title: Controlling for variable transposition rate with an age-adjusted site frequency spectrum

abstract: Recognition of the important role of transposable elements (TEs) in eukaryotic genomes quickly led to a burgeoning literature modeling and estimating the effects of selection on TEs. Much of the empirical work on selection has focused on analyzing the site frequency spectrum (SFS) of TEs. But TEs differ from standard evolutionary models in a number of ways that can impact the power and interpretation of the SFS. For example, rather than mutating under a clock-like model, transposition often occurs in bursts which can inflate particular frequency categories compared to expectations under a standard neutral model. If a TE burst has been recent, the excess of low frequency polymorphisms can mimic the effect of purifying selection. Here, we investigate how transposition bursts affect the frequency distribution of TEs and the correlation between age and allele frequency. Using information on the TE age distribution, we propose an age-adjusted site frequency spectrum to compare TEs and neutral polymorphisms to more effectively evaluate whether TEs are under selective constraints. We show that our approach can minimize instances of false inference of selective constraint, but also allows for a correct identification of even weak selection affecting TEs which experienced a transposition burst and is robust to at least simple demographic changes. The results presented here will help researchers working on TEs to more reliably identify the effects of selection on TEs without having to rely on the assumption of a constant transposition rate.


title: Sex-dependent resource defense in a nectar-feeding bat

abstract:
Aggressive resource defense spans from the transient monopolization of a resource up to the long-term maintenance of a territory. While such interference competition is common in nectar-feeding birds, reports in nectar-feeding bats are rare. Glossophaga bats have been observed to temporarily defend flowers but the extent of this monopolization, its effects on nectar intake, and underlying sexual differences remain unknown. We investigated resource defense behavior of Glossophaga mutica in the laboratory. We presented bats with two patches of computer-controlled artificial flowers and tracked individual nectar intake. Furthermore, we established an automated method for detecting aggressive interactions at the artificial flowers. Theoretical models of interference competition predict more aggressive interactions when resources are spatially more clumped. To test this, we varied resource distribution across two patches from clumped to distributed and monitored bats interactions in one male, one female, and four mixed-sex groups. Males engaged in aggressive interactions more often than females and in each group some individuals defended clumped artificial flowers against others. Subordinate males experienced a substantial decrease in nectar intake, while females were only marginally affected by male aggression. These results suggest that aggressive interactions and their effect on nectar intake are sex-dependent in G. mutica. Furthermore, aggressive interactions were more frequent and resource defense was only successful when resources were clumped. Our experimental set-up allowed us to perform an automated test of models of interference competition with a mammal under controlled laboratory conditions. This approach may pave the way for similar studies with other animals.

Lay summaryMales bully other males to get more food, but only when food is easy to defend. When flowers are spread out nectar-feeding bats rarely engage in fights. However, when there are rich flowers in one spot and no flowers elsewhere, some males start attacking others, denying them access to the nectar. Females do not seem bothered by such male bullies, but when there are no males around, some females become bullies themselves.

category: animal behavior and cognition


title: Prediction of allosteric sites and signalling: insights from benchmarking datasets

abstract: AO_SCPLOWBSTRACTC_SCPLOWAllostery is a pervasive mechanism which regulates the activity of proteins in living systems through binding of a molecule at a distant site from the orthosteric site of the protein. The universality of allosteric regulation complemented by the benefits of highly specific, potentially non-toxic and protein activity modulating allosteric drugs makes uncovering allosteric sites on proteins invaluable for drug discovery. However, there are few computational methods to effectively predict them. Bond-to-bond propensity analysis, a recently developed method, has successfully predicted allosteric sites for a diverse group of proteins with only the knowledge of the orthosteric sites and the corresponding ligands in 19 of 20 cases. The method is based on an energy-weighted atomistic protein graph and allows for computationally highly efficient analysis in atomistic detail. We here extended the analysis onto 432 structures of 146 proteins from two existing benchmarking datasets for allosteric proteins: ASBench and CASBench. We further refined the metrics to account for the cumulative effect of residues with high propensities and the crucial residues in a given site with two additional measures. The allosteric site is recovered for 95/113 proteins (99/118 structures) from ASBench and 32/33 proteins (304/314 structures) from CASBench, with the only a priori knowledge being the orthosteric site residues. Knowing the orthosteric ligands of the protein, the allosteric site is identified for 32/33 proteins (308/314 structures) from CASBench.

category: bioinformatics


title: pyFoldX: enabling biomolecular analysis and engineering along structural ensembles

abstract:
Recent years have seen an increase in the number of structures available, not only for new proteins but also for the same protein crystallized with different molecules and proteins. While protein design software have proven to be successful in designing and modifying proteins, they can also be overly sensitive to small conformational differences between structures of the same protein. To cope with this, we introduce here pyFoldX, a python library that allows the integrative analysis of structures of the same protein using FoldX, an established forcefield and modeling software. The library offers new functionalities for handling different structures of the same protein, an improved molecular parametrization module, and an easy integration with the data analysis ecosystem of the python programming language.

Availability and implementationpyFoldX is an open-source library that uses the FoldX software for energy calculations and modelling. The latter can be downloaded upon registration in http://foldxsuite.crg.eu/ and is free of charge for academics. Full details on installation, tutorials covering the library functionality, and the scripts used to generate the data and figures presented in this paper are available at https://github.com/leandroradusky/pyFoldX.


title: SeqDistK: a Novel Tool for Alignment-free Phylogenetic Analysis

abstract: Algorithms for constructing phylogenetic trees are fundamental to study the evolution of viruses, bacteria, and other microbes. Established multiple alignment-based algorithms are inefficient for large scale metagenomic sequence data because of their high requirement of inter-sequence correlation and high computational complexity. In this paper, we present SeqDistK, a novel tool for alignment-free phylogenetic analysis. SeqDistK computes the dissimilarity matrix for phylogenetic analysis, incorporating seven k-mer based dissimilarity measures, namely d2, d2S, d2star, Euclidean, Manhattan, CVTree, and Chebyshev. Based on these dissimilarities, SeqDistK constructs phylogenetic tree using the Unweighted Pair Group Method with Arithmetic Mean algorithm. Using a golden standard dataset of 16S rRNA and its associated phylogenetic tree, we compared SeqDistK to Muscle - a multi sequence aligner. We found SeqDistK was not only 38 times faster than Muscle in computational efficiency but also more accurate. SeqDistK achieved the smallest symmetric difference between the inferred and ground truth trees with a range between 13 to 18, while that of Muscle was 62. When measures d2, d2star, d2S, Euclidean, and k-mer size k=5 were used, SeqDistK consistently inferred phylogenetic tree almost identical to the ground truth tree. We also performed clustering of 16S rRNA sequences using SeqDistK and found the clustering was highly consistent with known biological taxonomy. Among all the measures, d2S (k=5, M=2) showed the best accuracy as it correctly clustered and classified all sample sequences. In summary, SeqDistK is a novel, fast and accurate alignment-free tool for large-scale phylogenetic analysis. SeqDistK software is freely available at https://github.com/htczero/SeqDistK.


title: Spatial analysis for highly multiplexed imaging data to identify tissue microenvironments

abstract: Highly multiplexed in situ imaging cytometry assays have made it possible to study the spatial organisation of numerous cell types simultaneously. We have addressed the challenge of quantifying complex multi-cellular relationships by proposing a statistical method which clusters local indicators of spatial association. Our approach successfully identifies distinct tissue architectures in datasets generated from three state-of-the-art high-parameter assays demonstrating its value in summarising the information-rich data generated from these technologies.


title: AMPing up the search: An in silico approach to identifying Antimicrobial Peptides (AMPs) with potential anti-biofilm activity

abstract: Antibiotic resistance is a public health threat, and the rise of multidrug-resistant bacteria, including those that form protective biofilms, further compounds this challenge. Antimicrobial peptides (AMPs) have been recognized for their anti-infective properties, including their ability to target processes important for biofilm formation. However, given the vast array of natural and synthetic AMPs, determining potential candidates for anti-biofilm testing is a significant challenge. In this study, we present an in silico approach, based on open-source tools, to identify AMPs with potential anti-biofilm activity. This approach is developed using the sortase-pilin machinery, important for adhesion and biofilm formation, of the multidrug-resistant, biofilm-forming pathogen C. striatum as the target. Using homology modeling, we modeled the structure of the C. striatum sortase C protein, resembling the semi-open lid conformation adopted during pilus biogenesis. Next, we developed a structural library of 5544 natural and synthetic AMPs from sequences in the DRAMP database. From this library, AMPs with known anti-Gram positive activity were filtered, and 100 select AMPs were evaluated for their ability to interact with the sortase C protein using in-silico molecular docking. Based on interacting residues and docking scores, we built a preference scale to categorize candidate AMPs in order of priority for future in vitro and in vivo biofilm studies. The considerations and challenges of our approach, and the resources developed, which includes a search-enabled repository of predicted AMP structures and protein-peptide interaction models relevant to biofilm studies (B-AMP), can be leveraged for similar investigations across other biofilm targets and biofilm-forming pathogens.


title: 2020 BioImage Analysis Survey: Community experiences and needs for the future

abstract:
In this paper, we summarize a global survey of 484 participants of the imaging community, conducted in 2020 through the NIH Center for Open BioImage Analysis (COBA). This 23-question survey covered experience with image analysis, scientific background and demographics, and views and requests from different members of the imaging community. Through open-ended questions we asked the community to provide feedback for the open-source tool developers and tool user groups. The communitys requests for tool developers include general improvement of tool documentation and easy-to-follow tutorials. Respondents encourage tool users to follow the best practices guidelines for imaging and ask their image analysis questions on the Scientific Community Image forum (forum.image.sc). We analyzed the communitys preferred method of learning, based on level of computational proficiency and work description. In general, written step-by-step and video tutorials are preferred methods of learning by the community, followed by interactive webinars and office hours with an expert. There is also enthusiasm for a centralized location online for existing educational resources. The survey results will help the community, especially developers, trainers, and organizations like COBA, decide how to structure and prioritize their efforts.

