentations to those generated by humans, which can be expensive and subject to unknown bias. We present here an approach that seeks to evaluate cell segmentation methods without relying upon comparison to results from humans. For this, we defined a number of segmentation quality metrics that can be applied to multichannel fluorescence images. We calculated these metrics for 11 previously-described segmentation methods applied to datasets from 4 multiplexed microscope modalities covering 5 tissues. Using principal component analysis to combine the metrics we defined an overall cell segmentation quality score and ranked the segmentation methods. All code and data are available in a Reproducible Research Archive.


title: ProteoDisco: A flexible R approach to generate customized protein databases for extended search space of novel and variant proteins in proteogenomic studies

abstract:
SummaryWe present an R-based open-source software termed ProteoDisco that allows for flexible incorporation of genomic variants, fusion-genes and (aberrant) transcriptomic variants from standardized formats into protein variant sequences. ProteoDisco allows for a flexible step-by-step workflow allowing for in-depth customization to suit a myriad of research approaches in the field of proteogenomics, on all organisms for which a reference genome and transcript annotations are available.

Availability and ImplementationProteoDisco (R package version [≥] 0.99) is available from https://github.com/ErasmusMC-CCBC/ProteoDisco/.

Contacth.vandewerken@erasmusmc.nl

Supplementary informationSupplementary table, figures and data files available.


title: Alternative polyadenylation characterizes epithelial and fibroblast phenotypic heterogeneity in pancreatic ductal adenocarcinoma

abstract: Human tumors are characterized by extensive intratumoral transcriptional variability within the cancer cell and stromal compartments. This variation drives phenotypic heterogeneity, producing cell states with differential pro- and anti-tumorigenic properties. While bulk RNA sequencing cannot achieve cell type specific transcriptional granularity, single cell sequencing has permitted an unprecedented view of these cell states. Despite this knowledge, we lack an understanding of the mechanistic drivers of this transcriptional and phenotypic heterogeneity. 3 untranslated region alternative polyadenylation (3 UTR-APA) drives gene expression alterations through regulation of 3 UTR length. These 3 UTR alterations modulate mRNA stability, protein expression and protein localization, resulting in cellular phenotypes including differentiation, cell proliferation, and migration. Therefore, we sought to determine whether 3 UTR-APA events could characterize phenotypic heterogeneity of tumor cell states. Here we analyze the largest single cell human pancreatic ductal adenocarcinoma (PDAC) dataset and resolve 3 UTR-APA patterns across PDAC cell states. We find that increased proximal 3 UTR-APA is associated with PDAC progression and characterizes a metastatic ductal epithelial subpopulation and an inflammatory fibroblast population. Furthermore, we find significant 3 UTR shortening events in cell state-specific marker genes associated with increased expression. Therefore, we propose that 3 UTR-APA drives phenotypic heterogeneity in cancer.

category: cancer biology


title: Hydrogen sulfide improves the cold stress resistance through the CsARF5-CsDREB3 module in cucumber

abstract:
Hydrogen sulfide (H2S) plays a crucial role in regulating cold tolerance. But the synergistic regulation of H2S and auxin in the plant response to cold stress has not been reported. In the study, we found that sodium hydrosulfide (NaHS, an H2S donor) treatment enhanced the cold tolerance of cucumber seedlings and increased the level of auxin. CsARF5, a cucumber auxin response factor (ARF) gene was isolated and its role in regulating H2S-mediated cold stress tolerance was described. Transgenic cucumber leaves overexpressing CsARF5 were obtained. Physiological analysis indicated that overexpression of CsARF5 enhanced the cold stress tolerance of cucumber and the regulation of the cold stress response by CsARF5 depends on H2S. In addition, molecular assays showed that CsARF5 modulated cold stress response by directly activating the expression of the dehydration-responsive element-binding (DREB)/C-repeat binding factor (CBF) gene CsDREB3, which was identified as a positive regulator of cold stress. Taken together, our results suggest that CsARF5 plays an important role in H2S-mediated cold stress in cucumber. These results shed light on the molecular mechanism by which H2S regulates cold stress response by mediating auxin signaling, and will provide insights for further studies on the molecular mechanism by which H2S regulates cold stress.

HighlightAuxin signaling participates in H2S-mediated cold stress through the CsARF5-CsDREB3 module in cucumber.

category: physiology


title: Moderate DNA methylation changes associated with nitrogen remobilization and leaf senescence in Arabidopsis

abstract:
O_LIThe lifespan of plants and tissues is restricted by environmental and genetic components. Following the transition to reproductive growth, leaf senescence ceases cellular life in monocarpic plants to remobilize nutrients to storage organs.
C_LIO_LIWe observed altered leaf to seed ratios, faster senescence progression and enhanced nitrogen remobilization from the leaves in two methylation mutants (ros1 and the triple dmr1/2 cmt3 knockout).
C_LIO_LIDNA methylation in wild type Col-0 leaves initially moderately declined with progressing leaf senescence, predominantly in the CG context, while the ultimate phase of leaf discoloration was associated with moderate de novo methylation of cytosines, primarily in the CHH context.
C_LIO_LIRelatively few differentially methylated regions, including one in the ROS1 promoter linked to the down-regulation of ROS1, were present, but these were unrelated to known senescence-associated genes.
C_LIO_LIDifferential methylation patterns were identified in transcription factor binding sites, such as the W-boxes that are targeted by WRKYs, which impaired transcription factor binding when methylated in vitro.
C_LIO_LIMutants that are defective in DNA methylation showed distinct nitrogen remobilization, which was associated with altered patterns of leaf senescence progression. But moderate methylome changes during leaf senescence were not specifically associated with up-regulated genes during senescence.
C_LI

category: plant biology


title: A ppGpp-mediated brake on photosynthesis is required for acclimation to nitrogen limitation in Arabidopsis.

abstract: Guanosine pentaphosphate and tetraphosphate (together referred to as ppGpp) are hyperphosphorylated nucleotides found in bacteria and the chloroplasts of plants and algae. In plants and algae artificial ppGpp accumulation can inhibit chloroplast gene expression, and influence photosynthesis, nutrient remobilisation, growth, and immunity. However, it is so far unknown whether ppGpp is required for abiotic stress acclimation in plants. Here, we demonstrate that ppGpp biosynthesis is necessary for acclimation to nitrogen starvation in Arabidopsis. We show that ppGpp is required for remodeling the photosynthetic electron transport chain to downregulate photosynthetic activity and for protection against oxidative stress. Furthermore, we demonstrate that ppGpp is required for coupling chloroplastic and nuclear gene expression during nitrogen starvation. Altogether, our work indicates that ppGpp is a pivotal regulator of chloroplast activity for stress acclimation in plants.


title: Novel biochemical, structural and systems insights into inflammatory signaling revealed by contextual interaction proteomics

abstract:
Protein-protein interactions (PPI) represent the main mode of the proteome organization in the cell. In the last decade, several large-scale representations of PPI networks have captured generic aspects of the functional organization of network components, but mostly lack the context of cellular states. However, the generation of contextual representations of PPI networks is essential for structural and systems-level modeling of biological processes and remains an unsolved challenge. In this study we describe an integrated experimental/computational strategy to achieve a contextualized modeling of PPI. This strategy defines the composition, stoichiometry, spatio-temporal organization and cellular requirements for the formation of target assemblies. We used this approach to generate an integrated model of the formation principles and architecture of a large signalosome, the TNF-receptor signaling complex (TNF-RSC). Overall, we show that the integration of systems- and structure-level information provides a generic, largely unexplored link between the modular proteome and cellular function.

