title: Species-resolved sequencing of low-biomass microbiomes by 2bRAD-M

abstract: Microbiome samples with low microbial biomass or severe DNA degradation remain challenging for amplicon-based (e.g., 16S/18S-rRNA) or whole-metagenome sequencing (WMS) approaches. Here, we introduce 2bRAD-M, a highly reduced and cost-effective metagenome-sequencing strategy which only sequences ~1% of metagenome and can simultaneously produce species-level bacterial, archaeal, and fungal profiles for low-biomass and highly degraded samples. For mock communities, 2bRAD-M can accurately generate species-level taxonomic profiles for otherwise hard-to-sequence samples with (i) low biomass of merely 1 pg of total DNA, (ii) high host DNA contamination (99%), and (iii) severely fragmented DNA (50-bp) from degraded samples. Tests of 2bRAD-M on stool, skin and environment-surface samples deliver successful reconstruction of comprehensive, high-resolution microbial profiles with agreement across 16S-rRNA, WMS and existing literature. In addition, it enables microbial profiling in formalin-fixed paraffin-embedded (FFPE) cervical tissue samples which were recalcitrant to conventional approaches due to the low amount and heavy degradation of microbial DNA, and discriminated healthy tissue, pre-invasive cancer and invasive cancer via species-level microbial profiles with 91.1% accuracy. Therefore, 2bRAD-M greatly expands the reach of microbiome sequencing.


title: CXCR6 enforced retention promotes resident memory CD8 T cell-mediated immunosurveillance and control of ovarian cancer.

abstract:
PurposeResident memory CD8 T cells owing to their ability to reside and persist in peripheral tissues, impart adaptive sentinel activity and amplify local immune response, have beneficial implications for tumor surveillance and control. The current study aims to clarify the less known chemotactic mechanisms that govern the localization, retention, and residency of memory CD8 T cells in the ovarian tumor microenvironment.

Experimental DesignRNA/FACS based profiling of chemokine receptor expression in CD8+ resident memory T cells in human ovarian cancer and analyze their association with survival. Analyze chemokine receptor role in anti-tumor response and control by resident memory T cells using prophylactic mice models of ovarian cancer, treated with adoptive transfer of OT1 T cells and vaccination with maraba virus-OVA to target Ovalbumin expressing tumor.

ResultsChemokine receptor profiling of CD8+CD103+ resident memory TILs in ovarian cancer patients revealed high expression of CXCR6. Analysis of the TCGA ovarian cancer database revealed CXCR6 to be associated with CD103 and increased patient survival. Functional studies in mouse models of ovarian cancer revealed that CXCR6 is a marker of resident, but not circulatory tumor-specific memory CD8 T cells. Knockout of CXCR6 in tumor-specific CD8 T cells showed reduced retention in tumor tissues leading to diminished resident memory responses and poor control of ovarian cancer

ConclusionsCXCR6 by promoting increased retention in tumor tissues serves a critical role in resident memory T cell-mediated immunosurveillance and control of ovarian cancer. Future studies warrant exploiting CXCR6 to promote resident memory response in cancers.

category: immunology


title: CXCR6 by increasing retention of memory CD8 T cells in the ovarian tumor microenvironment promotes immunosurveillance and control of ovarian cancer


title: Cobamide sharing drives skin microbiome dynamics

abstract: The human skin microbiome is a key player in human health, with diverse functions ranging from defense against pathogens to education of the immune system. While recent studies have begun to shed light on the valuable role that skin microorganisms have in maintaining a healthy skin barrier, a detailed understanding of the complex interactions that shape healthy skin microbial communities is limited. Cobamides, the vitamin B12 class of cofactor, are essential for organisms across the tree of life. Because this vitamin is only produced by a limited fraction of prokaryotes, cobamide sharing has been shown to mediate community dynamics within microbial communities. Here, we provide the first large-scale unbiased metagenomic assessment of cobamide biosynthesis and utilization in the skin microbiome. We show that while numerous and diverse taxa across the major bacterial phyla on the skin are cobamide dependent, relatively few species encode for de novo cobamide biosynthesis. We find that cobamide sharing shapes the network structure in microbial communities across the different microenvironments of the skin and that changes in community structure and microbiome diversity are driven by the abundance of cobamide producers in the Corynebacterium genus, in both healthy and disease skin states. Lastly, we find that de novo cobamide biosynthesis is enriched only in host-associated Corynebacterium species, including those prevalent on human skin. We confirm that the cofactor is produced in excess through quantification of cobamide production by skin-associated species isolated in the laboratory. Taken together, our results support a role for cobamide sharing within skin microbial communities, which we predict stabilizes the microbiome and mediates host interactions.

category: microbiology


title: Long-term persistence of crAss-like phage crAss001 is associated with phase variation in Bacteroides intestinalis

abstract:
The crAss-like phages are ubiquitous and highly abundant members of the human gut virome that infect commensal bacteria of the order Bacteroidales. Although incapable of classical lysogeny, these viruses demonstrate unexplained long-term persistence in the human gut microbiome, dominating the virome in some individuals. Here we demonstrate that rapid phase variation of alternate capsular polysaccharides plays an important role in dynamic equilibrium between phage sensitivity and resistance in B. intestinalis cultures, allowing phage and bacteria to multiply in parallel. The data also suggests the role of concomitant phage persistence mechanisms associated with delayed lysis of infected cells, such as carrier state infection. From an ecological and evolutionary standpoint this type of phage-host interaction is consistent with the Piggyback-the-Winner model, which suggests a preference towards lysogenic or other "benign" forms of phage infection when the host is stably present at high abundance.

TeaserCrAss-like phage persistence in Bacteroides is associated with capsule phase-variation and additional unexplored mechanisms.


title: The indoor environment - a potential source for intact human-associated anaerobes

abstract:
BackgroundPeople in westernised countries spend most of their time indoors. A healthy human microbiome relies on the interaction with and exchange of microbes that takes place between the human body and its environment. For this reason, the built environment might represent a potent source of commensal microbes. Anaerobic microbes are of particular interest, as researchers have not yet sufficiently clarified how the human microbiome acquires oxygen-sensitive microbes, such as obligate or facultative anaerobes.

MethodsWe sampled ten households and used propidium monoazide to assess the viability of the collected prokaryotes. We compared the microbiome profiles based on 16S rRNA gene sequencing and confirmed our results by genetic and cultivation-based analyses.

ResultsQuantitative and qualitative analysis revealed that most of the microbial taxa are of human origin. Less than 25% of the prokaryotic signatures found in built environment (BE) samples originate from intact - and thus potentially living - cells, indicating that aerobic and stress resistant taxa display an apparent survival advantage. Although the dominant microbial fraction identified on the bathroom floors is composed of aerobes, we confirmed the presence of strictly anaerobic taxa, including methanogenic archaea, in PMA-treated samples. As methanogens are regarded as highly sensitive to aerobic conditions, oxygen-tolerance experiments were performed with human-associated isolates to validate their survival. These results show that these taxa have a limited but substantial ability to survive in the BE. We determined that human-associated methanogens can survive oxic conditions for at least 6 h.

ConclusionsThis study enabled us to collect strong evidence that supports the hypothesis that obligate anaerobic taxa can survive in the BE for a limited amount of time. This suggests that the BE serves as a potential source of anaerobic human commensals.


title: Forecasting symptomatic influenza A infection based on pre-exposure gene expression using a Deep Learning approach

abstract:
Background and ObjectiveNot everyone gets sick after an exposure to influenza A viruses (IAV). Although KLRD1 has been identified as a potential biomarker for influenza susceptibility, it remains unclear whether forecasting symptomatic flu infection based on pre-exposure host gene expression might be possible.

MethodTo examine this hypothesis, we developed DeepFlu using the state-of-the-art deep learning approach on the human gene expression data infected with IAV subtype H1N1 or H3N2 viruses to forecast who would catch the flu prior to an exposure to IAV.

ResultsThe results indicated that such forecast is possible and, in other words, gene expression could reflect the strength of host immunity. In the leave-one-person-out cross-validation, DeepFlu based on deep neural network outperformed the models using convolutional neural network, random forest, or support vector machine, achieving 70.0% accuracy, 0.787 AUROC, and 0.758 AUPR for H1N1 and 73.8% accuracy, 0.847 AUROC, and 0.901 AUPR for H3N2. In the external validation, DeepFlu also reached 71.4% accuracy, 0.700 AUROC, and 0.723 AUPR for H1N1 and 73.5% accuracy, 0.732 AUROC, and 0.749 AUPR for H3N2, surpassing the KLRD1 biomarker. In addition, DeepFlu which was trained only by pre-exposure data worked the best than by other time spans and mixed training data of H1N1 and H3N2 did not necessarily enhance prediction. DeepFlu is available at https://github.com/ntou-compbio/DeepFlu.

