title: Incorporating outlier information into diffusion MR tractogram filtering for robust structural brain connectivity and microstructural analyses

abstract:
The white matter structures of the human brain can be represented using diffusion-weighted MRI tractography. Unfortunately, tractography is prone to find false-positive streamlines causing a severe decline in its specificity and limiting its feasibility in accurate structural brain connectivity analyses. Filtering algorithms have been proposed to reduce the number of invalid streamlines but the currently available filtering algorithms are not suitable to process data that contains motion artefacts which are typical in clinical research. We augmented the Convex Optimization Modelling for Microstructure Informed Tractography (COMMIT) filtering algorithm to adjust for these signal drop-out motion artifacts. We demonstrate with comprehensive Monte-Carlo whole brain simulations and in vivo infant data that our robust algorithm is capable in properly filtering tractography reconstructions despite these artefacts. We evaluated the results using parametric and non-parametric statistics and our results demonstrate that if not accounted for, motion artefacts can have severe adverse effect in the human brain structural connectivity analyses as well as in microstructural property mappings. In conclusion, the usage of robust filtering methods to mitigate motion related errors in tractogram filtering is highly beneficial especially in clinical studies with uncooperative patient groups such as infants. With our presented robust augmentation and open-source implementation, robust tractogram filtering is readily available.

HighlightsO_LIWe present a novel augmentation to tractogram filtering method that accounts for subject motion related signal dropout artefacts in diffusion weighted images.
C_LIO_LIOur method is validated with realistic Monte-Carlo whole brain simulations and evaluated with in vivo infant data.
C_LIO_LIWe show that even if data has 10% of motion corrupted slices our method is capable to mitigate their effect in structural brain connectivity analyses and microstructural mapping.
C_LI


title: Normal Aging in Mice is Associated with a Global Reduction in Cortical Spectral Power and a Network-Specific Decline in Functional Connectivity

abstract: Normal aging is associated with a variety of neurologic changes including declines in cognition, memory, and motor activity. These declines correlate with neuronal changes in synaptic structure and function. Degradation of brain network activity and connectivity represents a likely mediator of age-related functional deterioration resulting from these neuronal changes. Human studies have demonstrated both general decreases in spontaneous cortical activity and disruption of cortical networks with aging. Current techniques used to study cerebral network activity are hampered either by limited spatial resolution (e.g. electroencephalography, EEG) or limited temporal resolution (e.g., functional magnetic resonance imaging, fMRI). Here we utilize mesoscale imaging of neuronal activity in Thy1-GCaMP6f mice to characterize neuronal network changes in aging with high spatial resolution across a wide frequency range. We show that while evoked activity is unchanged with aging, spontaneous neuronal activity decreases across a wide frequency range (0.01-4Hz) involving all regions of the cortex. In contrast to this global reduction in cortical power, we found that aging is associated with functional connectivity (FC) deterioration of select networks including somatomotor, cingulate, and retrosplenial nodes. These changes are corroborated by reductions in homotopic FC and node degree within somatomotor and visual cortices. Finally, we found that whole cortex delta power and delta band node degree correlate with exploratory activity in young but not aged animals. Together these data suggest that aging is associated with global declines in spontaneous cortical activity and focal deterioration of network connectivity, and that these reductions may be associated with age-related behavioral declines.

category: neuroscience


title: Normal Aging in Mice is Associated with a Global Reduction in Cortical Spectral Power and a Network-Specific Declines in Functional Connectivity


title: Normal Aging in Mice is Associated with a Global Reduction in Cortical Spectral Power and Network-Specific Declines in Functional Connectivity


title: Geometry of inter-areal interactions in mouse visual cortex

abstract: The response of a set of neurons in an area is the result of the sensory input, the interaction of the neurons within the area as well as the long range interactions between areas. We aimed to study the relation between interactions among multiple areas, and if they are fixed or dynamic. The structural connectivity provides a substrate for these interactions, but anatomical connectivity is not known in sufficient detail and it only gives us a static picture. Using the Allen Brain Observatory Visual Coding Neuropixels dataset, which includes simultaneous recordings of spiking activity from up to 6 hierarchically organized mouse cortical visual areas, we estimate the functional connectivity between neurons using a linear model of responses to flashed static grating stimuli. We characterize functional connectivity between populations via interaction subspaces. We find that distinct subspaces of a source area mediate interactions with distinct target areas, supporting the notion that cortical areas use distinct channels to communicate. Most importantly, using a piecewise linear model for activity within each trial, we find that these interactions evolve dynamically over tens of milliseconds following a stimulus presentation. Inter-areal subspaces become more aligned with the intra-areal subspaces during epochs in which a feedforward wave of activity propagates through visual cortical areas. When the short-term dynamics are averaged over, we find that the interaction subspaces are stable over multiple stimulus blocks. These findings have important implications for understanding how information flows through biological neural networks composed of interconnected modules, each of which may have a distinct functional specialization.


title: Clock time: a foreign measure to brain dynamics

abstract:
Human thought is highly flexible and dynamic, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. Here, we argue that this goal is impeded by the time format of our data - clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. A more appropriate time format is cycles of brain oscillations, which coordinate neural firing and are widely implicated in cognition. These brain dynamics do not obey clock time - they start out of tune with clock time and drift apart even further as oscillations unpredictably slow down, speed up, and undergo abrupt changes. Since oscillations clock cognition, their dynamics should critically inform our analysis. We describe brain time warping as a new method to transform data in accordance with brain dynamics, which sets the time axis to cycles of clocking oscillations (a native unit) rather than milliseconds (a foreign unit). We also introduce the Brain Time Toolbox, a software library that implements brain time warping for electrophysiology data and tests whether it reveals information patterns in line with how the brain uses them.

