Miracle-dz/UniFAR-FTUs huggingface dataset:
Alpha oscillations shape sensory representation and perceptual accuracy

Alpha oscillatory activity (8–14 Hz) is the dominant rhythm in the awake brain, and is thought to play an important role in setting the brain’s internal state. Previous work has associated states of decreased alpha-band oscillatory power with enhanced neural excitability. However, opinions differ on whether and how such excitability enhancement modulates sensory signals of interest versus noise differently, and what, if any, the consequences are for the subsequent perceptual process. To address these questions, we used a novel paradigm to experimentally manipulate human subjects’ decision criteria in a visual detection task. In different blocks, we primed subjects with clearly visible stimuli to introduce either a liberal or conservative detection criterion for subsequent ambiguous stimuli. While we observed substantial criterion shifts under different priming conditions, such criterion shifts were not reflected in pre-stimulus alpha-band changes. Rather, we found that lower pre-stimulus alpha-band power in early visual cortices improved perceptual accuracy, accompanied by enhanced information content decodable from the neural activity patterns. Additionally, we showed that alpha oscillatory phase in parietal and frontal regions immediately before stimulus presentation modulated accuracy. Together, our results suggest that alpha-band dynamics modulate sensory signals of interest more strongly compared to noise, here resulting in enhanced information coding and improved perceptual accuracy. Significance Statement The internal state of our brain fluctuates, giving rise to variability in perception and action. Neural oscillations, most prominently in the alpha-band, have been suggested to play a role in setting this internal state. Here, we show that ongoing alpha-band activity in early visual regions predicts the quality of visual information decodable in neural activity patterns, and subsequently human observer’s accuracy in a visual detection task. Our results provide the heretofore first evidence that visual representation is modulated by ongoing alpha-band activity, and advance our understanding on how, when faced with unchanging external stimuli, internal neural fluctuations influence perception and behavior.
Large-scale analysis of SARS-CoV-2 spike-glycoprotein mutants demonstrates the need for continuous screening of virus isolates

Due to the widespread of the COVID-19 pandemic, the SARS-CoV-2 genome is evolving in diverse human populations. Several studies already reported different strains and an increase in the mutation rate. Particularly, mutations in SARS-CoV-2 spike-glycoprotein are of great interest as it mediates infection in human and recently approved mRNA vaccines are designed to induce immune responses against it. We analyzed 146,917 SARS-CoV-2 genome assemblies and 2,393 NGS datasets from GISAID, NCBI Virus and NCBI SRA archives focusing on non-synonymous mutations in the spike protein. Only around 13.8% of the samples contained the wild-type spike protein with no variation from the reference. Among the spike protein mutants, we confirmed a low mutation rate exhibiting less than 10 non-synonymous mutations in 99.98% of the analyzed sequences, but the mean and median number of spike protein mutations per sample increased over time. 2,592 distinct variants were found in total. The majority of the observed variants were recurrent, but only nine and 23 recurrent variants were found in at least 0.5% of the mutant genome assemblies and NGS samples, respectively. Further, we found high-confidence subclonal variants in about 15.1% of the NGS data sets with mutant spike protein, which might indicate co-infection with various SARS-CoV-2 strains and/or intra-host evolution. Lastly, some variants might have an effect on antibody binding or T-cell recognition. These findings demonstrate the increasing importance of monitoring SARS-CoV-2 sequences for an early detection of variants that require adaptations in preventive and therapeutic strategies.
Systems-Level Proteomics Evaluation of Microglia Response to Tumor-Supportive Anti-Inflammatory Cytokines