ConclusionsDeepFlu is a prognostic tool that can moderately recognize individuals susceptible to the flu and may help prevent the spread of IAV.

category: bioinformatics


title: DeepFlu: a deep learning approach for forecasting symptomatic influenza A infection based on pre-exposure gene expression


title: Spoken language comprehension activates the primary visual cortex

abstract:
Primary visual cortex (V1) is generally thought of as a low-level sensory area that primarily processes basic visual features. However, in congenitally blind individuals, V1 is involved in language processing, with no evidence of major changes in anatomical connectivity that could explain this seemingly drastic functional change. This is at odds with current accounts of neural plasticity, which emphasize the role of connectivity and conserved function in determining a neural tissues role even after atypical early experiences. To reconcile what appears to be unprecedented functional reorganization with known accounts of plasticity limitations, we tested whether V1 also responds to spoken language in sighted individuals. Using fMRI, we found that V1 in normally sighted individuals was indeed activated by comprehensible speech as compared to a reversed speech control condition, in a left-lateralized and focal manner. Activation in V1 for language was also significant and comparable for abstract and concrete words, suggesting it was not driven by visual imagery. Last, this activation did not stem from increased attention to the auditory onset of words, excluding general attention accounts. Together these findings suggest that V1 responds to verbal information even in sighted individuals, potentially to predict visual input. This capability might be the basis for the strong V1 language activation observed in people born blind, re-affirming the notion that plasticity is guided by pre-existing connectivity and abilities in the typically developed brain.

Significance statementHow flexible is the human brain? Studies of congenitally blind individuals showed that language activates the primary visual cortex. This has been interpreted as evidence for unprecedented functional plasticity from a low-level visual to a language area. To reconcile these findings with known limitations of plasticity based on intrinsic physiology and connectivity, we tested if similar activation can be found in sighted participants. We show that left-lateralized primary visual cortex is activated by spoken language comprehension in sighted individuals, . This suggests that plasticity even in complete blindness from birth is not limitless and is guided by pre-existing connectivity and abilities in the typically-developed brain.

category: neuroscience


title: Thinking ahead: prediction in context as a keystone of language in humans and machines

abstract: Departing from traditional linguistic models, advances in deep learning have resulted in a new type of predictive (autoregressive) deep language models (DLMs). Using a self-supervised next-word prediction task, these models are trained to generate appropriate linguistic responses in a given context. We provide empirical evidence that the human brain and autoregressive DLMs share three fundamental computational principles as they process natural language: 1) both are engaged in continuous next-word prediction before word-onset; 2) both match their pre-onset predictions to the incoming word to calculate post-onset surprise (i.e., prediction error signals); 3) both represent words as a function of the previous context. In support of these three principles, our findings indicate that: a) the neural activity before word-onset contains context-dependent predictive information about forthcoming words, even hundreds of milliseconds before the words are perceived; b) the neural activity after word-onset reflects the surprise level and prediction error; and c) autoregressive DLM contextual embeddings capture the neural representation of context-specific word meaning better than arbitrary or static semantic embeddings. Together, our findings suggest that autoregressive DLMs provide a novel and biologically feasible computational framework for studying the neural basis of language.


title: Fluorescent protein expression as a proxy of bacterial fitness in a high throughput assay

abstract:
Bacterial growth is classically assessed by measuring the increase in optical density of pure cultures in shaken liquid media. Measuring growth using optical density has severe limitations when studying multistrain interactions as it is not possible to measure the growth of individual strains within mixed cultures. Here we demonstrated that constitutively expressed fluorescent proteins can be used to track the growth of individual strains in different liquid media. Fluorescence measurements were highly correlated with optical density measurements and cell counts. This allowed us to assess bacterial growth not only in pure cultures, but also in mixed bacterial cultures and determine the impact of competitors on a focal strain, thereby assessing relative fitness. Furthermore, we were able to track the growth of two different strains simultaneously by using fluorescent proteins with differential excitation and emission wavelengths. Bacterial densities measured by fluorescence yielded more consistent data between technical replicates than optical density measurements. Our setup employs fluorescent microplate readers that allow for high throughput and replication.

ImportanceWe expand on an important limitation of the concept of measuring bacterial growth which is classically limited to one strain at a time. By adopting this approach, it is possible to measure growth of several bacterial strains simultaneously in high temporal resolution and in a high throughput manner. This is important to investigate bacterial interactions such as competition and facilitation.


title: Ageing disrupts reinforcement learning whilst learning to help others is preserved

abstract: Reinforcement learning is a fundamental mechanism displayed by many species. However, adaptive behaviour depends not only on learning about actions and outcomes that affect ourselves, but also those that affect others. Here, using computational reinforcement learning models, we tested whether young (age 18-36) and older (age 60-80, total n=152) adults can learn to gain rewards for themselves, another person (prosocial), or neither individual (control). Detailed model comparison showed that a model with separate learning rates for each recipient best explained behaviour. Young adults were faster to learn when their actions benefitted themselves, compared to helping others. Strikingly, compared to younger adults, older adults showed preserved prosocial learning rates but reduced self-relevant learning rates. Moreover, psychopathic traits were lower in older adults and negatively correlated with prosocial learning. These findings suggest learning how to benefit others is preserved across the lifespan with implications for reinforcement learning and theories of healthy ageing.


title: NMDAR-independent acetylcholine, serotonin, and norepinephrine mediated modulation of synaptic eligibility traces into LTD in mice visual cortex

abstract: In reward-based learning, synaptic eligibility traces are a well-defined theoretical solution for the conversion of initial co-activation of pre and postsynaptic neurons into long-term changes in synaptic strength by reward-linked neuromodulators. However, the types of neuromodulators involved in such a phenomenon in mouse visual cortex remain unknown. To characterize the Ex vivo condition, we used optogenetic stimulation of channelrhodopsin-(ChR2) expressing Cre/Ai32(ChR2-eYFP); Tph2-Cre/Ai32(ChR2-eYFP); Thi-Cre/Ai32(ChR2-eYFP) homozygous mice, which release acetylcholine, serotonin, and norepinephrine, respectively. With these mice it is possible to measure the transformation of eligibility traces into long-term changes by endogenous neuromodulators. Here we delineated that layer 2/3 neurons in the visual cortex showed no LTD after conditioning with paired-pulse low-frequency stimulation (ppLFS; 2Hz, 15 min). However, if conditioning was paired with acetylcholine, serotonin, or norepinephrine release upon 473 nm optical stimulation in brain slices, LTD occurs in every case. Thus, our data suggests a new pathway to connect the gap between stimulus and reward. Moreover, we found that stimulation by theta-glass or metal stimulators evoked IPSC traces with the same amplitudes but differences in decay kinetics, further questioning the appropriate use of stimulators in brain slices for evoking an event.


title: Oligodendrocytes depend on MCL-1 to prevent spontaneous apoptosis and white matter degeneration

abstract: Neurologic disorders often disproportionately affect specific brain regions, and different apoptotic mechanisms may contribute to white matter pathology in leukodystrophies or gray matter pathology in poliodystrophies. We previously showed that neural progenitors that generate cerebellar gray matter depend on the anti-apoptotic protein BCL-xL. Conditional deletion of Bcl-xL in these progenitors produces spontaneous apoptosis and cerebellar hypoplasia, while similar conditional deletion of Mcl-1 produces no phenotype. Here, we show that, in contrast, postnatal oligodendrocytes depend on MCL-1. We found that brain-wide Mcl-1 deletion caused apoptosis specifically in mature oligodendrocytes while sparing astrocytes and oligodendrocyte precursors, resulting in impaired myelination and progressive white matter degeneration. Disabling apoptosis through co-deletion of Bax or Bak rescued white matter degeneration, implicating the intrinsic apoptotic pathway in Mcl-1-dependence. Bax and Bak co-deletions rescued different aspects of the Mcl-1-deleted phenotype, demonstrating their discrete roles in white matter stability. MCL-1 protein abundance was reduced in eif2b5-mutant mouse model of the leukodystrophy vanishing white matter disease (VWMD), suggesting the potential for MCL-1 deficiency to contribute to clinical neurologic disease. Our data show that oligodendrocytes require MCL-1 to suppress apoptosis, implicate MCL-1 deficiency in white matter pathology, and suggest apoptosis inhibition as a leukodystrophy therapy.


title: Behavioral, Anatomical and Genetic Convergence of Affect and Cognition in Superior Frontal Cortex

abstract: Affective experience and cognitive abilities are key human traits that are interrelated in behavior and brain. Individual variation of affective and cognitive traits, as well as brain structure, has been shown to partly underlie genetic effects. However, to what extent affect and cognition have a shared genetic relationship with local brain structure is incompletely understood. Here we studied phenotypic and genetic correlations of cognitive and affective traits in behavior and brain structure (cortical thickness, surface area and subcortical volumes) in the twin-based Human Connectome Project sample (N = 1091). Both affective and cognitive trait scores were highly heritable and showed significant phenotypic correlation on the behavioral level. Cortical thickness in the left superior frontal cortex showed a phenotypic association with both affect and cognition, which was driven by shared genetic effects. Quantitative functional decoding of this region yielded associations with cognitive and emotional functioning. This study provides a multi-level approach to study the association between affect and cognition and suggests a convergence of both in superior frontal cortical thickness.


title: Allosteric activation of T-cell antigen receptor signalling by quaternary structure relaxation

abstract: The mechanism of T cell antigen receptor (TCR-CD3) signalling remains elusive. Here, we identified mutations in the transmembrane region of TCR{beta} or CD3{zeta} that augmented pMHC-induced signalling, not explicable by enhanced ligand binding, lateral diffusion, clustering or co-receptor function. Using a novel biochemical assay and molecular dynamics simulation, we demonstrated that the gain-of-function mutations loosened interaction between TCR{beta} and CD3{zeta}. We found that, similar to the activating mutations, pMHC binding reduced TCR{beta} cohesion with CD3{zeta}. This event occurred prior to CD3{zeta} phosphorylation and at 0{degrees}C. Moreover, we demonstrated that soluble monovalent pMHC alone induced signalling and reduced TCR{beta} cohesion with CD3{zeta} in membrane-bound or solubilised TCR-CD3. Our data provide compelling evidence that pMHC binding suffices to activate allosteric changes propagating from TCR{beta} to the CD3 subunits, reconfiguring interchain transmembrane region interactions. These dynamic modifications could change the arrangement of TCR-CD3 boundary lipids to licence CD3{zeta} phosphorylation and initiate signal propagation.


