title: Genes with 5' terminal oligopyrimidine tracts preferentially escape global suppression of translation by the SARS-CoV-2 NSP1 protein

abstract: Viruses rely on the host translation machinery to synthesize their own proteins. Consequently, they have evolved varied mechanisms to co-opt host translation for their survival. SARS-CoV-2 relies on a non-structural protein, Nsp1, for shutting down host translation. However, it is currently unknown how viral proteins and host factors critical for viral replication can escape a global shutdown of host translation. Here, using a novel FACS-based assay called MeTAFlow, we report a dose-dependent reduction in both nascent protein synthesis and mRNA abundance in cells expressing Nsp1. We perform RNA-Seq and matched ribosome profiling experiments to identify gene-specific changes both at the mRNA expression and translation level. We discover a functionally-coherent subset of human genes are preferentially translated in the context of Nsp1 expression. These genes include the translation machinery components, RNA binding proteins, and others important for viral pathogenicity. Importantly, we uncovered a remarkable enrichment of 5' terminal oligo-pyrimidine (TOP) tracts among preferentially translated genes. Using reporter assays, we validated that 5 UTRs from TOP transcripts can drive preferential expression in the presence of NSP1. Finally, we found that LARP1, a key effector protein in the mTOR pathway may contribute to preferential translation of TOP transcripts in response to Nsp1 expression. Collectively, our study suggests fine tuning of host gene expression and translation by Nsp1 despite its global repressive effect on host protein synthesis.


title: SARS CoV-2 nucleocapsid protein forms condensates with viral genomic RNA

abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes COVID-19, a pandemic that seriously threatens global health. SARS-CoV-2 propagates by packaging its RNA genome into membrane enclosures in host cells. The packaging of the viral genome into the nascent virion is mediated by the nucleocapsid (N) protein, but the underlying mechanism remains unclear. Here, we show that the N protein forms biomolecular condensates with viral genomic RNA both in vitro and in mammalian cells. Phase separation is driven, in part, by hydrophobic and electrostatic interactions. While the N protein forms spherical assemblies with unstructured RNA, it forms asymmetric condensates with viral RNA strands that contain secondary structure elements. Cross-linking mass spectrometry identified a region that forms interactions between N proteins in condensates, and truncation of this region disrupts phase separation. We also identified small molecules that alter the formation of N protein condensates. These results suggest that the N protein may utilize biomolecular condensation to package the SARS-CoV-2 RNA genome into a viral particle.

category: biophysics


title: Analysis of actin and focal adhesion organisation in U2OS cells on polymer nanostructures

abstract:
Cells in their natural environment are embedded in a complex surrounding consisting of biochemical and biomechanical cues directing cell properties and cell behaviour. Nonetheless, in vitro cell studies are typically performed on flat surfaces, with clear differences from the more complex situation cells experience in vivo. To increase the physiological relevance of these studies, a number of advanced cellular substrates for in vitro studies have been applied. One of these approaches include flat surfaces decorated with vertically aligned nanostructures.

In this work, we explore how U2OS cells are affected by arrays of polymer nanopillars fabricated on flat glass surfaces. We focus on describing changes to the organisation of the actin cytoskeleton and in the location, number and shape of focal adhesions. From our findings we identify that the cells can be categorised into different regimes based on their spreading and adhesion behaviour on nanopillars. A quantitative analysis suggests that cells seeded on dense nanopillar arrays are suspended on top of the pillars with focal adhesions forming closer to the cell periphery compared to flat surfaces or sparse pillar arrays. This change is analogous to similar responses for cells seeded on soft substrates.

Overall, we show that the combination of high throughput nanofabrication, advanced optical microscopy, molecular biology tools to visualise cellular processes and data analysis can be used to investigate how cells interact with nanostructured surfaces and will in the future help to create culture substrates that induce particular cell function.


title: Non-permissive SARS-CoV-2 infection in human neurospheres

abstract: Coronavirus disease 2019 (COVID-19) was initially described as a viral infection of the respiratory tract. It is now known, however, that several other organs are affected, including the brain. Neurological manifestations such as stroke, encephalitis, and psychiatric conditions have been reported in COVID-19 patients, but the neurotropic potential of the virus is still debated. Herein, we sought to investigate SARS-CoV-2 infection in human neural cells. We demonstrated that SARS-CoV-2 infection of neural tissue is non-permissive, however, it can elicit inflammatory response and cell damage. These findings add to the hypothesis that most of the neural damage caused by SARS-CoV-2 infection is due to a systemic inflammation leading to indirect harmful effects on the central nervous system despite the absence of local viral replication.

category: neuroscience


title: Single-component, self-assembling, protein nanoparticles presenting the receptor binding domain and stabilized spike as SARS-CoV-2 vaccine candidates

abstract:
Vaccination against SARS-CoV-2 provides an effective tool to combat the COIVD-19 pandemic. Here, we combined antigen optimization and nanoparticle display to develop vaccine candidates for SARS-CoV-2. We first displayed the receptor-binding domain (RBD) on three self-assembling protein nanoparticle (SApNP) platforms using the SpyTag/SpyCatcher system. We then identified heptad repeat 2 (HR2) in S2 as the cause of spike metastability, designed an HR2-deleted glycine-capped spike (S2G{Delta}HR2), and displayed S2G{Delta}HR2 on SApNPs. An antibody column specific for the RBD enabled tag-free vaccine purification. In mice, the 24-meric RBD-ferritin SApNP elicited a more potent neutralizing antibody (NAb) response than the RBD alone and the spike with two stabilizing proline mutations in S2 (S2P). S2G{Delta}HR2 elicited two-fold-higher NAb titers than S2P, while S2G{Delta}HR2 SApNPs derived from multilayered E2p and I3-01v9 60-mers elicited up to 10-fold higher NAb titers. The S2G{Delta}HR2-presenting I3-01v9 SApNP also induced critically needed T-cell immunity, thereby providing a promising vaccine candidate.

ONE-SENTENCE SUMMARYThe SARS-CoV-2 receptor binding domain and S2G{Delta}HR2 spike elicited potent immune responses when displayed on protein nanoparticles as vaccine candidates.

category: microbiology


title: Linking mountaintop removal mining to water quality for imperiled species using satellite data

abstract: Environmental laws need sound data to protect species and ecosystems. In 1996, a proliferation of mountaintop removal coal mines in a region home to over 50 federally protected species was approved under the Endangered Species Act. Although this type of mining can degrade terrestrial and aquatic habitats, the available data and tools limited the ability to analyze spatially extensive, aggregate effects of such a program. We used two large, public datasets to quantify the relationship between mountaintop removal coal mining and water quality measures important to the survival of imperiled species at a landscape scale across Kentucky, Tennessee, Virginia, and West Virginia. We combined an annual map of the extent of surface mines in this region from 1985 to 2015 generated from Landsat satellite imagery with public water quality data collected over the same time period from 4,260 monitoring stations within the same area. The water quality data show that chronic and acute thresholds for levels of aluminum, arsenic, cadmium, conductivity, copper, lead, manganese, mercury, pH, selenium, and zinc safe for aquatic life were exceeded thousands of times between 1985 and 2015 in streams that are important to the survival and recovery of species on the Endangered Species List. Linear mixed models showed that levels of manganese, sulfate, sulfur, total dissolved solids, total suspended solids, and zinc increased by 6.73E+01 to 6.87E+05 {micro}g/L and conductivity by 3.30E+06 {micro}S /cm for one percent increase in the mined proportion of the area draining into a monitoring station. The proportion of a drainage area that was mined also increased the likelihood that chronic thresholds for copper, lead, and zinc required to sustain aquatic life were exceeded. Finally, the proportion of a watershed that was mined was positively related to the likelihood that a waterway would be designated as impaired under the Clean Water Act. Together these results demonstrate that the extent of mountaintop removal mining, which can be derived from public satellite data, is predictive of water quality measures important to imperiled species - effects that must be considered under environmental law. These findings and the public data used in our analyses are pertinent to ongoing re-evaluations of the effects of current mine permitting regulations to the recovery and survival of federally protected species.

category: ecology


title: Functional assessment of the "two-hit" model for neurodevelopmental defects in Drosophila and X. laevis

abstract:
We previously identified a deletion on chromosome 16p12.1 that is mostly inherited and associated with multiple neurodevelopmental outcomes, where severely affected probands carried an excess of rare pathogenic variants compared to mildly affected carrier parents. We hypothesized that the 16p12.1 deletion sensitizes the genome for disease, while "second-hits" in the genetic background modulate the phenotypic trajectory. To test this model, we examined how neurodevelopmental defects conferred by knockdown of individual 16p12.1 homologs are modulated by simultaneous knockdown of homologs of "second-hit" genes in Drosophila melanogaster and Xenopus laevis. We observed that knockdown of 16p12.1 homologs affect multiple phenotypic domains, leading to delayed developmental timing, seizure susceptibility, brain alterations, abnormal dendrite and axonal morphology, and cellular proliferation defects. Compared to genes within the 16p11.2 deletion, which has higher de novo occurrence, 16p12.1 homologs were less likely to interact with each other in Drosophila models or a human brain-specific interaction network, suggesting that interactions with "second-hit" genes may confer higher impact towards neurodevelopmental phenotypes. Assessment of 212 pairwise interactions in Drosophila between 16p12.1 homologs and 76 homologs of patient-specific "second-hit" genes (such as ARID1B and CACNA1A), genes within neurodevelopmental pathways (such as PTEN and UBE3A), and transcriptomic targets (such as DSCAM and TRRAP) identified genetic interactions in 63% of the tested pairs. In 11 out of 15 families, homologs of patient-specific "second-hits" enhanced or suppressed the phenotypic effects of one or many 16p12.1 homologs. In fact, homologs of SETD5 synergistically interacted with homologs of MOSMO in both Drosophila and X. laevis, leading to modified cellular and brain phenotypes, as well as axon outgrowth defects that were not observed with knockdown of either individual homolog. Our results suggest that several 16p12.1 genes sensitize the genome towards neurodevelopmental defects, and complex interactions with "second-hit" genes determine the ultimate phenotypic manifestation.

