Miracle-dz/UniFAR-FTUs huggingface dataset:
Customization of a DADA2-based pipeline for fungal internal transcribed spacer 1 (ITS1) amplicon data sets

Identification and analysis of fungal communities commonly rely on internal transcribed spacer (ITS)-based amplicon sequencing. Currently, there is no gold standard to infer and classify fungal constituents, in part since methodologies have been adapted from analyses of bacterial communities. To achieve high resolution inference of fungi in clinical samples, we customized a DADA2-based pipeline using a mock community of eleven medically relevant fungi. While DADA2 allowed the discrimination of ITS1 sequences differing by a single nucleotide, quality filtering, sequencing bias, and database selection were identified as key variables determining the accuracy of sample inference. By fine-tuning quality filtering, we decreased the number of wrongly discarded sequences attributed to Aspergillus species, Saccharomyces cerevisiae, and Candida glabrata reads. We confirmed this effect in patient samples. By adapting a wobble nucleotide in the ITS1 forward primer region, we further increased the yield of S. saccharomyces and C. glabrata sequences. Finally, we showed that a BLAST-based algorithm based on the UNITE+INSD or the NCBI NT database achieved a higher reliability in species-level taxonomic annotation than the naïve Bayesian classifier implemented in DADA2. These steps optimized a robust fungal ITS1 sequencing pipeline that, in most instances, enables species level-assignment of community members.
Application of personalized differential expression analysis in human cancer proteome

Owing to the recent technological advances, liquid chromatography-mass spectrometry (LC-MS)-based quantitative proteomics can measure expression of thousands of proteins from biological specimens. Currently, several studies have used the LC-MS-based proteomics to measure protein expression levels in human cancer. Identifying differentially expressed proteins (DEPs) between tumors and normal controls is a common way to investigate carcinogenesis mechanisms. However, most statistical methods used for DEPs analysis can only identify deregulated proteins at the population-level and ignore the heterogeneous differential expression of proteins in individual patients. Thus, to identify patient-specific molecular defects for personalized medicine, it is necessary to perform personalized differential analysis at the scale of a single sample. To date, there is a scarcity of systematic and easy-to-handle tool that could be used to evaluate the performance of individualized difference expression analysis algorithms in human cancer proteome. Herein, we developed a user-friendly tool kit, IDEP, to enable implementation and evaluation of personalized difference expression analysis algorithms. IDEP evaluates five rank-based tools (RankComp v1/v2, PENDA, Peng and Quantile) through classic computational and functional criteria in lung, gastric and liver cancer proteome. The results show that the within-sample relative expression orderings (REOs) of protein pairs in normal tissues were highly stable, which provided the basis for individual level DEPs analysis. Moreover, these individualized difference analysis tools could reach much higher efficiency in detecting sample-specific deregulated proteins than the group-based methods. Pathway enrichment and survival analysis results were dataset and analysis method dependent. In summary, IDEP has integrated necessary toolkits for individualized identification of DEPs and supported flexible methods evaluation analysis and visualization modules. It could provide a robust and scalable framework to extract personalized deregulation patterns and could also be used for the discovery of prognostic biomarkers for personalized medicine.
Cancer cell migration on straight, wavy, loop and grid microfibre patterns

Cell migration plays an important role in physiological and pathological processes where the fibrillar morphology of extracellular matrices (ECM) could regulate the migration dynamics. To mimic the morphological characteristics of fibrillar matrix structures, low-voltage continuous electrospinning was adapted to construct straight, wavy, looped and gridded fibre patterns made of polystyrene (of fibre diameter ca. 3 μm). Cells were free to explore their different shapes in response to the directly-adhered fibre, as well as to the neighbouring patterns. For all the patterns studied, analysing cellular migration dynamics of MDA-MB-231 (a highly migratory breast cancer cell line) demonstrated two interesting findings: first, although cells dynamically adjust their shapes and migration trajectories in response to different fibrillar environments, their average step speed is minimally affected by the fibre global pattern; secondly, a switch in behaviour was observed when the pattern features approach the upper limit of the cell body’s minor axis, reflecting that cells’ ability to divert from an existing fibre track is limited by the size along the cell body’s minor axis. It is therefore concluded that the upper limit of cell body’s minor axis might act as a guide for the design of microfibre patterns for different purposes of cell migration.
Distinct but cooperating brain networks supporting semantic cognition