title: Multiple lineages of Streptomyces produce antimicrobials within passalid beetle galleries across eastern North America

abstract: Some insects form symbioses in which actinomycetes provide defense against pathogens by making antimicrobials. The range of chemical strategies employed across these associations, and how these strategies relate to insect lifestyle, remains underexplored. We assessed subsocial passalid beetles of the species Odontotaenius disjunctus, and their frass (fecal material) which is an important food resource within their galleries, as a model insect/actinomycete system. Through chemical and phylogenetic analyses, we found that O. disjunctus frass collected across eastern North America harbored multiple lineages of Streptomyces and diverse antimicrobials. Metabolites detected in frass displayed synergistic and antagonistic inhibition of a fungal entomopathogen, Metarhizium anisopliae, and multiple streptomycete isolates inhibited this pathogen when co-cultivated directly in frass. These findings support a model in which the lifestyle of O. disjunctus accommodates multiple Streptomyces lineages in their frass, resulting in a rich repertoire of antimicrobials that likely insulates their galleries against pathogenic invasion.


title: Evaluating coarse-grained MARTINI force-fields for capturing the ripple phase of lipid membranes

abstract:
Phospholipids, which are an integral component of cell membranes, exhibit a rich variety of lamellar phases modulated by temperature and composition. Molecular dynamics (MD) simulations have greatly enhanced our understanding of phospholipid membranes by capturing experimentally observed phases and phase transitions at molecular resolution. However, the ripple (P{beta}') membrane phase, observed as an intermediate phase below the main gel-to-liquid crystalline transition with some lipids, has been challenging to capture with MD simulations, both at all-atom and coarse-grained (CG) resolution. Here, with an aggregate ~2.5 s all-atom and ~122 s CG MD simulations, we systematically assess the ability of six CG MARTINI 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) lipid and water force-field (FF) variants, parametrized to capture the DPPC gel and fluid phases, for their ability to capture the P{beta}' phase, and compared observations with those from an all-atom FF. Upon cooling from the fluid phase to below the phase transition temperature with smaller (380-lipid) and larger (> 2200-lipid) MARTINI and all-atom (CHARMM36 FF) DPPC lipid bilayers, we observed that smaller bilayers with both all-atom and MARTINI FFs sampled interdigitated P{beta}' and ripple-like states, respectively. However, while all-atom simulations of the larger DPPC membranes exhibited the formation of the P{beta}' phase, similar to previous studies, MARTINI membranes did not sample interdigitated ripple-like states at larger system sizes. We then demonstrated that the ripple-like states in smaller MARTINI membranes were kinetically-trapped structures caused by finite size effects rather than being representative of true P{beta}' phases. We showed that even a MARTINI FF variant that could capture the tilted L{beta}' gel phase, a prerequisite for stabilizing the P{beta}' phase, could not capture the rippled phase upon cooling. Our study reveals that the current MARTINI FFs (including MARTINI3) may require specific re-parametrization of the interaction potentials to stabilize lipid interdigitation, a characteristic of the ripple phase.

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category: biophysics


title: A Tunable, Simplified Model for Biological Latch Mediated Spring Actuated Systems

abstract: We develop a model of latch-mediated spring actuated (LaMSA) systems relevant to comparative biomechanics and bioinspired design. The model contains five components: two motors (muscles), a spring, a latch, and a load mass. One motor loads the spring to store elastic energy and the second motor subsequently removes the latch, which releases the spring and causes movement of the load mass. We develop open-source software to accompany the model, which provides an extensible framework for simulating LaMSA systems. Output from the simulation includes information from the loading and release phases of motion, which can be used to calculate kinematic performance metrics that are important for biomechanical function. In parallel, we simulate a comparable, directly actuated system that uses the same motor and mass combinations as the LaMSA simulations. By rapidly iterating through biologically relevant input parameters to the model, simulated kinematic performance differences between LaMSA and directly actuated systems can be used to explore the evolutionary dynamics of biological LaMSA systems and uncover design principles for bioinspired LaMSA systems. As proof of principle of this concept, we compare a LaMSA simulation to a directly actuated simulation that includes a either Hill-type force-velocity trade-off or muscle activation dynamics, or both. For the biologically-relevant range of parameters explored, we find that the muscle force-velocity trade-off and muscle activation have similar effects on directly actuated performance. Including both of these dynamic muscle properties increases the accelerated mass range where a LaMSA system outperforms a directly actuated one.


title: Global analysis of multi-mutants to discover stabilizing amino acid substitutions

abstract:
The identification of amino acid substitutions that both enhance the stability and function of a protein is a key challenge in protein engineering. Technological advances have enabled assaying thousands of protein variants in a single high-throughput experiment, and more recent studies use such data in protein engineering. We present a Global Multi-Mutant Analysis (GMMA) that exploits the presence of multiply-substituted variants to identify individual amino acid substitutions that are beneficial for the stability and function across a large library of protein variants. We have applied GMMA to >54,000 variants of green fluorescent protein (GFP), each with known fluorescence output, and each carrying 1-15 amino acid substitutions. The GMMA method achieves a good fit to the data while being analytically transparent. The six top-ranking substitutions are demonstrated to progressively enhance GFP and in general, our analysis recovers nearly all the substitutions previously reported to be beneficial for GFP folding and function, only using a single experiment as input.

Significance StatementProtein engineering is carried out to improve proteins for practical applications by changing one or more amino acid residues in a protein. We present a method termed global multi-mutant analysis (GMMA) that helps solve two problems in protein engineering. First, because many proteins are already highly optimized, it can be difficult to identify individual variants that further improve function. Second, while it is possible to combine variants with small individual effects, such approaches may be hampered by non-additivity. GMMA identifies combinable effects of single substitutions from a large set of variants each carrying multiple substitutions. We demonstrate the approach on a set of 54,000 variants of green fluorescent protein and identify many enhancing single-substitutions from a single experiment.


title: Global analysis of multi-mutants to improveprotein function


title: Implementation of a Bayesian Secondary Structure Estimation Method for the SESCA Circular Dichroism Analysis Package

abstract:
Circular dichroism spectroscopy is a structural biology technique frequently applied to determine the secondary structure composition of soluble proteins. Our recently introduced computational analysis package SESCA aids the interpretation of protein circular dichroism spectra and enables the validation of proposed corresponding structural models. To further these aims, we present the implementation and characterization of a new Bayesian secondary structure estimation method in SESCA, termed SESCA_bayes. SESCA_bayes samples possible secondary structures using a Monte Carlo scheme, driven by the likelihood of estimated scaling errors and non-secondary-structure contributions of the measured spectrum. SESCA_bayes provides an estimated secondary structure composition and separate uncertainties on the fraction of residues in each secondary structure class. It also assists efficient model validation by providing a posterior secondary structure probability distribution based on the measured spectrum. Our presented study indicates that SESCA_bayes estimates the secondary structure composition with a significantly smaller uncertainty than its predecessor, SESCA_deconv, which is based on spectrum deconvolution. Further, the mean accuracy of the two methods in our analysis is comparable, but SESCA_bayes provides more accurate estimates for circular dichroism spectra that contain considerable non-SS contributions.

PROGRAM SUMMARYProgram Title: SESCA_bayes

CPC Library link to program files: (to be added by Technical Editor)

Developers repository link: https://www.mpibpc.mpg.de/sesca

Code Ocean capsule: (to be added by Technical Editor)

Licensing provisions: GPLv3

Programming language: Python

Supplementary material:

Nature of problem:

The circular dichroism spectrum of a protein is strongly correlated with its secondary structure composition. However, determining the secondary structure from a spectrum is hindered by non-secondary structure contributions and by scaling errors due the uncertainty of the protein concentration. If not taken properly into account, these experimental factors can cause considerable errors when conventional secondary-structure estimation methods are used. Because these errors combine with errors of the proposed structural model in a non-additive fashion, it is difficult to assess how much uncertainty the experimental factors introduce to model validation approaches based on circular dichroism spectra.