Background Microglia safeguard the CNS against injuries and pathogens by inducing an inflammatory response. When exposed to anti-inflammatory cytokines, these cells possess the ability to switch from an inflammatory to an immunosuppressive phenotype. Cancer cells exploit this property to evade the immune system, and elicit an anti-inflammatory microenvironment that facilitates tumor attachment and growth. Objective The tumor-supportive biological processes that are activated in microglia cells in response to anti-inflammatory cytokines released from cancer cells were explored with mass spectrometry and proteomic technologies. Methods Serum-depleted and non-depleted human microglia cells (HMC3) were treated with a cocktail of IL-4, IL-13, IL-10, TGFβ, and CCL2. The cellular protein extracts were analyzed by LC-MS/MS. Using functional annotation clustering tools, statistically significant proteins that displayed a change in abundance between cytokine-treated and non-treated cells were mapped to their biological networks and pathways. Results The proteomic analysis of HMC3 cells enabled the identification of ∼10,000 proteins. Stimulation with anti-inflammatory cytokines resulted in the activation of distinct, yet integrated clusters of proteins that trigger downstream a number of tumor-promoting biological processes. The observed changes could be classified into four major categories, i.e., mitochondrial gene expression, ECM remodeling, immune response, and impaired cell cycle progression. Intracellular immune activation was mediated mainly by the transducers of MAPK, STAT, TGFβ, NFKB, and integrin signaling pathways. Abundant collagen formation along with the expression of additional receptors, matrix components, growth factors, proteases and protease inhibitors, enabled ECM remodeling processes supportive of cell-cell and cell-matrix adhesion. Overexpression of integrins and their modulators was reflective of signaling processes that correlated ECM reorganization with cytoskeletal re-arrangements supportive of cell migration. Antigen processing/presentation was represented by HLA class I histocompatibility antigens, and correlated with upregulated proteasomal subunits, and vesicular/viral transport and secretory processes. Immunosuppressive and proangiogenic chemokines were detectable in low abundance. Pronounced pro-inflammatory, chemotactic or phagocytic trends were not observed, however, the expression of certain receptors and ECM proteins indicated the presence of such capabilities. Conclusions Comprehensive proteomic profiling of HMC3 cells stimulated with anti-inflammatory cytokines revealed a microglia phenotype that provides novel insights into the tumor microenvironment-driven mechanisms that fuel cancer development in the brain.
GRAFIMO: Variant and haplotype aware motif scanning on pangenome graphs

Transcription factors (TFs) are proteins that promote or reduce the expression of genes by binding short genomic DNA sequences known as transcription factor binding sites (TFBS). While several tools have been developed to scan for potential occurrences of TFBS in linear DNA sequences or reference genomes, no tool exists to find them in pangenome variation graphs (VGs). VGs are sequence-labelled graphs that can efficiently encode collections of genomes and their variants in a single, compact data structure. Because VGs can losslessly compress large pangenomes, TFBS scanning in VGs can efficiently capture how genomic variation affects the potential binding landscape of TFs in a population of individuals. Here we present GRAFIMO (GRAph-based Finding of Individual Motif Occurrences), a command-line tool for the scanning of known TF DNA motifs represented as Position Weight Matrices (PWMs) in VGs. GRAFIMO extends the standard PWM scanning procedure by considering variations and alternative haplotypes encoded in a VG. Using GRAFIMO on a VG based on individuals from the 1000 Genomes project we recover several potential binding sites that are enhanced, weakened or missed when scanning only the reference genome, and which could constitute individual-specific binding events. GRAFIMO is available as an open-source tool, under the MIT license, at https://github.com/pinellolab/GRAFIMO and https://github.com/InfOmics/GRAFIMO. Author summary Transcription factors (TFs) are key regulatory proteins and mutations occurring in their binding sites can alter the normal transcriptional landscape of a cell and lead to disease states. Pangenome variation graphs (VGs) efficiently encode genomes from a population of individuals and their genetic variations. GRAFIMO is an open-source tool that extends the traditional PWM scanning procedure to VGs. By scanning for potential TBFS in VGs, GRAFIMO can simultaneously search thousands of genomes while accounting for SNPs, indels, and structural variants. GRAFIMO reports motif occurrences, their statistical significance, frequency, and location within the reference or alternative haplotypes in a given VG. GRAFIMO makes it possible to study how genetic variation affects the binding landscape of known TFs within a population of individuals.
dcHiC: differential compartment analysis of Hi-C datasets

The compartmental organization of chromatin and its changes play important roles in distinct biological processes carried out by mammalian genomes. However, differential compartment analyses have been mostly limited to pairwise comparisons and with a main focus on only the compartment flips (e.g., A-to-B). Here, we introduce dcHiC, which utilizes quantile normalized compartment scores and a multivariate distance measure to identify significant changes in compartmentalization among multiple contact maps. Evaluating dcHiC on three collections of Hi-C contact maps from mouse neural differentiation (n=3), mouse hematopoiesis (n=10) and human LCL cell lines (n=20), we show its effectiveness and sensitivity in detecting biologically relevant differences, including those validated by orthogonal experiments. Across these experiments, dcHiC reported regions with dynamically regulated genes associated with cell identity, along with correlated changes in chromatin states, replication timing and lamin B1 association. With its efficient implementation, dcHiC not only enables high-resolution compartment analysis but also includes a suite of additional features, including standalone browser visualization, differential interaction identification, and time-series clustering. As such, it is an essential addition to the Hi-C analysis toolbox for the ever-growing number of contact maps being generated. dcHiC is freely available at https://github.com/ay-lab/dcHiC, and examples from this paper can be seen at https://ay-lab.github. io/dcHiC.
Evolution and connectivity influence the persistence and recovery of coral reefs under climate change in the Caribbean, Southwest Pacific, and Coral Triangle