Semantic cognition is a complex brain function involving multiple processes from sensory systems, semantic systems, to domain-general cognitive systems, reflecting its multifaceted nature. However, it remain unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we investigated the neural networks involved in semantic cognition using independent component analysis (ICA). We used a semantic judgement task and a pattern matching task as a control task with two levels of difficulty to disentangle task-specific networks from domain-general networks and to delineate task-specific involvement of these networks. ICA revealed that semantic processing recruited two task-specific networks (semantic network [SN] and extended semantic network [ESN]) as well as domain general networks including the frontoparietal network (FPN) and default mode network (DMN). Specifically, two distinct semantic networks were differently modulated by task difficulty. The SN was coupled with the extended semantic network and FPN but decoupled with the DMN, whereas the ESN was synchronised with the FPN and DMN. Furthermore, the degree of decoupling between the SN and DMN was associated with semantic performance. Our findings suggest that human higher cognition is achieved by the neural dynamics of brain networks, serving distinct and shared cognitive functions depending on task demands.
Energetics but not development is impacted in coral embryos exposed to ocean acidification

In light of the chronic stress and mass mortality reef-building corals face under climate change, it is critical to understand the processes essential to reef persistence and replenishment, including coral reproduction and development. Here we quantify gene expression and size sensitivity to ocean acidification across a set of developmental stages in the rice coral, Montipora capitata. Gametes and then embryos and swimming larvae were exposed to three pH treatments ranging from 7.8 (Ambient), 7.6 (Low) and 7.3 (Xlow) from fertilization to 9 days post-fertilization. Embryo development and size, planula volume, and stage-specific gene expression were compared between treatments at each stage to determine the effects of acidified seawater on early development. While there was no measurable size differentiation between fertilized eggs and embryos at the prawn chip stage exposed to ambient, low, and extreme low pH, early gastrula and planula raised in reduced pH treatments were significantly smaller than those raised in ambient seawater, suggesting an energetic cost to developing under low pH. However, no differentially expressed genes emerged between treatments at any time point, except swimming larvae. Larvae from pH 7.6 showed upregulation of genes involved in cell division, regulation of transcription, lipid metabolism, and oxidative stress in comparison to the other two treatments, and smallest sizes in this treatment. While low pH appears to increase energetic demands and trigger oxidative stress, the developmental process is robust to this at a molecular level, with swimming larval stage reached in all pH treatments. Summary statement This developmental time series tracks the physiological and transcriptomic outcomes of early coral development under ambient pH (pH 7.8), and two low pH conditions (pH 7.6 and 7.3).
Tissue-Specific Biochemical Differences Between Chronic Wasting Disease Prions Isolated From Free Ranging, White-Tailed Deer (Odocoileus virginianus)

Chronic wasting disease (CWD) is an invariably fatal prion disease affecting cervid species world-wide. Prions can manifest as distinct strains that can influence disease pathology and transmission. CWD is profoundly lymphotropic and most infected cervids likely shed peripheral prions replicated in lymphoid organs. However, CWD is a neurodegenerative disease and most research on prion strains has focused on neurogenic prions. Thus, a knowledge gap exists comparing prions in the brain to prions in the lymph node. In this study we compared prions from the obex and lymph node of naturally exposed white-tailed deer to identify potential biochemical strain differences. Here, we report biochemical evidence of strain differences between the brain and lymph node from these animals. Future work should examine the biological and zoonotic impact of these biochemical differences and examine more cervids from multiple locations to see if these differences are conserved across species and locations.
Spontaneous Emergence of Multicellular Heritability

The Major Transitions in evolution include events and processes that result in the emergence of new levels of biological individuality. For collectives to undergo Darwinian evolution, their traits must be heritable, but the emergence of higher-level heritability is poorly understood and has long been considered a stumbling block for nascent evolutionary transitions. A change in the means by which genetic information is utilized and transmitted has been presumed necessary. Using analytical models, synthetic biology, and biologicallyinformed simulations, we explored the emergence of trait heritability during the evolution of multicellularity. Contrary to existing theory, we show that no additional layer of genetic regulation is necessary for traits of nascent multicellular organisms to become heritable; rather, heritability and the capacity to respond to natural selection on multicellular-level traits can arise “for free. ” In fact, we find that a key emergent multicellular trait, organism size at reproduction, is usually more heritable than the underlying cell-level trait upon which it is based, given reasonable assumptions.
Key Substitutions in the Spike Protein of SARS-CoV-2 Variants Can Predict Resistance to Monoclonal Antibodies, but Other Substitutions Can Modify the Effects