Solution methodFor a given measured circular dichroism spectrum, the SESCA_bayes algorithm applies Bayesian statistics to account for scaling errors and non-secondary structure contributions and to determine the conditional secondary structure probability distribution. This approach relies on fast spectrum predictions based on empirical basis spectrum sets and joint probability distribution maps for scaling factors and non-secondary structure distributions. Because SESCA_bayes estimates the most probable secondary structure composition based on a probability-weighted sample distribution, it avoids the typical fitting errors that occur during conventional spectrum deconvolution methods. It also estimates the uncertainty of circular dichroism based model validation more accurately than previous methods of the SESCA analysis package.


title: Specific neuromodulation induced by alpha-based neurofeedback learning: A double-blind randomized study

abstract: The neuromodulation induced by neurofeedback training (NFT) remains a matter of debate. Investigating the modulation of brain activity specifically associated with NF requires controlling for multiple factors, such as reward, performance, congruency between task and targeted brain activity. This can be achieved using sham feedback (FB) control condition, equating all aspects of the experiment but the link between brain activity and FB. We aimed at investigating the modulation of individual alpha EEG activity induced by NFT in a double-blind, randomized, sham-controlled study. Forty-eight healthy participants were assigned to either NF (n=25) or control (n=23) group and performed alpha upregulation training (over 12 weeks) with a wearable EEG device. Participants of the NF group received FB based on their individual alpha activity. The control group received the auditory FB of participants of the NF group. An increase of alpha activity across training sessions was observed in the NF group only (p<0.001). This neuromodulation was selective in that it was not observed for theta (4-8Hz) and low beta (13-18Hz) activities. While alpha upregulation was found in the NF group only, psychological outcome variables showed increased feeling of control, decreased anxiety level and increased relaxation feeling in both the NF and control groups, without any significant difference between groups. This is interpreted in terms of learning context and placebo effects. Our results pave the way to self-learnt, NF-based neuromodulation with light-weighted, wearable EEG systems.


title: Alpha activity neuromodulation induced by individual alpha-based neurofeedback learning in ecological context: A double-blind randomized study


title: Quantifying bacterial evolution in the wild: a birthday problem for Campylobacter lineages

abstract:
Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the  birthday problem. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter coli (2.4 x 10-6 s/s/y) and Campylobacter jejuni (3.4 x 10-6 s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time-frame - analogous to a shared birthdays - and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species.

Author SummaryGrowth and reproduction in living organisms require DNA replication but this process is error prone. Along with variation introduced by horizontal gene transfer, it can lead to alterations in the nucleotide sequence. These nucleotide changes accumulate over time in successive generations at an approximately constant rate termed the molecular clock. Therefore, if this rate is known, one can estimate the date when two or more lineages diverged. In bacteria, this can be informative for understanding the time-scale of emergence and spread of pathogenic strains. Such analyses are robust when the ancestral population is known, such as for obligate pathogens that only infect humans. However, when the bacterium inhabits multiple hosts or niches it is difficult to infer direct ancestry from one strain to another, reducing the accuracy of molecular clock estimates. Here we focus on one such multi-host organism, Campylobacter, a leading cause of food-borne gastroenteritis. Reconstructing the population history by estimating empirical nucleotide change rates from carefully selected isolate pairs, and evaluating the maintenance of multiple lineages over time, we provide information about strain diversification. Our method is a new addition to the bacterial genomics toolkit that will help in understanding the spread of opportunistic pathogens.

category: genomics


title: Vectorized Capsid Generation in the Browser with Capsid.js

abstract:
MotivationFew online services exist for rendering high-quality viral capsid figures compatible with common productivity software to develop effective infographics in the field of virology.

ResultsThe capsid.js library renders class I viral capsids within an online application that parameterizes style options, perspectives, and lattice patterns with SVG export.

AvailabilityThis project is actively developed on GitHub (https://github.com/dnanto/capsid), distributed under the MIT License, hosted on GitHub Pages, and runs on modern browsers (https://dnanto.github.io/capsid/capsid.html).

Supplementary informationSupplementary data are available on GitHub.


title: Newfound coding potential of transcripts unveils missing members of human protein communities

abstract: Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions (i.e. UTRs, open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs) frequently encode proteins (termed alternative proteins). This suggests that previously identified protein-protein interaction networks are partially incomplete since alternative proteins are not present in conventional protein databases. Here we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high throughput human network proteomics dataset thereby revealing the presence of 280 alternative proteins in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 136 alternative proteins encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental gene. Finally, we experimentally validate several interactions involving alternative proteins. These data improve the blueprints of the human protein-protein interaction network and suggest functional roles for hundreds of alternative proteins.

category: systems biology


title: A SARS-CoV-2 neutralizing antibody selected from COVID-19 patients by phage display is binding to the ACE2-RBD interface and is tolerant to most known recently emerging RBD mutations

abstract:
The novel betacoranavirus SARS-CoV-2 causes a form of severe pneumonia disease, termed COVID-19 (coronavirus disease 2019). Recombinant human antibodies are proven potent neutralizers of viruses and can block the interaction of viral surface proteins with their host receptors. To develop neutralizing anti-SARS-CoV-2 antibodies, antibody gene libraries from convalescent COVID-19 patients were constructed and recombinant antibody fragments (scFv) against the receptor binding domain (RBD) of the S1 subunit of the viral spike (S) protein were selected by phage display. The selected antibodies were produced in the scFv-Fc format and 30 showed more than 80% inhibition of spike (S1-S2) binding to cells expressing ACE2, assessed by flow cytometry screening assay. The majority of these inhibiting antibodies are derived from the VH3-66 V-gene. The antibody STE90-C11 showed a sub nM IC50 in a plaque-based live SARS-CoV-2 neutralization assay. The in vivo efficacy of the antibody was demonstrated in the Syrian hamster and in the hACE2 mice model using a silenced human IgG1 Fc part. The crystal structure of STE90-C11 Fab in complex with SARS-CoV-2-RBD was solved at 2.0 [A] resolution showing that the antibody binds at the same region as ACE2 to RBD. The binding and inhibtion of STE90-C11 is not blocked by many known RBD mutations including N439K, L452R, E484K or L452R+E484Q (emerging B.1.617). STE90-C11 derived human IgG1 with Fc{gamma}R silenced Fc (COR-101) is currently undergoing Phase Ib/II clinical trials for the treatment of moderate to severe COVID-19.

In BriefHuman antibodies were selected from convalescent COVID-19 patients using antibody phage display. The antibody STE90-C11 is neutralizing authentic SARS-CoV-2 virus in vitro and in vivo and the crystal structure of STE90-C11 in complex with SARS-CoV-2-RBD revealed that this antibody is binding in the RBD-ACE2 interface. S1 binding of STE90-C11 and inhibition of ACE2 binding is not blocked by many known RBD mutations.

category: bioengineering


title: A hierarchy of linguistic predictions during natural language comprehension

abstract: Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions. Here, we address both issues by analysing brain recordings of participants listening to audiobooks, and using a deep neural network (GPT-2) to precisely quantify contextual predictions. First, we establish that brain responses to words are modulated by ubiquitous, probabilistic predictions. Next, we disentangle model-based predictions into distinct dimensions, revealing dissociable signatures of syntactic, phonemic and semantic predictions. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, showing that the brain spontaneously predicts upcoming language at multiple levels of abstraction.


title: Normalizing the brain connectome for communication through synchronization

abstract:
Networks in neuroscience determine how brain function unfolds, and their perturbations lead to psychiatric disorders and brain disease. Brain networks are characterized by their connectomes, which comprise the totality of all connections, and are commonly described by graph theory. This approach is deeply rooted in a particle view of information processing, based on the quantification of informational bits such as firing rates. Oscillations and brain rhythms demand, however, a wave perspective of information processing based on synchronization. We extend traditional graph theory to a dual particle-wave-perspective, integrate time delays due to finite transmission speeds and derive a normalization of the connectome. When applied to the data base of the Human Connectome project, we explain the emergence of frequency-specific network cores including the visual and default mode networks. These findings are robust across human subjects (N=100) and are a fundamental network property within the wave picture. The normalized connectome comprises the particle view in the limit of infinite transmission speeds and opens the applicability of graph theory to a wide range of novel network phenomena, including physiological and pathological brain rhythms. These two perspectives are orthogonal, but not incommensurable, when understood within the novel here proposed generalized framework of structural connectivity.

AUTHOR SUMMARYAll networks are composed of nodes and links, forming the structural frame, in which communication occurs. We demonstrate that graph theoretical tools make the implicit assumption of information transmission via exchange of bits, suggesting that the stronger connected nodes are more impactful upon the remainder of the network. This corollary does not extend to communication through oscillations, which is the prominent information carrier in brain networks. We extend traditional network analysis to the oscillatory domain and derive a novel network normalization including descriptive metrics. Along the prototypical example of the brain as a network, we illustrate the consequences of this novel approach and demonstrate that the normalization robustly explains the emergence of the prominent frequency-specific network cores, which cannot be understood within the traditional framework.


title: Learning differentially shapes prefrontal and hippocampal activity patterns during classical conditioning

abstract: The ability to use sensory cues to inform goal directed actions is a critical component of intelligent behavior. To study how sound cues are translated into anticipatory licking during classical appetitive conditioning, we employed high-density electrophysiological recordings from the hippocampal CA1 area and the prefrontal cortex (PFC). CA1 and PFC neurons undergo distinct learning dependent changes at the single cell level and maintain representations of cue identity during anticipatory behavior at the population level. In addition, reactivation of task-related neuronal assemblies during hippocampal awake Sharp-Wave Ripples (aSWR) changed within individual sessions in CA1 and over the course of multiple sessions in PFC. Despite both areas being highly engaged and synchronized during the task, we found no evidence for coordinated single cell or assembly activity during conditioning trials or aSWR.