Glossary

O_TBL View this table:
org.highwire.dtl.DTLVardef@d81c2org.highwire.dtl.DTLVardef@c1ff2corg.highwire.dtl.DTLVardef@57dfa4org.highwire.dtl.DTLVardef@11b8c43org.highwire.dtl.DTLVardef@195a419_HPS_FORMAT_FIGEXP  M_TBL C_TBL


title: Molecular characterization of AMPA receptor trafficking vesicles

abstract: Regulated delivery of AMPA receptors (AMPARs) to the postsynaptic membrane is an essential step in synaptic strength modification, and in particular, long-term potentiation (LTP). While LTP has been extensively studied using electrophysiology and light microscopy, several questions regarding the molecular mechanisms of AMPAR delivery via trafficking vesicles remain outstanding, including the gross molecular make up of AMPAR trafficking organelles and identification and location of calcium sensors required for SNARE complex-dependent membrane fusion of such trafficking vesicles with the plasma membrane. Here, we isolated AMPAR trafficking vesicles (ATVs) from whole mouse brains via immunoprecipitation and characterized them using immunoelectron microscopy, immunoblotting, and liquid chromatography tandem mass spectrometry (LC-MS/MS). We identified several proteins on ATVs that were previously found to play a role in AMPAR trafficking, including SNARES (including synaptobrevin 2), Rabs, the SM protein Munc18-1, a calcium-sensor (synaptotagmin-1), as well as several new markers, including synaptophysin and synaptogyrin on ATV membranes. Additionally, we identified two populations of ATVs based on size and molecular composition: small-diameter, synaptobrevin-2- and GluA1-containing ATVs and larger transferrin-receptor-, GluA1-, GluA2-, GluA3-containing ATVs. The smaller population of ATVs likely represents a trafficking vesicle whose fusion is essential for LTP. These findings reveal the important role of AMPAR sorting into fusion-competent trafficking vesicles that are implicated in synaptic strength modification and reveal candidates of putative effectors and regulators of AMPAR trafficking.


title: Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film

abstract: Intracranial human recordings are a valuable and rare resource that the whole neuroscience community can benefit from. Making such data available to the neuroscience community not only helps tackle the reproducibility issues in science, it also helps make more use of this valuable data. The latter is especially true for data collected using naturalistic tasks. Here, we describe a dataset collected from a large group of human subjects while they watched a short audiovisual film. The dataset is characterized by several unique features. First, it combines a large amount of intracranial data from 51 intracranial electroencephalography (iEEG) participants, who all did the same task. Second, the intracranial data are accompanied by fMRI recordings acquired for the same task in 30 functional magnetic resonance imaging (fMRI) participants. Third, the data were acquired using a rich audiovisual stimulus, for which we provide detailed speech and video annotations. This multimodal dataset can be used to address questions about neural mechanisms of multimodal perception and language comprehension as well as the nature of the neural signal acquired during the same task across brain recording modalities.


title: Transcranial theta-burst stimulation of primary sensory cortex attenuates somatosensory threat memory in humans

abstract: Sensory cortices are required for learning to discriminate complex stimuli that predict threat from those that predict safety in rodents. Yet, sensory cortices may not be needed to learn threat associations to simple stimuli. It is unknown whether these findings apply in humans. Here, we investigated the role of primary sensory cortex in discriminative threat conditioning with simple and complex somatosensory conditioned stimuli (CS) in healthy humans. Immediately before conditioning, participants received continuous theta-burst transcranial magnetic stimulation (cTBS) to primary somatosensory cortex either in the CS-contralateral or CS-ipsilateral hemisphere. After overnight consolidation, threat memory was attenuated in the contralateral compared to the ipsilateral group, as indicated by reduced startle eye-blink potentiation. There was no evidence for a difference between simple and complex stimuli, or that CS identification or conditioning was affected, suggesting a stronger effect of cTBS on consolidation than on initial stimulus processing. We propose that non-invasive stimulation of sensory cortex may provide a new avenue for interfering with threat memories in humans.


title: Quantifying spinal cord vascular permeability in the mouse using intravital imaging

abstract: Sensory perception and motor dexterity is coordinated by in part distinct anatomical centres in the spinal cord. Importantly the spinal cord is the first modulatory relay hub for coordinating sensory and motor inputs to allow control of an organisms response to a sensory experience and to orientate proprioceptive outputs. This is whilst communicating with higher centres within the brain to undertake greater complex neurophysiological function such as pain perception. This begins to outline the complexity of the nervous system communication. To allow this integral system to function efficiently neuronal homeostasis needs to be maintained with energy expenditure matched by proficient delivery of nutrients. This factor introduces the vascular system that extensively interacts in a multifaceted manner with differing aspects of the nervous system. Part of this multi-factoral interaction is through the heterogenic cellular makeup of the vascular network that delivers and modulates the molecular transport of such nutrients to spinal cord tissues, but also controlling penetration and migration of harmful pathogens and agents. Therefore the spinal cord is susceptible to any alterations in the microvessel integrity (e.g. vascular leakage) and/or function (e.g. cessated blood flow) of this vascular network, which principally occurs in times of pathology. Typically investigations into microvessel function have utilised histological and/or tracer based in-vivo assays. Methodologies such as evans blue extravasation have been used inconjunction with in-vitro cell biology assays such as transwell assays to determine microvessel integrity or function that only provides snapshots of developing vasculopathy. Adopting in-vivo imaging approaches, allow for real time functional measurements of the ongoing physiological function within the spinal cord, providing direct measurement of the vascular processes in play, including vascular architecture, blood flow and/or permeability. This technique in mouse allow for direct visualisation of cellular and/or mechanistic influence upon vascular function through utilising disease, transgenic and/or viral approaches. This combination of attributes allows for in depth real time understanding of the function of the vascular network within the spinal cord.


title: Enteric glial cells favour accumulation of anti-inflammatory macrophages during the resolution of muscularis inflammation

abstract:
ObjectiveMonocyte-derived macrophages (M{varphi}s) are crucial regulators during muscularis inflammation. However, it is unclear which microenvironmental factors are responsible for monocyte recruitment and neurotrophic M{varphi} differentiation in this paradigm. Here, we investigate M{varphi} heterogeneity at different stages of muscularis inflammation and determine how environmental cues can attract and activate tissue protective M{varphi}s.