Author SummaryCopy-number variants, or deletions and duplications in the genome, are associated with multiple neurodevelopmental disorders. The developmental delay-associated 16p12.1 deletion is mostly inherited, and severely affected children carry an excess of "second-hits" variants compared to mildly affected carrier parents, suggesting that additional variants modulate the clinical manifestation. We studied this "two-hit" model using Drosophila and Xenopus laevis, and systematically tested how homologs of "second-hit" genes modulate neurodevelopmental defects observed for 16p12.1 homologs. We observed that 16p12.1 homologs independently led to multiple neurodevelopmental features and weakly interacted with each other, suggesting that interactions with "second-hit" homologs potentially have a higher impact towards neurodevelopmental defects than interactions between 16p12.1 homologs. We tested 212 pairwise interactions of 16p12.1 homologs with "second-hit" homologs and genes within conserved neurodevelopmental pathways, and observed modulation of neurodevelopmental defects caused by 16p12.1 homologs in 11 out of 15 families, and 16/32 of these changes could be attributed to genetic interactions. Interestingly, we observed that SETD5 homologs interacted with homologs of MOSMO, which conferred additional neuronal phenotypes not observed with knockdown of individual homologs. We propose that the 16p12.1 deletion sensitizes the genome to multiple neurodevelopmental defects, and complex interactions with "second-hit" genes determine the clinical trajectory of the disorder.

category: genomics


title: The adaptive value of tandem communication in ants: insights from an agent-based model

abstract: Social animals often share information about the location of resources, such as a food source or a new nest-site. One well-studied communication strategy in ants is tandem running, whereby a leader guides a recruit to a resource. Tandem running is considered an example of animal teaching because a leader adjusts her behaviour and invests time to help another ant to learn the location of a resource more efficiently. Tandem running also has costs, such as waiting inside the nest for a leader and a reduced walking speed. Whether and when these costs outweigh the benefits of tandem running is not well understood. We developed an agent-based simulation model to investigate the conditions that favour communication by tandem running during foraging. We predicted that the spatio-temporal distribution of food sources, colony size and the ratio of scouts and recruits affect colony foraging success. Our results suggest that communication is favoured when food sources are hard to find, of variable quality and long lasting. These results mirror the findings of simulations of honeybee communication. Scouts locate food sources faster than tandem followers in some environments, suggesting that tandem running may fulfil the criteria of teaching only in some situations. Furthermore, tandem running was only beneficial above a critical colony size threshold. Taken together, our model suggests that there is a considerable parameter range that favours colonies that do not use communication, which could explain why many social insects with small colony sizes forage solitarily.

category: animal behavior and cognition


title: Computationally Grafting an IgE Epitope onto a Scaffold: Implications for a Pan Anti-Allergy Vaccine Design

abstract: Allergy is becoming an intensifying disease among the world population, particularly in the developed world. Once allergy develops, sufferers are permanently trapped in a hyper-immune response that makes them sensitive to innocuous substances, such as the protein cupin in peanuts. The immune pathway concerned with developing allergy is the Th2 immune pathway where the IgE antibody (targeting innocuous substances) binds to its Fc{varepsilon}RI receptor on Mast and Basophil cells. Currently, there is not a permanent treatment for allergies. This paper discusses a strategy and a protocol that could disrupt the binding between the antibody and its receptor for a potential permanent treatment. Ten proteins were computationally designed to display a human IgE motif very close in proximity to the IgE antibodiess Fc{varepsilon}RI receptors binding site in an effort for these proteins to be used as a vaccine against our own IgE antibody. The motif of interest was the FG motif and it was excised and grafted onto a Staphylococcus aureus protein (PDB ID 1YN3). The new structures (motif + scaffold) had their sequences re-designed around the motif to find an amino acid sequence that would fold to the designed structures correctly. These ten computationally designed proteins showed successful folding when simulated using Rosettas AbinitioRelax folding simulation and the IgE epitope was clearly displayed in its native three-dimensional structure in all of them. These designed proteins have the potential to be used as a pan anti-allergy vaccine by guiding the immune system towards developing antibodies against the bodys own IgE antibody, thus neutralising it, and presumably permanently shutting down a major aspect of the Th2 immune pathway. This work employed in silico based methods for designing the proteins and did not include any experimental verifications.

category: bioinformatics


title: ComMet: A method for comparing metabolic states in genome-scale metabolic models

abstract: Being comprehensive knowledge bases of cellular metabolism, Genome-scale metabolic models (GEMs) serve as mathematical tools for studying cellular flux states in various organisms. However, analysis of large-scale (human) GEMs, still presents considerable challenges with respect to objective selection and reaction flux constraints. In this study, we introduce a model-based method, ComMet (Comparison of Metabolic states), for comprehensive analysis of large metabolic flux spaces and comparison of various metabolic states. ComMet allows (a) an in-depth characterisation of achievable flux states, (b) comparison of flux spaces from several conditions of interest and (c) identification and visualization of metabolically distinct network modules. As a proof-of-principle, we employed ComMet to extract the biochemical differences in the human adipocyte network (iAdipocytes1809) arising due to unlimited/blocked uptake of branched-chain amino acids. Our study opens avenues for exploring several metabolic conditions of interest in both microbe and human models. ComMet is open-source and is available at https://github.com/macsbio/commet.

category: systems biology


title: Phosphorylation of luminal region of the SUN-domain protein Mps3 promotes nuclear envelope localization during meiosis

abstract: During meiosis, protein ensembles in the nuclear envelope (NE) containing SUN- and KASH-domain proteins, called linker nucleocytoskeleton and cytoskeleton (LINC) complex, promote the chromosome motion. Yeast SUN-domain protein, Mps3, forms multiple meiosis-specific ensembles on NE, which show dynamic localisation for chromosome motion; however, the mechanism by which these Mps3 ensembles are formed during meiosis remains largely unknown. Here, we showed that the cyclin-dependent protein kinase (CDK) and Dbf4-dependent Cdc7 protein kinase (DDK) regulate meiosis-specific dynamics of Mps3 on NE, particularly by mediating the resolution of Mps3 clusters and telomere clustering. We also found that the luminal region of Mps3 juxtaposed to the inner nuclear membrane is required for meiosis-specific localisation of Mps3 on NE. Negative charges introduced by meiosis-specific phosphorylation in the luminal region of Mps3 alter its interaction with negatively charged lipids by electric repulsion in reconstituted liposomes. Phospho-mimetic substitution in the luminal region suppresses the localisation of Mps3 via the inactivation of CDK or DDK. Our study revealed multi-layered phosphorylation-dependent regulation of the localisation of Mps3 on NE for meiotic chromosome motion and NE remodelling.

category: molecular biology


title: PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images

abstract:
PurposeDiffusion weighted MRI imaging (DWI) is often subject to low signal-to-noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document.

MethodsThe proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter-scan intensity normalization; susceptibility-, eddy current-, and motion-induced artifact correction; and slice-wise signal drop-out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness-of-fit and fractional anisotropy analyses.

ResultsRaw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility-, eddy current-, and motion-induced artifacts; imputed signal-lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file-type conversion errors and was shown to be effective on externally available datasets.

ConclusionThe proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI-focused software packages with intuitive QA.

category: bioengineering


title: Contextual effects in motor adaptation adhere to associative learning rules

abstract:
Traditional associative learning tasks focus on the formation of associations between salient events and arbitrary stimuli that predict those events. This is exemplified in cerebellar-dependent delay eyeblink conditioning, where arbitrary cues such as a light or tone act as conditioning stimuli that predict aversive sensations at the cornea. Here we ask if a similar framework could be applied to another type of cerebellar-dependent sensorimotor learning- sensorimotor adaptation. Models of sensorimotor adaptation posit that the introduction of an environmental perturbation results in an error signal that is used to update an internal model of a sensorimotor map for motor planning. Here we take a step towards an integrative account of these two forms of cerebellar-dependent learning, examining the relevance of core concepts from associative learning for sensorimotor adaptation. Using a visuomotor adaptation reaching task, we paired movement-related feedback with neutral auditory or visual contextual cues that served as conditioning stimuli (CSs). Trial-by trial changes in feedforward movement kinematics exhibited two key signatures of associative learning: Differential conditioning and compound conditioning. Moreover, after compound conditioning, a robust negative correlation was observed between responses to the two elemental CSs of the compound (i.e., overshadowing), consistent with the additivity principle posited by theories of associative learning. The existence of associative learning effects in sensorimotor adaptation provides a proof-of-concept for linking cerebellar-dependent learning paradigms within a common theoretical framework.

IMPACT STATEMENTCore associative learning phenomena that are observed in studies of eyeblink conditioning are also observed in sensorimotor adaptation, pointing to a common framework for these distinct cerebellar-dependent motor learning processes.


title: Contextual effects in sensorimotor adaptation adhere to associative learning rules


title: Transcriptional alterations in opioid use disorder reveal an interplay between neuroinflammation and synaptic remodeling

abstract:
BackgroundPrevalence rates of opioid use disorder (OUD) have increased dramatically, accompanied by a surge of overdose deaths. While opioid dependence has been extensively studied in preclinical models, an understanding of the biological alterations that occur in the brains of people who chronically use opioids and who are diagnosed with OUD remains limited. To address this limitation, RNA-sequencing (RNA-seq) was conducted on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc), regions heavily implicated in OUD, from postmortem brains in subjects with OUD.