Impact statementThe Bioimage analysis community consists of software developers, imaging experts, and users, all with different expertise, scientific background, and computational skill levels. The NIH funded Center for Open Bioimage Analysis (COBA) was launched in 2020 to serve the cell biology communitys growing need for sophisticated open-source software and workflows for light microscopy image analysis. This paper shares the result of a COBA survey to assess the most urgent ongoing needs for software and training in the community and provide a helpful resource for software developers working in this domain. Here, we describe the state of open-source bioimage analysis, developers and users requests from the community, and our resulting view of common goals that would serve and strengthen the community to advance imaging science.


title: Analysis of key genes and pathways associated with the pathogenesis of Type 2 diabetes mellitus

abstract: Type 2 diabetes mellitus (T2DM) is the most common endocrine disorder which poses a serious threat to human health. This investigation aimed to screen the candidate genes differentially expressed in T2DM by bioinformatics analysis. The expression profiling by high throughput sequencing of GSE81608 dataset was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network construction and TF-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the diagnostics value and expression of identified hub genes. A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins and metabolism. The top centrality hub genes APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5 and SQSTM1 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network construction and TF-hub gene regulatory network. ROC analysis provide diagnostics value of hub genes. This study identified key genes, signal pathways and therapeutic agents, which might help us, improve our understanding of the mechanisms of HGPS and identify some new therapeutic agents for T2DM.


title: Evaluation of ChIC-based data requires normalization that properly retains signal-to-noise ratios

abstract: Several chromatin immunocleavage-based (ChIC) methods using Tn5 transposase have been developed to profile histone modifications and transcription factors bindings1-5. A recent preprint by Wang et al. raised potential concerns that these methods are prone to open chromatin bias6. While the authors are appreciated for alerting the community for this issue, it has been previously described and discussed by Henikoff and colleagues in the original CUT&Tag paper3,7. However, as described for CUT&Tag3, the signal-to-noise ratio is essential for Tn5-based profiling methods and all antibody-based enrichment assays. Based on this notion, we would like to point out a major analysis issue in Wang et al. that caused a complete loss or dramatic reduction of enrichment at true targets for datasets generated by Tn5-based methods, which in turn artificially enhanced the relative enrichment of potential open chromatin bias. Such analysis issue is caused by distinct background normalizations used towards ChIP-based (chromatin immunoprecipitation) data and Tn5-based data in Wang et al. Only the normalization for Tn5-based data, but not ChIP-seq based data, yielded such effects. Distortion of such signal-to-noise ratio would consequently lead to misleading results.


title: A deep learning-based approach to model anomalous diffusion of membrane proteins: The case of the nicotinic acetylcholine receptor

abstract: We present a concatenated deep-learning multiple neural network system for the analysis of single-molecule trajectories. We apply this machine learning-based analysis to characterize the translational diffusion of the nicotinic acetylcholine receptor at the plasma membrane, experimentally interrogated using superresolution optical microscopy. The receptor protein displays a heterogeneous diffusion behavior that goes beyond the ensemble level, with individual trajectories exhibiting more than one diffusive state, requiring the optimization of the neural networks through a hyperparameter analysis for different numbers of steps and durations, especially for short trajectories (<50 steps) where the accuracy of the models is most sensitive to localization errors. We next use the statistical models to test for Brownian, continuous-time random walk, and fractional Brownian motion, and introduce and implement an additional, two-state model combining Brownian walks and obstructed diffusion mechanisms, enabling us to partition the two-state trajectories into segments, each of which is independently subjected to multiple analysis. The concatenated multi-network system evaluates and selects those physical models that most accurately describe the receptors translational diffusion. We show that the two-state Brownian-obstructed diffusion model can account for the experimentally observed anomalous diffusion (mostly subdiffusive) of the population and the heterogeneous single-molecule behavior, accurately describing the majority (72.5% to 88.7% for -bungarotoxin-labeled receptor and between 73.5% and 90.3% for antibody-labeled molecules) of the experimentally observed trajectories, with only [~]15% of the trajectories fitting to the fractional Brownian motion model.

category: biophysics


title: Let-7b-5p, miR-184, and miR-22-3p: Multianalyte Plasma Biomarkers for NSCLC Diagnosis and for Predicting Resistance to Osimertinib

abstract: Low-dose computed tomography (LDCT) Non-Small Cell Lung (NSCLC) screening is associated with high false-positive rates, leading to unnecessary expensive and invasive follow ups. There is a need for minimally invasive approaches to improve the accuracy of NSCLC diagnosis. Plasma extracellular vesicle (EV) and circulating microRNA (miRNA) have been proposed as cancer screening biomarkers. However, the identification of highly sensitive and broadly predictive core miRNA signatures remains a challenge. Also, how these systemic and diverse miRNAs impact cancer drug response is not well understood. Using an integrative approach, we examined plasma EV and circulating miRNA isolated from NSCLC patients versus screening controls with a similar risk profile. We found that combining EV (Hsa-miR-184, Let-7b-5p) and circulating (Hsa-miR-22-3p) miRNAs abundance robustly discriminates between NSCLC patients and high-risk cancer-free controls. Diagnosed NSCLC patients harboring sensitizing mutations in epidermal growth factor receptor EGFR (T790M, L578R) are treated with Osimertinib, a potent tyrosine kinase inhibitor (TKI). Nearly all patients develop TKI resistance via complex mechanisms and progress. We found that Hsa-miR-22-3p, Hsa-miR-184, and Let-7b-5p functionally converge on WNT/{beta}catenin and mTOR/AKT signaling axes, known cancer therapy resistance signals. Targeting Hsa-miR-22-3p and Hsa-miR-184 desensitized EGFR-mutated (T790M, L578R) NSCLC cells to Osimertinib. These findings suggest that the expression levels of circulating hsa-miR-22-3p combined with EV hsa-miR-184 and Let-7b-5p levels potentially define a core biomarker signature for improving the accuracy of NSCLC diagnosis. Importantly, these biomarkers have the potential to enable prospective identification of patients who are at risk of responding poorly to Osimertinib alone but likely to benefit from Osimertinib/AKT blockade combination treatments.

category: cancer biology


title: Combining Plasma Extracellular Vesicle Let-7b-5p, miR-184 and Circulating miR-22-3p Levels for NSCLC Diagnosis and Drug Resistance Prediction


title: A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology

abstract:
BackgroundImage-based machine learning tools hold great promise for clinical applications in nephropathology and kidney research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often face prohibitive challenges in using these tools to their full potential, including the lack of technical expertise, suboptimal user interface, and limited computation power.

MethodsWe have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis.

ResultsBy segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in murine models of aging, diabetic nephropathy, and HIV associated nephropathy.

ConclusionThe ability to access this tool over the internet will facilitate widespread use by computational non-experts. Histo-Cloud is open source and adaptable for segmentation of any histological structure regardless of stain. Histo-Cloud will greatly accelerate and facilitate the generation of datasets for machine learning in the analysis of kidney histology, empowering computationally novice end-users to conduct deep feature analysis of tissue slides.

category: pathology


title: Leptin Signalling in the Ovary of Diet-Induced Obese Mice Regulates Activation of Nod-Like Receptor Protein 3 Inflammasome

abstract: 1Obesity leads to ovarian dysfunction and the establishment of local leptin resistance. The aim of our study was to characterise levels of Nod-Like Receptor Protein 3 (NLRP3) inflammasome activation during obesity progression in the mouse ovaries and liver and test the putative role of leptin on its regulation. C57BL/6J mice were treated with equine chorionic gonadotropin (eCG) or human chorionic gonadotropin (hCG) for oestrous cycle synchronisation and ovaries collection. In diet-induced obesity (DIO) model, mice were fed chow diet (CD) or high fat diet (HFD) for 4 or 16 weeks (wk), whereas in hyperleptinemic model (LEPT), mice were injected with leptin for 16 days (16L) or saline (16C) and in the genetic obese leptin-deficient ob/ob (+/? and -/-) animals were fed CD for 4wk. Either ovaries and liver were collected, as well as cumulus cells (CCs) after superovulation from DIO and LEPT. In DIO protocol, protein expression of NLRP3 inflammasome components was increased in 4wk HFD, but decreased in 16wk HFD. Moreover LEPT and ob/ob models revealed NLRP3 and IL-1{beta} upregulation in 16L and downregulation in ob/ob. Transcriptome analysis of CC showed common genes between LEPT and 4wk HFD modulating NLRP3 inflammasome. Moreover analysis in the liver showed upregulation of NLRP3 protein only after 16wk HFD, but also the downregulation of NLRP3 protein in ob/ob-/-. We showed the link between leptin signalling and NLRP3 inflammasome activation in the ovary throughout obesity progression in mice, elucidating the molecular mechanisms underpinning ovarian failure in maternal obesity.

category: physiology


title: The dynamic interaction of systemic inflammation and the hypothalamic-pituitary-adrenal (HPA) axis during and after major surgery

abstract: Major surgery and critical illness produce a potentially life threatening systemic inflammatory response. The hypothalamic-pituitary-adrenal (HPA) axis is one of the key physiological systems that counterbalances this systemic inflammation through changes in adrenocorticotrophic hormone (ACTH) and cortisol. These hormones normally exhibit highly correlated ultradian pulsatility with an amplitude modulated by circadian processes. However, these dynamics are disrupted by major surgery and critical illness. In this work, we characterise the inflammatory, ACTH and cortisol responses of patients undergoing cardiac surgery and show that the HPA axis response can be classified into one of three phenotypes: single-pulse, two-pulses and multiple-pulses dynamics. We develop a mathematical model of cortisol secretion and metabolism that predicts the physiological mechanisms responsible for these different phenotypes. We show that the effects of inflammatory mediators are important only in the single-pulse pattern in which normal pulsatility is lost - suggesting that this phenotype could be indicative of the greatest inflammatory response. Investigating whether and how these phenotypes are correlated with clinical outcomes will be critical to patient prognosis and designing interventions to improve recovery.