Therapeutic antibodies are effective in preventing severe disease from SARS-CoV-2 infection (COVID-19), but their effectiveness may be reduced by virus variants with mutations affecting the spike protein. To help predict resistance to therapeutic antibodies in emerging variants, we profiled resistance patterns of 25 antibody products in late stages of clinical development against a large panel of variants that include single and multiple substitutions found in the spike protein. ABSTRACT Mutations in the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants can compromise the effectiveness of therapeutic antibodies. Most clinical-stage therapeutic antibodies target the spike receptor binding domain (RBD), but variants often have multiple mutations in several spike regions. To help predict antibody potency against emerging variants, we evaluated 25 clinical-stage therapeutic antibodies for neutralization activity against 60 pseudoviruses bearing spikes with single or multiple substitutions in several spike domains, including the full set of substitutions in B.1. 1.7 (alpha), B.1. 351 (beta), P.1 (gamma), B.1. 429 (epsilon), B.1. 526 (iota), A.23. 1, and R.1 variants. We found that 14 of 15 single antibodies were vulnerable to at least one RBD substitution, but most combination and polyclonal therapeutic antibodies remained potent. Key substitutions in variants with multiple spike substitutions predicted resistance, but the degree of resistance could be modified in unpredictable ways by other spike substitutions that may reside outside the RBD. These findings highlight the importance of assessing antibody potency in the context of all substitutions in a variant and show that epistatic interactions in spike can modify virus susceptibility to therapeutic antibodies. IMPORTANCE Therapeutic antibodies are effective in preventing severe disease from SARS-CoV-2 infection (COVID-19), but their effectiveness may be reduced by virus variants with mutations affecting the spike protein. To help predict resistance to therapeutic antibodies in emerging variants, we profiled resistance patterns of 25 antibody products in late stages of clinical development against a large panel of variants that include single and multiple substitutions found in the spike protein. We found that the presence of a key substitution in variants with multiple spike substitutions can predict resistance against a variant but that other substitutions can affect the degree of resistance in unpredictable ways. These findings highlight complex interactions among substitutions in the spike protein affecting virus neutralization and, potentially, virus entry into cells.
Echidna: integrated simulations of single-cell immune receptor repertoires and transcriptomes

Single-cell sequencing now enables the recovery of full-length immune repertoires [B cell receptor (BCR) and T cell receptor (TCR) repertoires], in addition to gene expression information. The feature-rich datasets produced from such experiments require extensive and diverse computational analyses, each of which can significantly influence the downstream immunological interpretations, such as clonal selection and expansion. Simulations produce validated standard datasets, where the underlying generative model can be precisely defined and furthermore perturbed to investigate specific questions of interest. Currently, there is no tool that can be used to simulate a comprehensive ground truth single-cell dataset that incorporates both immune receptor repertoires and gene expression. Therefore, we developed Echidna, an R package that simulates immune receptors and transcriptomes at single-cell resolution. Our simulation tool generates annotated single-cell sequencing data with user-tunable parameters controlling a wide range of features such as clonal expansion, germline gene usage, somatic hypermutation, and transcriptional phenotypes. Echidna can additionally simulate time-resolved B cell evolution, producing mutational networks with complex selection histories incorporating class-switching and B cell subtype information. Finally, we demonstrate the benchmarking potential of Echidna by simulating clonal lineages and comparing the known simulated networks with those inferred from only the BCR sequences as input. Together, Echidna provides a framework that can incorporate experimental data to simulate single-cell immune repertoires to aid software development and bioinformatic benchmarking of clonotyping, phylogenetics, transcriptomics and machine learning strategies.
The zebra finch auditory cortex reconstructs occluded syllables in conspecific song

Sensory input provides incomplete and often misleading information about the physical world. To compensate, the brain uses internal models to predict what the inputs should be from context, experience, and innate biases (Liberman and Mattingly, 1985; Komatsu, 2006; Gilbert and Sigman, 2007; Heald and Nusbaum, 2014). For example, when speech is interrupted by noise, humans perceive the missing sounds behind the noise (Miller and Licklider, 1950; Warren, 1970; Samuel, 1996), a perceptual illusion known as phonemic (or auditory) restoration. The neural mechanisms allowing the auditory system to generate predictions that override ascending sensory information remain poorly understood. Here, we show that the zebra finch (Taeniopygia guttata) exhibits auditory restoration of conspecific song both in a behavioral task and in neural recordings from the equivalent of auditory cortex. Decoding the responses of a population of single units to occluded songs reveals the spectrotemporal structure of the missing syllables. Surprisingly, restoration occurs under anesthesia and for songs that the bird has not heard. These results show that an internal model of the general structure of conspecific vocalizations can bias sensory processing without attention.
Pathotyping of Newcastle Disease Virus: a Novel Single BsaHI Digestion Method of Detection and Differentiation of Avirulent Strains (Lentogenic and Mesogenic Vaccine Strains) from Virulent Virus