MethodsWe performed RNA-seq on the DLPFC and NAc from unaffected comparison subjects (n=20) and subjects diagnosed with OUD (n=20). Our transcriptomic analyses identified differentially expressed (DE) transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric ordering (RRHO). Weighted gene co-expression analyses (WGCNA) also identified OUD-specific modules and gene networks. Integrative analyses between DE transcripts and GWAS datasets using linkage disequilibrium score (LDSC) assessed the genetic liability psychiatric-related phenotypes.

ResultsRRHO analyses revealed extensive overlap in transcripts between DLPFC and NAc in OUD, primarily relating to synaptic remodeling and neuroinflammation. Identified transcripts were enriched for factors that control pro-inflammatory cytokine-mediated, chondroitin sulfate, and extracellular matrix signaling. Cell-type deconvolution implicated a role for microglia as a critical driver for opioid-induced neuroplasticity. Using LDSC, we discovered genetic liabilities for risky behavior, attention deficit hyperactivity disorder, and depression.

ConclusionsOverall, our findings reveal new connections between the brains immune system and opioid dependence in the human brain.


title: Dynamic gene expression and growth underlie cell-to-cell heterogeneity in Escherichia coli stress response

abstract: Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is important because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found several examples of pulsatile expression. Single-cell growth rates were often anti-correlated with gene expression, with changes in growth preceding changes in expression. These expression and growth dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that fluctuations in gene expression and growth dynamics in stress response networks can have direct consequences for survival.


title: The potential of parrotfish faeces in replenishing reefs with coral-associated microbiome

abstract: Sparisoma viride is the most abundant parrotfish in the Caribbean and is considered as the most important excavator due to corallivore behaviour. Parrotfishes are a keystone group that favour the growth and resilience of coral reefs removing macroalgae and structuring the benthic communities. The microbial symbiotic communities are involved in multiple functions related to nutrition and immunity maintaining corals health. Because S. viride scrape coral tissues, the skeleton and the algae on coral, it could be important reservoirs or vectors of microorganism for the corals through the faeces dispersion, however, the role of parrotfishes as reservoirs are poorly studied. Establishing microbial communities present in parrotfish faeces will contribute to understand the ecological impact of parrotfishes in coral resilience. We investigated the composition of disseminated bacteria and the extent to which the cell integrity of dinoflagellate photosymbionts (Symbiodiniaceae) is maintained in the faeces and compare with sediments and water column controls. Then, we analysed diversity and structure of bacterial communities at family level and search similarities between faeces of the study and coral associated microbiome reported in the literature. Similar levels of structural integrity and photosynthetic health of Symbidiodinaceae cells were found in both faeces and reef sediments. Besides, the sediments microbiome echoes the parrotfish faecal microbiome by sharing high diversity and a similar bacterial community composition. Several bacterial families were present in parrotfish faeces and in coral microbiome reported in the literature highlighting the dispersal potential of parrotfishes replenishing coral reefs. Despite the sampling limitations, these findings uncover the potential role of the excavator parrotfish in enriching environmental reservoirs, especially reef sediments, with coral-associated bacteria and photosynthetic microalgae. Parrotfishes could reinforce the coral microbiome and facilitate coral symbiont acquisition, key features critical to maintaining the fitness of one of the most threatened ecosystems on Earth. This finding could be considered as a first step in uncovering a mechanism for reef-microbiome maintenance.


title: Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile

abstract: Though Clostridioides difficile is among the most studied anaerobes, the interplay of metabolism and regulation that underlies its ability to colonize the human gut is unknown. We have compiled public resources into three models and a portal to support comprehensive systems analysis of C. difficile. First, by leveraging 151 transcriptomes from 11 studies we generated a regulatory model (EGRIN) that organizes 90% of C. difficile genes into 297 high quality conditional co-regulation modules. EGRIN predictions, validated with independent datasets, recapitulated and extended regulons of key transcription factors, implicating new genes for sporulation, carbohydrate transport and metabolism. Second, by advancing a metabolic model, we discovered that 15 amino acids, diverse carbohydrates, and 10 metabolic genes are essential for C. difficile growth within an intestinal environment. Finally, by integrating EGRIN with the metabolic model, we developed a PRIME model that revealed unprecedented insights into combinatorial control of essential processes for in vivo colonization of C. difficile and its interactions with commensals. We have developed an interactive web portal (http://networks.systemsbiology.net/cdiff-portal/) to disseminate all data, algorithms, and models to support collaborative systems analyses of C. difficile.


title: The piRNA pathway sustains adult neurogenesis by repressing protein synthesis and cellular senescence

abstract: Adult Neural progenitor cells (aNPCs) ensure lifelong neurogenesis in the mammalian hippocampus. Proper regulation of aNPC fate entails important implications for brain plasticity and healthy aging. Piwi proteins and the small noncoding RNAs interacting with them (piRNAs) are best known in gonads as repressors of transposons. Here, we show that Piwil2 (Mili) and piRNAs are abundant in aNPCs of the postnatal mouse hippocampus and demonstrate that this pathway is essential for proper neurogenesis. Particularly, depleting the piRNA pathway in aNPCs impaired neurogenesis, increased senescence and accordingly the generation of reactive glia. Moreover, this manipulation primarily elevated 5S ribosomal RNA, SINEB1 and mRNAs encoding ribosomal proteins and regulators of translation, resulting in higher polysome density and protein synthesis upon differentiation. Our results provide evidence of an essential role for the piRNA pathway in maintaining homeostasis to sustain neural stem cell fate, underpinning its possible involvement in brain plasticity and successful aging.


title: Proteomic analysis of metabolic pathways supports chloroplast-mitochondria cross-talk in a Cu-limited diatom

abstract:
Diatoms are one of the most successful phytoplankton groups in our oceans, being responsible for over 20% of the Earths photosynthetic productivity. Their chimeric genomes have genes derived from red algae, green algae, bacteria and heterotrophs, resulting in multiple isoenzymes targeted to different cellular compartments with the potential for differential regulation under nutrient limitation. The resulting interactions between metabolic pathways are not yet fully understood.

We previously showed how acclimation to Cu limitation enhanced susceptibility to overreduction of the photosynthetic electron transport chain and its reorganization to favor photoprotection over light-harvesting in the oceanic diatom Thalassiosira oceanica (Hippmann et al., 2017). In order to gain a better understanding of the overall metabolic changes that help alleviate the stress of Cu limitation, we have further analyzed the comprehensive proteomic datasets generated in that study to identify differentially expressed proteins involved in carbon, nitrogen and oxidative stress-related metabolic pathways.

Metabolic pathway analysis showed integrated responses to Cu limitation. The up-regulation of ferredoxin (Fdx) was correlated with up-regulation of plastidial Fdx-dependent isoenzymes involved in nitrogen assimilation as well as enzymes involved in glutathione synthesis, thus integrating nitrogen uptake and metabolism with photosynthesis and oxidative stress resistance. The differential expression of glycolytic isoenzymes located in the chloroplast and mitochondria may enable them to channel both excess electrons and/or ATP between these compartments. Additional evidence for chloroplast-mitochondrial cross-talk is the increased expression of chloroplast and mitochondrial proteins involved in the proposed malate shunt under Cu limitation.

One sentence summaryDiatoms adapt to Cu limitation by regulating their large repertoire of isoenzymes to channel electrons away from the chloroplast, enhance nitrogen uptake, and integrate the oxidative stress response. 123


title: Mapping Brain-Behavior Space Relationships Along the Psychosis Spectrum

abstract: Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically-grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 cross-diagnostic PSD patients, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results. Instead, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and gene expression maps. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.


title: Behavioral evidence for nested central pattern generator control of Drosophila grooming

abstract: Central pattern generators (CPGs) are neurons or neural circuits that produce periodic output without requiring patterned input. More complex behaviors can be assembled from simpler subroutines, and nested CPGs have been proposed to coordinate their repetitive elements, organizing control over different time-scales. Here, we use behavioral experiments to establish that Drosophila grooming may be controlled by nested CPGs. On a short time-scale (5-7 Hz), flies execute periodic leg sweeps and rubs. More surprisingly, transitions between bouts of head cleaning and leg rubbing are also periodic on a longer time-scale (0.3 - 0.6 Hz). We examine grooming at a range of temperatures to show that the frequencies of both oscillations increase - a hallmark of CPG control - and also that the two time-scales increase at the same rate, indicating that the nested CPGs may be linked. This relationship also holds when sensory drive is held constant using optogenetic activation, but the rhythms can decouple in spontaneously grooming flies, showing that alternative control modes are possible. Loss of sensory feedback does not disrupt periodicity but slows the longer time-scale alternation. Nested CPGs simplify generation of complex but repetitive behaviors, and identifying them in Drosophila grooming presents an opportunity to map the neural circuits that constitute them.