DesignSingle cell RNA sequencing was performed on immune cells from the muscularis of wild-type and CCR2-/- mice at different timepoints after muscularis inflammation. CX3CR1GFP/+ and CX3CR1CreERT2 R26YFP mice were analyzed by flow cytometry and immunofluorescence. The transcriptome of enteric glial cells (EGCs) was investigated using PLPCreERT2 Rpl22HA mice. In addition, we assessed the effect of supernatant from neurosphere-derived EGCs on monocyte differentiation based on the expression of pro- and anti-inflammatory factors.

ResultsMuscularis inflammation induced marked alterations in mononuclear phagocyte populations associated with a rapid infiltration of Ly6c+ monocytes that locally acquired unique transcriptional states. Trajectory inference analysis revealed two main pro-resolving M{varphi} subpopulations during the resolution of muscularis inflammation, i.e. Cd206+ MhcIIhi and Timp2+ MhcIIlo M{varphi}s, which were both derived from CCR2+ monocytes. Interestingly, we found that EGCs were able to sense damage to the muscularis to stimulate monocyte recruitment and differentiation towards pro-resolving M{varphi}s via CCL2 and CSF1, respectively.

ConclusionOur study provides a comprehensive insight into pro-resolving M{varphi} differentiation and their regulators during muscularis inflammation. We deepened our understanding in the interaction between EGCs and M{varphi}s, thereby highlighting pro-resolving M{varphi} differentiation as a potential novel therapeutic strategy for the treatment of intestinal inflammation.

category: immunology


title: An ancient antimicrobial protein co-opted by a fungal plant pathogen for in planta mycobiome manipulation

abstract:
Microbes typically secrete a plethora of molecules to promote niche colonization. Soil-dwelling microbes are well-known producers of antimicrobials that are exploited to outcompete microbial co-inhabitants. Also plant pathogenic microbes secrete a diversity of molecules into their environment for niche establishment. Upon plant colonization, microbial pathogens secrete so-called effector proteins that promote disease development. While such effectors are typically considered to exclusively act through direct host manipulation, we recently reported that the soil-borne fungal xylem-colonizing vascular wilt pathogen Verticillium dahliae exploits effector proteins with antibacterial properties to promote host colonization through the manipulation of beneficial host microbiota. Since fungal evolution preceded land plant evolution, we now speculate that a subset of the pathogen effectors involved in host microbiota manipulation evolved from ancient antimicrobial proteins of terrestrial fungal ancestors that served in microbial competition prior to the evolution of plant pathogenicity. Here, we show that V. dahliae has co-opted an ancient antimicrobial protein as effector, named VdAMP3, for mycobiome manipulation in planta. We show that VdAMP3 is specifically expressed to ward off fungal niche competitors during resting structure formation in senescing mesophyll tissues. Our findings indicate that effector-mediated microbiome manipulation by plant pathogenic microbes extends beyond bacteria and also concerns eukaryotic members of the plant microbiome. Finally, we demonstrate that fungal pathogens can exploit plant microbiome-manipulating effectors in a life-stage specific manner, and that a subset of these effectors has evolved from ancient antimicrobial proteins of fungal ancestors that likely originally functioned in manipulation of terrestrial biota.

SIGNIFICANCE STATEMENTMicrobes secrete a diversity of molecules into their environment to mediate niche colonization. During host ingress, plant pathogenic microbes secrete effector proteins that facilitate disease development, many of which deregulate host immune responses. We recently demonstrated that plant pathogens additionally exploit effectors with antibacterial activities to manipulate beneficial plant microbiota to promote host colonization. Here, we show that the fungal pathogen Verticillium dahliae has co-opted an ancient antimicrobial protein, that likely served in microbial competition in terrestrial environments before land plants existed, as effector for the manipulation of fungal competitors during host colonization. Thus, we demonstrate that pathogen effector repertoires comprise antifungal proteins, and speculate such effectors could be exploited for the development of novel antimycotics.

category: microbiology


title: Amyloid aggregation of Streptococcus mutans Cnm influences its collagen-binding activity

abstract:
The glycosylated collagen- and laminin-binding surface adhesin Cnm is present in approximately 20% of S. mutans clinical isolates and is associated with systemic infections and increased caries risk. Other surface-associated collagen-binding proteins of S. mutans such as P1 and WapA have been demonstrated to form an amyloid quaternary structure with functional implications within biofilms. In silico analysis predicted that the {beta}-sheet rich N-terminal collagen-binding domain (CBD) of Cnm has propensity for amyloid aggregation, whereas the threonine-rich C-terminal domain was predicted to be disorganized. In this study, thioflavin-T fluorescence and electron microscopy were used to show that Cnm forms amyloids either in its native glycosylated or recombinant non-glycosylated forms and that the CBD of Cnm is the main amyloidogenic unit of Cnm. We then performed a series of in vitro, ex vivo and in vivo assays to characterize the amylogenic properties of Cnm. In addition, Congo red birefringence indicated that Cnm is a major amyloidogenic protein of S. mutans biofilms. Competitive binding assays using collagen-coated microtiter plates and dental roots, a substrate rich in collagen, revealed that Cnm monomers inhibit S. mutans binding to collagenous substrates whereas Cnm amyloid aggregates lose this property. Thus, while Cnm contributes to recognition and initial binding of S. mutans to collagen-rich surfaces, Cnm amyloid aggregation appears to represent a mechanism to modulate this activity in mature biofilms.