The extensive use of the NDV vaccine strain and the existence of avirulent NDV strains in wild birds makes it difficult to diagnose Newcastle Disease virus (NDV). The intracerebral pathogenicity index (ICPI) and/or sequencing-based identification, which are required to determine virulent NDV, are time-consuming, costly, difficult, and cruel techniques. ABSTRACT We provide a novel single restriction enzyme (RE; BsaHI) digestion approach for detecting distinct pathotypes of Newcastle disease virus (NDV). After scanning 4,000 F gene nucleotide sequences in the NCBI database, we discovered a single RE (BsaHI) digestion site in the cleavage site. APMV-I “F gene” class II-specific primer-based reverse transcriptase PCR was utilized to amplify a 535-bp fragment, which was then digested with the RE (BsaHI) for pathotyping avian NDV field isolates and pigeon paramyxovirus-1 isolates. The avirulent (lentogenic and mesogenic strains) produced 189- and 346-bp fragments, respectively, but the result in velogenic strains remained undigested with 535-bp fragments. In addition, 45 field NDV isolates and 8 vaccine strains were used to confirm the approach. The sequence-based analysis also agrees with the data obtained utilizing the single RE (BsaHI) digestion approach. The proposed technique has the potential to distinguish between avirulent and virulent strains in a short time span, making it valuable in NDV surveillance and monitoring research. IMPORTANCE The extensive use of the NDV vaccine strain and the existence of avirulent NDV strains in wild birds makes it difficult to diagnose Newcastle Disease virus (NDV). The intracerebral pathogenicity index (ICPI) and/or sequencing-based identification, which are required to determine virulent NDV, are time-consuming, costly, difficult, and cruel techniques. We evaluated 4,000 F gene nucleotide sequences and discovered a restriction enzyme (RE; BsaHI) digestion technique for detecting NDV and vaccine pathotypes in a short time span, which is cost-effective and useful for field cases as well as for large-scale NDV monitoring and surveillance. The data acquired using the single RE BsaHI digestion technique agree with the sequence-based analysis.
Host phylogeny drives the structure and diversity of insect microbiota

6 Microorganisms have an enormous impact on most of the life that inhabits our planet. Insects 7 are an excellent example, as research showed that several microbial species are essential for insect 8 nutrition, reproduction, fitness, defence and many other functions. More recently, we assisted to 9 an exponential growth of studies describing the taxonomical composition of bacterial communities 10 across insects’ phylogeny. However, there is still an outstanding question that needs to be answered: 11 which factors contribute most in shaping insects’ microbiomes? This study tries to find an answer 12 to this question by taking advantage of publicly available sequencing data and reanalysing over 13 4,000 samples of insect-associated bacterial communities under a common framework. Results 14 suggest that insect taxonomy has a wider impact on the structure and diversity of their associated 15 microbial communities than the other factors considered (diet, sex, life stage, sample origin and 16 treatment). Also, a survey of the literature highlights several methodological limitations that 17 needs to be considered in future research endeavours. This study proofs the amount of collective 18 effort that lead to the current understanding of insect-microbiota interactions and their influence on 19 insect biology, ecology and evolution with potential impact on insect conservation and management 20 practices. 21
Absolute copy number fitting from shallow whole genome sequencing data

Low-coverage or shallow whole genome sequencing (sWGS) approaches can efficiently detect somatic copy number aberrations (SCNAs) at low cost. This is clinically important for many cancers, in particular cancers with severe chromosomal instability (CIN) that frequently lack actionable point mutations and are characterised by poor disease outcome. Absolute copy number (ACN), measured in DNA copies per cancer cell, is required for meaningful comparisons between copy number states, but is challenging to estimate and in practice often requires manual curation. Using a total of 60 cancer cell lines, 148 patient-derived xenograft (PDX) and 142 clinical tissue samples, we evaluate the performance of available tools for obtaining ACN from sWGS. We provide a validated and refined tool called Rascal (relative to absolute copy number scaling) that provides improved fitting algorithms and enables interactive visualisation of copy number profiles. These approaches are highly applicable to both pre-clinical and translational research studies on SCNA-driven cancers and provide more robust ACN fits from sWGS data than currently available tools.
Specialized neurons in the right habenula mediate response to aversive olfactory cues

Hemispheric specializations are well studied at the functional level but less is known about the underlying neural mechanisms. We identified a small cluster of cholinergic neurons in the right dorsal habenula (dHb) of zebrafish, defined by their expression of the lecithin retinol acyltransferase domain containing 2a (lratd2a) gene and their efferent connections with a subregion of the ventral interpeduncular nucleus (vIPN). The unilateral lratd2a-expressing neurons are innervated by a subset of mitral cells from both the left and right olfactory bulb and are activated upon exposure of adult zebrafish to the aversive odorant cadaverine that provokes avoidance behavior. Using an intersectional strategy to drive expression of the botulinum neurotoxin specifically in these neurons, we find that adults no longer show protracted avoidance to cadaverine. Mutants with left-isomerized dHb that lack these neurons are less repelled by cadaverine and their behavioral response to alarm substance, a potent aversive cue, is diminished. However mutants in which both dHb have right identity appear more reactive to alarm substance. The results implicate an asymmetric dHb-vIPN neural circuit in processing of aversive olfactory cues and modulating resultant behavioral responses.