title: A point mutation in the kinase domain of CRK10 leads to xylem vessel collapse and activates defence responses

abstract: Cysteine-rich receptor-like kinases (CRKs) are a large family of plasma membrane-bound receptors ubiquitous in higher plants. They are transcriptionally regulated by a wide variety of environmental cues and stresses, however their precise biological roles remain largely unknown. Here we report a novel mutant isolated for the CYSTEINE-RICH RECEPTOR-LIKE KINASE 10 (CRK10) of Arabidopsis thaliana which harbours the substitution of alanine 397 by a threonine in the C-helix of its kinase domain and which we registered as crk10-A397T in the community database. In situ phosphorylation assays with the His-tagged wild type (WT) and crk10-A397T versions of the CRK10 kinase domain revealed that both alleles are active kinases capable of auto-phosphorylation with the newly introduced threonine acting as an additional phosphorylation site in crk10-A397T. Phenotypically the mutant is a dwarf and the analysis of thin cross sections with light and transmission electron microscopy revealed that collapsed xylem vessels in roots and hypocotyls are very likely the cause for this reduction in stature. Transcriptomic analysis of WT and mutant hypocotyls revealed that predominantly biotic and abiotic stress-responsive genes are constitutively up-regulated in the mutant. Root-infection assays with the vascular pathogen Fusarium oxysporum demonstrated that the crk10-A397T mutant has enhanced resistance to this pathogen compared to WT plants. Taken together our results suggest that crk10-A397T is a gain-of-function allele of CRK10 and open up new avenues for the investigation of this elusive receptor-like kinase family.

category: plant biology


title: Caracterization of Am -A genomes chromosomes in diploid wheat, polyploid wheat and triticales by marker cytogenetic

abstract: The distribution and the Caracterization of constitutive heterochromatin in A-Am genomes of diploid wheat (progenitor), polyploid wheat (hybrids) and triticales (primary and secondary) are analyzed and compared by C-bands. The Comparison of zones rich in highly repeated DNA sequences marked by C bands on the all chromosomes of Am - A genomes revealed an important structural heterogeneity. Four chromosomes of Triticum monococcum (1Am-3Am-4Am-5Am) are almost similar to their homologues in wheat (Triticum durum, Triticum aestivum) and triticale, by the presence or absence of C bands. Contrary to the chromosomes 2Am (rich in heterochromatin),6Am-7Am (absence of C bands) show a great differentiation compared to their homologues of Triticum durum and Triticum aestivum and x-Triticosecale Wittmack. In the triticales, A genome chromosomes are richer in heterochromatin compared to theirs homologous of polyploid wheats. This is explained by a "genome shock The confrontation of a C-bands genome (Triticum monococcum) with a C+ bands genome (durum wheat / or common wheat) produces an interspecific hybrid which at the sixth generation reveals C+ bands (triticales).The variations observed in our vegetal material indicated the existence of an intervarietal and interspecific heterochromatic polymorphism. The presence of B chromosomes in triticales, could be explained as a manifestation of their adaptation.


title: Hierarchical Bayesian models of transcriptional and translational regulation processes with delays

abstract:
MotivationSimultaneous recordings of gene network dynamics across large populations have revealed that cell characteristics vary considerably even in clonal lines. Inferring the variability of parameters that determine gene dynamics is key to understanding cellular behavior. However, this is complicated by the fact that the outcomes and effects of many reactions are not observable directly. Unobserved reactions can be replaced with time delays to reduce model dimensionality and simplify inference. However, the resulting models are non-Markovian, and require the development of new inference techniques.

ResultsWe propose a non-Markovian, hierarchical Bayesian inference framework for quantifying the variability of cellular processes within and across cells in a population. We illustrate our approach using a delayed birth-death process. In general, a distributed delay model, rather than a popular fixed delay model, is needed for inference, even if only mean reaction delays are of interest. Using in silico and experimental data we show that the proposed hierarchical framework is robust and leads to improved estimates compared to its non-hierarchical counterpart. We apply our method to data obtained using time-lapse microscopy and infer the parameters that describe the dynamics of protein production at the single cell and population level. The mean delays in protein production are larger than previously reported, have a coefficient of variation of around 0.2 across the population, and are not strongly correlated with protein production or growth rates.

AvailabilityAccompanying code in Python is available at https://github.com/mvcortez/Bayesian-Inference.

Contactkresimir.josic@gmail.comkresimir.josic@gmail.com, jaekkim@kaist.ac.kr jaekkim@kaist.ac.kr, cbskust@korea.ac.kr cbskust@korea.ac.kr

category: systems biology


title: Differences in working memory coding of biological motion attributed to oneself and others

abstract: The question how the brain distinguishes between information about oneself and the rest of the world is of fundamental interest to both philosophy and neuroscience. This question can be approached empirically by investigating how associating stimuli with oneself leads to differences in neurocognitive processing. However, little is known about the brain network involved in forming such self-associations for, specifically, bodily stimuli. In this fMRI study, we sought to distinguish the neural substrates of representing a full-body movement as ones movement and as someone elses movement. Participants performed a delayed match-to-sample working memory task where a retained full-body movement (displayed using point-light walkers) was arbitrarily labelled as ones own movement or as performed by someone else. By using arbitrary associations we aimed to address a limitation of previous studies, namely that our own movements are more familiar to us than movements of other people. A searchlight multivariate decoding analysis was used to test where information about types of movement and about self-association was coded. Movement specific activation patterns was found in a network of regions also involved in perceptual processing of movement stimuli, however not in early sensory regions. Information about whether a memorized movement was associated with the self or with another person was found to be coded by activity in the left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), bilateral supplementary motor area, and (at reduced threshold) in the left temporoparietal junction (TPJ). These areas are frequently reported as involved in action understanding (IFG, MFG) and domain-general self/other distinction (TPJ). Finally, in univariate analysis we found that selecting a self-associated movement for retention was related to increased activity in the ventral medial prefrontal cortex.

category: neuroscience


title: Molecular signature and target-specificity of inhibitory circuits formed by Martinotti cells in the mouse barrel cortex

abstract:
In the neocortex, fast synaptic inhibition orchestrates both spontaneous and sensory-evoked activity. GABAergic interneurons (INs) inhibit pyramidal neurons (PNs) directly, modulating their output activity and thus contributing to balance cortical networks. Moreover, several IN subtypes also inhibit other INs, forming specific disinhibitory circuits, which play crucial roles in several cognitive functions. Here, we studied a homogeneous subpopulation of somatostatin (SST)-positive INs, the Martinotti cells (MCs) in layer 2/3 of the mouse barrel cortex (both sexes). MCs are a prominent IN subclass inhibiting the distal portion of PN apical dendrites, thus controlling dendrite electrogenesis and synaptic integration. Yet, it is poorly understood whether MCs inhibit other elements of the cortical circuits, and the connectivity properties with non-PN targets are unknown. We found that MCs have a strong preference for PN dendrites, but they also considerably connect with parvalbumin (PV)-positive, vasoactive intestinal peptide (VIP)-expressing and layer 1 (L1) INs. Remarkably, GABAergic synapses from MCs exhibited clear cell-type-specific short-term plasticity. Moreover, whereas the biophysical properties of MC-PN synapses were consistent with distal dendritic inhibition, MC-IN synapses exhibited characteristics of fast perisomatic inhibition. Finally, MC-PN connections used 5-containing GABAARs, but this subunit was not expressed by the other INs targeted by MCs. We reveal a specialized connectivity blueprint of MCs within different elements of superficial cortical layers. In addition, our results identify 5-GABAARs as the molecular fingerprint of MC-PN dendritic inhibition. This is of critical importance, given the role of 5-GABAARs in cognitive performance and their involvement in several brain diseases.

Significance statementMartinotti cells (MCs) are a prominent subclass of SST-expressing GABAergic INs, specialized in controlling distal dendrites of PNs and taking part in several cognitive functions. Here we characterize the connectivity pattern of MCs with other INs in the superficial layers (L1 and L2/3) of the mouse barrel cortex. We found that the connectivity pattern of MCs with PNs as well as PV, VIP and L1 INs exhibit target-specific plasticity and biophysical properties. The stark specificity of 5-GABAARs at MC-PN synapses, and the lack or functional expression of this subunit by other cell types, define the molecular identity of MC-PN connections and the exclusive involvement of this outstanding inhibitory circuits in 5-dependent cognitive tasks.


title: Functional Connectivity of the World's Protected Areas

abstract: Rapid environmental change threatens to isolate the worlds wildlife populations and intensify biodiversity loss. Global policies have called for expanding and connecting the worlds protected areas (PAs) to curtail the crisis, yet how well PA networks currently support wildlife movement, and where connectivity conservation or restoration is most critical, have never been mapped globally. Here, we map the functional connectivity (how animals move through landscapes) of the worlds terrestrial PAs for the first time. Also, going beyond existing global connectivity indices, we quantify national PA-connectedness using an approach that meaningfully represents animal movement through anthropogenic landscapes. We find that reducing the human footprint may improve national PA-connectivity more than adding new PAs; however, both strategies are critical for improving and preserving connectivity in places where the predicted flow of animal movement is highly concentrated. We show that the majority of critical connectivity areas (CCAs) (defined as globally important areas of concentrated animal movements) remain unprotected. Of these, 72% overlap with previously-identified global conservation priority areas, while 3% of CCAs occur within moderate to heavily modified lands. Conservation and restoration of CCAs could safeguard connectivity of the worlds PAs, and dovetail with previously identified global conservation priorities.