IMPORTANCEStreptococcus mutans is a keystone pathogen that promotes caries by acidifying the dental biofilm milieu. The collagen- and laminin-binding glycoprotein Cnm is a virulence factor found in about 20% of the clinical isolates of S. mutans. Expression of Cnm by S. mutans is associated with niche expansion, allowing colonization of multiple sites in the body including collagen-rich surfaces such as dentin and heart valves. Here, we demonstrate for the first time that Cnm function appears to be modulated by its aggregation status. As a monomer, its primary function is to promote attachment to collagenous substrates via its collagen binding domain (CBD). However, in later stages of biofilm maturation, the same CBD of Cnm self-assembles into amyloid fibrils, losing the ability to bind to collagen and likely becoming a component of the biofilm matrix. Our findings shed light into the role of functional amyloids in S. mutans pathobiology and ecology.


title: Splicing stimulates antisense transcription by RNA polymerase II at DNA double-strand breaks in Drosophila cells

abstract: DNA double-strand breaks are among the most toxic lesions that can occur in a genome and their faithful repair is thus of great importance. Recent findings have uncovered local transcription that initiates at the break and forms a non-coding transcript, called damage-induced long non-coding RNA (dilncRNA), which helps to coordinate the DNA transactions necessary for repair. We provide nascent RNA sequencing-based evidence that RNA polymerase II transcribes the dilncRNA in Drosophila and that this is more efficient for DNA breaks in an intron-containing gene, consistent with the higher damage-induced siRNA levels downstream of an intron. The spliceosome thus stimulates recruitment of RNA polymerase II to the break, rather than merely promoting the annealing of sense and antisense RNA to form the siRNA precursor. In contrast, RNA polymerase III nascent RNA libraries did not contain reads corresponding to the cleaved loci and selective inhibition of RNA polymerase III did not reduce the yield of damage-induced siRNAs. Finally, the damage-induced siRNA density was unchanged downstream of a T8 sequence, which terminates RNA polymerase III transcription. We thus found no evidence for a participation of RNA polymerase III in dilncRNA transcription in cultured Drosophila cells.

category: molecular biology


title: RNA polymerase II is recruited to DNA double-strand breaks for dilncRNA transcription in Drosophila


title: A rat model of male pregnancy

abstract:
Male pregnancy is a unique phenomenon in syngnathidae which refers to embryo or fetus incubation by males. However, whether male mammalian animals have the potential to conceive and maintain pregnancy remains unclear. Here, we constructed a rat model of pregnancy in the male parabiont using a four-step strategy. First, a heterosexual parabiotic pair was produced by surgically joining a castrated male rat and a female rat. After 8 weeks, uterus transplantation was performed on the male parabiont. After recovery, blastocyst-stage embryos were transplanted to the grafted uterus of the male parabiont and the native uterus of the female parabiont. Caesarean section was performed at embryonic day 21.5. The success rate of the model was 3.68%, and pups were only delivered from the male parabiont under pregnant blood exposure. Our results reveal the potential for rat embryonic development in male parabionts, which may have a profound impact on reproductive biology.

One-sentence summaryA rat model of pregnancy was constructed in the male parabiont using a four-step strategy.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/447686v2_ufig1.gif" ALT="Figure 1">
View larger version (46K):
org.highwire.dtl.DTLVardef@1f0694eorg.highwire.dtl.DTLVardef@91997forg.highwire.dtl.DTLVardef@f47086org.highwire.dtl.DTLVardef@7a33f_HPS_FORMAT_FIGEXP  M_FIG C_FIG

category: developmental biology


title: A rat model of pregnancy in the male parabiont


title: Sustained experimental activation of FGF8/ERK in the developing chicken spinal cord reproducibly models early events in ERK-mediated tumorigenesis

abstract: Most human cancers demonstrate activated MAPK/ERK pathway signaling as a key tumor initiation step, but the immediate steps of further oncogenic progression are poorly understood due to a lack of appropriate models. Spinal cord differentiation follows caudal elongation in vertebrate embryos; both processes are regulated by a FGF8 gradient highest in neuromesodermal progenitors (NMP), where kinase effectors ERK1/2 maintain an undifferentiated state. FGF8/ERK signal attenuation is necessary for NMPs to progress to differentiation. We show that sustained ERK1/2 activity, using a constitutively active form of the kinase MEK1 (MEK1ca) in the chicken embryo, reproducibly provokes neopasia in the developing spinal cord. Transcriptomic data show that neoplasia not only relies on the maintenance of NMP gene expression, and the inhibition of genes expressed in the differentiating spinal cord, but also on a profound change in the transcriptional signature of the spinal cord cells leading to a complete loss of cell-type identity. MEK1ca expression in the developing spinal cord of the chicken embryo is therefore a tractable in vivo model to identify the critical factors fostering malignancy in ERK-induced tumorigenesis.


title: The calcifying interface in a stony coral's primary polyp: An interplay between seawater and an extracellular calcifying space

abstract: Stony coral exoskeletons build the foundation to the most biologically diverse yet fragile marine ecosystems on earth, coral reefs. Understanding corals biomineralization mechanisms is therefore crucial for coral reef management and for using coral skeletons in geochemical studies. In this study, we combine in-vivo and cryo-electron microscopy with single-cell RNA-seq data to gain novel insights into the calcifying micro-environment that facilitates biomineralization in primary polyps of the stony coral Stylophora pistillata. We show an intimate involvement of seawater in this micro-environment. We further document increased tissue permeability and a highly dispersed cell packing in the tissue secreting the coral skeleton (i.e. calicoblastic). We also observe an extensive filopodial network containing carbon-rich vesicles extruding from some of the calicoblastic cells. Single-cell RNA-Seq data interrogation shows that calicoblastic cells express genes involved in filopodia and vesicle structure and function. These observations provide a new conceptual framework for resolving stony corals biomineralization processes.