title: Phenotype bias determines how RNA structures occupy the morphospace of all possible shapes

abstract: Morphospaces representations of phenotypic characteristics are often populated unevenly, leaving large parts unoccupied. Such patterns are typically ascribed to contingency, or else to natural selection disfavouring certain parts of the morphospace. The extent to which developmental bias, the tendency of certain phenotypes to preferentially appear as potential variation, also explains these patterns is hotly debated. Here we demonstrate quantitatively that developmental bias is the primary explanation for the occupation of the morphospace of RNA secondary structure (SS) shapes. Upon random mutations, some RNA SS shapes (the frequent ones) are much more likely to appear than others. By using the RNAshapes method to define coarse-grained SS classes, we can directly compare the frequencies that non-coding RNA SS shapes appear in the RNAcentral database to frequencies obtained upon random sampling of sequences. We show that: a) Only the most frequent structures appear in nature; the vast majority of possible structures in the morphospace have not yet been explored. b) Remarkably small numbers of random sequences are needed to produce all the RNA SS shapes found in nature so far. c) Perhaps most surprisingly, the natural frequencies are accurately predicted, over several orders of magnitude in variation, by the likelihood that structures appear upon uniform random sampling of sequences. The ultimate cause of these patterns is not natural selection, but rather strong phenotype bias in the RNA genotype-phenotype map, a type of developmental bias or "findability constraint", which limits evolutionary dynamics to a hugely reduced subset of structures that are easy to "find".

category: evolutionary biology


title: Altered biomechanical strategies of the paretic hip and knee joints during a step-up task: a pilot study

abstract: Stroke often leads to chronic motor impairments in the paretic lower limb that can constrain lower extremity movement and negatively impact the ability to navigate stairs or curbs. This exploratory study investigated the differences in hip and knee biomechanical strategies during a step-up task between 5 adults with hemiparetic stroke and 5 age-matched adults without stroke. Participants were instructed to step up onto a 4-inch platform, where joint biomechanics were quantified for the hip in the frontal plane and the hip and knee in the sagittal plane. Peak joint kinematics were identified during the leading limb swing phase and peak joint moments and power were identified during the leading limb pull-up phase of stance. Mixed effects regression models estimated fixed effects of limb (3 levels: control dominant, stroke non-paretic, and stroke paretic) on biomechanical outcomes, while a random effect of participant controlled for within-participant correlations. Repeated assessments within participants (approximately 60 trials per lower limb) increased the effective sample size from 10 to between 12.0 to 19.6. Altered biomechanical strategies of the paretic lower limb included reduced flexion angles and increased pelvic obliquity angles during swing, decreased power generation in the hip frontal plane during stance, and decreased moment and power generation in the knee sagittal plane during stance. A strategy of substantial interest was the elevated hip sagittal plane moment and power generation in both stroke limbs. Overall, our findings suggest that chronic motor impairments from stroke can lead to inefficient biomechanical strategies when stepping up.


title: Stimulus-selective lateral signaling between olfactory afferents enables parallel encoding of distinct CO2 dynamics

abstract:
An important problem in sensory processing is how lateral interactions that mediate the integration of information across sensory channels function with respect to stimulus tuning. We demonstrate a novel form of selective crosstalk between specific olfactory channels that occurs between primary olfactory receptor neurons (ORNs). Neurotransmitter release from ORNs can be driven by two distinct sources of excitation, feedforward activity derived from the odorant receptor and lateral input originating from specific subsets of other ORNs. Consequently, levels of presynaptic release can become dissociated from firing rate. Stimulus-selective lateral signaling results in the distributed representation of CO2, a behaviorally important environmental cue that elicits spiking in only a single ORN class, in multiple olfactory channels. Different CO2-responsive channels preferentially transmit distinct stimulus dynamics, thereby expanding the coding bandwidth for CO2. These results generalize to additional odors and olfactory channels, revealing a subnetwork of lateral interactions between ORNs that reshape the spatial and temporal structure of odor representations in a stimulus-specific manner.

One Sentence SummaryA novel subnetwork of stimulus-selective lateral interactions between primary olfactory sensory neurons enables new sensory computations.


title: Ultra-high field (7T) functional magnetic resonance imaging in amyotrophic lateral sclerosis: a pilot study

abstract: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of the central nervous system that results in a progressive loss of motor function and ultimately death. It is critical, yet also challenging, to develop non-invasive biomarkers to identify, localize, measure and/or track biological mechanisms implicated in ALS. Such biomarkers may also provide clues to identify potential molecular targets for future therapeutic trials. Herein we report on a pilot study involving twelve participants with ALS and nine age-matched healthy controls who underwent high-resolution resting state functional magnetic resonance imaging at an ultra-high field of 7 Tesla. A group-level whole-brain analysis revealed a disruption in long-range functional connectivity between the superior sensorimotor cortex (in the precentral gyrus) and bilateral cerebellar lobule VI. Post hoc analyses using atlas-derived left and right cerebellar lobule VI revealed decreased functional connectivity in ALS participants that predominantly mapped to bilateral postcentral and precentral gyri. Cerebellar lobule VI is a transition zone between anterior motor networks and posterior non-motor networks in the cerebellum, and is associated with a wide range of key functions including complex motor and cognitive processing tasks. Our observation of the involvement of cerebellar lobule VI adds to the growing number of studies implicating the cerebellum in ALS. Future avenues of scientific investigation should consider how high-resolution imaging at 7T may be leveraged to visualize differences in functional connectivity disturbances in various genotypes and phenotypes of ALS along the ALS-frontotemporal dementia spectrum.


title: Perturbation of amygdala-cortical projections reduces ensemble coherence of palatability coding in gustatory cortex

abstract: Taste palatability is centrally involved in consumption decisions--we ingest foods that taste good and reject those that dont. Gustatory cortex (GC) and basolateral amygdala (BLA) almost certainly work together to mediate palatability-driven behavior, but the precise nature of their interplay during taste decision-making is still unknown. To probe this issue, we discretely perturbed (with optogenetics) activity in BLA[->]GC axons during taste deliveries. This perturbation strongly altered GC taste responses, but while the perturbation itself was tonic (2s), the alterations were not--changes preferentially aligned with the onset times of previously-described taste response epochs, and reduced evidence of palatability-related activity in the "late-epoch" of the responses without reducing the amount of taste identity information available in the "middle epoch." Finally, BLA[->]GC perturbations changed behavior-linked taste response dynamics themselves, distinctively diminishing the abruptness of ensemble transitions into the late epoch. These results suggest that BLA "organizes" behavior-related GC taste dynamics.


title: Uniparental nuclear inheritance following bisexual mating in fungi

abstract: Some remarkable animal species require an opposite-sex partner for their sexual development but discard the partners genome before gamete formation, generating hemi-clonal progeny in a process called hybridogenesis. Here, we discovered a similar phenomenon, termed pseudosexual reproduction, in a basidiomycete human fungal pathogen, Cryptococcus neoformans, where exclusive uniparental inheritance of nuclear genetic material was observed during bisexual reproduction. Analysis of strains expressing fluorescent reporter proteins revealed instances where only one of the parental nuclei was present in the terminal sporulating basidium. Whole-genome sequencing revealed the nuclear genome of the progeny was identical with one or the other parental genome. Pseudosexual reproduction was also detected in natural isolate crosses where it resulted in mainly MAT progeny, a bias observed in Cryptococcus ecological distribution as well. The meiotic recombinase Dmc1 was found to be critical for pseudosexual reproduction. These findings reveal a novel, and potentially ecologically significant, mode of eukaryotic microbial reproduction that shares features with hybridogenesis in animals.


title: Differences in evolutionary accessibility determine which equally effective regulatory motif evolves to generate pulses

abstract: Transcriptional regulatory networks (TRNs) are enriched for certain "motifs". Motif usage is commonly interpreted in adaptationist terms, i.e. that the optimal motif evolves. But certain motifs can also evolve more easily than others. Here, we computationally evolved TRNs to produce a pulse of an effector protein. Two well-known motifs, type 1 incoherent feed-forward loops (I1FFLs) and negative feedback loops (NFBLs), evolved as the primary solutions. Which motif evolves more often depends on selection conditions, but under all conditions, either motif achieves similar performance. I1FFLs generally evolve more often than NFBLs, unless we select for a tall pulse. I1FFLs are more evolutionarily accessible early on, before the effector protein evolves high expression; when NFBLs subsequently evolve, they tend to do so from a conjugated I1FFL-NFBL genotype. In the empirical S. cerevisiae TRN, output genes of NFBLs had higher expression levels than those of I1FFLs. These results suggest that evolutionary accessibility, and not relative functionality, shapes which motifs evolve in TRNs, and does so as a function of the expression levels of particular genes.


title: Dietary restriction in the long-chain acyl-CoA dehydrogenase knockout mouse

abstract: Patients with a disorder of mitochondrial long-chain fatty acid {beta}-oxidation (FAO) have reduced fasting tolerance and may present with hypoketotic hypoglycemia, hepatomegaly, (cardio)myopathy and rhabdomyolysis. Patients should avoid a catabolic state because it increases reliance on FAO as energy source. It is currently unclear whether weight loss through a reduction of caloric intake is safe in patients with a FAO disorder. We used the long-chain acyl-CoA dehydrogenase knockout (LCAD KO) mouse model to study the impact of dietary restriction (DR) on the plasma metabolite profile and cardiac function. For this, LCAD KO and wild type (WT) mice were subjected to DR (70% of ad libitum chow intake) for 4 weeks and compared to ad libitum chow fed mice. We found that DR had a relatively small impact on the plasma metabolite profile of WT and LCAD KO mice. Echocardiography revealed a small decrease in left ventricular systolic function of LCAD KO mice, which was most noticeable after DR, but there was no evidence of DR-induced cardiac remodeling. Our results suggest that weight loss through DR does not have acute and detrimental consequences in a mouse model for FAO disorders.

category: physiology


title: Seizure localisation with attention-based graph neural networks

abstract:
In this paper, we introduce a machine learning methodology for localising the seizure onset zone in subjects with epilepsy. We represent brain states as functional networks obtained from intracranial electroen-cephalography recordings, using correlation and the phase locking value to quantify the coupling between different brain areas.