category: ecology


title: Revisiting a classic hybrid zone: rapid movement of the northern flicker hybrid zone in contemporary times

abstract: Natural hybrid zones have provided important insights into the evolutionary process, and their geographic stability/instability over time can help to disentangle the underlying biological processes that maintain them. Here, we leverage replicated sampling of an identical transect across the hybrid zone between yellow-shafted and red-shafted flickers in the Great Plains to assess its stability over [~]60 years (1955-1957 to 2016-2018). We identify a [~]73 km westward shift in the hybrid zone center towards the range of the red-shafted flicker, but find no associated changes in width over our sampling period. In fact, the hybrid zone remains remarkably narrow, suggesting some kind of selective pressure maintains the zone. By comparing to previous work in the same geographic region, it appears likely that the movement in the hybrid zone has occurred rapidly in the years since the early 1980s. This recent, rapid movement may be related to changes in climate or land management practices that have allowed asymmetric westward movement of yellow-shafted flickers into the Great Plains.

category: evolutionary biology


title: Desolvation Energy Explains Partitioning of Client Proteins into Condensates

abstract: Membraneless organelles are cellular compartments that form by liquid-liquid phase separation of one or more components. Other molecules, such as other proteins and nucleic acids, will distribute between the cytoplasm and the liquid compartment in accordance with the thermodynamic drive to lower the free energy of the system. The resulting distribution colocalizes molecular species, to carry out a diversity of functions. Two factors could drive this partitioning: the difference in solvation between the dilute versus dense phase, and intermolecular interactions between the client and scaffold proteins. Here, we develop a set of knowledge-based potentials that allow for the direct comparison between desolvation energy and pairwise interaction energy terms, and use these to examine experimental data from two systems: protein cargo dissolving within phase-separated droplets made from FG repeat proteins of the nuclear pore complex, and client proteins dissolving within phase-separated FUS droplets. We find close agreement between desolvation energies of the client proteins and the experimentally determined values of the partition coefficients, while pairwise interaction energies between client and scaffold show weaker correlations. These results show that client stickiness is sufficient to explain differential partitioning of clients within these two phase-separated systems without taking into account the composition of the condensate. This suggests that selective trafficking of client proteins to distinct membraneless organelles requires recognition elements beyond the client sequence composition.


title: Deep Learning Features Encode Interpretable Morphologies within Histological Images

abstract: Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains difficult. Most studies have considered interpretability in a post hoc fashion, e.g. by presenting example regions with strongly predicted class labels. However, such an approach does not explain the biological features that contribute to correct predictions. To address this problem, here we investigate the interpretability of H&E-derived CNN features (the feature weights in the final layer of a transfer-learning-based architecture), which we show can be construed as abstract morphological genes ("mones") with strong independent associations to biological phenotypes. We observe that many mones are specific to individual cancer types, while others are found in multiple cancers especially from related tissue types. We also observe that mone-mone correlations are strong and robustly preserved across related cancers. Importantly, linear mone-based classifiers can very accurately separate 38 distinct classes (19 tumor types and their adjacent normals, AUC=97.1% {+/-} 2.8% for each class prediction), and linear classifiers are also highly effective for universal tumor detection (AUC=99.2% {+/-} 0.12%). This linearity provides evidence that individual mones or correlated mone clusters may be associated with interpretable histopathological features or other patient characteristics. In particular, the statistical similarity of mones to gene expression values allows integrative mone analysis via expression-based bioinformatics approaches. We observe strong correlations between individual mones and individual gene expression values, notably mones associated with collagen gene expression in ovarian cancer. Mone-expression comparisons also indicate that immunoglobulin expression can be identified using mones in colon adenocarcinoma and that immune activity can be identified across multiple cancer types, and we verify these findings by expert histopathological review. Our work demonstrates that mones provide a morphological H&E decomposition that can be effectively associated with diverse phenotypes, analogous to the interpretability of transcription via gene expression values.


title: Bias in miRNA enrichment analysis related to gene functional annotations

abstract:
BackgroundmiRNA functional enrichment is a type of analysis that is used to predict which biological functions may be affected by a group of miRNAs or validate whether a list of dysregulated miRNAs are linked to a diseased state. The standard method for functional enrichment analysis uses the hypergeometric distribution to produce p-values, depicting the strength of the association between a group of miRNAs and a biological function. However, in 2015, it was shown that this approach suffers from a bias related to miRNA targets produced by target prediction algorithms and a new randomization test was proposed to alleviate this issue.

ResultsWe demonstrate the existence of another previously unreported underlying bias which affects gene annotation data sets; additionally, we show that the statistical measure used for the established randomization test is not sensitive enough to account for it. In this context, we show that the use of Jaccard coefficient (an alternative statistical measure) is able to alleviate the aforementioned issue.

ConclusionsIn this paper, we illustrate the existence of a new bias affecting the miRNA functional enrichment analysis. This bias makes Fishers exact test unsuitable for miRNA functional enrichment analyses and there is also a need to adjust the established unbiased test accordingly. We propose the use of a modified version of the established test and in order to facilitate its use, we introduce a novel unbiased miRNA enrichment analysis tool that implements the proposed method. At the same time, by leveraging bit vectors, our tool guarantees fast and scalable execution.

AvailabilityAll datasets used in the experiments throughout this paper are openly accessible on Zenodo (https://doi.org/10.5281/zenodo.5175819).


title: Molecular Swiss Army Knives: Tardigrade CAHS Proteins Mediate Desiccation Tolerance Through Multiple Mechanisms

abstract: Tardigrades, also known as water bears, make up a phylum of small but extremely hardy animals, renowned for their ability to survive extreme stresses, including desiccation. How tardigrades survive desiccation is one of the enduring mysteries of animal physiology. Here we show that CAHS D, an intrinsically disordered protein belonging to a unique family of proteins possessed only by tardigrades, undergoes a liquid-to-gel phase transition in a concentration dependent manner. Unlike other gelling proteins, such as gelatin, our data support a mechanism in which gel formation of CAHS D is driven by intermolecular {beta}-{beta} interactions. We find that gel formation corresponds with strong coordination of water and slowing of water diffusion. The degree of water coordination correlates with the ability of CAHS D to protect lactate dehydrogenase from unfolding when dried. This implies that the mechanism for unfolding protection can be attributed to a combination of hydration and slowed molecular motion. Conversely, rapid diffusion leading to efficient molecular shielding appears to be the predominant mechanism preventing protein aggregation. Our study demonstrates that distinct mechanisms are required for holistic protection during desiccation, and that protectants, such as CAHS D, can act as molecular  Swiss Army Knives capable of providing protection through several different mechanisms simultaneously.


title: Tardigrade CAHS Proteins Act as Molecular Swiss Army Knives to Mediate Desiccation Tolerance Through Multiple Mechanisms


title: Learning predictive cognitive maps with spiking neurons during behaviour and replays.

abstract: We describe a framework where a biologically plausible spiking neural network mimicking hippocampal layers learns a cognitive map known as the successor representation. We show analytically how, on the algorithmic level, the learning follows the TD({lambda}) algorithm, which emerges from the underlying spike-timing dependent plasticity rule. We then analyze the implications of this framework, uncovering how behavioural activity and experience replays can play complementary roles when learning the representation of the environment, how we can learn relations over behavioural timescales with synaptic plasticity acting on the range of milliseconds, and how the learned representation can be flexibly encoded by allowing state-dependent delay discounting through neuromodulation and altered firing rates.


title: Columnar localization and laminar origin of cortical surface electrical potentials

abstract:
Electrocorticography (ECoG) methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. To address this gap, we recorded from rat auditory cortex using customized ECoG, and simulated cortical surface electrical potentials with a full-scale, biophysically detailed cortical column model. Experimentally, ECoG-derived auditory representations were tonotopically organized and signals were anisotropically localized to [≤]{+/-}200 m, i.e., a single cortical column. Biophysical simulations reproduce experimental findings, and indicate that neurons in cortical layers V and VI contribute [~]85% of evoked high-gamma signal recorded at the surface. Cell number and synchronicity were the primary biophysical properties determining laminar contributions to evoked ECoG signals, while distance was only a minimal factor. Thus, evoked ECoG signals primarily originate from neurons in the infragranular layers of a single cortical column.

In BriefBaratham et al., investigated the localization and origins of sensory evoked ECoG responses. They experimentally found that ECoG responses were anisotropically localized [≤]{+/-}200 m, i.e., a single cortical column. Biophysically detailed simulations revealed that neurons in layers V &VI were the primary sources of evoked ECoG responses, in contrast to common thinking.

HighlightsEvoked ECoG signals are localized on the surface to a cortical column.

Neurons in cortical layers V and VI constitute the vast majority of the signal recorded at the surface.