title: RCaN: a software for Chance and Necessity modelling

abstract:
Uncertainty is a challenge in modelling ecological systems and has been a source of misunderstandings between modelers and non-modelers. The "Chance and Necessity" (CaN) modelling approach has been proposed to address this issue, in the case of trophic network modelling. CaN modelling focuses exploring food-web trajectories that can satisfy fundamental physical and biological laws, while being compatible with observations and domain knowledge. This type of approach can facilitate discussion among actors as it promotes sharing of information and does not presuppose any knowledge of modelling practices. It is therefore suitable for participatory modelling, i.e. a modelling approach in which different actors can confront their knowledge and understanding of the marine system and of the associated uncertainties.

One important ingredient to achieve participatory modelling is the availability of a modelling platform that is efficient, fast and transparent, so that all actors can understand and follow the modelling steps and choices, and can rapidly visualize and discuss the results. But, until now, there existed no software to easily perform CaN modelling. Here, we present RCaN and RCaNconstructor. Combined, these provide the first tool to build CaN models in an intuitive way that is 1) suitable within participatory frameworks, 2) transparent, 4) computationally efficient, 5) fully documented through the provision of meta-information and 6) supportive of exploratory analyses through predefined graphical functions.

category: ecology


title: Beyond tracking climate: niche evolution during native range expansion and its implications for novel invasions

abstract:
AimAlthough ecological niche models have been instrumental in understanding the widespread species distribution shifts under global change, rapid niche shifts limit model transferability to novel locations or time periods. Niche shifts during range expansion have been studied extensively in invasive species, but may also occur in native populations tracking climate change. We compared niche shifts during both types of range expansion in a Mediterranean annual plant to ask (i) whether the species native range expansion tracked climate change, (ii) whether further range expansion was promoted by niche expansion, and (iii) how these results changed forecasts of two ongoing invasions in Australia and California.

LocationEurasian Holarctic, California and Australia

TaxonDittrichia graveolens (L.) Greuter (Asteraceae)

MethodsNiche shifts were quantified in both environmental and geographic space, using the framework of niche centroid shift, overlap, unfilling, and expansion (COUE) as well as Maximum Entropy modelling. We used the historic native distribution and climate data (1901-1930) to project the expected distribution in the present climate (1990-2019), and compared it to the observed current distribution of D. graveolens. Finally, we compared invasion forecasts based on the historic and present native niches.

ResultsWe found that D. graveolens expanded its native range well beyond what would be sufficient to track climate change, associated with a 5.5% niche expansion towards more temperate climates. In contrast, both invasions showed niche conservatism, and were (still) constrained to climatic areas matching the historic native niche.

Main conclusionsour results show that contrary to hypotheses in the literature, niche shifts are not necessarily more rapid in invasions than in native range expansions. We conclude that niche expansion during the process of climate tracking may cause further range expansion than expected based on climate change alone.


title: Beyond tracking climate: niche shifts during native range expansion and their implications for novel invasions


title: Genetic analysis of praziquantel resistance in schistosome parasites implicates a Transient Receptor Potential channel

abstract:
Mass treatment with praziquantel (PZQ) monotherapy is the mainstay for schistosomiasis treatment. This drug shows imperfect cure rates in the field and parasites showing reduced PZQ response can be selected in the laboratory, but the extent of resistance in Schistosoma mansoni populations is unknown. We examined the genetic basis of variation in PZQ response in a S. mansoni population (SmLE-PZQ-R) selected with PZQ in the laboratory: 35% of these worms survive high dose (73 {micro}g/mL) PZQ treatment. We used genome wide association to map loci underlying PZQ response. The major chr. 3 peak contains a transient receptor potential (Sm.TRPMPZQ) channel (Smp_246790), activated by nanomolar concentrations of PZQ. PZQ response shows recessive inheritance and marker-assisted selection of parasites at a single Sm.TRPMPZQ SNP enriched populations of PZQ-resistant (PZQ-ER) and sensitive (PZQ-ES) parasites showing >377 fold difference in PZQ response. The PZQ-ER parasites survived treatment in rodents better than PZQ-ES. Resistant parasites show 2.25-fold lower expression of Sm.TRPMPZQ than sensitive parasites. Specific chemical blockers of Sm.TRPMPZQ enhanced PZQ resistance, while Sm.TRPMPZQ activators increased sensitivity. A single SNP in Sm.TRPMPZQ differentiated PZQ-ER and PZQ-ES lines, but mutagenesis showed this was not involved in PZQ-response, suggesting linked regulatory changes. We surveyed Sm.TRPMPZQ sequence variation in 259 parasites from the New and Old World revealing one nonsense mutation that results in a truncated protein with no PZQ-binding site. Our results demonstrate that Sm.TRPMPZQ underlies variation in PZQ response in S. mansoni and provides an approach for monitoring emerging PZQ-resistance alleles in schistosome elimination programs.