Corals are experiencing unprecedented decline from climate change-induced mass bleaching events. Dispersal not only contributes to coral reef persistence through demographic rescue but can also hinder or facilitate evolutionary adaptation. Locations of reefs that are likely to survive future warming therefore remain largely unknown, particularly within the context of both ecological and evolutionary processes across complex seascapes that differ in temperature range, strength of connectivity, network size, and other characteristics. Here, we used eco-evolutionary simulations to examine coral adaptation to warming across reef networks in the Caribbean, the Southwest Pacific, and the Coral Triangle. We assessed the factors associated with coral persistence in multiple reef systems to understand which results are general and which are sensitive to particular geographic contexts. We found that evolution can be critical in preventing extinction and facilitating the long-term recovery of coral communities in all regions. Furthermore, the strength of immigration to a reef (destination strength) and current sea surface temperature robustly predicted reef persistence across all reef networks and across temperature projections. However, we found higher initial coral cover, slower recovery, and more evolutionary lag in the Coral Triangle, which has a greater number of reefs and more larval settlement than the other regions. We also found the lowest projected future coral cover in the Caribbean. These findings suggest that coral reef persistence depends on ecology, evolution, and habitat network characteristics, and that, under an emissions stabilization scenario (RCP 4.5), recovery may be possible over multiple centuries.
Impact of Propionic Acidemia on Brain Astrocytes

Propionic acidemia (PA) is an inborn error of metabolism (IEM) caused by mutations in the enzyme propionyl CoA carboxylase (PCC). It is characterized by the inability to break down branched chain amino acids and odd chain fatty acids, causing a buildup of toxic organic acids in blood. PA affects every organ in the body with particularly severe manifestations in the brain, like hyperammonemia, hypomyelination, seizures, cognitive impairments, optic nerve atrophy and autism spectrum disorders. Dietary management and liver transplantation have helped to ameliorate the acute expression of the disorder, but do not prevent the chronic toxicity that builds up in brain. Despite the severe brain manifestation of the disease, little is known about the mechanisms by which PA affects the nervous system. PCCA and PCCB, the two subunits required for a functional PCC enzyme, are both expressed not only in neurons but also in astrocytes. Using the two rodent genetic models of PA currently available, with mutations in PCCA, we have evaluated the involvement of astrocytes in the neuropathology of propionic acidemia. These mice exhibit cardiac pathology and hyperammonemia, similar to what is observed in patients with PA. We found that wild type (wt) astrocytes positively respond to treatment with L-Carnitine, a therapeutic approach commonly used in patients with PA, by improved survival and more efficient mitochondrial morphology. Transcriptome analysis from astrocytes derived from the wt or the mutant mice confirm that these astrocytes lack exons 3 and 4 like in the human mutations of PA. However, no other genes/exons were statistically significant with regards to differential expression between astrocytes derived from KO or from WT animals, suggesting that astrocytes in culture may be able to compensate the PCC deficiency. Histological analysis of neuronal and glial markers during brain development (TUJ1, MAP2 for neurons; nestin and Iba1 for glia) do not show significant alterations neither in distribution nor numbers of cells in the developing brain of the PCCA-/- mice. Analysis in the adult brain of mutant mice shows some variable degree of microgliosis but no indication of reactive astrocytes. No gross abnormalities were observed in cortex, hippocampus, striatum or cerebellum of adult brains of PCCA-/- mice, either. In summary, astrocytes from PCCA deficient mice show surprisingly little alterations both in vitro and in vivo. Our results evidence the need to further understand the effects of PA in brain cells to help develop potential new therapies that can preserve brain function in children affected by this devastating disease. HIGHLIGHTS Astrocytes detoxify ammonia in brain and may be affected by propionic acidemia, a disorder that causes hyperammonemia in brain. RNA seq of astrocytes in culture derived from PCCA mutant mice does not show effect in these cells. In vivo analysis of glial and neuronal cells also shows no difference in development or adult mutant mice Astrocytes may not be an adequate target of clinical therapies in this disorder
Structural variability and concerted motions of the T cell receptor – CD3 complex

We investigate the structural and orientational variability of the membrane-embedded T cell receptor (TCR) – CD3 complex in extensive atomistic molecular dynamics simulations based on the recent cryo-EM structure determined by Dong et al. (2019). We find that the TCR extracellular (EC) domain is highly variable in its orientation by attaining tilt angles relative to the membrane normal that range from 15° to 55°. The tilt angle of the TCR EC domain is both coupled to a rotation of the domain and to characteristic changes throughout the TCR – CD3 complex, in particular in the EC interactions of the Cβ FG loop of the TCR, as well as in the orientation of transmembrane helices. The concerted motions of the membrane-embedded TCR – CD3 complex revealed in our simulations provide atomistic insights for force-based models of TCR activation, which involve such structural changes in response to tilt-inducing forces on antigen-bound TCRs.
Rare long-range cortical connections enhance information processing