title: Individualized cyclic mechanical loading improves callus properties during the remodelling phase of fracture healing in mice as assessed from time-lapsed in vivo imaging

abstract: Fracture healing is regulated by mechanical loading. Understanding the underlying mechanisms during the different healing phases is required for targeted mechanical intervention therapies. Here, the influence of individualized cyclic mechanical loading on the remodelling phase of fracture healing was assessed in a mouse femur defect model. After bridging of the defect, a loading group (n=10) received individualized cyclic mechanical loading (8-16 N, 10 Hz, 5 min, 3x/week) based on computed strain distribution in the callus using animal-specific real-time micro-finite element analysis. Controls (n=10) received 0 N treatment at the same post-operative time-points. By registration of consecutive scans, structural and dynamic callus morphometric parameters were followed in three callus sub-volumes and the adjacent cortex showing that the remodelling phase of fracture healing is highly responsive to cyclic mechanical loading with changes in dynamic parameters leading to significantly larger callus formation and mineralization. Loading-mediated maintenance of callus remodelling was associated with distinct effects on Wnt-signalling-associated molecular targets Sclerostin and RANKL in callus sub-regions and the adjacent cortex. Given these distinct local protein expression patterns induced by cyclic mechanical loading, the femur defect loading model with individualized load application seems suitable to understand the local spatio-temporal mechano-molecular regulation of the different fracture healing phases.


title: RuBisCO adaptation is more limited by phylogenetic constraint than by catalytic trade-off

abstract: Rubisco assimilates CO2 to form the sugars that fuel life on earth. Correlations between rubisco kinetic traits across species have led to the proposition that rubisco adaptation is highly constrained by catalytic trade-offs. However, these analyses did not consider the phylogenetic context of the enzymes that were analysed. Thus, it is possible that the correlations observed were an artefact of the presence of phylogenetic signal in rubisco kinetics and the phylogenetic relationship between the species that were sampled. Here, we conducted a phylogenetically-resolved analysis of rubisco kinetics and show that there is a significant phylogenetic signal in rubisco kinetic traits. We re-evaluated the extent of catalytic trade-offs accounting for this phylogenetic signal and found that all were attenuated. Following phylogenetic correction, the largest catalytic trade-offs were observed between the Michaelis constant for CO2 and carboxylase turnover ([~]21-37 %), and between the Michaelis constants for CO2 and O2 ([~]9-19 %), respectively. All other catalytic trade-offs were substantially attenuated such that they were marginal (<9 %) or non-significant. This phylogenetically resolved analysis of rubisco kinetic evolution also identified kinetic changes that occur concomitant with the evolution of C4 photosynthesis. Finally, we show that phylogenetic constraints (most likely caused by a slow rate of molecular evolution) have played a larger role than catalytic trade-offs in limiting the evolution of rubisco kinetics. Thus, although there is strong evidence for some catalytic trade-offs, rubisco adaptation has been more limited by phylogenetic constraint than by the combined action of all such trade-offs.

category: plant biology


title: Estimating effects of parents' cognitive and non-cognitive skills on offspring education using polygenic scores

abstract: Understanding how parents cognitive and non-cognitive skills influence offspring education is vital for educational, family and economic policy. We use genetics (GWAS-by-subtraction) to assess a latent, broad non-cognitive skills dimension. To index parental effects controlling for genetic transmission, we estimate indirect parental genetic effects of polygenic scores on childhood and adulthood educational outcomes, using siblings (N=47,459), adoptees (N=6,407), and parent-offspring trios (N=2,534) in three UK and Dutch cohorts. We find that parental cognitive and non-cognitive skills affect offspring education through their environment: on average across cohorts and designs, indirect genetic effects explain 36-40% of population polygenic score associations. However, indirect genetic effects are lower for achievement in the Dutch cohort, and for the adoption design. We identify causes of higher sibling- and trio-based estimates: prenatal indirect genetic effects, population stratification, and assortative mating. Our phenotype-agnostic, genetically sensitive approach has established overall environmental effects of parents skills, facilitating future mechanistic work.

category: genetics


title: CIAlign - A highly customisable command line tool to clean, interpret and visualise multiple sequence alignments.

abstract:
BackgroundThroughout biology, multiple sequence alignments (MSAs) form the basis of much investigation into biological features and relationships. These alignments are at the heart of many bioinformatics analyses. However, sequences in MSAs are often incomplete or very divergent, which leads to poorly aligned regions or large gaps in alignments. This slows down computation and can impact conclusions without being biologically relevant. Therefore, cleaning the alignment by removing these regions can substantially improve analyses. Manual editing of MSAs is very widespread but is time-consuming and difficult to reproduce.

ResultsWe present a comprehensive, user-friendly MSA trimming tool with multiple visualisation options. Our highly customisable command line tool aims to give intervention power to the user by offering various options, and outputs graphical representations of the alignment before and after processing to give the user a clear overview of what has been removed.

The main functionalities of the tool include removing regions of low coverage due to insertions, removing gaps, cropping poorly aligned sequence ends and removing sequences that are too divergent or too short. The thresholds for each function can be specified by the user and parameters can be adjusted to each individual MSA. CIAlign is designed with an emphasis on solving specific and common alignment problems and on providing transparency to the user.

ConclusionCIAlign effectively removes problematic regions and sequences from MSAs and provides novel visualisation options. This tool can be used to refine alignments for further analysis and processing. The tool is aimed at anyone who wishes to automatically clean up parts of an MSA and those requiring a new, accessible way of visualising large MSAs.


title: leADS: improved metabolic pathway inference based on active dataset subsampling

abstract:
Metabolic pathways are composed of reaction sequences catalyzed by enzymes. The set of reactions within and between cells comprises a reactome. Pathways and reactomes can be predicted from organismal or multi-organismal genomes using rule-based or machine learning methods. While machine learning methods overcome issues of probability and scale associated with rule-based methods, several complications remain that can degrade performance including inadequately labeled training data, missing feature information, and inherent imbalances in the distribution of pathways within a dataset. Here, we present leADS (multi-label learning based on active dataset subsampling), a machine learning method, that uses subsampling to reduce the negative impact of training loss due to class imbalance. We demonstrate leADs performance using organismal and multi-organismal datasets in relation to other machine learning pathway prediction methods.

Availability and implementationleADS is available under the GNU license at github.com/hallamlab/leADS. A wiki, including a tutorial, is available at github.com//hallamlab/leADS/wiki

Contactshallam@mail.ubc.ca


title: Frequency Spectra and the Color of Cellular Noise

abstract: The invention of the Fourier integral in the 19th century laid the foundation for modern spectral analysis methods. By decomposing a (time) signal into its essential frequency components, these methods uncovered deep insights into the signal and its generating process, precipitating tremendous inventions and discoveries in many fields of engineering, technology, and physical science. In systems and synthetic biology, however, the impact of frequency methods has been far more limited despite their huge promise. This is in large part due to the difficulties encountered in connecting the underlying stochastic reaction network in the living cell, whose dynamics is typically modelled as a continuous-time Markov chain (CTMC), to the frequency content of the observed, distinctively noisy single-cell trajectories. Here we draw on stochastic process theory to develop a spectral theory and computational methodologies tailored specifically to the computation and analysis of frequency spectra of noisy cellular networks. Specifically, we develop a generic method to obtain accurate Pade approximations of the spectrum from a handful of trajectory simulations. Furthermore, for linear networks, we present a novel decomposition result that expresses the frequency spectrum in terms of its sources. Our results provide new conceptual and practical methods for the analysis and design of noisy cellular networks based on their output frequency spectra. We illustrate this through diverse case studies in which we show that the single-cell frequency spectrum facilitates topology discrimination, synthetic oscillator optimization, cybergenetic controller design, systematic investigation of stochastic entrainment, and even parameter inference from single-cell trajectory data.

category: synthetic biology


title: Robustness of individualized inferences from longitudinal resting state dynamics

abstract: Tracking how individual human brains change over extended timescales is crucial in scenarios ranging from healthy aging to stroke recovery. Tracking these neuroplastic changes with resting state (RS) activity is a promising but poorly understood possibility. It remains unresolved whether a persons RS activity over time can be reliably decoded to distinguish neurophysiological changes from confounding differences in cognitive state during rest. Here, we assessed whether this confounding can be minimized by tracking the configuration of an individuals RS activity that is shaped by their distinctive neurophysiology rather than cognitive state. Using EEG, individual RS activity was acquired over five consecutive days along with activity in tasks that were devised to simulate the confounding effects of inter-day cognitive variation. As inter-individual differences are shaped by neurophysiological differences, the inter-individual differences in RS activity on one day were analyzed (using machine learning) to identify a distinctive configuration in each individuals RS activity. Using this configuration as a classifier-rule, an individual could be re-identified with high accuracy from 2-second samples of the instantaneous oscillatory power acquired on a different day both from RS and confounded-RS. Importantly, the high accuracy of cross-day classification was achieved only with classifiers that combined information from multiple frequency bands at channels across the scalp (with a concentration at characteristic fronto-central and occipital zones). These findings support the suitability of longitudinal RS to support robust individualized inferences about neurophysiological change in health and disease.


title: Predicting MEG resting-state functional connectivity using microstructural information

abstract:
Understanding how human brain microstructure influences functional connectivity is an important endeavor. In this work, magnetic resonance imaging data from ninety healthy participants were used to calculate structural connectivity matrices using the streamline count, fractional anisotropy, radial diffusivity and a myelin measure (derived from multicomponent relaxometry) to assign connection strength. Unweighted binarized structural connectivity matrices were also constructed. Magnetoencephalography resting-state data from those participants were used to calculate functional connectivity matrices, via correlations of the Hilbert envelopes of beamformer timeseries at the delta, theta, alpha and beta frequency bands. Non-negative matrix factorization was performed to identify the components of the functional connectivity. Shortest-path-length and search-information analyses of the structural connectomes were used to predict functional connectivity patterns for each participant.