Our method is based on graph neural networks (GNNs) and the attention mechanism, two of the most significant advances in artificial intelligence in recent years. Specifically, we train a GNN to distinguish between functional networks associated with interictal and ictal phases. The GNN is equipped with an attention-based layer that automatically learns to identify those regions of the brain (associated with individual electrodes) that are most important for a correct classification. The localisation of these regions does not require any prior information regarding the seizure onset zone.

We show that the regions of interest identified by the GNN strongly correlate with the localisation of the seizure onset zone reported by electroencephalographers. We report results both for human patients and for simulators of brain activity. We also show that our GNN exhibits uncertainty on those patients for which the clinical localisation was unsuccessful, highlighting the robustness of the proposed approach.


title: Age-related decline in cortical inhibitory tone strengthens motor memory

abstract: Ageing disrupts the finely tuned excitation/inhibition balance (E:I) across cortex, driven by a natural decline in inhibitory tone ({gamma}-amino butyric acid, GABA). This causes functional decrements. However, in young adults, experimentally lowering GABA in sensorimotor cortex enhances adaptation memory. Therefore, using a cross-sectional design, here we tested the hypothesis that as sensorimotor cortical GABA declines naturally with age, adaptation memory would increase, and the former would explain the latter. Results confirmed this prediction. To probe causality, we used brain stimulation to further lower sensorimotor cortical GABA during adaptation. Across individuals, how stimulation changed memory depended on sensorimotor cortical E:I. In those with low E:I, stimulation increased memory; in those with high E:I stimulation reduced memory. Thus, we identify a form of motor memory that improves naturally with age, depends causally on sensorimotor cortex neurochemistry, and may be a potent target for motor skill preservation strategies in healthy ageing and neurore-habilitation.


title: Spontaneous recurrent seizures in an intra-amygdala kainate microinjection model of temporal lobe epilepsy are differentially sensitive to antiseizure drugs

abstract:
The discovery and development of novel antiseizure drugs (ASDs) that are effective in controlling pharmacoresistant spontaneous recurrent seizures (SRSs) continues to represent a significant unmet clinical need. The Epilepsy Therapy Screening Program (ETSP) has undertaken efforts to address this need by adopting animal models that represent the salient features of human pharmacoresistant epilepsy and employing these models for preclinical testing of investigational ASDs. One such model that has garnered increased interest in recent years is the mouse variant of the Intra-Amygdala Kainate (IAK) microinjection model of mesial temporal lobe epilepsy (MTLE). In establishing a version of this model, several methodological variables were evaluated for their effect(s) on pertinent quantitative endpoints. Although administration of a benzodiazepine 40 minutes after kainate (KA) induced status epilepticus (SE) is commonly used to improve survival, data presented here demonstrates similar outcomes (mortality, hippocampal damage, latency periods, and 90-day SRS natural history) between mice given midazolam and those that were not. Using a version of this model that did not interrupt SE with a benzodiazepine, a 90-day natural history study was performed and survival, latency periods, SRS frequencies and durations, and SRS clustering data were quantified. Finally, an important step towards model adoption is to assess the sensitivities or resistances of SRSs to a panel of approved and clinically used ASDs. Accordingly, the following ASDs were evaluated for their effects on SRSs in these mice: phenytoin (20 mg/kg, b.i.d.), carbamazepine (30 mg/kg, t.i.d.), valproate (240 mg/kg, t.i.d.), diazepam (4 mg/kg, b.i.d.), and phenobarbital (25 and 50 mg/kg, b.i.d.). Valproate, diazepam, and phenobarbital significantly attenuated SRS frequency relative to vehicle controls at doses devoid of observable adverse behavioral effects. Only diazepam significantly increased seizure freedom. Neither phenytoin nor carbamazepine significantly altered SRS frequency or freedom under these experimental conditions. These data demonstrate that SRSs in this IAK model of MTLE are pharmacoresistant to two representative sodium channel-inhibiting ASDs (phenytoin and carbamazepine) but not to GABA receptor modulating ASDs (diazepam and phenobarbital) or a mixed-mechanism ASD (valproate). Accordingly, this model is being incorporated into the NINDS-funded ETSP testing platform for treatment resistant epilepsy.

HighlightsO_LIAn intra-amygdala kainate model of TLE was evaluated for pharmacoresistant seizures
C_LIO_LIAdministration of midazolam during status epilepticus did not affect mortality
C_LIO_LIModel characteristics were evaluated over a 90-day natural history study
C_LIO_LISpontaneous seizures were resistant to phenytoin and carbamazepine
C_LIO_LISpontaneous seizures were sensitive to valproic acid, diazepam, and phenobarbital
C_LI


title: Mouse and Human Antibodies that Bind HLA-E-Leader Peptide Complexes and Enhance NK Cell Cytotoxicity

abstract: HLA-E is a non-classical class Ib molecule that has limited polymorphism and binds HLA class Ia leader peptides (VL9). HLA-E-VL9 complexes interact with the natural killer (NK) cell receptors NKG2A-C/CD94 and regulate NK cell-mediated cytotoxicity. Here we isolated a murine IgM antibody 3H4, that specifically recognized HLA-E-VL9 bound complexes and enhanced killing of HLA-E-VL9-expressing cells by an NKG2A+ NK cell line. Structural analysis revealed how 3H4 prevents CD94/NKG2A docking on HLA-E-VL9 by binding with an overlapping footprint. Upon in vitro maturation, an affinity-optimized 3H4 IgG showed enhanced NK killing of HLA-E-VL9-expressing cells. Remarkably, HLA-E-VL9-specific IgM autoantibodies with similar specificity and functions to 3H4 were subsequently isolated from naive B cells of cytomegalovirus (CMV)-negative, healthy male human donors. Thus, a repertoire of germline low affinity HLA-E-VL9-reactive antibodies are present in both naive human and murine B cell repertoires. These antibodies can enhance NK cell cytotoxicity and therefore have potential for therapeutic modulation of NK cell function.


title: An Omic and Multidimensional Spatial Atlas from Serial Biopsies of an Evolving Metastatic Breast Cancer

abstract: Mechanisms of therapeutic resistance manifest in metastatic cancers as tumor cell intrinsic alterations and extrinsic microenvironmental influences that can change during treatment. To support the development of methods for the identification of these mechanisms in individual patients, we present here an Omic and Multidimensional Spatial (OMS) Atlas generated from four serial biopsies of a metastatic breast cancer patient during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata including treatment times and doses, anatomic imaging, and blood-based response measurements to exploratory analytics including comprehensive DNA, RNA, and protein profiles, images of multiplexed immunostaining, and 2- and 3-dimensional scanning electron micrographs. These data reveal aspects of therapy-associated heterogeneity and evolution of the cancers genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples showing how integrative analyses of these data provide insights into potential mechanisms of response and resistance, and suggest novel therapeutic vulnerabilities.

category: cancer biology


title: Adaptation of Bacillus thuringiensis to plant colonisation affects differentiation and toxicity

abstract:
Bacillus cereus group (Bacillus cereus sensu lato) has a diverse ecology, including various species that are vertebrate or invertebrate pathogens. Few isolates from the B. cereus group have however been demonstrated to benefit plant growth. Therefore, it is crucial to explore how bacterial development and toxicity evolves during plant colonization. Herein, we investigated Bacillus thuringiensis (Cry-) adaptation to the colonization of Arabidopsis thaliana roots, and monitored changes in cellular differentiation in experimentally evolved isolates. Isolates from two populations displayed improved iterative ecesis on roots and increased toxicity against insect larvae. Molecular dissection and recreation of a causative mutation revealed the importance of a non-sense mutation in the rho transcription terminator gene. Transcriptome analysis revealed how Rho impacts various B. thuringiensis genes involved in carbohydrate metabolism and virulence. Our work suggests that evolved multicellular aggregates have a fitness advantage over single cells when colonizing plants, creating a trade-off between swimming and multicellularity in evolved lineages, in addition to unrelated alterations in pathogenicity.

ImportanceBiologicals-based plant protection relies on the use of safe microbial strains. During application of biologicals to the rhizosphere, microbes adapt to the niche, including genetic mutations shaping the physiology of the cells. Here, the experimental evolution of Bacillus thuringiensis lacking the insecticide crystal toxins was examined on the plant root to reveal how adaptation shapes the differentiation of this bacterium. Interestingly, evolution of certain linages led to increased emetic toxin production, hemolysis and insect larvae pathogenesis in B. thuringiensis driven by transcriptional rewiring. Further, our detailed study reveals how inactivation of the transcription termination protein Rho promotes aggregation on the plant root in addition to altered differentiation and pathogenesis in B. thuringiensis.


title: MASiVar: Multisite, Multiscanner, and Multisubject Acquisitions for Studying Variability in Diffusion Weighted Magnetic Resonance Imaging

abstract:
PurposeDiffusion weighted imaging (DWI) allows investigators to identify structural, microstructural, and connectivitybased differences between subjects, but variability due to session and scanner biases is a challenge.