One Sentence SummaryA transient receptor potential channel determines variation in praziquantel-response in Schistosoma mansoni.

category: genetics


title: Genetic analysis of praziquantel response in schistosome parasites implicates a Transient Receptor Potential channel


title: Impact of SNP calling quality on the detection of transmission ratio distortion in goats

abstract: Transmission ratio distortion (TRD) is the preferential transmission of one specific allele to offspring at the expense of the other one. The existence of TRD is mostly explained by the segregation of genetic variants with deleterious effects on the developmental processes that go from the formation of gametes to fecundation and birth. A few years ago, a statistical methodology was implemented in order to detect TRD signals on a genome-wide scale as a first step to uncover the biological basis of TRD and reproductive success in domestic species. In the current work, we have analyzed the impact of SNP calling quality on the detection of TRD signals in a population of Murciano-Granadina goats. Seventeen bucks and their offspring (N=288) were typed with the Goat SNP50 BeadChip, while the genotypes of the dams were lacking. Performance of a genome-wide scan revealed the existence of 36 SNPs showing significant evidence of TRD. When we calculated GenTrain scores for each one of the SNPs, we observed that 25 SNPs showed scores below 0.8. The allele frequencies of these SNPs in the offspring were not correlated with the allele frequencies estimated in the dams with statistical methods, thus evidencing that flawed SNP calling quality might lead to the detection of spurious TRD signals. We conclude that, when performing TRD scans, the GenTrain scores of markers should be taken into account to discriminate SNPs that are truly under TRD from those yielding spurious signals due to technical problems.


title: Deep Learning-Based Brain Transcriptomic Signatures Associated with the Neuropathological and Clinical Severity of Alzheimer's Disease

abstract: Brain tissue gene expression from donors with and without Alzheimers disease (AD) have been used to help inform the molecular changes associated with the development and potential treatment of this disorder. Here, we use a deep learning method to analyze RNA-seq data from 1,114 brain donors from the AMP-AD consortium to characterize post-mortem brain transcriptome signatures associated with amyloid-{beta} plaque, tau neurofibrillary tangles, and clinical severity in multiple AD dementia populations. Starting from the cross-sectional data in the ROSMAP cohort (n = 634), a deep learning framework was built to obtain a trajectory that mirrors AD progression. A severity index (SI) was defined to quantitatively measure the progression based on the trajectory. Network analysis was then carried out to identify key gene (index gene) modules present in the model underlying the progression. Within this dataset, SIs were found to be very closely correlated with all AD neuropathology biomarkers (R [~] 0.5, p < 1e-11) and global cognitive function (R = -0.68, p < 2.2e-16). We then applied the model to additional transcriptomic datasets from different brain regions (MAYO, n = 266; MSBB, n = 214), and observed that the model remained significantly predictive (p < 1e-3) of neuropathology and clinical severity. The index genes that significantly contributed to the model were integrated with AD co-expression regulatory networks, resolving four discrete gene modules that are implicated in vascular and metabolic dysfunction in different cell types respectively. Our work demonstrates the generalizability of this signature to frontal and temporal cortex measurements and additional brain donors with AD, other age-related neurological disorders and controls; and revealed the transcriptomic network modules contribute to neuropathological and clinical disease severity. This study illustrates the promise of using deep learning methods to analyze heterogeneous omics data and discover potentially targetable molecular networks that can inform the development, treatment and prevention of neurodegenerative diseases like AD.

category: genomics


title: The effect of in vitro culture on unicellular eukaryotes: adaptation of Trypanosoma brucei brucei bloodstream forms results in gene copy-number changes.

abstract: Most researchers who study unicellular eukaryotes work with an extremely limited number of laboratory-adapted isolates that were obtained from the field decades ago, but the effects of passage in laboratory rodents, and adaptation to in vitro culture, have been little studied. For example, the vast majority of studies of Trypanosoma brucei biology have concentrated on just two strains, Lister 427 and EATRO1125, which were taken from the field over half a century ago and have since have undergone innumerable passages in rodents and culture. We here describe two new Trypanosoma brucei brucei strains. MAK65 and MAK98, which have undergone only 3 rodent passages since isolation from Ugandan cattle. High-coverage sequencing revealed that adaptation of the parasites to culture was accompanied by changes in gene copy numbers. T. brucei has so far been considered to be uniformly diploid, but we also found trisomy of chromosome 5 not only in one Lister 427 culture, but also in the MAK98 field isolate. Trisomy of chromosome 6, and increased copies of other chromosome segments, were also seen in established cultured lines. The two new T. brucei strains should be useful to researchers interested in trypanosome differentiation and pathogenicity. Initial results suggested that the two strains have differing infection patterns in rodents. MAK65 is uniformly diploid and grew more reproducibly in bloodstream-form culture than MAK98.


title: In vitro culture of freshly isolated Trypanosoma brucei brucei bloodstream forms results in gene copy-number changes.


title: The genome sequence of the avian vampire fly (Philornis downsi), an invasive nest parasite of Darwins finches in Galpagos

abstract: The invasive avian vampire fly (Philornis downsi) is considered one of the greatest threats to the unique and endemic avifauna of the Galapagos Islands, Ecuador. The fly parasitizes nearly every passerine species, including Darwins finches, in the Galapagos. The fly is thought to have been introduced from mainland Ecuador, although the full pathway of invasion is not yet known. The majority of research to date has focused on the effects of the fly on the fitness of avian hosts and explorations of mitigation methods. A lag in research related to the genetics of this invasion demonstrates, in part, a need to develop full-scale genomic resources with which to address further questions within this system. In this study, an adult P. downsi collected from San Cristobal Island within the Galapagos archipelago was sequenced to generate a high-quality genome assembly. We examined various features of the genome (e.g., coding regions, non-coding transposable elements) and carried out comparative genomics analysis against other dipteran genomes. We identified lists of gene families that are significantly expanding/contracting in P. downsi that are related to insecticide resistance, detoxification, and potential feeding ecology and counter defense against host immune responses. The P. downsi genome assembly provides an important foundational resource for studying the molecular basis of its successful invasion in the Galapagos and the dynamics of its population across multiple islands. The findings of significantly changing gene families associated with insecticide resistance and immune responses highlight the need for further investigations into the role of different gene families in aiding the flys successful invasion. Furthermore, this genomic resource will also better help inform future research studies and mitigation strategies aimed at minimizing the flys impact on the birds of the Galapagos.