The microstructure-informed algorithms predicted the components of the functional connectivity more accurately than they predicted the total functional connectivity. This provides a methodology for better understanding of functional mechanisms. The shortest-path-length algorithm exhibited the highest prediction accuracy. Of the weights of the structural connectivity matrices, the streamline count and the myelin measure gave the most accurate predictions, while the fractional anisotropy performed poorly. Overall, different structural metrics paint very different pictures of the structural connectome and its relationship to functional connectivity.


title: FGF8-mediated signaling regulates tooth developmental pace and size during odontogenesis

abstract: The developing human and mouse teeth constitute an ideal model system to study the regulatory mechanism underlying organ growth control due to the fact that their teeth share highly conserved and well-characterized developmental processes and their developmental tempo vary notably. In the current study, we manipulated heterogenous recombination between human and mouse dental tissues and demonstrate that the dental mesenchyme dominates the tooth developmental tempo and FGF8 could be a critical player during this developmental process. Forced activation of FGF8 signaling in the dental mesenchyme of mice promoted cell proliferation, prevented cell apoptosis via p38 and perhaps PI3K-Akt intracellular signaling, and impelled the transition of the cell cycle from G1- to S-phase in the tooth germ, resulting in the slowdown of the tooth developmental pace. Our results provide compelling evidence that extrinsic signals can profoundly affect tooth developmental tempo and the dental mesenchymal FGF8 could be a pivotal factor in controlling developmental pace in a non-cell-autonomous manner during mammalian odontogenesis.

category: developmental biology


title: FGF8-mediated signaling regulates tooth developmental pace during odontogenesis


title: X chromosome-dependent disruption of placental regulatory networks in hybrid dwarf hamsters

abstract: Embryonic development in mammals is highly sensitive to changes in gene expression within the placenta. The placenta is also highly enriched for genes showing parent-of-origin or imprinted expression, which is predicted to evolve rapidly in response to parental conflict. However, little is known about the evolution of placental gene expression, or if divergence of placental gene expression plays an important role in mammalian speciation. We used crosses between two species of dwarf hamsters (Phodopus sungorus and P. campbelli) to examine the genetic and regulatory underpinnings of severe placental overgrowth in their hybrids. Using quantitative genetic mapping and mitochondrial substitution lines, we show that overgrowth of hybrid placentas was primarily caused by genetic differences on the maternally inherited P. sungorus X chromosome. Mitochondrial interactions did not contribute to abnormal hybrid placental development, and there was only weak correspondence between placental disruption and embryonic growth. Genome-wide analyses of placental transcriptomes from the parental species and first and second-generation hybrids revealed a central group of co-expressed X-linked and autosomal genes that were highly enriched for maternally-biased expression. Expression of this gene network was strongly correlated with placental size and showed widespread misexpression dependent on epistatic interactions with X-linked hybrid incompatibilities. Collectively, our results indicate that the X chromosome is likely to play a prominent role in the evolution of placental gene expression and the accumulation of hybrid developmental barriers between mammalian species.

category: evolutionary biology


title: Mean-field modeling of brain-scale dynamics for the evaluation of EEG source-space networks

abstract: Understanding the dynamics of brain-scale functional networks at rest and during cognitive tasks is the subject of intense research efforts to unveil fundamental principles of brain functions. To estimate these large-scale brain networks, the emergent method called "electroencephalography (EEG) source connectivity" has generated increasing interest in the network neuroscience community, due to its ability to identify cortical brain networks with satisfactory spatio-temporal resolution, while reducing mixing and volume conduction effects. However, no consensus has been reached yet regarding a unified EEG source connectivity pipeline, and several methodological issues have to be carefully accounted for to avoid pitfalls. Thus, a validation toolbox that provides flexible "ground truth" models is needed for an objective methods/parameters evaluation and, thereby an optimization of the EEG source connectivity pipeline. In this paper, we show how a recently developed large-scale model of brain-scale activity, named COALIA, can provide to some extent such ground truth by providing realistic simulations of source-level and scalp-level activity. Using a bottom-up approach, the model bridges cortical micro-circuitry and large-scale network dynamics. Here, we provide an example of the potential use of COALIA to analyze, in the context of epileptiform activity, the effect of three key factors involved in the "EEG source connectivity" pipeline: (i) EEG sensors density, (ii) algorithm used to solve the inverse problem, and (iii) functional connectivity measure. Results showed that a high electrode density (at least 64 channels) is required to accurately estimate cortical networks. Regarding the inverse solution/connectivity measure combination, the best performance at high electrode density was obtained using the weighted minimum norm estimate (wMNE) combined with the weighted phase lag index (wPLI). Although those results are specific to the considered aforementioned context (epileptiform activity), we believe that this model-based approach can be successfully applied to other experimental questions/contexts. We aim at presenting a proof-of-concept of the interest of COALIA in the network neuroscience field, and its potential use in optimizing the EEG source-space network estimation pipeline.


title: Endogenous memory reactivation during sleep in humans is clocked by slow oscillation spindle complexes.

abstract: Sleep is thought to support memory consolidation via reactivation of prior experiences, with particular electrophysiological sleep signatures (slow oscillations (SOs) and sleep spindles) gating the information flow between relevant brain areas. However, empirical evidence for a role of endogenous memory reactivation (i.e., without experimentally delivered memory cues) for consolidation in humans is lacking. Here, we devised a paradigm in which participants acquired associative memories before taking a nap. Multivariate decoding was then used to capture endogenous memory reactivation during non-rapid eye movement (NREM) sleep in surface EEG recordings. Our results reveal reactivation of learning material during SO-spindle complexes, with the precision of SO-spindle coupling predicting reactivation strength. Critically, reactivation strength (i.e. classifier evidence in favor of the previously studied stimulus category) in turn predicts the level of consolidation across participants. These results elucidate the memory function of sleep in humans and emphasize the importance of SOs and spindles in clocking endogenous consolidation processes.


title: Privacy preserving storage of sequenced genomic data

abstract:
IntroductionCurrent and future applications of genomic data may raise ethical and privacy concerns. Processing and storing these data introduces a risk of abuse by a potential adversary since a human genome contains sensitive personal information. For this reason, we developed a privacy preserving method, called Varlock, for secure storage of sequenced genomic data.

Materials and methodsWe used a public set of population allele frequencies to mask personal alleles detected in genomic reads. Each personal allele described by the public set is masked by a randomly selected population allele with respect to its frequency. Masked alleles are preserved in an encrypted confidential file that can be shared, in whole or in part, using public-key cryptography.

ResultsOur method masked personal variants and introduced new variants detected in a personal masked genome. Alternative alleles with lower population frequency were masked and introduced more often. We performed a joint PCA analysis of personal and masked VCFs, showing that the VCFs between the two groups can not be trivially mapped. Moreover, the method is reversible and personal alleles can be unmasked in specific genomic regions on demand.

ConclusionOur method masks personal alleles within genomic reads while preserving valuable non-sensitive properties of sequenced DNA fragments for further research. Personal alleles may be restored in desired genomic regions and shared with patients, clinics, and researchers. We suggest that the method can provide an additional layer of security for storing and sharing the raw aligned reads.


title: Alpha fluctuations regulate the accrual of visual information to awareness

abstract: Endogenous brain processes play a paramount role in shaping up perceptual phenomenology. This is illustrated by the alternations experienced by humans (and other animals) when watching perceptually ambiguous, static images. We hypothesised that endogenous alpha fluctuations in the visual cortex pace the accumulation of sensory information leading to perceptual outcomes. Here, we addressed this hypothesis using binocular rivalry combined with visual entrainment and electroencephalography in humans (64 female, 53 male). The results revealed a correlation between the individual frequency of alpha oscillations in the occipital cortex and perceptual alternation rates experienced during binocular rivalry. In subsequent experiments we show that regulating endogenous brain activity via rhythmic entrainment produced corresponding changes in perceptual alternation rate. These changes were observed only in the alpha range but not at lower entrainment frequencies, and were much reduced when using arrhythmic stimulation. Additionally, entraining at frequencies above the alpha range did not result in speeding up perceptual alternation rates. Overall, these findings support the notion that visual information is accumulated via alpha cycles to promote the emergence of conscious perceptual representations. We suggest that models of binocular rivalry incorporating posterior alpha as a pacemaker can provide an important advance in the comprehension of the dynamics of visual awareness.


title: Characterisation of protease activity during SARS-CoV-2 infection identifies novel viral cleavage sites and cellular targets for drug repurposing

abstract: SARS-CoV-2 is the causative agent behind the COVID-19 pandemic, and responsible for over 170 million infections, and over 3.7 million deaths worldwide. Efforts to test, treat and vaccinate against this pathogen all benefit from an improved understanding of the basic biology of SARS-CoV-2. Both viral and cellular proteases play a crucial role in SARS-CoV-2 replication, and inhibitors targeting proteases have already shown success at inhibiting SARS-CoV-2 in cell culture models. Here, we study proteolytic cleavage of viral and cellular proteins in two cell line models of SARS-CoV-2 replication using mass spectrometry to identify protein neo-N-termini generated through protease activity. We identify previously unknown cleavage sites in multiple viral proteins, including major antigenic proteins S and N, which are the main targets for vaccine and antibody testing efforts. We discovered significant increases in cellular cleavage events consistent with cleavage by SARS-CoV-2 main protease, and identify 14 potential high-confidence substrates of the main and papain-like proteases, validating a subset with in vitro assays. We showed that siRNA depletion of these cellular proteins inhibits SARS-CoV-2 replication, and that drugs targeting two of these proteins: the tyrosine kinase SRC and Ser/Thr kinase MYLK, showed a dose-dependent reduction in SARS-CoV-2 titres. Overall, our study provides a powerful resource to understand proteolysis in the context of viral infection, and to inform the development of targeted strategies to inhibit SARS-CoV-2 and treat COVID-19.