Significance StatementIn this work, we propose a critical shift in the way we analyze, and think the study of, protein-protein interactions (PPI), and present an experimental and computational framework to model them in the cellular context. We applied this framework to the signalosome tumor necrosis factor receptor signaling complex (TNF-RSC), and generated an integrated model of its formation and architecture that provides new insights and resolved controversies regarding its organization and regulation. To achieve a contextual modelling of PPIs, we first optimized and developed, and then combined, approaches to map the composition of a target complex, its absolute stoichiometry, its spatial organization and assembly/disassembly dynamics, its temporal dependence on signaling, and its reliance on cellular resources.

category: systems biology


title: A computational framework to identify metabolic engineering strategies for the co-production of metabolites

abstract: Microbial production of chemicals is a more sustainable alternative to traditional chemical processes. However, the shift to bioprocess is usually accompanied by a drop in economic feasibility. Co-production of more than one chemical can improve the economy of bioprocesses, enhance carbon utilization and also ensure better exploitation of resources. While a number of tools exist for in silico metabolic engineering, there is a dearth of computational tools that can co-optimize the production of multiple metabolites. In this work, we propose an eXtended version of Flux Scanning based on Enforced Objective Flux (XFSEOF), identify intervention strategies to co-optimize for a set of metabolites. XFSEOF can be used to identify all pairs of products that can be co-optimized with ease, by a single intervention. Beyond this, it can also identify higher-order intervention strategies for a given set of metabolites. We have employed this tool on the genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae, and identified intervention targets that can co-optimize the production of pairs of metabolites under both aerobic and anaerobic conditions. Anaerobic conditions were found to support the co-production of a higher number of metabolites when compared to aerobic conditions in both organisms. The proposed computational framework will enhance the ease of study of metabolite co-production and thereby aid the design of better bioprocesses.


title: Serotype-based evaluation of an optogenetic construct in rat cortical astrocytes

abstract: Optogenetics is a modern technique which has been recently expanded to non-neuronal cell types, e.g., astrocytes, and involves targeted gene delivery of light-sensitive ion channels like Channelrhodopsin-2 (ChR2). Optogenetic regulation of astrocytic activity can be used for therapeutic intervention of several neurological disorders. Astrocytic gene delivery, viz adeno-associated viral (AAV) vectors, have proven to be robust, time-, and cost-efficient contrary to the generation of transgenic animal models. When transducing astrocytes with an AAV vector, it is imperative to perform a serotype evaluation of the AAV vector due to variability in serotype transduction efficiency depending on species, target region and construct length. Rats have been a very successful animal model for studying a variety of brain disorders, from which ChR2-based intervention of astrocytes will benefit. However, the most efficient AAV capsid serotype targeting astrocytes for ChR2 expression in the in vivo rat brain cortex has not been characterized. To address this, we have evaluated AAV serotypes 1, 5, and 8 of the vector AAV-GFAP-hChR2(H134)-mCherry targeting astrocytes in the rat brain neocortex. Results show that serotype 8 exhibits promising transduction patterns, as it has demonstrated the highest tangential and radial viral spread in the rat brain. Our research will facilitate translational research for future applications of optogenetics involving the transduction of rat brain cortical astrocytes.

category: neuroscience


title: Activity-dependent modulation of NMDA receptors by endogenous zinc shapes dendritic function in cortical neurons.

abstract: Activation of NMDA receptors (NMDARs) has been proposed to be a key component of single neuron computations in vivo. However is unknown if specific mechanisms control the function of such receptors and modulate input-output transformations performed by cortical neurons under in vivo-like conditions. Here we found that in layer 2/3 pyramidal neurons (L2/3 PNs), repeated synaptic stimulation results in an activity-dependent decrease in NMDARs activity by vesicular zinc. Such a mechanism shifted the threshold for dendritic non-linearities and strongly reduced LTP induction. Modulation of NMDARs was cell- and pathway-specific, being present selectively in L2/3-L2/3 connections but absent in ascending bottom-up inputs originating from L4 neurons. Numerical simulations highlighted that activity-dependent modulation of NMDARs has an important influence in dendritic computations endowing L2/3 PN dendrites with the ability to sustain dendritic non-linear integrations constant across different regimes of synaptic activity like those found in vivo. The present results therefore provide a new perspective on the action of vesicular zinc in cortical circuits by highlighting the role of this endogenous ion in normalizing dendritic integration of PNs during a constantly changing synaptic input pattern.


title: Short-term assessment of subfoveal injection of AAV2-hCHM gene augmentation in choroideremia using adaptive optics ophthalmoscopy

abstract: Subretinal injection for gene augmentation in retinal degenerations forcefully detaches the neural retina from the retinal pigment epithelium (RPE), potentially damaging photoreceptors and/or RPE cells. Here, we use adaptive optics scanning light ophthalmoscopy (AOSLO) to assess the short-term integrity of the cone mosaic following subretinal injections of AAV2-hCHM gene augmentation in subjects with choroideremia (CHM). Nine adult CHM patients received uniocular subfoveal injections of low dose (5x1010 vector genome (vg) per eye, n=5) or high dose (1x1011 vg per eye, n=4) AAV2-hCHM. The macular regions of both eyes were imaged pre- and one-month post-injection using a custom-built, multimodal AOSLO. Post-injection cone inner segment mosaics were compared to pre-injection mosaics at multiple regions of interest (ROIs). Post-injection AOSLO images showed preservation of the cone mosaic in all 9 AAV2-hCHM injected eyes. Mosaics appeared intact and contiguous one-month post-injection, with the exception of foveal disruption in one patient. Co-localized optical coherence tomography showed foveal cone outer segment (COS) shortening post-injection (significant, n=4; non-significant, n=4; unchanged, n=1). Integrity of the cone mosaic is maintained following subretinal delivery of AAV2-hCHM, providing strong evidence in support of the safety of the injections. Minor foveal thinning observed following surgery corresponds with short-term COS shortening rather than cone cell loss.