Different laminar contributions to ECoG signal are driven by cell density and synchronicity.


title: Cervical Spinal Cord Injury Leads to Injury and Metabolic Dysfunction of the Lung

abstract: High-cervical spinal cord injury (SCI) often disrupts respiratory motor pathways and disables breathing in the affected population. Moreover, cervically injured individuals are at risk for developing acute lung injury (ALI), which predicts substantial mortality rates. While the correlation between ALI and SCI has been found in the clinical setting, the field lacks an animal model to interrogate the fundamental biology of this relationship. To begin to address this gap, we performed an experimental cervical SCI and assessed lung injury in adult rats. We demonstrate that animals display signs of ALI two weeks post-SCI. We also observed aberrant N-glycan metabolism determined by matrix-assisted laser desorption/ionization mass spectrometry imaging. Collectively, we establish for the first time a model of ALI after SCI at an acute time point that can be used to monitor the progression of lung damage, as well as identify potential targets to ameliorate ALI.


title: Unique Characterization of Spatiotemporal Neuronal Network Activity

abstract: We prove that three-spike motifs and phase relationships between frequency bands are essential to characterizing spatiotemporal neural activity and, in fact, sufficient. This follows from applying a theorem from optical science to show that all finite neural data have both unique triple (third-order) correlation and unique bispectrum. We simplify triple correlation by classifying three-spike motifs into motif-classes according to their sequencing, which can embody well-studied neural properties such as synchrony, feedback, feedforward, convergence, and divergence. Summing triple correlations within these classes yields a summary revealing structure underlying the neural network data. This simple approach demonstrates the power of complete statistical representations of neural activity. Since these representations generalize across recording modalities, we present our analysis as a potential avenue for investigation throughout the field.


title: Precision engineering of an anti-HLA-A2 chimeric antigen receptor in regulatory T cells for transplant immune tolerance

abstract: Infusion of regulatory T cells (Tregs) engineered with a chimeric antigen receptor (CAR) targeting donor-derived human leukocyte antigen (HLA) is a promising strategy to promote transplant tolerance. Here, we describe an anti-HLA-A2 CAR (A2-CAR) generated by grafting the complementarity-determining regions (CDRs) of a human monoclonal anti-HLA-A2 antibody into the framework regions of the Herceptin 4D5 single-chain variable fragment and fusing it with a CD28-{zeta} signaling domain. The CDR-grafted A2-CAR maintained the specificity of the original antibody. We then generated HLA-A2 mono-specific human CAR Tregs either by deleting the endogenous T-cell receptor (TCR) via CRISPR/Cas9 and introducing the A2-CAR using lentiviral transduction or by directly integrating the CAR construct into the TCR alpha constant locus using homology-directed repair. These A2-CAR+TCRdeficient human Tregs maintained both Treg phenotype and function in vitro. Moreover, they selectively accumulated in HLA-A2-expressing islets transplanted from either HLA-A2 transgenic mice or deceased human donors. A2-CAR+TCRdeficient Tregs did not impair the function of these HLA-A2+ islets, whereas similarly engineered A2-CAR+TCRdeficientCD4+ conventional T cells rejected the islets in less than 2 weeks. A2-CAR+TCRdeficient Tregs delayed graft-versus-host disease only in the presence of HLA-A2, expressed either by co-transferred peripheral blood mononuclear cells or by the recipient mice. Altogether, we demonstrate that genome-engineered mono-antigen-specific A2-CAR Tregs localize to HLA-A2-expressing grafts and exhibit antigen-dependent in vivo suppression, independent of TCR expression. These approaches may be applied towards developing precision Treg cell therapies for transplant tolerance.

category: immunology


title: Stimulation of the Dorsal Root Ganglion using an Injectrode

abstract:
ObjectiveThe goal of this work was to compare afferent fiber recruitment by dorsal root ganglion (DRG) stimulation using an injectable polymer electrode (Injectrode(R)) and a more traditional cylindrical metal electrode.

ApproachWe exposed the L6 and L7 DRG in four cats via a partial laminectomy or burr hole. We stimulated the DRG using an Injectrode or a stainless steel electrode using biphasic pulses at three different pulse widths (80, 150, 300 s) and pulse amplitudes spanning the range used for clinical DRG stimulation. We recorded antidromic evoked compound action potentials (ECAPs) in the sciatic, tibial, and common peroneal nerves using nerve cuffs. We calculated the conduction velocity of the ECAPs and determined the charge-thresholds and recruitment rates for ECAPs from A, A{beta}, and A{delta} fibers. We also performed electrochemical impedance spectroscopy measurements for both electrode types.

Main ResultsThe ECAP thresholds for the Injectrode did not differ from the stainless steel electrode across all primary afferents (A, A{beta}, A{delta}) and pulse widths; charge-thresholds increased with wider pulse widths. Thresholds for generating ECAPs from A{beta} fibers were 100.0 {+/-} 32.3 nC using the stainless steel electrode, and 90.9 {+/-} 42.9 nC using the Injectrode. The ECAP thresholds from the Injectrode were consistent over several hours of stimulation. The rate of recruitment was similar between the Injectrodes and stainless steel electrode and decreased with wider pulse widths.

SignificanceThe Injectrode can effectively excite primary afferents when used for DRG stimulation within the range of parameters used for clinical DRG stimulation. The Injectrode can be implanted through minimally invasive techniques while achieving similar neural activation to conventional electrodes, making it an excellent candidate for future DRG stimulation and neuroprosthetic applications.

category: bioengineering


title: Characterizing Protein Conformational Space Using Robotics-Based Search and Topological Data Analysis

abstract: An essential step to understanding how different functionalities of proteins work is to explore their conformational space. However, because of the fleeting nature of conformational changes in proteins, investigating protein conformational spaces is a challenging task to do experimentally. Nonetheless, computational methods have shown to be practical to explore these conformational pathways. In this work, we use Topological Data Analysis (TDA) methods to evaluate our previously introduced algorithm called RRTMC, that uses a combination of Rapidly-exploring Random Trees algorithm and Monte Carlo criteria to explore these pathways. TDA is used to identify the intermediate conformations that are generated the most by RRTMC and examine how close they are to existing known intermediate conformations. We concluded that the intermediate conformations generated by RRTMC are close to existing experimental data and that TDA can be a helpful tool to analyze protein conformation sampling methods.


title: Using Topological Data Analysis and RRT to Investigate Protein Conformational Spaces


title: Deciphering Rubber Tree Growth Using Network-Based Multi Omics Approaches

abstract: Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.


title: Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches


title: Ten Ostreobium (Ulvophyceae) strains from Great Barrier Reef corals as a resource for algal endolith biology and genomics

abstract: Ostreobium is a genus of siphonous green algae that lives as an endolith in carbonate substrates under extremely limited light conditions and has recently been gaining attention due to its roles in reef carbonate budgets and its association with reef corals. Knowledge about this genus remains fairly limited due to the scarcity of strains available for physiological studies. Here, we report on 10 strains of Ostreobium isolated from coral skeletons from the Great Barrier Reef. Phenotypic diversity showed differences in the gross morphology and in few structures. Phylogenetic analyses of the tufA and rbcL put the strains in the context of the lineages identified previously through environmental sequencing. The chloroplast genomes of our strains are all around 80k bp in length and show that genome structure is highly conserved, with only a few insertions (some containing putative protein-coding genes) differing between the strains. The addition of these strains from the Great Barrier Reef to our toolkit will help develop Ostreobium as a model species for endolithic growth, low-light photosynthesis and coral-algal associations.

category: genetics


title: Application of components analysis in dynamic thermal breast imaging to identify pathophysiologic mechanisms of heat transfer

abstract:
SignificanceOf the most compelling unsolved issues in the paradigm to create success in the field of breast cancer infrared imaging is localization of direct internal heat of the tumor. The contribution of differential heat production related to metabolism versus perfusion is not understood. Previous work until now has not shown progress beyond identifying veins which are fed by the  hot cancer. Employing signal analysis techniques, we probe important questions which may lead to further understanding pathophysiology of heat transfer occurring in the setting of malignancy.

AimWhen using thermal imaging to detect breast cancer, the dominant heat signature is that of indirect heat transported in gradient away from the tumor location. Unprocessed images strikingly display vasculature which acts to direct excess heat superficially towards the skin surface before dissipating. In current clinical use, interpretation of thermogram images considers abnormal vascular patterns and overall temperature as indicators of disease. The goal of this work is to present a processing method for dynamic external stimulus thermogram images to isolate and separate the indirect vascular heat while revealing the desired direct heat from the tumor.

ApproachIn dynamic thermal imaging of the breast, a timed series of images are taken following application of external temperature stimulus (most often cooled air). While the tumor heat response is thought to be independent of the external stimulus, the secondary heat of the veins is known to be affected by vasomodulation. The recorded data is analyzed using independent component analysis (ICA) and principal component analysis (PCA) methods. ICA separates the image sequence into new independent images having a common characteristic time behavior. Resulting individual components are analyzed for correspondence to the presence or lack of vasomodulation.

ResultsUsing the Brazilian visual lab mastology data set containing dynamic thermograms, applying components analysis resulted in three corresponding images: 1. Minimum change as a function of applied temperature or time (suggests correlation with the cancer generated heat), 2. Moderate temperature dependence (suggests correlation with veins affected by vasomodulation) and 3. Complex time behavior (suggests correlation with heat absorption due to high tumor perfusion). All components appear clear and distinct.

ConclusionsApplying signal processing methods to the dynamic infrared data, we found three distinct components with correspondence to understood physiologic processes. The two cases shown are self-evident of the capability of the method but are lacking supporting ground truth that is unavailable with such a limited data set. Validation of this proposed paradigm and studying furthering clinical applications has potential to create significant achievement for IR modality in diagnostic imaging.


title: Circulating microRNAs as noninvasive biomarkers for canine Cushing's syndrome

abstract:
Canine Cushings syndrome (hypercortisolism) can be caused by a pituitary tumor (pituitary-dependent hypercortisolism; PDH) or a cortisol-secreting adrenocortical tumor (csACT). For both cases, noninvasive biomarkers that could pre-operatively predict the risk of recurrence after surgery would greatly impact clinical decision making. The aim of this study was to determine whether circulating microRNAs (miRNAs) can be used as noninvasive biomarkers for canine Cushings syndrome.

After a pilot study with 40 miRNAs in blood samples of healthy dogs (n = 3), dogs with PDH (n = 3) and dogs with a csACT (n = 4), we selected a total of 20 miRNAs for the definitive study. In the definitive study, these 20 miRNAs were analyzed in blood samples of healthy dogs (n = 6), dogs with PDH (n = 19, pre-and post-operative samples) and dogs with a csACT (n = 26, pre-operative samples).

In dogs with PDH, six miRNAs (miR-122-5p, miR-126-5p, miR-141-3p, miR-222-3p, miR-375-3p and miR-483-3p) were differentially expressed compared to healthy dogs. Of one miRNA, miR-122-5p, the expression levels did not overlap between healthy dogs and dogs with PDH (p = 2.9x10-4), significantly decreased after hypophysectomy (p = 0.013), and were significantly higher (p = 0.017) in dogs with recurrence (n = 3) than in dogs without recurrence for at least one year after hypophysectomy (n = 7). In dogs with csACTs, two miRNAs (miR-483-3p and miR-223-3p) were differentially expressed compared to healthy dogs. Additionally, miR-141-3p was expressed significantly lower (p = 0.009) in dogs with csACTs that had a histopathological Utrecht score of [≥] 11 compared to those with a score of < 11.