title: The genome sequence of the avian vampire fly (Philornis downsi), an invasive nest parasite of Darwin's finches in Galapagos


title: Indigenous ancestry and admixture in the Uruguayan population

abstract:
The Amerindian group known as the Charruas inhabited Uruguay at the timing of European colonial contact. Even though they were extinguished as an ethnic group as a result of a genocide, Charruan heritage is part of the Uruguayan identity both culturally and genetically. While mitochondrial DNA studies have shown evidence of Amerindian ancestry in living Uruguayans, here we undertake whole-genome sequencing of 10 Uruguayan individuals with Charruan heritage. We detect chromosomal segments of Amerindian ancestry supporting the presence of indigenous genetic ancestry in living descendants. Specific haplotypes were found to be enriched in  Charruas and rare in the rest of the Amerindian groups studied. Some of these we interpret as the result of positive selection, as we identified selection signatures and they were located mostly within genes related to the infectivity of specific viruses.

Historical records describe contacts of the Charruas with other Amerindians, such as Guarani, and patterns of genomic similarity observed here concur with genomic similarity between these groups. Less expected, we found a high genomic similarity of the Charruas to Diaguita from Argentinian and Chile, which could be explained by geographically proximity.

Finally, by fitting admixture models of Amerindian and European ancestry for the Uruguayan population, we were able to estimate the timing of the first pulse of admixture between European and Uruguayan indigenous peoples in 1658 and the second migration pulse in 1683. Both dates roughly concurring with the Franciscan missions in 1662 and the foundation of the city of Colonia in 1680 by the Spanish.


title: Ghrelin proteolysis by insulin-degrading enzyme

abstract: Here we report proteolysis of synthetic acylated human ghrelin by recombinant human insulin-degrading enzyme (IDE). Kinetic parameters and sites of proteolytic cleavage were evaluated. Ghrelin proteolysis by IDE was inhibited by ethylenediaminetetraacetate (EDTA), a metal chelating agent. Ghrelin proteolysis appears at least somewhat specific to M16 family proteases such as IDE, as the M13 protease neprilysin (NEP) did not exhibit ghrelin proteolysis in this study. A quenched fluorogenic peptide substrate comprising the primary sites of IDE-mediated ghrelin proteolysis (Mca-QRVQQRKESKK(Dnp)-OH; Mca: 7-methoxycoumarin-3-carboxylic acid; Dnp: 2,4-dinitrophenyl) was developed and used to evaluate enzyme specificity and kinetic parameters of proteolysis. Like acyl ghrelin, Mca-QRVQQRKESKK(Dnp)-OH was efficiently cleaved by IDE central to the target sequence. We anticipate that this quenched fluorogenic peptide substrate will be of value to future studies of ghrelin proteolysis by IDE and potentially other peptidases.

category: biochemistry


title: BacPROTACs mediate targeted protein degradation in bacteria

abstract: Hijacking the cellular protein degradation system offers unique opportunities for drug discovery, as exemplified by proteolysis targeting chimeras (PROTACs). Despite their superior properties over classical inhibitors, it has so far not been possible to reprogram the bacterial degradation machinery to interfere with microbial infections. Here, we develop small-molecule degraders, so-called BacPROTACs, that bind to the substrate receptor of the ClpC:ClpP protease, priming neo-substrates for degradation. In addition to their targeting function, BacPROTACs activate ClpC, transforming the resting unfoldase into its functional state. The induced higher-order oligomer was visualized by cryo-EM analysis, providing a structural snapshot of activated ClpC unfolding a protein substrate. Finally, degradation assays performed in mycobacteria demonstrate in vivo activity of BacPROTACs, highlighting the potential of the technology to provide next generation antibiotics.


title: Muscope: A miniature on-chip lensless microscope

abstract: In the past few decades, a significant amount of effort has been put into developing different lensless microscope designs. The existing lensless microscopes are capable of offering high resolution and wide field-of-view using super-resolution and computational techniques. But, the employment of macroscopic illumination system and unscalable opto-mechanical components limit their cost-effectiveness, scalability, mass production and on-chip integration. In this work, we report Muscope, an on-chip microscope, which fixes these issues. It extends a few mm in each dimension and comprises of an off-the-shelf electronic assembly. The futuristic microLED display chip is utilised as the light source. Each microLED on the chip functions as a microscopic light source whose position and brightness can be electronically controlled. To demonstrate Muscope, we imaged human blood smear and microbeads of diameter upto 1 m. We also provide a proof-of-concept of its suitability with super-resolution and field-of-view enhancement techniques, without additional hardware compulsions.

category: bioengineering


title: Segmentation of Pancreatic Ductal Adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and Texture Descriptors

abstract: Fully automated and volumetric segmentation of critical tumors may play a crucial role in diagnosis and surgical planning. One of the most challenging tumor segmentation tasks is localization of Pancreatic Ductal Adenocarcinoma (PDAC). Exclusive application of conventional methods does not appear promising. Deep learning approaches has achieved great success in the computer aided diagnosis, especially in biomedical image segmentation. This paper introduces a framework based on convolutional neural network (CNN) for segmentation of PDAC mass and surrounding vessels in CT images by incorporating powerful classic features, as well. First, a 3D-CNN architecture is used to localize the pancreas region from the whole CT volume using 3D Local Binary Pattern (LBP) map of the original image. Segmentation of PDAC mass is subsequently performed using 2D attention U-Net and Texture Attention U-Net (TAU-Net). TAU-Net is introduced by fusion of dense Scale-Invariant Feature Transform (SIFT) and LBP descriptors into the attention U-Net. An ensemble model is then used to cumulate the advantages of both networks using a 3D-CNN. In addition, to reduce the effects of imbalanced data, a new loss function is proposed as a weighted combination of three classic losses including Generalized Dice Loss (GDL), Weighted Pixel-Wise Cross Entropy loss (WPCE) and boundary loss. Due to insufficient sample size for vessel segmentation, we used the above-mentioned pre-trained networks and fin-tuned them. Experimental results show that the proposed method improves the Dice score for PDAC mass segmentation in portal-venous phase by 7.52% compared to state-of-the-art methods (from 53.08% to 60.6%) in term of DSC. Besides, three dimensional visualization of the tumor and surrounding vessels can facilitate the evaluation of PDAC treatment response.