title: Altered interactions between circulating and tissue-resident CD8 T cells with the colonic mucosa define colitis associated with immune checkpoint inhibitors

abstract: Therapeutic blockade of co-inhibitory immune receptors PD-1 and CTLA-4 has revolutionized oncology, but treatments are limited by immune-related adverse events (IRAEs). IRAE Colitis (irColitis) is the most common, severe IRAE affecting up to 25% of patients on dual PD-1 and CTLA-4 inhibition. Here, we present a systems biology approach to define the cell populations and transcriptional programs driving irColitis. We collected paired colon mucosal biopsy and blood specimens from 13 patients with irColitis, 8 healthy individuals, and 8 controls on immune checkpoint inhibitors (ICIs), and analyzed them with single-cell/nuclei RNA sequencing with paired TCR and BCR sequencing, multispectral fluorescence microscopy, and secreted factor analysis (Luminex). We profiled 299,407 cells from tissue and blood and identified 105 cell subsets that revealed significant tissue remodeling in active disease. Colon mucosal immune populations were dominated by tissue-resident memory (TRM) ITGAE-expressing CD8 T cells representing a phenotypic spectrum defined by gene programs associated with T cell activation, cytotoxicity, cycling, and exhaustion. CD8 TRM and effector CD4 T cells upregulated type 17 immune programs (IL17A, IL26) and Tfh-like programs (CXCL13, PDCD1). We also identified for the first time an increased abundance of two KLRG1 and ITGB2-expressing CD8 T cell populations with circulatory cell markers, including a GZMK TRM-like population and a CX3CR1 population that is predicted to be intravascular. These two populations were more abundant in irColitis patients treated with dual PD-1/CTLA-4 inhibition than those receiving anti-PD-1 monotherapy. They also had significant TCR sharing with PBMCs, suggesting a circulatory origin. In irColitis we observed significant epithelial turnover marked by fewer LGR5-expressing stem cells, more transit amplifying cells, and upregulation of apoptotic and DNA-sensing programs such as the cGAS-STING pathway. Mature epithelial cells with top crypt genes upregulated interferon-stimulated pathways, CD274 (PD-L1), anti-microbial genes, and MHC-class II genes, and downregulated aquaporin and solute-carrier gene families, likely contributing to epithelial cell damage and absorptive dysfunction. Mesenchymal remodeling was defined by increased endothelial cells, both in irColitis patients and specifically in patients on dual PD-1/CTLA-4 blockade. Cell-cell communication analysis identified putative receptor-ligand pairs that recruit CD8 T cells from blood to inflamed endothelium and positive feedback loops such as the CXCR3 chemokine system that retain cells in tissue. This study highlights the cellular and molecular drivers underlying irColitis and provides new insights into the role of CTLA-4 and PD-1 signaling in maintaining CD8 TRM homeostasis, regulating CD8 T recruitment from blood, and promoting epithelial-immune crosstalk critical to gastrointestinal immune tolerance and intestinal barrier function.

category: immunology


title: Chromomycin A5 induces bonafide immunogenic cell death in metastatic melanoma

abstract: Some first-line cytotoxic chemotherapics, e.g. doxorubicin, paclitaxel and oxaliplatin, induce activation of the immune system through immunogenic cell death (ICD). Tumor cells undergoing ICD function as a vaccine, releasing damage-associated molecular patterns (DAMPs), which act as adjuvants, and neoantigens of the tumor are recognized as antigens. ICD induction is rare, however it yields better and long-lasting antitumor responses to chemotherapy. Advanced metastatic melanoma (AMM) is incurable for more than half of patients. The discovery of ICD inducers against AMM is an interesting drug discovery strategy with high translational potential. Here we evaluated ICD induction of four highly cytotoxic chromomycins A (CA5-8). B16-F10, a metastatic melanoma cell line, treated with CA5-8 and doxorubicin exhibited ICD features such as autophagy and apoptosis, externalization of calreticulin, and releasing of HMGB1. However, CA5-treated cells had the best profile, also inducing ATP release, ERp57 externalization, phosphorylation of eIF2 and altering expression of transcription of genes related to autophagy, endoplasmic reticulum stress, and apoptosis. Bonafide ICD induction by CA5 was confirmed by a C57BL/6 mice vaccination assay with CA5-treated cells. These findings support a high potential of CA5 as an anticancer candidate against AMM.


title: Antigen identification and high-throughput interaction mapping by reprogramming viral entry

abstract: Deciphering immune recognition is critical for understanding a broad range of diseases and for the development of effective vaccines and immunotherapies. Efforts to do so are limited by a lack of technologies capable of simultaneously capturing the complexity of adaptive immune receptor repertoires and the landscape of potential antigens. To address this, we present RAPTR (Receptor-Antigen Pairing by Targeted Retroviruses). RAPTR combines viral pseudotyping and molecular engineering approaches to enable one-pot library on library interaction screens by displaying antigens on the surface of lentiviruses and encoding their identity in the viral genome. Antigen-specific viral infection of cells allows readout of both antigen and receptor identities via single-cell sequencing. The resulting system is modular, scalable, and compatible with any cell type, making it easily implemented. These techniques provide a suite of new tools for targeted viral entry, molecular engineering, and interaction screens with broad potential applications.


title: Exploring the structural basis to develop efficient multi-epitope vaccines displaying interaction with HLA and TAP and TLR3 molecules to prevent NIPAH infection, a global threat to human health

abstract:
BackgroundNipah virus (NiV) is an emerging zoonotic virus that caused several serious outbreaks in the South Asian region with high mortality rates ranging from 40 to 90% since 2001. NiV infection causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. No specific vaccine has yet been reported against NiV.

Methodology and Principal FindingsRecently, the design of some Multi-Epitope Vaccines (MEV) has been proposed but that involves vary limited number of epitopes which limits the potential of vaccine. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have designed two MEVs composed of 33 Cytotoxic T lymphocyte (CTL) epitopes and 38 Helper T lymphocyte (HTL) epitopes. Both the MEVs carry potential B cell linear epitope overlapping regions, B cell discontinuous epitopes as well as IFN-{gamma} inducing epitopes. Hence the designed MEVs carry potential to elicit cell-mediated as well as humoral immune response. Selected CTL and HTL epitopes were validated for their stable molecular interactions with HLA class I and II alleles as well as in case of CTL epitopes, with human transporter associated with antigen processing (TAP). Human {beta}-defensin 2 and {beta}-defensin 3 were used as adjuvants to enhance the immune response of both the MEVs. Molecular dynamics simulation studies of MEVs-TLR3 ectodomain (Toll-Like Receptor 3) complex indicate the stable molecular interaction. Further, the codon optimized cDNA of both the MEVs has shown high expression potential in the mammalian host cell line (Human). Hence for further studies, the designed MEV constructs could be expressed and tried in-vivo as potential vaccine candidates against NiV.