These results indicate that circulating miRNAs have the potential to be noninvasive biomarkers in dogs with Cushings syndrome that may contribute to clinical decision-making.


title: Food interactions observed in a pharmacokinetic investigation comparing two marketed cold preparations (BNO1016 and ELOM-080) after administration to male beagle dogs

abstract: The cold remedies Sinupret extract (BNO 1016) and Gelomyrtol forte (ELOM-080) represent the two top-selling cold remedies in Germany nowadays. Whereas BNO 1016 is a typical immediate release coated tablet, ELOM-080 is an enteric-coated soft gelatin capsule. The latter formulation, however, is at risk of pharmacokinetic interactions affecting absorption especially in the case of concomitant food intake. In the present pilot study, we investigated the risk of a possible food effect on BNO 1016 in comparison to ELOM-080 in three male beagle dogs. Single doses of BNO 1016 and ELOM-80 at 80 mg/kg and 160 mg/kg, respectively, were administered under fasting and fed conditions according to a 4-period, 4-treatment within-design. Blood sampling took place until up to 30 h p.a. and plasma concentrations of gentiopicroside, verbenalin and from a further marker analyte (BNO 1016 analytes) as well as 1,8-cineole, limonene and perillic acid (ELOM-080 analytes) were determined. Pharmacokinetic parameters focusing on rate and extent of absorption were derived. BNO 1016 analytes demonstrated a homogenous course in all animals in both, the fasted and fed state. Pharmacokinetic characteristics of a typical immediate release drug formulation were observed for all analytes and a food effect could be ruled out. ELOM-080 analytes also showed a homogeneous picture in the fasted state. However, lag-times (tlag) of up to 2 h p.a. with corresponding tmax values of 3 to 4 h were observed, reflecting a longer gastric residence time of the formulation. In the fed state, ELOM-080 showed significant pharmacokinetic characteristics suggesting a clear food effect. A major observation was a double peak phenomenon that could be observed in two out of three dogs. Furthermore, lag-times of some analytes up to 3-4 h and corresponding tmax values of up to 6-8 h occurred. In contrast to BNO 1016, these findings suggest that, as with other enteric-coated formulations, there may be a significant risk for food effects with ELOM-080 also in humans.

category: pharmacology and toxicology


title: Skin stem cells orchestrate de novo generation of extrathymic regulatory T cells to establish a temporary protective niche during wound healing

abstract: Adult stem cells reside in various tissues to govern homeostasis and repair damage. During wound healing, these stem cells must be mobilized to enter the center of the injury where they are exposed to many inflammatory immune cells infiltrating the wounded tissue. While these immune cells are indispensable for preventing infections and clearing dead cells, they can also create a harsh inflammatory environment which could potentially damage the stem cells and prevent their self-renewal and differentiation. Here, using a model of cutaneous wound healing in which hair follicle stem cells (HFSCs) repair the wound, we show that, upon migrating into the wound, skin stem cells acquire a strong immune modulatory capacity which allows them to sculpt a temporary immune suppressive niche for self-protection. We reveal that the HFSCs in the wound bed orchestrate extrathymic differentiation of regulatory T (Treg) cells by providing co-stimulation to the woundinfiltrating CD4 effector T cells. In this way, Treg cells can be generated de novo in close proximity to and can intimately protect HFSCs from the collateral damage inflicted by inflammatory neutrophils. This study uncovered a striking inflammatory adaptation capacity unique to adult tissue stem cells which allows them to shape their own immune suppressive niche during wound repair.


title: The clinical utility of two high-throughput 16S rRNA gene sequencing workflows for taxonomic assignment of unidentifiable bacterial pathogens in MALDI-TOF MS

abstract: Bacterial pathogens that cannot be identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) are occasionally encountered in clinical laboratories. The 16S rRNA gene is often used for sequence-based analysis to identify these bacterial species. Nevertheless, traditional Sanger sequencing is laborious, time-consuming and low-throughput. Here, we compared two commercially available 16S rRNA gene sequencing tests, which are based on Illumina and Nanopore sequencing technologies, respectively, in their ability to identify the species of 172 clinical isolates that failed to be identified by MALDI-TOF MS. Sequencing data were analyzed by respective built-in analysis programs (MiSeq Reporter Software and Epi2me) and BLAST+ (v2.11.0). Their agreement with Sanger sequencing on species-level identification was determined. Discrepancies were resolved by whole-genome sequencing. The diagnostic accuracy of each workflow was determined using the composite sequencing result as the reference standard. Despite the high base-calling accuracy of Illumina sequencing, we demonstrated that the Nanopore workflow had a comparatively higher taxonomic resolution at the species level. Using built-in analysis algorithms, the concordance of Sanger 16S with the Illumina and Nanopore workflows was 33.14% and 87.79%, respectively. The agreement was 65.70% and 83.14%, respectively, when BLAST+ was used for analysis. Compared with the reference standard, the diagnostic accuracy of optimized Nanopore 16S was 96.36%, which was identical to Sanger 16S and was better than Illumina 16S (71.52%). The turnaround time of the Illumina workflow and the Nanopore workflow was 78h and 8.25h, respectively. The per-sample cost of the Illumina and Nanopore workflows was US$28.5 and US$17.7, respectively.

category: microbiology


title: Inhibitors of anti-apoptotic Bcl-2 family proteins exhibit potent and broad-spectrum anti-mammarenavirus activity via cell cycle arrest at G0/G1 phase

abstract:
Targeting host factors is a promising strategy to develop broad-spectrum antiviral drugs. Drugs targeting anti-apoptotic Bcl-2 family proteins that were originally developed as tumor suppressors have been reported to inhibit multiplication of different types of viruses. However, the mechanisms whereby Bcl-2 inhibitors exert their antiviral activity remain poorly understood. In this study, we have investigated the mechanisms by which obatoclax (OLX) and ABT-737 Bcl-2 inhibitors exhibited a potent antiviral activity against the mammarenavirus lymphocytic choriomeningitis virus (LCMV). OLX and ABT-737 potent anti-LCMV activity was not associated with their pro-apoptotic properties, but rather their ability of inducing cell arrest at G0/G1 phase. OLX and ABT-737 mediated inhibition of Bcl-2 correlated with reduced expression levels of thymidine kinase 1 (TK1), cyclin A2 (CCNA2), and cyclin B1 (CCNB1) cell cycle regulators. In addition, siRNA-mediated knock down of TK1, CCNA2, and CCNB1 resulted in reduced levels of LCMV multiplication. The antiviral activity exerted by Bcl-2 inhibitors correlated with reduced levels of viral RNA synthesis at early times of infection. Importantly, ABT-737 exhibited moderate efficacy in a mouse model of LCMV infection, and Bcl-2 inhibitors displayed broad-spectrum antiviral activities against different mammarenaviruses and SARS-CoV-2. Our results suggest that Bcl-2 inhibitors, actively being explored as anti-cancer therapeutics, might be repositioned as broad-spectrum antivirals.

IMPORTANCEAnti-apoptotic Bcl-2 inhibitors have been shown to exert potent antiviral activities against various types of viruses via mechanisms that are currently poorly understood. This study has revealed that Bcl-2 inhibitors mediated cell cycle arrest at the G0/G1 phase, rather than their pro-apoptotic activity, plays a critical role in blocking mammarenavirus multiplication in cultured cells. In addition, we show that Bcl-2 inhibitor ABT-737 exhibited moderate anti-mammarenavirus activity in vivo, and that Bcl-2 inhibitors displayed broad-spectrum antiviral activities against different mammarenaviruses and SARS-CoV-2. Our results suggest that Bcl-2 inhibitors, actively being explored as anti-cancer therapeutics, might be repositioned as broad-spectrum antivirals.


title: Usutu virus uses langerin as a receptor to productively infect Langerhans cells more efficiently than West Nile virus.

abstract:
Usutu virus (USUV) and West Nile virus (WNV) are phylogenetically close emerging arboviruses transmitted by mosquitoes, and constitute a global public health threat. Since USUV and WNV enter the body through the skin, the first immune cells they encounter are skin-resident dendritic cells, the most peripheral outpost of immune defense. This unique network is composed of Langerhans cells (LCs) and dermal DCs, which reside in the epidermis and the dermis, respectively.