title: Characterisation of protease activity during SARS-CoV-2 infection identifies novel viral cleavage sites and cellular targets with therapeutic potential


title: Cerebrospinal fluids from healthy pregnant women does not harbor a detectable microbial community

abstract:
Cerebrospinal fluids circulating human central nervous system have long been considered aseptic in healthy individuals, because normally the blood-brain barrier protects against microbial invasions. However, this dogma has been questioned by several reports that microbes were identified in human brains, raising the question whether a microbial community is present in cerebrospinal fluids of healthy individuals without neurological diseases. Here, we collected and analyzed metagenomic and metatranscriptomic sequencing data of cerebrospinal fluid specimens from a cohort of 23 pregnant women aged between 23 and 40 and one-to-one matched contamination controls. From data analysis of 116 specimens of eight different types, we detected 619 nonredundant microbial taxa which were dominated by bacteria (75%) and viruses (24%). In cerebrospinal fluids metagenomic samples, a total of 76 redundant species were detected including four (one nonredundant) eukaryota taxa, eleven (four nonredundant) bacteria, and 61 (21 nonredundant) viruses that were mostly bacteriophages. Metagenomic data analysis found no significant difference between cerebrospinal fluid specimens and negative controls in terms of microbial species diversity. In addition, no active or viable microbiome were present in the cerebrospinal fluid samples after subtracting microbes detected in contamination controls. In conclusion, we found no strong evidence that colonized microbial community exist in the cerebrospinal fluids of healthy individuals.

IMPORTANCEMicrobiome are prevalent throughout human bodies with profound health implications. However, it remains unclear whether a microbiome is present and active in human cerebrospinal fluids that are long considered aseptic given the blood-brain barrier. Here, we applied unbiased metagenomic and metatranscriptomic sequencing to detect microbiome in cerebrospinal fluids collected from a cohort of 23 pregnant women with matched controls. By analyzing 116 specimens of eight types, no strong evidence was found to support a presence of colonized microbiome in the cerebrospinal fluids. Our findings have profound implications to human immunity against neurological infections and disorders, providing a guide for disease diagnostics, prevention and therapeutics in clinical settings.


title: Computational circuit mechanisms underlying thalamic control of attention

abstract: The thalamus engages in attention by amplifying relevant signals and filtering distractors. Whether architectural features of thalamic circuitry offer a unique locus for attentional control is unknown. We developed a circuit model of excitatory thalamocortical and inhibitory reticular neurons, capturing key observations from task-engaged animals. We found that top-down inputs onto reticular neurons regulate thalamic gain effectively, compared to direct thalamocortical inputs. This mechanism enhances downstream readout, improving detection, discrimination, and cross-modal performance. The model revealed heterogeneous thalamic responses that enable decoding top-down versus bottom-up signals. Spiking activity from task-performing mice supported model predictions, with a similar coding geometry in auditory thalamus and readout strategy in auditory cortex. Dynamical systems analysis explained why reticular neurons are potent sites for control, and how lack of excitatory connectivity among thalamocortical neurons enables separation of top-down from bottom-up signals. Our work reveals mechanisms for attentional control and connects circuit architectures to computational functions.


title: Distinctive properties of cones in the retinal clock and the circadian system

abstract: The circadian system is a hierarchical network of cell and tissue-specific oscillators synchronized to the environmental light/dark cycle. Entrainment is mediated by the retina through diverse photosensitive cells and pigments. The retina is itself a complex circadian system whose cellular constitutive elements have not been fully characterized. By using the Nrl-/- cone gain-of-function mouse model we here show that the retinal network comprises an autonomous oscillator harbored in cones. We further provide novel evidence for an input from cones to the master clock, as revealed under constant light condition.


title: A non-canonical lipid droplet metabolism regulates the conversion of alpha-Synuclein to proteolytic resistant forms in neurons of a Drosophila model of Parkinson disease

abstract: Parkinsons disease (PD) is a neurodegenerative disorder characterized by alpha-synuclein (Syn) aggregation and associated with abnormalities in lipid metabolism. The accumulation of lipids in cytoplasmic organelles called lipid droplets (LDs) was observed in cellular models of PD. To investigate the pathophysiological consequences of interactions between Syn and proteins that regulate the homeostasis of LDs, we used a transgenic Drosophila model of PD, in which human Syn is specifically expressed in photoreceptor neurons. We first found that overexpression of the LD-coating proteins perilipin 1 or 2 (dPlin1/2), which limit the access of lipases to LDs, markedly increased triacylglyclerol (TG) loaded LDs in neurons. However, dPlin-induced-LDs in neurons are independent of lipid anabolic (diacylglycerol acyltransferase 1/Midway, fatty acid transport protein/dFatp) and catabolic (lipase Brummer) enzymes, indicating that non-canonical mechanisms regulate neuronal LD homeostasis. Interestingly, the accumulation of LDs induced by several distinct LD proteins (dPlin1, dPlin2, CG7900 or KlarsichtLD-BD) was synergistically amplified by the co-expression of Syn, which was found at the surface of LDs both in photoreceptors neurons of Drosophila and in human neuroblastoma cells. Finally, the accumulation of LDs increased the resistance of Syn to proteolytic digestion, a phenomenon associated with Syn aggregation in human neurons. We thus propose that Syn cooperates with LD proteins to inhibit lipolysis and that binding of Syn to LDs contributes to the pathogenic misfolding and aggregation of Syn in neurons.

category: cell biology


title: Conductance-Based Structural Brain Connectivity in Aging and Dementia

abstract:
BackgroundStructural brain connectivity has been shown to be sensitive to the changes that the brain undergoes during Alzheimers disease (AD) progression.

MethodsIn this work, we used our recently proposed structural connectivity quantification measure derived from diffusion MRI, which accounts for both direct and indirect pathways, to quantify brain connectivity in dementia. We analyzed data from the ADNI-2 and OASIS-3 datasets to derive relevant information for the study of the changes that the brain undergoes in AD. We also compared these datasets to the HCP dataset, as a reference, and eventually validated externally on two cohorts of the EDSD database.

ResultsOur analysis shows expected trends of mean conductance with respect to age and cognitive scores, significant age prediction values in aging data, and regional effects centered among sub-cortical regions, and cingulate and temporal cortices.

DiscussionResults indicate that the conductance measure has prediction potential, especially for age, that age and cognitive scores largely overlap, and that this measure could be used to study effects such as anti-correlation in structural connections.

Impact statementThis work presents a methodology and a set of analyses that open new possibilities in the study of healthy and pathological aging. The methodology used here is sensitive to direct and indirect pathways in deriving brain connectivity measures from dMRI, and therefore provides information that many state-of-the-art methods do not account for. As a result, this technique may provide the research community with ways to detect subtle effects of healthy aging and AD.


title: Effective connectivity and spatial selectivity-dependent fMRI changes elicited by microstimulation of pulvinar and LIP

abstract:
The thalamic pulvinar and the lateral intraparietal area (LIP) share reciprocal anatomical connections and are part of an extensive cortical and subcortical network involved in spatial attention and oculomotor processing. The goal of this study was to compare the effective connectivity of dorsal pulvinar (dPul) and LIP and to probe the dependency of microstimulation effects on task demands and spatial tuning properties of a given brain region. To this end, we applied unilateral electrical microstimulation in the dPul (mainly medial pulvinar) and LIP in combination with event-related BOLD fMRI in monkeys performing fixation and memory-guided saccade tasks. Microstimulation in both dPul and LIP enhanced task-related activity in monosynaptically-connected fronto-parietal cortex and along the superior temporal sulcus (STS) including putative face patch locations, as well as in extrastriate cortex. LIP microstimulation elicited strong activity in the opposite homotopic LIP while no homotopic activation was found with dPul stimulation. Both dPul and LIP stimulation also elicited activity in several heterotopic cortical areas in the opposite hemisphere, implying polysynaptic propagation of excitation. Despite extensive activation along the intraparietal sulcus evoked by LIP stimulation, there was a difference in frontal and occipital connectivity elicited by posterior and anterior LIP stimulation sites. Comparison of dPul stimulation with the adjacent but functionally dissimilar ventral pulvinar also showed distinct connectivity. On the level of single trial timecourses within each region of interest (ROI), most ROIs did not show task-dependence of stimulation-elicited response modulation. Across ROIs, however, there was an interaction between task and stimulation, and task-specific correlations between the initial spatial selectivity and the magnitude of stimulation effect were observed. Consequently, stimulation-elicited modulation of task-related activity was best fitted by an additive model scaled down by the initial response amplitude. In summary, we identified overlapping and distinct patterns of thalamocortical and corticocortical connectivity of pulvinar and LIP, highlighting the dorsal bank and fundus of STS as a prominent node of shared circuitry. Spatial task-specific and partly polysynaptic modulations of cue and saccade planning delay period activity in both hemispheres exerted by unilateral pulvinar and parietal stimulation provide insight into the distributed interhemispheric processing underlying spatial behavior.