ConclusionWe conclude that the MEVs designed and in silico validated here could be highly potential vaccine candidate to combat NiV, with greater effectiveness, high specificity and large human population coverage worldwide.

AUTHOR SUMMARYNipah Virus (NiV) has caused several outbreaks in past two decades calming large number of human lives. Our present work aims to design and in silico validate Multi-Epitope Vaccine against NiV. The current approach to design vaccine involves whole virus or full length proteins as vaccine candidates against NiV. These approaches carry chances of raising the unwanted non-neutralizing antibodies which have been found to cause clinical complexities. Recently few Multi-Epitope vaccines have also been proposed, but they have involved limited number of epitopes for vaccine design in result limiting the effectiveness and human population coverage. Here in our MEVs we have involved all the proteins of NiV to design the vaccine. Moreover since we have used in silico validated epitopes we may conclude that the here proposed MEVs would be highly specific, effective and potential vaccine candidate to combat NiV with large human population coverage worldwide.


title: Non-lesional and Lesional Lupus Skin Share Inflammatory Phenotypes that Drive Activation of CD16+ Dendritic Cells

abstract: Cutaneous lupus erythematosus (CLE) is a disfiguring and poorly understood condition frequently associated with systemic lupus. Studies to date suggest that non-lesional keratinocytes play a role in disease predisposition, but this has not been investigated in a comprehensive manner or in the context of other cell populations. To investigate CLE immunopathogenesis, normal-appearing skin, lesional skin, and circulating immune cells from lupus patients were analyzed via integrated single-cell RNA-sequencing and spatial-seq. We demonstrate that normal-appearing skin of lupus patients represents a type I interferon-rich,  prelesional environment that skews gene transcription in all major skin cell types and dramatically distorts cell-cell communication. Further, we show that lupus-enriched CD16+ dendritic cells undergo robust interferon education in the skin, thereby gaining pro-inflammatory phenotypes. Together, our data provide a comprehensive characterization of lesional and non-lesional skin in lupus and identify a role for skin education of CD16+ dendritic cells in CLE pathogenesis.


title: Donor Macrophages Modulate Rejection after Heart Transplantation

abstract:
BackgroundCellular rejection after heart transplantation imparts significant morbidity and mortality. Current immunosuppressive strategies are imperfect, target recipient T-cells, and have a multitude of adverse effects. The innate immune response plays an essential role in the recruitment and activation of T-cells. Targeting the donor innate immune response would represent the earliest interventional opportunity within the immune response cascade. There is limited knowledge regarding donor immune cell types and functions in the setting of cardiac transplantation and no current therapeutics exist for targeting these cell populations.

MethodsUsing genetic lineage tracing, cell ablation, and conditional gene deletion, we examined donor mononuclear phagocyte diversity and function during acute cellular rejection of transplanted hearts in mice. We performed single cell RNA sequencing on donor and recipient macrophages, dendritic cells, and monocytes at multiple timepoints after transplantation. Based on our single cell RNA sequencing data, we evaluated the functional relevance of donor CCR2+ and CCR2- macrophages using selective cell ablation strategies in donor grafts prior to transplant. Finally, we perform functional validation of our single cell-derived hypothesis that donor macrophages signal through MYD88 to facilitate cellular rejection.

ResultsDonor macrophages persisted in the transplanted heart and co-existed with recipient monocyte-derived macrophages. Single-cell RNA sequencing identified donor CCR2+ and CCR2- macrophage populations and revealed remarkable diversity amongst recipient monocytes, macrophages, and dendritic cells. Temporal analysis demonstrated that donor CCR2+ and CCR2- macrophages were transcriptionally distinct, underwent significant morphologic changes, and displayed unique activation signatures after transplantation. While selective depletion of donor CCR2- macrophages reduced allograft survival, depletion of donor CCR2+ macrophages prolonged allograft survival. Pathway analysis revealed that donor CCR2+ macrophages were being activated through MYD88/NF-{beta} signaling. Deletion of MYD88 in donor macrophages resulted in reduced antigen presenting cell recruitment, decreased emergence of allograft reactive T-cells, and extended allograft survival.

ConclusionsDistinct populations of donor and recipient macrophages co-exist within the transplanted heart. Donor CCR2+ macrophages are key mediators of allograft rejection and inhibition of MYD88 signaling in donor macrophages is sufficient to suppress rejection and extend allograft survival. This highlights the therapeutic potential of donor heart-based interventions.


title: Management effectiveness suggests a role in structuring herbivorous fish communities in Sinai marine protected areas, Gulf of Aqaba

abstract:
Herbivorous reef fishes are critically important for maintaining the health and resilience of coral reefs. In the Egyptian Gulf of Aqaba (GoA), many of these herbivores are important fishery targets, however, little is known about their biomass and size structure patterns. Here, we conduct a large-scale ([~]250 km of coastline) assessment of the status of herbivorous fish populations on 30 reef sites from eight coastal regions in the GoA. These regions are subjected to three levels of fishing and protection, ranging from almost no fishing (No-take, NT), and moderately fished (via Gear-restriction, GR) to heavily fished (Open-access, OA). We found that the NT fishery reserve was the most effective in maintaining herbivorous fish richness, body-size, and biomass across all functional groups, though numerical density was not. Total herbivore biomass was 4.3 and 2.8 times higher on NT reefs and GR reefs respectively than on OA reefs. Among GoA regions, only Ras Mohammed and Sharm El-Sheikh (unfished), and Nabq (moderately fished) met the global mean herbivore biomass target of [~]30 kg/500 m2. Our work also highlights three important results regarding the impacts of fishing and fisheries management on herbivorous fish populations: (i) size structure was heavily skewed toward smaller individuals, with fishes less than (20 cm) accounting for 81.1% of the population in heavily fished OA reefs vs. 52.8% at unfished NT reefs, (ii) biomass of larger herbivore individuals (>35 cm) accounted for less than 1% of the total biomass in OA reefs vs. 37% at NT reefs, and (iii) large-bodied target species, Cetoscarus bicolor, Naso unicorn, and Kyphosus spp., accounting for 15.9% of the total biomass at NT reefs on average, while they were virtually absent from OA reefs. Collectively, these findings suggest that many principal fishery species in the central-northern regions of the GoA have been overexploited, which in turn can lead to reef degradation. Therefore, there is an urgent need to develop a participatory management approach and enforce restrictions on destructive fishing gear in order to promote recovery of herbivore biomass.