Using human skin explants, we show that while both viruses can replicate in keratinocytes, they can also infect resident DCs with distinct tropism, since WNV preferentially infects DCs in the dermis, whereas USUV has a greater propensity to infect LCs. Using both purified human epidermal LCs (eLCs) and monocyte derived LCs (MoLCs), we confirm that LCs sustain a faster and more efficient replication of USUV compared with WNV and that this correlates with a more intense innate immune response to USUV compared with WNV. Next, we show that ectopic expression of the LC-specific C-type lectin receptor (CLR), langerin, in HEK293T cells allows WNV and USUV to bind and enter, but supports the subsequent replication of USUV only. Conversely, blocking or silencing langerin in MoLCs or eLCs made them resistant to USUV infection, thus demonstrating that USUV uses langerin to enter and replicate in LCs. Altogether, our results demonstrate that LCs constitute privileged target cells for USUV in human skin, because langerin favors its entry and replication. Intriguingly, this suggests that USUV efficiently escapes the antiviral functions of langerin, which normally safeguards LCs from most viral infections.


title: Usutu virus escapes langerin-induced restriction to productively infect human Langerhans cells, unlike West Nile virus.


title: Core Protein-Directed Antivirals and Importinβ Can Synergistically Disrupt HBV Capsids

abstract:
Viral structural proteins can have multiple activities. Antivirals that target structural proteins have potential to exhibit multiple antiviral mechanisms. Hepatitis B Virus (HBV) core protein (Cp) is involved in most stages of the viral lifecycle: it assembles into capsids, packages viral RNA, is a metabolic compartment for reverse transcription, interacts with nuclear trafficking machinery, and disassembles to release the viral genome into the nucleus. During nuclear localization, HBV capsids bind to host importins (e.g. Imp{beta}) via Cps C-terminal domain (CTD); the CTD is localized to the interior of the capsid and is transiently exposed on the exterior. We used HAP12 as a representative Cp Allosteric Modulators (CpAMs), a class of antivirals that inappropriately stimulates and misdirects HBV assembly and deforms capsids. CpAM impact on other aspects of the HBV lifecycle is poorly understood. We investigated how HAP12 influenced the interactions between empty or RNA-filled capsids with Imp{beta} and trypsin in vitro. We showed that HAP12 can modulate CTD accessibility and capsid stability, depending on the saturation of HAP12-binding sites. We demonstrated that Imp{beta} synergistically contributes to capsid disruption at high levels of HAP12 saturation, using electron microscopy to visualize disruption and rearrangement of Cp dimers into aberrant complexes. However, RNA-filled capsids resisted the destabilizing effects of HAP12 and Imp{beta}. In summary, we show host protein-induced catalysis of capsid disruption, an unexpected additional mechanism of action for CpAMs. Potentially, untimely capsid disassembly can hamper the HBV lifecycle and also cause the virus to become vulnerable to host innate immune responses.

IMPORTANCEThe HBV core, an icosahedral complex of 120 copies of the homodimeric core (capsid) protein with or without packaged nucleic acid, is transported to the host nucleus by its interaction with host importin proteins. Importin-core interaction requires the core protein C-terminal domain, which is inside the capsid, to "flip" to the capsid exterior. Core-protein directed drugs that affect capsid assembly and stability have been developed recently. We show that these molecules can, synergistically with importins, disrupt capsids. This mechanism of action, synergism with host protein, has potential to disrupt the virus lifecycle and activate the innate immune system.


title: Tuning levels of low-complexity domain interactions to modulate endogenous oncogenic transcription

abstract: Gene activation by mammalian transcription factors (TFs) requires dynamic, multivalent, and selective interactions of their intrinsically disordered low-complexity domains (LCDs), but how such interactions mediate transcription remains unclear. It has been proposed that extensive LCD-LCD interactions culminating in liquid-liquid phase separation (LLPS) of TFs is the dominant mechanism underlying transactivation. Here, we investigated how tuning the amount and localization of LCD-LCD interactions in vivo affects transcription of endogenous human genes. Quantitative single-cell and single-molecule imaging reveals that the oncogenic TF EWS/FLI1 requires a finely tuned range of LCD-LCD interactions to efficiently activate target genes. Modest or more dramatic increases in LCD-LCD interactions toward putative LLPS repress EWS/FLI1-driven transcription in patient cells. Likewise, ectopically creating LCD-LCD interactions to sequester EWS/FLI1 into a bona fide LLPS compartment, the nucleolus, inhibits EWS/FLI1-driven transcription and oncogenic transformation. Our findings reveal fundamental principles underlying LCD-mediated transcription and suggest mislocalizing specific LCD-LCD interactions as a novel therapeutic strategy for targeting disease-causing TFs.

category: molecular biology


title: SNARE-dependent mitochondria-lysosome contacts regulate glial mitochondrial dynamics and dopaminergic neuron survival

abstract: Mitochondria are dynamic organelles that undergo fission and fusion, enabling swift structural modification to adapt cellular needs. Disturbances in mitochondrial dynamics, frequently defects ascribed to neurons, have been associated with pathological contexts such as neurodegeneration in Parkinsons disease. Nonetheless, the mechanism of glial mitochondrial dynamics contributing to neurodegeneration remains unclear. Here we present evidence that the Drosophila R-SNARE VAMP7 regulates glial mitochondrial dynamics and dopaminergic neuron survival via modulating the dynamic of mitochondria-lysosome contact, which determines the mitochondrial fission site. Independent of its characterized role in autophagosome-lysosome fusion, glial VAMP7 depletion causes mitochondrial elongation and dysfunction, increased ROS levels, and production of lipid droplets. These conferred changes in glia in turn affects nearby dopaminergic neuron survival. Glial VAMP7 genetically interacts with the mitochondrial fission/fusion factors Drp1 and Marf1 and controls glial mitochondrial dynamics via regulating the frequency and duration of mitochondria-lysosome contact. Our findings indicate that SNARE proteins, although not direct mediators on mitochondrial fusion, provide spatial cues to modulate glial mitochondrial fission via organelle contacts, impacting on neuron survival in a non-cell-autonomous manner.

category: cell biology


title: Reciprocal regulation of p21 and Chk1 controls the Cyclin D1-RB pathway to mediate senescence onset after DNA damage-induced G2 arrest

abstract: Senescence is an irreversible proliferation withdrawal that can be initiated after DNA damage-induced cell cycle arrest in G2 phase to prevent genomic instability. Senescence onset in G2 is not well understood; it requires p53 and RB family tumour suppressors, but how they are regulated to convert a temporary cell cycle arrest into a permanent one remains unknown. Here, we show that a previously unrecognised balance between the CDK inhibitor p21 and Chk1 controls D-type cyclin-CDK activity during G2 arrest. In non-transformed cells, p21 activates RB in G2 by inhibiting Cyclin D1-CDK2/CDK4. The resulting G2 exit, which precedes appearance of senescence markers, is associated with a mitotic bypass, Chk1 inhibition and DNA damage foci reduction. In p53/RB-proficient cancer cells, compromised G2 exit correlates with sustained Chk1 activity, delayed p21 induction, untimely Cyclin E1 re-expression and genome reduplication. Chk1 depletion promotes cell cycle exit by inducing p21 binding to Cyclin D1 and Cyclin E1-CDK complexes and down-regulating CDK6, whereas Chk2 knockdown promotes RB phosphorylation and delays G2 exit. In conclusion, p21 and Chk2 oppose Chk1 to maintain RB activity, thus controlling DNA damage-induced senescence onset in G2.


title: Identification of INSR protein structural differences in Diabetes Mellitus type 2 subjects from protein sequences

abstract: In this paper, we constructed several models of the Insulin Receptor protein(abbreviated INSR) from protein sequences from pathogenic and benign variants of type 2 Diabetes Mellitus patients. Through modeling these variants, we were able to determine which sections of the tertiary structure of the INSR protein were linked to type 2 Diabetes Mellitus. Ultimately, we created a map of the INSR protein and indicated which parts of the protein structure had significant effects on type 2 Diabetes Mellitus. We concluded differences in the charged/polar amino acids on the lower right section of the structure(amino acid numbers 487 and 750) were associated with pathogenic variants, while charged/polar differences on the lower left of the structure(amino acid numbers 669 and 784) had no impact on pathogenicity. We observed several differences in the amino acid chain structure, however they were not unique to the pathogenic variants; they were also seen in the benign variants.

category: biochemistry


title: Specific length and structure rather than high thermodynamic stability enable regulatory mRNA stem-loops to pause translation

abstract: Translating ribosomes unwind mRNA secondary structures by three basepairs each elongation cycle. Despite the ribosome helicase, certain mRNA stem-loops stimulate programmed ribosomal frameshift by inhibiting translation elongation. Here, using mutagenesis, biochemical and single-molecule experiments, we examine whether high stability of three basepairs, which are unwound by the translating ribosome, is critical for inducing ribosome pauses. We find that encountering frameshift-inducing mRNA stem-loops from the E. coli dnaX mRNA and the gag-pol transcript of Human Immunodeficiency Virus (HIV) hinders A-site tRNA binding and slows down ribosome translocation by 15-20 folds. By contrast, unwinding of first three basepairs adjacent to the mRNA entry channel slows down the translating ribosome by only 2-3 folds. Rather than high thermodynamic stability, specific length and structure enable regulatory mRNA stem-loops to stall translation by forming inhibitory interactions with the ribosome. Our data provide the basis for rationalizing transcriptome-wide studies of translation and searching for novel regulatory mRNA stem-loops.


title: Use of the Azure Kinect to measure foot clearance during obstacle crossing

abstract: Obstacle crossing is a typical adaptive locomotion known to be related to the risk of falls. Previous conventional studies have used elaborate and costly optical motion capture systems, which not only represent a considerable expense but also require participants to visit a laboratory. To overcome these shortcomings, we aimed to develop a practical and inexpensive solution for measuring obstacle-crossing behavior by using the Microsoft Azure Kinect, one of the most promising markerless motion capture systems. We validated the Azure Kinect as a tool to measure foot clearance and compared its performance to that of an optical motion capture system (Qualisys). We also determined the effect of the Kinect sensor placement on measurement performance. Sixteen healthy young men crossed obstacles of different heights (50, 150, and 250 mm). Kinect sensors were placed in front of and beside the obstacle as well as diagonally between those positions. As indices of measurement quality, we counted the number of measurement failures and calculated the systematic and random errors between the foot clearance measured by the Kinect and Qualisys. We also calculated the Pearson correlation coefficients between the Kinect and Qualisys measurements. The number of measurement failures and the systematic and random error were minimized when the Kinect was placed diagonally in front of the obstacle on the same side as the trail limb. The high correlation coefficient (r > 0.890) observed between the Kinect and Qualisys measurements suggests that the Azure Kinect has excellent potential for measuring foot clearance during obstacle-crossing tasks.


title: DeepANIS: Predicting antibody paratope from concatenated CDR sequences by integrating bidirectional long-short-term memory and transformer neural networks

abstract:
MotivationAntibodies are a type of important biomolecules in the humoral immunity system, which can bind tightly to potential antigens with high affinity and specificity. An accurate identification of the paratope, the binding sites with antigens, is crucial for antibody mechanistic research and design. Although many methods have been developed for paratope prediction, further improvement of their accuracy is necessary.