MethodsTo investigate DWI variability, we present MASiVar, a multisite dataset consisting of 319 diffusion scans acquired at 3T from b = 1000 to 3000 s/mm2 across 14 healthy adults, 83 healthy children (5 to 8 years), three sites, and four scanners as a publicly available, preprocessed, and de-identified dataset. With the adult data, we demonstrate the capacity of MASiVar to simultaneously quantify the intrasession, intersession, interscanner, and intersubject variability of four common DWI processing approaches: (1) a tensor signal representation, (2) a multi-compartment neurite orientation dispersion and density model, (3) white matter bundle segmentation, and (4) structural connectomics. Respectively, we evaluate region-wise fractional anisotropy (FA), mean diffusivity, and principal eigenvector; region-wise cerebral spinal fluid volume fraction, intracellular volume fraction, and orientation dispersion index; bundle-wise shape, volume, FA, and length; and whole connectome correlation and maximized modularity, global efficiency, and characteristic path length.

ResultsWe plot the variability in these measures at each level and find that it consistently increases with intrasession to intersession to interscanner to intersubject effects across all processing approaches and that sometimes interscanner variability can approach intersubject variability.

ConclusionsThis study demonstrates the potential of MASiVar to more globally investigate DWI variability across multiple levels and processing approaches simultaneously and suggests harmonization between scanners for multisite analyses should be considered prior to inference of group differences on subjects.


title: Identification of a High-frequency Intra-host SARS-CoV-2 spike Variant with Enhanced Cytopathic and Fusogenic Effect

abstract:
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that is continuously evolving. Although its RNA-dependent RNA polymerase exhibits some exonuclease proofreading activity, viral sequence diversity can be produced by replication errors and host factors. A diversity of genetic variants can be observed in the intra-host viral population structure of infected individuals. Most mutations will follow a neutral molecular evolution and wont make significant contributions to variations within and between infected hosts. Herein, we profiled the intra-sample genetic diversity of SARS-CoV-2 variants using high-throughput sequencing datasets from 15,289 infected individuals and infected cell lines. Most of the genetic variations observed, including C->U and G->U, were consistent with errors due to heat-induced DNA damage during sample processing and/or sequencing protocols. Despite high mutational background, we identified recurrent intra-variable positions in the samples analyzed, including several positions at the end of the gene encoding the viral Spike (S) protein. Strikingly, we observed a high-frequency C->A missense mutations resulting in the S protein lacking the last 20 amino acids (S{Delta}20). We found that this truncated S protein undergoes increased processing and increased syncytia formation, presumably due to escaping M protein retention in intracellular compartments. Our findings suggest the emergence of a high-frequency viral sublineage that is not horizontally transmitted but potentially involved in intra-host disease cytopathic effects.

IMPORTANCEThe mutation rate and evolution of RNA viruses correlate with viral adaptation. While most mutations do not have significant contributions to viral molecular evolution, some are naturally selected and cause a genetic drift through positive selection. Many recent SARS-CoV-2 variants have been recently described and show phenotypic selection towards more infectious viruses. Our study describes another type of variant that does not contribute to inter-host heterogeneity but rather phenotypic selection toward variants that might have increased cytopathic effects. We identified that a C-terminal truncation of the Spike protein removes an important ER-retention signal, which consequently results in a Spike variant that easily travels through the Golgi toward the plasma membrane in a pre-activated conformation, leading to increased syncytia formation.


title: Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation

abstract:
Systems memory consolidation involves the transfer of memories across brain regions and the transformation of memory content. For example, declarative memories that transiently depend on the hippocampal formation are transformed into long-term memory traces in neocortical networks, and procedural memories are transformed within cortico-striatal networks. These consolidation processes are thought to rely on replay and repetition of recently acquired memories, but the cellular and network mechanisms that mediate the changes of memories are poorly understood. Here, we suggest that systems memory consolidation could arise from Hebbian plasticity in networks with parallel synaptic pathways -- two ubiquitous features of neural circuits in the brain. We explore this hypothesis in the context of hippocampus-dependent memories. Using computational models and mathematical analyses, we illustrate how memories are transferred across circuits and discuss why their representations could change. The analyses suggest that Hebbian plasticity mediates consolidation by transferring a linear approximation of a previously acquired memory into a parallel pathway. Our modelling results are further in quantitative agreement with lesion studies in rodents. Moreover, a hierarchical iteration of the mechanism yields power-law forgetting -- as observed in psychophysical studies in humans. The predicted circuit mechanism thus bridges spatial scales from single cells to cortical areas and time scales from milliseconds to years.

Author summaryAfter new memories are acquired, they can be transferred over time into other brain areas -- a process called systems memory consolidation. For example, new declarative memories, which refer to the conscious memory of facts and events, depend on the hippocampus. Older declarative memories, however, also rely on neocortical networks. The cellular mechanisms underlying such a transfer are poorly understood. In this work, we show that a simple and in the brain ubiquitous connectivity pattern, combined with a standard learning rule, leads to gradual memory transfer. We illustrate our proposed mechanism in numerical simulations and mathematical analyses. At the neurophysiological level, our theory explains experimental findings on memory storage in the hippocampal formation when specific pathways between neural populations are disrupted. At the psychophysical level, we can account for the power-law forgetting curves typically found in humans. A consequence of the proposed model is that consolidated memories can yield faster responses because they are stored in increasingly shorter synaptic pathways between sensory and motor areas. By giving a mechanistic explanation of the consolidation process, we contribute to the understanding of the transfer of memories and the reorganization of memories over time.


title: Efferent control of hearing sensitivity and protection via inner ear supporting cells

abstract: It is well-known that medial olivocochlear (MOC) efferent nerves innervate outer hair cells (OHCs) and inhibit OHC electromotility to control hearing sensitivity. Here, we report that the MOC nerve fibers associated with MOC neurotransmitter acetylcholine (ACh) receptors and presynaptic vesicular acetylcholine transporters (VAChT) also innervated the cochlear supporting cells (SCs). Application of ACh could evoke inward currents in SCs and reduced gap junctions (GJs) between them with long-lasting effect. We further found that uncoupling of GJs between SCs shifted OHC electromotility to the left hyperpolarization direction and enhanced the direct effect of ACh on OHC electromotility. Diminution of this control by deficiency of GJs between SCs compromised the regulation of active cochlear amplification and increased susceptibility to noise. These data suggest that the MOC efferent system has functional innervations with SCs. Such efferent innervation may have an important role in the protection of hearing from noise and slow efferent effect.


title: Ca2+-dependent mechanism of membrane insertion and destabilization by the SARS-CoV-2 fusion peptide

abstract:
Cell penetration after recognition of the SARS-CoV-2 virus by the ACE2 receptor, and the fusion of its viral envelope membrane with cellular membranes, are the early steps of infectivity. A region of the Spike protein (S) of the virus, identified as the "fusion peptide" (FP), is liberated at its N-terminal site by a specific cleavage occurring in concert with the interaction of the receptor binding domain of the Spike. Studies have shown that penetration is enhanced by the required binding of Ca2+ ions to the FPs of corona viruses, but the mechanisms of membrane insertion and destabilization remain unclear. We have predicted the preferred positions of Ca2+ binding to the SARS-CoV-2-FP, the role of Ca2+ ions in mediating peptide-membrane interactions, the preferred mode of insertion of the Ca2+-bound SARS-CoV-2-FP and consequent effects on the lipid bilayer from extensive atomistic molecular dynamics (MD) simulations and trajectory analyses. In a systematic sampling of the interactions of the Ca2+-bound peptide models with lipid membranes SARS-CoV-2-FP penetrated the bilayer and disrupted its organization only in two modes involving different structural domains. In one, the hydrophobic residues F833/I834 from the middle region of the peptide are inserted. In the other, more prevalent mode, the penetration involves residues L822/F823 from the LLF motif which is conserved in CoV-2-like viruses, and is achieved by the binding of Ca2+ ions to the D830/D839 and E819/D820 residue pairs. FP penetration is shown to modify the molecular organization in specific areas of the bilayer, and the extent of membrane binding of the SARS-CoV-2 FP is significantly reduced in the absence of Ca2+ ions. These findings provide novel mechanistic insights regarding the role of Ca2+ in mediating SARS-CoV-2 fusion and provide a detailed structural platform to aid the ongoing efforts in rational design of compounds to inhibit SARS-CoV-2 cell entry.