HighlightsO_LILarge-scale assessment of the status of herbivorous fishes in the northern Red Sea.
C_LIO_LIComparison of herbivorous fish assemblages across three levels of fishing pressure.
C_LIO_LILarge-bodied herbivore species were either rare or absent at heavily fished reefs.
C_LIO_LILoss of these key herbivores may boost algal dominance, thus diminish reef functionality.
C_LIO_LIPromoting local community participation in the fishery management process.
C_LI

category: ecology


title: Herbivorous fish of Sinai marine protected areas (Gulf of Aqaba): Structure baseline for potential thermal stress impact management


title: Benchmarking statistical methods for analyzing parent-child dyads in genetic association studies

abstract: Genetic association studies of child health outcomes often employ family-based designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multi-ethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

category: genetics


title: Non-linear Archetypal Analysis of Single-cell RNA-seq Data by Deep Autoencoders

abstract: Advances in single-cell RNA sequencing (scRNA-seq) have led to successes in discovering novel cell types and understanding cellular heterogeneity among complex cell populations through cluster analysis. However, cluster analysis is not able to reveal continuous spectrum of states and underlying gene expression programs (GEPs) shared across cell types. We introduce scAAnet, an autoencoder for single-cell non-linear archetypal analysis, to identify GEPs and infer the relative activity of each GEP across cells. We use a count distribution-based loss term to account for the sparsity and overdispersion of the raw count data and add an archetypal constraint to the loss function of scAAnet. We first show that scAAnet outperforms existing methods for archetypal analysis across different metrics through simulations. We then demonstrate the ability of scAAnet to extract biologically meaningful GEPs using publicly available scRNA-seq datasets including a pancreatic islet dataset, a lung idiopathic pulmonary fibrosis dataset and a prefrontal cortex dataset.


title: MM-Deacon: Multimodal molecular domain embedding analysis via contrastive learning

abstract: AO_SCPLOWBSTRACTC_SCPLOWMolecular representation learning plays an essential role in cheminformatics. Recently, language model-based approaches have been popular as an alternative to traditional expert-designed features to encode molecules. However, these approaches only utilize a single modality for representing molecules. Driven by the fact that a given molecule can be described through different modalities such as Simplified Molecular Line Entry System (SMILES), The International Union of Pure and Applied Chemistry (IUPAC), and The IUPAC International Chemical Identifier (InChI), we propose a multimodal molecular embedding generation approach called MM-Deacon (multimodal molecular domain embedding analysis via contrastive learning). MM-Deacon is trained using SMILES and IUPAC molecule representations as two different modalities. First, SMILES and IUPAC strings are encoded by using two different transformer-based language models independently, then the contrastive loss is utilized to bring these encoded representations from different modalities closer to each other if they belong to the same molecule, and to push embeddings farther from each other if they belong to different molecules. We evaluate the robustness of our molecule embeddings on molecule clustering, cross-modal molecule search, drug similarity assessment and drug-drug interaction tasks.


title: Determining jumping performance from a single body-worn accelerometer using machine learning

abstract: External peak power in the countermovement jump is frequently used to monitor athlete training. The gold standard method uses force platforms, but they are unsuitable for field-based testing. However, alternatives based on jump flight time or Newtonian methods applied to inertial sensor data have not been sufficiently accurate for athlete monitoring. Instead, we developed a machine learning model based on characteristic features (functional principal components) extracted from a single body-worn accelerometer. Data were collected from 69 male and female athletes at recreational, club or national levels, who performed 696 jumps in total. We considered vertical countermovement jumps (with and without arm swing), sensor anatomical locations, machine learning models and whether to use resultant or triaxial signals. Using a novel surrogate model optimisation procedure, we obtained the lowest errors with a support vector machine when using the resultant signal from a lower back sensor in jumps without arm swing. This model had a peak power RMSE of 2.3 W{middle dot}kg-1 (5.1% of the mean), estimated using nested cross validation and supported by an independent holdout test (2.0 W{middle dot}kg-1). This error is lower than in previous studies, although it is not yet sufficiently accurate for a field-based method. Our results demonstrate that functional data representations work well in machine learning by reducing model complexity in applications where signals are aligned in time. Our optimisation procedure also was shown to be robust can be used in wider applications with low-cost, noisy objective functions.


title: Multi-objective prioritisation of candidate epitopes for diagnostic test development

abstract:
BackgroundThe development of peptide-based diagnostic tests requires the identification of epitopes that are at the same time highly immunogenic and, ideally, unique to the pathogen of interest, to minimise the chances of cross-reactivity. Existing computational pipelines for the prediction of linear B-cell epitopes tend to focus exclusively on the first objective, leaving considerations of cross-reactivity to later stages of test development.

ResultsWe present a multi-objective approach to the prioritisation of candidate epitopes for experimental validation, in the context of diagnostic test development. The dual objectives of uniqueness (measured as dissimilarity from known epitope sequences from other pathogens) and predicted immunogenicity (measured as the probability score returned by the prediction model) are considered simultaneously. Validation was performed using data from three distinct pathogens (namely the nematode Onchocerca volvulus, the Epstein-Barr Virus and the Hepatitis C Virus), with predictions derived using an organism-specific prediction approach. The multi-objective rankings returned sets of non-dominated solutions as potential targets for the development of diagnostic tests with lower probability of false positives due to cross-reactivity.

ConclusionsThe application of the proposed approach to three test pathogens led to the identification of 20 new potential epitopes, with both high probability and a high degree of exclusivity to the target organisms. The results indicate the potential of the proposed approach to provide enhanced filtering and ranking of potential candidates, highlighting potential cross-reactivities and including this information into the test development process right from the target identification and prioritisation step.


title: Characterization of striatal dopamine projections across striatal subregions in behavioral flexibility

abstract: Behavioral flexibility is key to survival in a dynamic environment. While flexible, goal-directed behaviors are initially dependent on dorsomedial striatum, they become dependent on lateral striatum with extended training as behaviors become inflexible. Similarly, dopamine release shifts from ventromedial to lateral striatum across learning, and impairment of lateral dopamine release disrupts habitual, inflexible responding. This raises the possibility that lateral dopamine release is a causative mechanism in establishing inflexible behaviors late in training, though this has not been directly tested. Here, we utilized optogenetics to activate dopamine terminals in dorsal medial (DMS), dorsal lateral (DLS), and ventral (NAc) striatum in DATcre mice to determine how specific dopamine subpopulations impact behavioral flexibility. Mice performed a reversal task in which they self-stimulated DMS, DLS, or NAc dopamine terminals by pressing one of two levers before action-outcome lever contingencies were reversed. Consistent with presumed ventromedial/lateral striatal function, we found that mice self-stimulating ventromedial dopamine terminals rapidly reversed lever preference following contingency reversal, while mice self-stimulating dopamine terminals in DLS showed impaired reversal learning. These impairments were characterized by more regressive errors and reliance on lose-stay strategies following reversal, suggesting reward insensitivity and overreliance on previously learned actions. This study supports a model of striatal function in which dorsomedial dopamine facilitates goal-directed responding, and dorsolateral dopamine release is a key mechanism in supporting the transition toward inflexible behaviors.