HighlightsO_LIElectrical stimulation of pulvinar and LIP was used to study fMRI effective connectivity
C_LIO_LIBoth regions activated prefrontal cortex and the dorsal bank of superior temporal sulcus
C_LIO_LIActivations within and across hemispheres suggest polysynaptic propagation
C_LIO_LIStimulation effects show interactions between task- and spatial selectivity
C_LIO_LIStimulation effects are best fitted by an additive model scaled by the initial response
C_LI


title: Time course of homeostatic structural plasticity in response to optogenetic stimulation in mouse anterior cingulate cortex

abstract: Plasticity is the mechanistic basis of development, aging, learning and memory, both in healthy and pathological brains. Structural plasticity is rarely accounted for in computational network models, due to a lack of insight into the underlying neuronal mechanisms and processes. Little is known about how the rewiring of networks is dynamically regulated. To inform such models, we characterized the time course of neural activity, the expression of synaptic proteins, and neural morphology employing an in vivo optogenetic mouse model. We stimulated pyramidal neurons in the anterior cingulate cortex of mice and harvested their brains at 1.5 h, 24 h, and 48 h after stimulation. Stimulus-induced cortical hyperactivity persisted up to 1.5 h and decayed to baseline after 24 h, indicated by c-Fos expression. The synaptic proteins VGLUT1 and PSD-95, in contrast, were upregulated at 24 h and downregulated at 48 h, respectively. Spine density and spine head volume were also increased at 24 h and decreased at 48 h. This specific sequence of events reflects a continuous joint evolution of activity and connectivity that is characteristic of the model of homeostatic structural plasticity. Our computer simulations thus corroborate the observed empirical evidence from our animal experiments.


title: The role of miR-31-5p in the development of intervertebral disk degeneration and its therapeutic potential

abstract: Intervertebral disc degeneration (IDD) refers to the abnormal response of cell-mediated progressive structural failure. In order to understand the molecular mechanism of the maintenance and destruction of the intervertebral disc, new IDD treatment methods are developed. Here, we first analyzed the key regulators of IDD through miRNA microarrays. The cell structure and morphology were discovered by Histological and radiographic. Then, the level of miR-31-5p was disclosed by qRT-PCR. The association between miR-31-5p and SDF-1/CXCR7 axis was discovered by 3'-Untranslated region (UTR) cloning and luciferase assay. The apoptosis of cells under different treatments was disclosed by Flow cytometer. The cell proliferation was discovered by EdU assay. Finally, the protein levels of SDF-1, CXCR7, ADAMTS-5, Col II, Aggrecan and MMP13 were discovered by Western blot. The results show that miR-31-5p is a key regulator of IDD and its level is down-regulated in IDD. Overexpression of miR-31-5p facilitates NP cell proliferation, inhibits apoptosis, facilitates ECM formation and inhibits the level of matrix degrading enzymes in NP cells. The SDF-1/CXCR7 axis is the direct target of miR-31-5p. miR-31-5p acts on IDD by regulating SDF-1/CXCR7. In vitro experiments further verified that the up-regulation of miR-31-5p prevented the development of IDD. In conclusion, overexpression of miR-31-5p can inhibit IDD by regulating SDF-1/CXCR7.


title: Fixed single-cell RNA sequencing for understanding virus infection and host response

abstract: Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited because current high-throughput RNA sequencing methods are incompatible with paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq, a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single-cells. We show that FD-seq preserves the mRNA integrity and relative abundances during fixation and subsequent cell retrieval. Furthermore, FD-seq detects a higher number of genes and transcripts than methanol fixation. We applied FD-seq to investigate two important questions in Virology. First, by analyzing a rare population of cells supporting lytic reactivation of the human tumor virus KSHV, we identified TMEM119 as a host factor that mediates viral reactivation. Second, we found that upon infection with the betacoronavirus OC43, which causes the common cold and is a close relative of SARS-CoV-2, pro-inflammatory pathways are primarily upregulated in lowly-infected cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell populations, and preserving and inactivating pathogenic samples that cannot be handled under regular biosafety measures.


title: Spontaneous Escherichia coli persisters with week-long survival dynamics and lasting memory of a short starvation pulse

abstract: The vast majority of a bacterial population is quickly killed when treated with a lethal concentration of antibiotics. The time scale of this killing is often comparable with the bacterial generation time before addition of antibiotics. Yet, a small subpopulation typically survives for an extended period. However, the long-term killing dynamics of bacterial cells has not been fully quantified even in well-controlled laboratory conditions. We constructed a week-long killing assay and followed the survival fraction of Escherichia coli K12 exposed to a high concentration of ciprofloxacin. We found that long-term survivors were formed during exponential growth, with some cells surviving at least 7 days. The long-term dynamics contained at least three timescales, which greatly enhances predictions of the population survival time compared to the biphasic extrapolation from the short term behavior. Furthermore, we observed a surprisingly long memory effect of a brief carbon starvation pulse, which was dependent on the (p)ppGpp synthase relA. Specifically, one hour of carbon starvation prior to antibiotics exposure increased the surviving fraction by nearly 100-fold even after 4 days of ciprofloxacin treatment.


title: Existence of log-phase Escherichia coli persisters and lasting memory of a starvation pulse


title: Phylogenomic assessment of the role of hybridization and introgression in trait evolution

abstract: Trait evolution among a set of species--a central theme in evolutionary biology--has long been understood and analyzed with respect to a species tree. However, the field of phylogenomics, which has been propelled by advances in sequencing technologies, has ushered in the era of species/gene tree incongruence and, consequently, a more nuanced understanding of trait evolution. For a trait whose states are incongruent with the branching patterns in the species tree, the same state could have arisen independently in different species (homoplasy) or followed the branching patterns of gene trees, incongruent with the species tree (hemiplasy). Another evolutionary process whose extent and significance are better revealed by phylogenomic studies is gene flow between different species. In this work, we present a phylogenomic method for assessing the role of hybridization and introgression in the evolution of polymorphic or monomorphic binary traits. We apply the method to simulated evolutionary scenarios to demonstrate the interplay between the parameters of the evolutionary history and the role of introgression in a binary traits evolution (which we call xenoplasy). Very importantly, we demonstrate, including on a biological data set, that inferring a species tree and using it for trait evolution analysis in the presence of gene flow could lead to misleading hypotheses about trait evolution.


title: Geographic heterogeneity impacts drug resistance predictions in Mycobacterium tuberculosis

abstract:
The efficacy of antibiotic drug treatments in tuberculosis (TB) is significantly threatened by the development of drug resistance. There is a need for a robust diagnostic system that can accurately predict drug resistance in patients. In recent years, researchers have been taking advantage of whole-genome sequencing (WGS) data to infer antibiotic resistance. In this work we investigate the power of machine learning tools in inferring drug resistance from WGS data on three distinct datasets differing in their geographical diversity.

We analyzed data from the Relational Sequencing TB Data Platform, which comprises global isolates from 32 different countries, the PATRIC database, containing isolates contributed by researchers around the world, and isolates collected by the British Columbia Centre for Disease Control in Canada. We predicted drug resistance to the first-line drugs: isoniazid, rifampicin, ethambutol, pyrazinamide, and streptomycin. We focused on the genes which previous evidence suggests are involved in drug resistance in TB.

We called single-nucleotide polymorphisms using the Snippy pipeline, then applied different machine learning models. Following best practices, we chose the best parameters for each model via cross-validation on the training set and evaluated the performance via the sensitivity-specificity tradeoffs on the testing set.

To the best of our knowledge, our study is the first to predict antibiotic resistance in TB across multiple datasets. We obtained a performance comparable to that seen in previous studies, but observed that performance may be negatively affected when training on one dataset and testing on another, suggesting the importance of geographical heterogeneity in drug resistance predictions. In addition, we investigated the importance of each gene within each model, and recapitulated some previously known biology of drug resistance. This study paves the way for further investigations, with the ultimate goal of creating an accurate, interpretable and globally generalizable model for predicting drug resistance in TB.

Author summaryDrug resistance in pathogenic bacteria such as Mycobacterium tuberculosis can be predicted by an application of machine learning models to next-generation sequencing data. The received wisdom is that following standard protocols for training commonly used machine learning models should produce accurate drug resistance predictions.

In this paper, we propose an important caveat to this idea. Specifically, we show that considering geographical diversity is critical for making accurate predictions, and that different geographic regions may have disparate drug resistance mechanisms that are predominant. By comparing the results within and across a regional dataset and two international datasets, we show that model performance may vary dramatically between settings.

In addition, we propose a new method for extracting the most important variants responsible for predicting resistance to each first-line drug, and show that it is to recapitulate a large amount of what is known about the biology of drug resistance in Mycobacterium tuberculosis.


title: Relating neural oscillations to laminar fMRI connectivity

abstract: Laminar fMRI holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded EEG and high resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions. Our results indicate that our task induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent alpha band oscillations relate to laminar specific fMRI connectivity. These differential effects for the alpha and beta bands suggest a complex picture of possibly co-occurring neural processes that can differentially affect laminar connectivity.


title: Function of the HYDROXYCINNAMOYL-CoA:SHIKIMATE HYDROXYCINNAMOYL TRANSFERASE is evolutionarily conserved in embryophytes

abstract: The plant phenylpropanoid pathway generates a major class of specialized metabolites and precursors of essential extracellular polymers that initially appeared upon plant terrestrialization. Despite its evolutionary significance, little is known about the complexity and function of this major metabolic pathway in extant bryophytes, which represent the non-vascular stage of embryophyte evolution. Here, we report that the HYDROXYCINNAMOYL-CoA:SHIKIMATE HYDROXYCINNAMOYL TRANSFERASE (HCT) gene that plays a critical function in the phenylpropanoid pathway during seed plant development, is functionally conserved in Physcomitrium patens (Physcomitrella), in the moss lineage of bryophytes. Phylogenetic analysis indicates that bonafide HCT function emerged in the progenitor of embryophytes. In vitro enzyme assays, moss phenolic pathway reconstitution in yeast and in planta gene inactivation coupled to targeted metabolic profiling, collectively indicate that P. patens HCT (PpHCT), similar to tracheophyte HCT orthologs, uses shikimate as a native acyl acceptor to produce a p-coumaroyl-5-O-shikimate intermediate. Phenotypic and metabolic analyses of loss-of-function mutants show that PpHCT is necessary for the production of caffeate derivatives, including previously reported caffeoyl-threonate esters, and for the formation of an intact cuticle. Deep conservation of HCT function in embryophytes is further suggested by the ability of HCT genes from P. patens and the liverwort Marchantia polymorpha to complement an Arabidopsis thaliana CRISPR/Cas9 hct mutant, and by the presence of phenolic esters of shikimate in representative species of the three bryophyte lineages.


title: Inference of recent admixture using genotype data

abstract:
The inference of biogeographic ancestry (BGA) has become a focus of forensic genetics. Misinference of BGA can have profound unwanted consequences for investigations and society. We show that recent admixture can lead to misclassification and erroneous inference of ancestry proportions, using state of the art analysis tools with (i) simulations, (ii) 1000 genomes project data, and (iii) two individuals analyzed using the ForenSeq DNA Signature Prep Kit. Subsequently, we extend existing tools for estimation of individual ancestry (IA) by allowing for different IA in both parents, leading to estimates of parental individual ancestry (PIA), and a statistical test for recent admixture. Estimation of PIA outperforms IA in most scenarios of recent admixture. Furthermore, additional information about parental ancestry can be acquired with PIA that may guide casework.