ResultsIn this study, we concatenated the sequences of Complementarity Determining Regions (CDRs) within a single antibody to better capture nonlocal interactions between different CDRs and loop type-specific features for improving paratope prediction. We further integrated BiLSTM and transformer networks to gain the dependencies among the residues within the concatenated CDR sequences and to increase the interpretability of the model. The new method called DeepANIS (Antibody Interacting Site prediction) outperforms other antibody paratope prediction methods compared.

AvailabilityThe DeepANIS method is freely available as a webserver at https://biomed.nscc-gz.cn:9094/apps/DeepANIS and for download at https://github.com/HideInDust/DeepANIS

Contactyangyd25@mail.sysu.edu.cn or zhouyq@szbl.ac.cn

Supplementary informationSupplementary data are available at Bioinformatics online.

category: bioinformatics


title: Carbon isotope composition for agronomic diagnostic: predicting yield and yield response to nitrogen in wheat

abstract: Rainfed crops rely on two sources of water: stored soil water at sowing and seasonal rain. In strongly seasonal winter-rainfall environments, stored soil water at sowing is minor, and uncertain seasonal rainfall is a source of risk. In south-eastern Australia, under-fertilisation is a common outcome of nitrogen risk management with implications for yield and soil mining. Here we explore the use of carbon isotope composition ({delta} 13C) to capture the effects of water in the prediction of yield and guide nitrogen management. In the sampled environment, crops receive at least 50% of seasonal rainfall by stem elongation, and at least 70% of seasonal rainfall by flowering. In a sample of 1518 plots, yield varied from 0.07 to 9.96 t ha-1 and correlated with {delta} 13C measured with isotope ratio mass spectrometer (IRMS) at flowering; this is consistent with the rainfall pattern and the physiology of the crop featuring a critical period for yield from 300 {degrees}Cd before to 100 {degrees}Cd after anthesis. In a sample of 135 plots, yield varied from 1.2 to 8.4 t ha-1 and correlated with {delta} 13C measured with IRMS at stem elongation. Yield response to nitrogen, defined as the difference between yield in fertilised crops (50 to 200 kg N ha-1) and unfertilised controls, correlated with {delta} 13C measured with IRMS at stem elongation, except for late-sown crops. Mid-infrared spectroscopy (MIR) returned estimates of {delta} 13C that agreed with {delta} 13C measured with IRMS (calibration: R2 = 0.82, RMSE = 0.53{per thousand}, n = 833; validation: R2 = 0.70, RMSE = 0.75{per thousand}, n = 364). We conclude that a MIR based, high-throughput, affordable measurement of {delta} 13C could be scaled to guide nitrogen management of wheat in winter-rainfall environments.


title: Spatiotemporally Resolved Multivariate Pattern Analysis for M/EEG

abstract:
An emerging goal in neuroscience is tracking what information is represented in brain activity over time as a participant completes some task. Whilst EEG and MEG offer millisecond temporal resolution of how activity patterns emerge and evolve, standard decoding methods present significant barriers to interpretability as they obscure the underlying spatial and temporal activity patterns. We instead propose the use of a generative encoding model framework that simultaneously infers the multivariate spatial patterns of activity and the variable timing at which these patterns emerge on individual trials. An encoding model inversion allows predictions to be made about unseen test data in the same way as in standard decoding methodology. These SpatioTemporally Resolved MVPA (STRM) models can be flexibly applied to a wide variety of experimental paradigms, including classification and regression tasks. We show that these models provide insightful maps of the activity driving predictive accuracy metrics; demonstrate behaviourally meaningful variation in the timing of pattern emergence on individual trials; and achieve predictive accuracies that are either equivalent or surpass those achieved by more widely used methods. This provides a new avenue for investigating the brains representational dynamics and could ultimately support more flexible experimental designs in future.

HIGHLIGHTSO_LIWe introduce SpatioTemporally Resolved MVPA (STRM), an approach that explicitly models how successive stages of stimulus processing are distributed in both space and time in M/EEG data.
C_LIO_LIWe show that STRM is broadly applicable to diverse types of M/EEG data and outputs meaningful and interpretable maps of how neural representations evolve in space and time at millisecond resolution.
C_LIO_LIThe trial-specific deviations in activity pattern timings identified by STRM are not random, but vary systematically with inter-trial differences in behavioural, cognitive and physiological variables.
C_LIO_LIThese methods result in predictive accuracy metrics that are mostly equivalent to, or a modest improvement on, conventional methods.
C_LI


title: Complexity of brain dynamics as a correlate of consciousness in anaesthetized monkeys

abstract: The use of anaesthesia is a fundamental tool in the investigation of consciousness. Anesthesia procedures allow to investigate different states of consciousness from sedation to deep anesthesia within controlled scenarios. In this study we use information quantifiers to measure the complexity of electrocorticogram recordings in monkeys. We apply these metrics to compare different stages of general anesthesia for evaluating consciousness in several anesthesia protocols. We find that the complexity of brain activity can be used as a correlate of consciousness. For two of the anaesthetics used, propofol and medetomidine, we find that the anaesthetised state is accompanied by a reduction in the complexity of brain activity. On the other hand we observe that use of ketamine produces an increase in complexity measurements. We relate this observation with increase activity within certain brain regions associated with the ketamine used doses. Our measurements indicate that complexity of brain activity is a good indicator for a general evaluation of different levels of consciousness awareness, both in anesthetized and non anesthetizes states.


title: The role of visual experience in brain inter-individual variability

abstract:
Visual cortex organization is highly consistent across individuals. But to what degree does this consistency depend on life experience, in particular sensory experience? In this study, we asked whether visual cortex reorganization in congenital blindness results in connectivity patterns that are particularly variable across individuals, focusing on resting-state functional connectivity (RSFC) patterns from primary visual cortex. We show that the absence of shared visual experience results in more-variable RSFC patterns across blind individuals than sighted controls. Increased variability is specifically found in areas that show a group difference between the blind and sighted in their RSFC. These findings reveal a relationship between brain plasticity and individual variability in which reorganization manifests variably across individuals. We further investigated the different patterns of reorganization in the blind, showing that the connectivity to frontal regions, proposed to have a role in reorganization of the visual cortex of the blind towards higher cognitive roles, is highly variable. In a supplementary analysis, we link some of the variability in visual-to-frontal connectivity to another environmental factor - duration of formal education. Together, these findings show a role of sensory and socioeconomic experience in imposing consistency on brain organization. By revealing the idiosyncratic nature of neural reorganization, these findings highlight the importance of considering individual differences in fitting sensory aids and restoration approaches for vision loss.

Significance statementThe typical visual system is highly consistent across individuals. What are the origins of this consistency? Comparing the consistency of visual cortex connectivity between people born blind and sighted people, we showed that blindness results in higher variability, suggesting a key impact of individual experience on brain organization. Further, connectivity patterns that changed following blindness were particularly variable, resulting in diverse patterns of brain reorganization. Individual differences in reorganization were also directly affected by non-visual experiences in the blind (years of formal education). Together, these findings show a role of sensory and socioeconomic experiences in creating individual differences in brain organization and endorse the use of individual profiles for rehabilitation and restoration of vision loss.


title: ExSTED microscopy reveals contrasting functions of dopamine and somatostatin CSF-c neurons along the central canal

abstract:
The spatial location of cerebrospinal fluid contacting (CSF-c) neurons enables important regulatory homeostatic functions regarding pH and motion control. Their intricate organization, facing the central canal and extending across the spinal cord, in relation to specific subtypes is poorly understood. This calls for imaging methods with a high spatial resolution (5-10 nm) to resolve the synaptic and ciliary compartments of each individual cell to elucidate their signalling pathways and enough throughput to dissect the cellular organization. Here, light-sheet and expansion microscopy resolved the persistent ventral and lateral organization of dopamine and somatostatin CSF-c neuronal types.

The number of somatostatin-containing dense core vesicles, resolved by STED microscopy, was shown to be markedly reduced upon each exposure to alkaline or acidic pH inhibiting any movement as part of a homeostatic response. Their cilia symmetry was unravelled by ExSTED as sensory in contrast with the motile one found in the dopaminergic ph insensitive neurons. This novel experimental workflow elucidates the functional role of CSF-c neuron subtypes in situ paving the way for further spatial and functional cell type classification.


title: A two-staged bacterial process coupling methanotrophic and heterotrophic bacteria for 1-alkene production from methane

abstract: Methane (CH4) is a sustainable carbon feedstock source for aerobic CH4-oxidizing bacteria (methanotrophs) to produce value-added chemicals. Under substrate-limited (e.g., CH4, oxygen and nitrogen) conditions, CH4 oxidation results in the production of various short-chain organic acids and platform chemicals. These CH4-derived products could be broadened by utilizing them as a feedstock for heterotrophic bacteria. As a proof of concept, a two-stage system for CH4 abatement and 1-alkene production was developed in this study. Types I and II methanotrophs, i.e., Methylobacter tundripaludum SV96 and Methylocystis rosea SV97, respectively, were investigated in batch tests under different CH4 and air supplementation schemes. CH4 oxidation under either microaerobic or aerobic conditions induced the production of formate, acetate, succinate, and malate in M. tundripaludum SV96, accounting for 4.8-7.0% of consumed CH4-carbon while M. rosea SV97 produced the same compounds except for malate, and with lower efficiency than M. tundripaludum SV96, accounting for 0.7-1.8% of consumed CH4-carbon For the first time, the organic acids-rich spent media of methanotrophs were successfully used for 1-alkene production using engineered Acinetobacter baylyi ADP1  tesA-undA cells. The highest yield of 1-undecene was obtained from spent medium of M. tundripaludum SV96 at 68.9 {+/-} 11.6 mol mol Csubstrate-1.


title: Batch experiments demonstrating a two-stage bacterial process coupling methanotrophic and heterotrophic bacteria for 1-alkene production from methane