title: In vivo intraoral waterflow quantification reveals hidden mechanisms of suction feeding in fish

abstract: Virtually all fish rely on flows of water to transport food to the back of their pharynx. While external flows that draw food into the mouth are well described, how intra-oral water flows manage to deposit food at the esophagus entrance remains unknown. In theory, the posteriorly moving water must, at some point, curve laterally and/or ventrally to exit through the gill slits. Such flows would eventually carry food away from the esophagus instead of towards it. This apparent paradox calls for a filtration mechanism to deviate food from the suction-feeding streamlines. To study this gap in our fundamental understanding of how fish feed, we developed and applied a new technique to quantify three-dimensional patterns of intra-oral water flows in vivo. We combined stereoscopic high-speed x-ray videos to quantify skeletal motion (XROMM) with 3D x-ray particle tracking (XPT) of approximately neutrally buoyant spheres of 1.4 mm in diameter. We showed, for carp (Cyprinus carpio) and tilapia (Oreochromis niloticus), that water tracers displayed higher curvatures than food tracers, indicating an inertia-driven filtration. In addition, tilapia also exhibited a  central jet flow pattern, which aids in quickly carrying food to the pharyngeal jaw region. When the food was trapped at the branchial basket, it was resuspended and carried more centrally by periodical bidirectional waterflows, synchronized with head-bone motions. By providing a complete picture of the suction-feeding process and revealing fundamental differences in food transport mechanisms among species, this new technique opens a new area of investigation to fully understand how most aquatic vertebrates feed.


title: Evolutionary history of an Alpine archaeognath(Machilis pallida) - insights from different variant types

abstract: Reconstruction of species histories is a central aspect of evolutionary biology. Patterns of genetic variation within and among populations can be leveraged to elucidate evolutionary processes and demographic histories. However, interpreting genetic signatures and unraveling the contributing processes can be challenging, in particular for non-model organisms with complex reproductive modes and genome organization. One way forward is the combined consideration of patterns revealed by different molecular markers (nuclear vs. mitochondrial) and types of variants (common vs. rare) that differ in their age, mode and rate of evolution. Here, we applied this approach to Machilis pallida (Archaeognatha), an Alpine jumping bristletail considered parthenogenetic and triploid. We generated de-novo transcriptome and mitochondrial assemblies to obtain high-density data to investigate patterns of mitochondrial and common and rare nuclear variation in 17 M. pallida individuals sampled across the Alps from all known populations. We find that the different variant types capture distinct aspects of the evolutionary history and discuss the observed patterns in the context of parthenogenesis, polyploidy and survival during glaciation. This study highlights the potential of different variant types to unravel complex evolutionary scenarios and the suitability of M. pallida and the genus Machilis as a study system for the evolution of sexual strategies and polyploidization during environmental change. We also emphasize the need for further research which will be stimulated and facilitated by these newly generated resources and insights.


title: Using AlphaFold to predict the impact of single mutations on protein stability and function

abstract: AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability ({Delta}{Delta}G) and function. To study the question we extracted metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known {Delta}{Delta}G values. Additionally, we correlated the AlphaFold predictions on the impact of a single mutation on structure with a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold cannot be immediately applied to other problems or applications in protein folding.


title: Energy status-promoted growth and development of Arabidopsis require copper deficiency response transcriptional regulator SPL7

abstract: Copper (Cu) is a cofactor of around 300 Arabidopsis proteins including photosynthetic and mitochondrial electron transfer chain enzymes critical for ATP production and carbon fixation. Plant acclimation to Cu deficiency requires the transcription factor SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE7 (SPL7). We report that in the wild type and in the spl7-1 mutant, respiratory electron flux via Cu-dependent cytochrome c oxidase remained unaffected under both normal and low-Cu cultivation conditions. Contrary to the wild type, supplementing Cu-deficient media with exogenous sugar failed to stimulate growth of spl7-1. The spl7-1 mutant accumulated carbohydrates including the signaling sugar trehalose 6-phosphate, as well as ATP and NADH, also under normal Cu supply and without sugar supplementation. Late flowering of spl7-1 was in agreement with its attenuated sugar responsiveness. Functional TOR and SnRK1 kinase signaling in spl7-1 suggested against fundamental defects in these energy-signaling hubs. Sequencing of chromatin immunoprecipitates combined with transcriptomics identified direct targets of SPL7-mediated positive regulation, including FE SUPEROXIDE DISMUTASE1 (FSD1), COPPER-DEFICIENCY-INDUCED TRANSCRIPTION FACTOR1 (CITF1) and uncharacterized bHLH23 (CITF2), as well as an enriched upstream GTACTRC motif. In summary, transducing energy availability into growth and reproductive development requires the function of SPL7. Our results could help to increase crop yields, especially on Cu-deficient soils.


title: Physical and functional interactome atlas of human receptor tyrosine kinases

abstract: Much cell-to-cell communication is facilitated by cell surface receptor tyrosine kinases (RTKs). These proteins phosphorylate their downstream cytoplasmic substrates in response to stimuli such as growth factors. Despite their central roles, the functions of many RTKs are still poorly understood. To resolve the lack of systematic knowledge, we used three complementary methods to map the molecular context and substrate profiles of RTKs. We used affinity purification coupled to mass spectrometry (AP-MS) to characterize stable binding partners and RTK-protein complexes, proximity-dependent biotin identification (BioID) to identify transient and proximal interactions, and an in vitro kinase assay to identify RTK substrates. To identify how kinase interactions depend on kinase activity, we also used kinase-deficient mutants. Our data represent a comprehensive, systemic mapping of RTK interactions and substrates. This resource adds information regarding well-studied RTKs, offers insights into the functions of less well-studied RTKs, and highlights RTK-RTK interactions and shared signaling pathways.


title: Perception affects the brain's metabolic response to sensory stimulation

abstract:
Processing of incoming sensory stimulation triggers an increase of cerebral perfusion and blood oxygenation (neurovascular response) as well as an alteration of the metabolic neurochemical profile (neurometabolic response). Here we show that perceived and unperceived isoluminant chromatic flickering stimuli designed to have similar neurovascular responses as measured by blood oxygenation level dependent functional MRI (BOLD-fMRI) in primary visual cortex (V1) have markedly different neurometabolic responses as measured by functional MRS. In particular, a significant regional buildup of lactate, an index of aerobic glycolysis, and glutamate, an index of malate-aspartate shuttle, occurred in V1 only when the flickering is perceived, without any relation with behavioral or physiological variables. Wheras the BOLD-fMRI signal in V1, a proxy for input to V1, was insensitive to flickering perception by design, the BOLD-fMRI signal in secondary visual areas was larger during perceived than unperceived flickering indicating increased output from V1. These results indicate that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1, and that 1H-fMRS provides unique information about local input/output balance that is not measured by BOLD-fMRI.