What are the key topological features of connectivity critically relevant for generating the dynamics underlying efficient cortical function? A candidate feature that has recently emerged is that the connectivity of the mammalian cortex follows an exponential distance rule, which includes a small proportion of long-range high-weight anatomical exceptions to this rule. Whole-brain modelling of large-scale human neuroimaging data in 1003 participants offers the unique opportunity to create two models with and without long-range exceptions and explicitly study their functional consequences. We found that rare long-range exceptions are crucial for significantly improving information processing. Furthermore, modelling in a simplified ring architecture shows that this improvement is greatly enhanced by the turbulent regime found in empirical neuroimaging data. Overall, the results provide strong empirical evidence for the immense functional benefits of long-range exceptions combined with turbulence for information processing.
A recurrent cortical model can parsimoniously explain the effect of expectations on sensory processes

The effect of prior knowledge and expectations on perceptual and decision-making processes have been extensively studied. Yet, the computational mechanisms underlying those effects have been a controversial issue. Recently, using a recursive Bayesian updating scheme, unmet expectations have been shown to entail further computations, and consequently delay perceptual processes. Here we take a step further and model these empirical findings with a recurrent cortical model, which was previously suggested to approximate Bayesian inference (Heeger, 2017). Our model fitting results show that the cortical model can successfully predict the behavioral effects of expectation. That is, when the actual sensory input does not match with the expectations, the sensory process needs to be completed with additional, and consequently longer, computations. We suggest that this process underlies the delay in perceptual thresholds in unmet expectations. Overall our findings demonstrate that a parsimonious recurrent cortical model can explain the effects of expectation on sensory processes.
Plant pathogens convergently evolved to counteract redundant nodes of an NLR immune receptor network

In plants, NLR (nucleotide-binding domain and leucine-rich repeat-containing) proteins can form receptor networks to confer hypersensitive cell death and innate immunity. One class of NLRs, known as NRCs (NLR required for cell death), are central nodes in a complex network that protects against multiple pathogens and comprises up to half of the NLRome of solanaceous plants. Given the prevalence of this NLR network, we hypothesized that pathogens convergently evolved to secrete effectors that target NRC activities. To test this, we screened a library of 167 bacterial, oomycete, nematode and aphid effectors for their capacity to suppress the cell death response triggered by the NRC-dependent disease resistance proteins Prf and Rpi-blb2. Among five of the identified suppressors, one cyst nematode protein and one oomycete protein suppress the activity of autoimmune mutants of NRC2 and NRC3, but not NRC4, indicating that they specifically counteract a subset of NRC proteins independently of their sensor NLR partners. Whereas the cyst nematode effector SPRYSEC15 binds the nucleotide-binding domain of NRC2 and NRC3, the oomycete effector AVRcap1b suppresses the response of these NRCs via the membrane trafficking-associated protein NbTOL9a (Target of Myb 1-like protein 9a). We conclude that plant pathogens have evolved to counteract central nodes of the NRC immune receptor network through different mechanisms. Coevolution with pathogen effectors may have driven NRC diversification into functionally redundant nodes in a massively expanded NLR network.
The Mutation Profile of SARS-CoV-2 Is Primarily Shaped by the Host Antiviral Defense

Understanding SARS-CoV-2 evolution is a fundamental effort in coping with the COVID-19 pandemic. The virus genomes have been broadly evolving due to the high number of infected hosts world-wide. Mutagenesis and selection are the two inter-dependent mechanisms of virus diversification. However, which mechanisms contribute to the mutation profiles of SARS-CoV-2 remain under-explored. Here, we delineate the contribution of mutagenesis and selection to the genome diversity of SARS-CoV-2 isolates. We generated a comprehensive phylogenetic tree with representative genomes. Instead of counting mutations relative to the reference genome, we identified each mutation event at the nodes of the phylogenetic tree. With this approach, we obtained the mutation events that are independent of each other and generated the mutation profile of SARS-CoV-2 genomes. The results suggest that the heterogeneous mutation patterns are mainly reflections of host (i) antiviral mechanisms that are achieved through APOBEC, ADAR, and ZAP proteins and (ii) probable adaptation against reactive oxygen species. Importance SARS-CoV-2 genomes are evolving worldwide. Revealing the evolutionary characteristics of SARS-CoV-2 is essential to understand host-virus interactions. Here, we aim to understand whether mutagenesis or selection is the primary driver of SARS-CoV-2 evolution. This study provides an unbiased computational method for profiling and analyzing independently occurring SARS-CoV-2 mutations. The results point out three host antiviral mechanisms shaping the mutational profile of SARS-CoV-2 through APOBEC, ADAR, and ZAP proteins. Besides, reactive oxygen species might have an impact on the SARS-CoV-2 mutagenesis.