STATEMENT OF SIGNIFICANCESARS-CoV-2, the cause of the COVID-19 pandemic, penetrates host cell membranes and uses viral-to-cellular membrane fusion to release its genetic material for replication. Experiments had identified a region termed "fusion peptide" (FP) in the Spike proteins of coronaviruses, as the spearhead in these initial processes, and suggested that Ca2+ is needed to support both functions. Absent structure and dynamics-based mechanistic information these FP functions could not be targeted for therapeutic interventions. We describe the development and determination of the missing information from analysis of extensive MD simulation trajectories, and propose specific Ca2+-dependent mechanisms of SARS-CoV-2-FP membrane insertion and destabilization. These results offer a structure-specific platform to aid the ongoing efforts to use this target for the discovery and/or of inhibitors.


title: Quadratic Mutual Information estimation of mouse dLGN receptive fields reveals asymmetry between ON and OFF visual pathways

abstract: The longstanding theory of "parallel processing" predicts that, except for a sign reversal, ON and OFF cells are driven by a similar pre-synaptic circuit and have similar visual field coverage, direction/orientation selectivity, visual acuity and other functional properties. However, recent experimental data challenges this view. Here we present an information theory based receptive field (RF) estimation method - quadratic mutual information (QMI) - applied to multi-electrode array electrophysiological recordings from the mouse dorsal lateral geniculate nucleus (dLGN). This estimation method provides more accurate RF estimates than the commonly used Spike-Triggered Average (STA) method, particularly in the presence of spatially correlated inputs. This improved efficiency allowed a larger number of RFs (285 vs 189 cells) to be extracted from a previously published dataset. Fitting a spatial-temporal Difference-of-Gaussians (ST-DoG) model to the RFs revealed that while the structural RF properties of ON and OFF cells are largely symmetric, there were some asymmetries apparent in the functional properties of ON and OFF visual processing streams - with OFF cells preferring higher spatial and temporal frequencies on average, and showing a greater degree of orientation selectivity.


title: Spatial distribution of local patch extinctions drives recovery dynamics in metacommunities

abstract:
Human activities lead more and more to the disturbance of plant and animal communities with local extinctions as a consequence. While these negative effects are clearly visible at a local scale, it is less clear how such local patch extinctions affect regional processes, such as metacommunity dynamics and the distribution of diversity in space. Since local extinctions may not be isolated events in space but rather cluster together, it is crucial to investigate their effects in a spatially explicit framework.

Here, we use experimental microcosms and numerical simulations to understand the relationship between local patch extinctions and metacommunity dynamics. More specifically, we investigate the effects of the amount and spatial autocorrelation of extinctions in a full factorial design. Experimentally, we found that local patch extinctions increased inter-patch ({beta}-) diversity by creating differences between perturbed and unperturbed patches and at the same time increased local (-) diversity by delaying the competitive exclusion of inferior competitors. Most importantly, recolonization dynamics depended more strongly on the spatial distribution of patch extinctions than on the amount of extinctions per se. Clustered local patch extinctions reduced mixing between perturbed and unperturbed patches which led to slower recovery, lower -diversity in unperturbed patches and higher {beta}-diversity. Results from a metacommunity model matched the experimental observations qualitatively when the model included ranked competitive interactions, giving a hint at the underlying mechanisms.

Our results highlight that local patch extinctions can increase the diversity within and between communities, that the strength of these effects depends on the spatial distribution of extinctions and that the effects of local patch extinctions can spread regionally, throughout a landscape. These findings are highly relevant for conservation and management of spatially structured communities under global change.

category: ecology


title: Minimal information for Chemosensitivity assays (MICHA): A next-generation pipeline to enable the FAIRification of drug screening experiments

abstract: Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of MICHA (Minimal Information for Chemosensitivity Assays), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents, and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets, and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies, as well as six recently conducted COVID-19 studies. With the MICHA webserver and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.


title: In vivo Evaluation and in silico Prediction of the Toxicity of Drepanoalpha Hard capsules

abstract:
GRAPHICAL ABSTRACT

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org.highwire.dtl.DTLVardef@12dbf1aorg.highwire.dtl.DTLVardef@5d6e9forg.highwire.dtl.DTLVardef@9ba26org.highwire.dtl.DTLVardef@9c2017_HPS_FORMAT_FIGEXP  M_FIG C_FIG ABSTRACTO_ST_ABSEthnopharmacological relevanceC_ST_ABSDrepanoalpha(R) hard capsules, a dry ethanolic extract (drug-extract ratio, 100/11) of a mixture of Justicia secunda Vahl and Moringa oleifera Lam dried leaves (1: 1, w/w) are used for the management of sickle cell disease in the Democratic Republic of Congo.

Aim of the studyThis phytomedicine safety was investigated by acute and sub-acute administration in Guinea pigs.

Materials and methodsHealthy, male and nulliparous and non-pregnant female Guinea pigs were obtained from "Laboratory of Animal Experimentation and Toxicology" of the Department of Biology, Faculty of Sciences, University of Kinshasa. The animals were randomly selected, marked and divided into 2 groups of 5 animals each (3 males and 2 females) and 4 groups of 3 animals each for acute and sub-acute toxicity studies, respectively. The contents of hard capsules were dissolved in normal saline solution (NaCl 9 {per thousand}). Animals received by gavage a single dose of 5000 mg/ kg of body weight (B.W.) of Drepanoalpha(R) hard capsules (acute toxicity) and 125 mg/ kg, 250 mg/ kg and 500 mg/ kg of B.W. twice daily for 28 days (sub-acute toxicity). Normal saline solution was used as control. Hematological, biochemical and histopathological analyses were performed and the behavior of the animals was observed after treatment.

ResultsThe median lethal dose (LD50) is higher than 5000 mg/ kg of B.W., and the relative weights of vital organs (kidneys, liver and heart) collected from Guinea pigs at the end of treatment on D14 (acute toxicity) and D28 (sub-acute toxicity) has not undergone significant changes (p > 0.05). The results of haematological (red and white blood cells counts, haemoglobin, haematocrit) and biochemical (ALT, AST, albumin, total protein) tests did not show significant differences between control and test groups (=0.05 for acute toxicity), while the histopathological study revealed no damage to the various organs excised.

ConclusionThe results indicate the safety of Drepanoalpha(R) hard capsules, confirming previous studies, in rats and Guinea pigs, based on aqueous decoction of its raw herbs mixtures and the corresponding lyophilizate.

category: pharmacology and toxicology


title: Co-regulating many properties by co-adjusting few ion channels increases ion channel correlations and the risk of regulation failure

abstract: Neurons regulate their excitability by adjusting their ion channel levels. Degeneracy - achieving equivalent outcomes (excitability) using different solutions (channel combinations) - facilitates this regulation by enabling a disruptive change in one channel to be offset by compensatory changes in other channels. But neurons must co-regulate many properties. Pleiotropy - the impact of one channel on more than one property - complicates regulation because a compensatory ion channel change that restores one property to its target value often disrupts other properties. How then does a neuron simultaneously regulate multiple properties? Here we demonstrate that of the many channel combinations producing the target value for one property (the single-output solution set), few combinations produce the target value for other properties. Combinations producing the target value for two or more properties (the multi-output solution set) correspond to the intersection between single-output solution sets. Properties can be effectively co-regulated only if the number of adjustable channels (nin) exceeds the number of regulated properties (nout). Ion channel correlations emerge during homeostatic regulation when the dimensionality of solution space (nin - nout) is low. Even if each property can be regulated to its target value when considered in isolation, regulation as a whole fails if single-output solution sets do not intersect. Our results also highlight that ion channels must be co-adjusted with different ratios to regulate different properties, which suggests that each error signal drives modulatory changes independently, despite those changes ultimately affecting the same ion channels.


title: Minimal requirements for a neuron to co-regulate many properties and the implications for ion channel correlations and robustness


title: Easy to interpret Coordinate Based Meta-Analysis of neuroimaging studies: Analysis of Brain Coordinates (ABC)

abstract: Functional MRI and voxel-based morphometry (VBM) are important approaches to testing hypotheses in neuroscience, helping us to understand neurological disease, and brain function and development. However, they are technically challenging with no one optimal generalisable method, and the multiple popular techniques have been shown to produce different results. Furthermore, results may be sensitive to settings, such as smoothing or statistical thresholding, that can be difficult to optimise per hypothesis. It is useful, therefore, to be able to meta-analyse published results from such studies that tested a similar hypothesis potentially using different analysis methods, scanners, and protocols as well as different subjects. Coordinate based meta-analysis (CBMA) offers this using only commonly reported summary results. It is the aim of CBMA to find those results that indicate replicable effects across studies. However, just like the multiple analysis methods offered for neuroimaging, there are now multiple CBMA algorithms each with specific features and empirical parameters/assumptions. Results derived from CBMA are inevitably conditional on the algorithm used, so conclusions are clearer when the analysis approach is easy to understand. With this in mind a new CBMA method (Analysis of Brain Coordinates; ABC) is presented, with the aim of being easy to interpret by eliminating empirical assumptions where possible and by relating statistical thresholding directly to replication of effect.


title: Predicting lineage-specific differences in open chromatin across dozens of mammalian genomes

abstract:
BackgroundEvolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation at many enhancers, distal regulatory elements that control spatio-temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific, code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.

ResultsWe present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that is able to predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Then, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity and liver enhancers associated with liver regeneration have a stronger tendency than the general population to have predicted lineage-specific open chromatin.

ConclusionThe framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.

category: genetics


title: Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin


title: De novo macrocyclic peptides for inhibiting, stabilising and probing the function of the Retromer endosomal trafficking complex

abstract: The Retromer complex (Vps35-Vps26-Vps29) is essential for endosomal membrane trafficking and signalling. Mutations in Retromer cause late-onset Parkinsons disease, while viral and bacterial pathogens can hijack the complex during cellular infection. To modulate and probe its function we have created a novel series of macrocyclic peptides that bind Retromer with high affinity and specificity. Crystal structures show the majority of cyclic peptides bind to Vps29 via a Pro-Leu-containing sequence, structurally mimicking known interactors such as TBC1D5, and blocking their interaction with Retromer in vitro and in cells. By contrast, macrocyclic peptide RT-L4 binds Retromer at the Vps35-Vps26 interface and is a more effective molecular chaperone than reported small molecules, suggesting a new therapeutic avenue for targeting Retromer. Finally, tagged peptides can be used to probe the cellular localisation of Retromer and its functional interactions in cells, providing novel tools for studying Retromer function.

category: biochemistry