HighlightsO_LIWe improve statistical methods as used in STRUCTURE and ADMIXTURE for Biogeographical Ancestry (BGA) inference to account for recent admixture, i.e. different admixture of both parents.
C_LIO_LIThe resulting recent admixture model has a higher accuracy in estimating individual admixture in most cases.
C_LIO_LIWe give a likelihood ratio test for recent admixture, which is both highly specific and sensitive for recent admixture.
C_LIO_LIWe find evidence of recent admixture in the 1000 genomes dataset.
C_LIO_LIThe self-report on recent admixture of two self-sequenced samples was only confirmed in one case.
C_LI


title: Fixation and effective size in a haploid-diploid population with asexual reproduction

abstract:
The majority of population genetic theory assumes fully haploid or diploid organisms with obligate sexuality, despite complex life cycles with alternating generations being commonly observed. To reveal how natural selection and genetic drift shape the evolution of haploid-diploid populations, we analyze a stochastic genetic model for populations that consist of a mixture of haploid and diploid individuals, allowing for asexual reproduction and niche separation between haploid and diploid stages. Applying a diffusion approximation, we derive the fixation probability and describe its dependence on the reproductive values of haploid and diploid stages, which depend strongly on the extent of asexual reproduction in each phase and on the ecological differences between them.

Highlight- Classical models consider fully haploid or diploid populations
- We model haploid-diploid life cycles allowing for asexual reproduction
- We obtain the fixation probability of alleles subject to selection and drift
- Reproductive values of haploid and diploid stages shape their evolution


title: RatsPub: a webservice aided by deep learning to mine PubMed for addiction-related genes

abstract: Interpreting and integrating results from omics studies typically requires a comprehensive and time consuming survey of extant literature. Here, we introduce GeneCup, an easy to use literature mining web service that searches all PubMed abstracts for user-provided gene symbols in conjunction with a set of custom keywords organized into a customized ontology, as well as results from human genome-wide association studies (GWAS). As an example, we organized over 300 keywords related to drug addiction into seven categories. The literature search is conducted by querying the NIH PubMed server using a programming interface, which is followed by retrieving abstracts from a local copy of the PubMed archive. The main results presented to the user are individual sentences containing the gene symbol, organized by the keywords they also contain. These sentences are presented through an interactive graphical interface or as tables. GWAS results are displayed using a similar method. All results are linked to the original abstract in PubMed. In addition, a convolutional neural network is employed to distinguish sentences describing systemic stress from those describing cellular stress. The automated and comprehensive search strategy provided by GeneCup facilitates the integration of new discoveries from omic studies with existing literature. GeneCup is free and open source software. The source code of GeneCup and the link to a running instance is available at https://github.com/hakangunturkun/GeneCup


title: GeneCup: mine PubMed for gene relationships using custom ontology and deep learning


title: Cortical actin properties controlled by Drosophila Fos aid macrophage infiltration against surrounding tissue resistance

abstract: The infiltration of immune cells into tissues underlies the establishment of tissue resident macrophages, and responses to infections and tumors. Yet the mechanisms immune cells utilize to negotiate tissue barriers in living organisms are not well understood, and a role for cortical actin has not been examined. Here we find that the tissue invasion of Drosophila macrophages, also known as plasmatocytes or hemocytes, utilizes enhanced cortical F-actin levels stimulated by the Drosophila member of the fos proto oncogene transcription factor family (Dfos, Kayak). RNA sequencing analysis and live imaging show that Dfos enhances F-actin levels around the entire macrophage surface by increasing mRNA levels of the membrane spanning molecular scaffold tetraspanin TM4SF, and the actin cross-linking filamin Cheerio which are themselves required for invasion. Both the filamin and the tetraspanin enhance the cortical activity of Rho1 and the formin Diaphanous and thus the assembly of cortical actin, which is a critical function since expressing a dominant active form of Diaphanous can rescue the Dfos macrophage invasion defect. In vivo imaging shows that Dfos enhances the efficiency of the initial phases of macrophage tissue entry. Genetic evidence argues that this Dfos-induced program in macrophages counteracts the constraint produced by the tension of surrounding tissues and buffers the properties of the macrophage nucleus from affecting tissue entry. We thus identify strengthening the cortical actin cytoskeleton through Dfos as a key process allowing efficient forward movement of an immune cell into surrounding tissues.


title: APC-mutant cells exploit compensatory chromosome alterations to restore tumour cell fitness

abstract: Certain copy number alterations (CNAs) are strongly associated with particular cancer types. However, the mechanisms that underlie selection of specific CNAs remain unknown. Here, we identified functional relationships between recurrent CNAs in colorectal cancers (CRCs) and adenomatous polyposis coli (APC) mutations. Quantitative phenotyping of mitotic spindles highlighted APC functions at centrosomes where APC positively regulated Aurora A kinase (AURKA). Upon APC inactivation, elevated {beta}-catenin levels blocked AURKA activation, which caused chromosome instability and suppressed proliferation, resulting in the generation and selection of AURKA-activating CNAs. Arm-level amplification of chromosomes that contained AURKA and AURKA activator genes was observed in APC-mutant CRCs, early stage mouse tumours, and cells in culture, which was concomitant with an increase in growth potential. Our findings demonstrate a mechanism that restores tumour cell fitness through compensatory chromosome alterations to overcome adverse effects of prior mutations, which may affect the course of cancer type-specific CNA formation.


title: Persistence and invasiveness of high-level heteroplasmy through biparental transmission of a selfish mitochondrial genome in Drosophila.

abstract: Heteroplasmy is the coexistence of more than one type of mitochondrial genomes in an organism. Although widespread sequencing has identified several cases of transient or low-level heteroplasmy that primarily occur through mutation or paternal leakage, stable, high-titer heteroplasmy remains rare in animals. In this study we present a unique, stable and high-level heteroplasmy in male and female flies belonging to the neotropical Drosophila paulistorum species complex. We show that mitochondria of D. paulistorum are polyphyletic and form two clades,  and {beta}, with two subclades each. Mitochondrial genomes of the 2 subclade appear functional based on their genomic integrity but are exclusively found in heteroplasmic flies and never in homoplasmy, suggesting that they are a secondary mitotype with distinct functionality from the primary one. Using qPCR, we show that 2 titers do not respond to energetic demands of the cell and are generally higher in males than females. By crossing hetero- and homoplasmic flies, we find that 2 can be transmitted to their offspring via both parents and that levels are dependent on nuclear background. Following 2 mitotype levels during embryogenesis, we demonstrate that this secondary mitotype replicates rapidly just after fertilization of the egg in a period when primary mitochondria are dormant. This so-called "Replication precox" phenotype likely prevents the 2 mitotype from being outcompeted by the primary mitotype - and thereby secures its persistence and further spread as a selfish complete mt-genome, we hereby designate "Spartacus". Finally, we reconstruct the evolutionary history of mitochondrial genomes in the willistoni subgroup uncovering signs of multiple mitotype losses and introgressions. Our data indicate an -like mitochondrial ancestor in the willistoni subgroup, with the {beta} mitotype likely acquired via introgression from an unidentified donor. We hypothesize that the selfish characteristics of 2 might have emerged as a response to competition for inheritance with the introgressed {beta} mitotype.


title: Local projections of layer Vb-to-Va are more effective in lateral than in medial entorhinal cortex

abstract: The entorhinal cortex, in particular neurons in layer V, allegedly mediate transfer of information from the hippocampus to the neocortex, underlying long-term memory. Recently, this circuit has been shown to comprise a hippocampal output recipient layer Vb and a cortical projecting layer Va. With the use of in vitro electrophysiology in transgenic mice specific for layer Vb, we assessed the presence of the thus necessary connection from layer Vb-to-Va in the functionally distinct medial (MEC) and lateral (LEC) subdivisions; MEC, particularly its dorsal part, processes allocentric spatial information, whereas the corresponding part of LEC processes information representing elements of episodes. Using identical experimental approaches, we show that connections from layer Vb-to-Va neurons are more effective in LEC compared with dorsal MEC. This indicates that the hippocampal-cortex output circuit is more effective in LEC, suggesting that episodic systems-consolidation may use LEC-derived information more than allocentric spatial information from MEC.