Significance statementVisual perception has a measurable metabolic effect in the primary visual cortex (V1). Here we show that the upregulation of energy metabolism induced by isoluminant chromatic flickering depends on subjective visual perception. Within V1, perceived and unperceived stimuli that are contrast-matched to elicit similar blood-oxygenation level-dependent fMRI response are associated with clearly distinct neurochemical profiles. Specifically, regional accumulations of lactate (an index of aerobic glycolysis) and glutamate (an index of malate-aspartate shuttle) only develop during perceived stimuli, together with a larger activation of secondary visual areas. Our results imply a dissociation between metabolic and functional response, and indicate that that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1.


title: Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities

abstract: Every T cell receptor (TCR) repertoire is shaped by a complex probabilistic tangle of genetically determined biases and immune exposures. T cells combine a random V(D)J recombination process with a selection process to generate highly diverse and functional TCRs. The extent to which an individuals genetic background is associated with their resulting TCR repertoire diversity has yet to be fully explored. Using a previously published repertoire sequencing dataset paired with high-resolution genome-wide genotyping from a large human cohort, we infer specific genetic loci associated with V(D)J recombination probabilities using genome-wide association inference. We show that V(D)J gene usage profiles are associated with variation in the TCRB locus and, specifically for the functional TCR repertoire, variation in the major histocompatibility complex locus. Further, we identify specific variations in the genes encoding the Artemis protein and the TdT protein to be associated with biasing junctional nucleotide deletion and N-insertion, respectively. These results refine our understanding of genetically-determined TCR repertoire biases by confirming and extending previous studies on the genetic determinants of V(D)J gene usage and providing the first examples of trans genetic variants which are associated with modifying junctional diversity. Together, these insights lay the groundwork for further explorations into how immune responses vary between individuals.


title: Single-cell profiling reveals periventricular CD56bright NK cell accumulation in multiple sclerosis

abstract: Multiple sclerosis (MS) is a chronic demyelinating disease characterised by immune cell infiltration resulting in lesions that preferentially affect periventricular areas of the brain. Despite research efforts to define the role of various immune cells in MS pathogenesis, the focus has been on a few immune cell populations while full-spectrum analysis, encompassing others such as natural killer (NK) cells, has not been performed. Here, we used single-cell mass cytometry (CyTOF) to profile the immune landscape of brain periventricular areas - septum and choroid plexus - and blood from MS donors and controls with and without other neurological diseases. Using a 37-marker panel, we revealed the infiltration of T cells and antibody-secreting cells in periventricular brain regions and identified a novel NK cell signature specific to MS. CD56bright NK cells accumulated in the septum of MS donors, displaying an activated and migratory phenotype that was similar to that of CD56bright NK cells in their circulation. We validated this signature by multiplex immunohistochemistry and found that NK cells with high expression of granzyme K, which is typical of the CD56bright subset, accumulated in both periventricular lesions and the choroid plexus. Together, our multi-tissue single-cell data suggests that CD56bright NK cells infiltrate the periventricular brain regions in MS patients via both the blood-brain and blood-CSF barriers and brings NK cells to the spotlight of MS pathology.


title: Identification and Functional Annotation of Long Intergenic Non-coding RNAs in the Brassicaceae

abstract: Long intergenic noncoding RNAs (lincRNAs) are a large yet enigmatic class of eukaryotic transcripts with critical biological functions. Despite the wealth of RNA-seq data available, lincRNA identification lags in the plant lineage. In addition, there is a need for a harmonized identification and annotation effort to enable cross-species functional and genomic comparisons. In this study we processed >24 Tbp of RNA-seq data from >16,000 experiments to identify ~130,000 lincRNAs in four Brassicaceae: Arabidopsis thaliana, Camelina sativa, Brassica rapa, and Eutrema salsugineum. We used Nanopore RNA-seq, transcriptome-wide structural information, peptide data, and epigenomic data to characterize these lincRNAs and identify functional motifs. We then used comparative genomic and transcriptomic approaches to highlight lincRNAs in our dataset with sequence or transcriptional evolutionary conservation, including lincRNAs transcribed adjacent to orthologous genes that display little sequence similarity and likely function as transcriptional regulators. Finally, we used guilt-by-association techniques to further classify these lincRNAs according to putative function. LincRNAs with Brassicaceae-conserved putative miRNA binding motifs, short ORFs, and whose expression is modulated by abiotic stress are a few of the annotations that will prioritize and guide future functional analyses.


title: The aging lung mucosa: A proteomics study

abstract: The elderly population is at increased risk of acute and chronic respiratory infections and other pulmonary diseases, and it is estimated that this population will double in the next 30 years. Biochemical changes in the lung alveolar mucosa and lung cells alter local immune response as we age, creating opportunities for invading pathogens to establish successful infections. Indeed, the lungs of the elderly are a pro-inflammatory, pro-oxidative, dysregulated environment but this environment has remained understudied. We performed a comprehensive, quantitative proteomic profile of the lung mucosa in the elderly, developing insight into the molecular fingerprints, pathways, and regulatory networks that characterize the lung in old age. We identified neutrophils in the lungs of elderly individuals as possible contributors to dysregulated lung tissue environment. This study establishes a baseline for future investigations to develop strategies to mitigate susceptibility to respiratory infections in the elderly.


title: Assessing computational variant effect predictors with a large prospective cohort

abstract: Computational predictors can help interpret pathogenicity of human genetic variants, especially for the majority of variants where no experimental data are available. However, because we lack a high-quality unbiased test set, identifying the best-performing predictors remains a challenge. To address this issue, we evaluated missense variant effect predictors using genotypes and traits from a prospective cohort. We considered 139 gene-trait combinations with rare-variant burden association based on at least one of four systematic studies using phenotypes and whole-exome sequences from ~200K UK Biobank participants. Using an evaluation set of 35,525 rare missense variants and the relevant associated traits, we assessed the correlation of participants traits with scores derived from 20 computational variant effect predictors. We found that two predictors--VARITY and REVEL--outperformed all others according to multiple performance measures. We expect that this study will help in selecting variant effect predictors, for both research and clinical purposes, while providing an unbiased benchmarking strategy that can be applied to additional cohorts and predictors.


title: Increased Activation in the Fusiform Face Area to Greebles is a Result of Expertise Training, Not by its Face-likeness

abstract: In 2011, Brants, Wagemans, & Op de Beeck (JOCN 23:12, pp. 3949-3958) trained eight individuals to become Greeble experts, and found neuronal inversion effects [NIEs; i.e., higher Fusiform Face Area (FFA) activity for upright, rather than inverted Greebles]. These effects were also found for faces, both before and after training. By claiming to have replicated the seminal Greeble training study (i.e., Gauthier, Tarr, Anderson, Skudlarski, & Gore, 1999, Nat Neurosci, 2, 568-573), Brants et al. interpreted these results as participants viewing Greebles as faces throughout training, contrary to the original argument of subjects becoming Greeble experts only after training. However, such a claim presents two issues. First, the behavioral training results of Brants et al. did not replicate those of Gauthier et al (1999), raising concerns of whether the right training regime had been adopted. Second, both a literature review and meta-analysis of NIE in the FFA suggest its unreliability as an index of face(-like) processing. To empirically evaluate these issues, the present study compared two documented training paradigms (i.e., Gauthier & Tarr, 1997, Vision Res, 37, 1673-1682; and Gauthier, Williams, Tarr, & Tanaka, 1998, Vision Res, 38, 2401-2428) and explored their impact on the FFA. The results showed significant increases in the FFA for Greebles, and a clear neural "adaptation" (i.e., decreased activity for faces following Greebles, but not following non-face objects, in the FFA) both only in the Gauthier97 group, and only after training, reflecting clear modulation of expertise following "appropriate" training. In both groups, no clear NIE for faces nor Greebles were found. Collectively, these data invalidate the two assumptions behind the Brants et al. findings, and provide not only the updated support, but also the new evidence, for the perceptual expertise hypothesis of FFA.


title: An ultra-low frequency spike timing dependent plasticity-based approach for treating alcohol use disorder

abstract:
Alcohol use disorder (AUD) is a chronic relapsing brain disorder characterized by an impaired ability to stop or control alcohol consumption despite adverse social, occupational, or health consequences. AUD affects nearly one-third of adults at some point during their lives, with an associated cost of approximately $249 billion annually in the U.S. alone. The effects of alcohol consumption are expected to increase significantly during the COVID-19 pandemic, with alcohol sales increased by approximately 54%, potentially exacerbating health concerns and risk-taking behaviors. Unfortunately, existing pharmacological and behavioral therapies for AUD have historically been associated with poor success rates, with approximately 40% of individuals relapsing within three years of treatment.

Pre-clinical studies have shown that chronic alcohol consumption leads to significant changes in synaptic function within the dorsal medial striatum (DMS), one of the brain regions associated with AUD and responsible for mediating goal-directed behavior. Specifically, chronic alcohol consumption has been associated with hyperactivity of dopamine receptor 1 (D1) medium spiny neurons (MSN) and hypoactivity of dopamine receptor 2 (D1) MSNs within the DMS. Optogenetic, chemogenetic, and transgenic approaches have demonstrated that reducing the D1/D2 MSN signaling imbalance decreases alcohol self-administration in rodent models of AUD. However, these approaches cannot be studied clinically at this time.

Here, we present an electrical stimulation alternative that uses ultra-low (<=1Hz) frequency (ULF) spike-timing dependent plasticity (STDP) to reduce DMS D1/D2 MSN signaling imbalances by stimulating D1-MSN afferents into the GPi and ACC glutamatergic projections to the DMS in a time-locked stimulation sequence. Our data suggest that GPi/ACC ULF-STDP selectively decreases DMS D1-MSN hyperactivity leading to reduced alcohol consumption without evoking undesired affective behaviors in a two-bottle choice mouse model of AUD.


title: Hybrid EEG-EMG system to detect steering actions in car driving settings

abstract: Understanding mental processes in complex human behaviour is a key issue in the context of driving, representing a milestone for developing user-centred assistive driving devices. Here we propose a hybrid method based on electroencephalographic (EEG) and electromyographic (EMG) signatures to distinguish left from right steering in driving scenarios. Twenty-four participants took part in the experiment consisting of recordings 128-channel EEG as well as EMG activity from deltoids and forearm extensors in non-ecological and ecological steering tasks. Specifically, we identified the EEG mu rhythm modulation correlates with motor preparation of self-paced steering actions in the non-ecological task, while the concurrent EMG activity of the left (right) deltoids correlates with right (left) steering. Consequently, we exploited the mu rhythm de-synchronization resulting from the non-ecological task to detect the steering side by means of a cross-correlation analysis with the ecological EMG signals. Results returned significant cross-correlation values showing the coupling between the non-ecological EEG feature and the muscular activity collected in ecological driving conditions. Moreover, such cross-correlation patterns discriminate left from right steering with an earlier dynamic with respect to the single EMG signal. This hybrid system overcomes the limitation of the EEG signals collected in ecological settings such as low reliability, accuracy and adaptability, thus adding to the EMG the characteristic predictive power of the cerebral data. These results are a proof of concept of how it is possible to complement different physiological signals to control the level of assistance needed by the driver.


title: Cerebellar stimulations prevent Levodopa-induced dyskinesia in mice and normalize brain activity

abstract: Chronic Levodopa therapy, the gold-standard treatment of Parkinsons Disease (PD), leads to the emergence of involuntary movements, called levodopa-induced dyskinesia (LID). Cerebellar stimulations have been shown to decrease LID severity in PD patients. Here, in order to determine how cerebellar stimulations induce LID alleviation, we performed daily short trains of optogenetic stimulations of Purkinje cells (PC) in freely moving mice. We demonstrated that these stimulations are sufficient to suppress LID or even prevent their development. This symptomatic relief is accompanied by the normalization of aberrant neuronal discharge in the cerebellar nuclei, the motor cortex and the parafascicular thalamus. Inhibition of the cerebello-parafascicular pathway counteracted the beneficial effect of cerebellar stimulations. Moreover, cerebellar stimulations reversed plasticity in D1 striatal neurons and normalized the overexpression of FosB, a transcription factor causally linked to LID. These findings demonstrate LID alleviation and prevention by daily PC stimulations, which restore the function of a wide brain motor network, and may be valuable for LID treatment.