title: NanoSpring: reference-free lossless compression of nanopore sequencing reads using an approximate assembly approach

abstract:
MotivationThe amount of data produced by genome sequencing experiments has been growing rapidly over the past several years, making compression important for efficient storage, transfer and analysis of the data. In recent years, nanopore sequencing technologies have seen increasing adoption since they are portable, real-time and provide long reads. However, there has been limited progress on compression of nanopore sequencing reads obtained in FASTQ files. Previous work ENANO focuses mostly on quality score compression and does not achieve significant gains for the compression of read sequences over general-purpose compressors. RENANO achieves significantly better compression for read sequences but is limited to aligned data with a reference available.

ResultsWe present NanoSpring, a reference-free compressor for nanopore sequencing reads, relying on an approximate assembly approach. We evaluate NanoSpring on a variety of datasets including bacterial, metagenomic, plant, animal, and human whole genome data. For recently basecalled high quality nanopore datasets, NanoSpring achieves close to 3x improvement in compression over state-of-the-art reference-free compressors. The computational requirements of NanoSpring are practical, although it uses more time and memory during compression than previous tools to achieve the compression gains.

AvailabilityNanoSpring is available on GitHub at https://github.com/qm2/NanoSpring.

Supplementary informationSupplementary data are available on BioRxiv.

category: bioinformatics


title: Shape-restrained modelling of protein-small molecule complexes with HADDOCK

abstract:
Small molecule docking remains one of the most valuable computational techniques for the structure prediction of protein-small molecule complexes. It allows us to study the interactions between compounds and the protein receptors they target at atomic detail, in a timely and efficient manner. Here we present a new protocol in HADDOCK, our integrative modelling platform, which incorporates homology information for both receptor and compounds. It makes use of HADDOCKs unique ability to integrate information in the simulation to drive it toward conformations which agree with the provided data. The focal point is the use of shape restraints derived from homologous compounds bound to the target receptors. We have developed two protocols: In the first, the shape is composed of fake atom beads based on the position of the heavy atoms of the homologous template compound, whereas in the second the shape is additionally annotated with pharmacophore data, for some or all beads. For both protocols, ambiguous distance restraints are subsequently defined between those beads and the heavy atoms of the ligand to be docked. We have benchmarked the performance of these protocols with a fully unbound version of the widely used DUD-E dataset. In this unbound docking scenario, our template/shape-based docking protocol reaches an overall success rate of 81% on 99 complexes, which is close to the best results reported for bound docking on the DUD-E dataset.

Table of contents graphic

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/447890v1_ufig1.gif" ALT="Figure 1">
View larger version (26K):
org.highwire.dtl.DTLVardef@15faf1dorg.highwire.dtl.DTLVardef@e1d311org.highwire.dtl.DTLVardef@1e8225eorg.highwire.dtl.DTLVardef@1285ed0_HPS_FORMAT_FIGEXP  M_FIG C_FIG


title: Optimized Splitting of RNA Sequencing Data by Species

abstract: Gene expression studies using chimeric xenograft transplants or co-culture systems have proven to be valuable to uncover cellular dynamics and interactions during development or in disease models. However, the mRNA sequence similarities among species presents a challenge for accurate transcript quantification. To identify optimal strategies for analyzing mixed-species RNA sequencing data, we evaluate both alignment-dependent and alignment-independent methods. Alignment of reads to a pooled reference index is effective, particularly if optimal alignments are used to classify sequencing reads by species, which are re-aligned with individual genomes, generating >97% accuracy across a range of species ratios. Alignment-independent methods, such as Convolutional Neural Networks, which extract the conserved patterns of sequences from two species, classify RNA sequencing reads with over 85% accuracy. Importantly, both methods perform well with different ratios of human and mouse reads. Our evaluation identifies valuable and effective strategies to dissect species composition of RNA sequencing data from mixed populations.


title: Motif-based phosphoproteome clustering improves modeling and interpretation

abstract:
Cell signaling is orchestrated in part through a network of protein kinases and phosphatases. Dysregulation of kinase signaling is widespread in diseases such as cancer and is readily targetable through inhibitors of kinase enzymatic activity. Mass spectrometry-based analysis of kinase signaling can provide a global view of kinase signaling regulation but making sense of these data is complicated by its stochastic coverage of the proteome, measurement of substrates rather than kinase signaling itself, and the scale of the data collected. Here, we implement a dual data and motif clustering strategy (DDMC) that simultaneously clusters substrate peptides into similarly regulated groups based on their variation within an experiment and their sequence profile. We show that this can help to identify putative upstream kinases and supply more robust clustering. We apply this clustering to large-scale clinical proteomic profiling of lung cancer and identify conserved proteomic signatures of tumorigenicity, genetic mutations, and tumor immune infiltration. We propose that DDMC provides a general and flexible clustering strategy for the analysis of phosphoproteomic data.

One-sentence SummaryDDMC is a general and flexible strategy for phosphoproteomic analysis by clustering phosphopeptides using both their phosphorylation abundance and sequence motifs.


title: SignalP 6.0 achieves signal peptide prediction across all types using protein language models

abstract:
Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. As experimental characterization of SPs is costly, prediction algorithms are applied to predict them from sequence data. However, existing methods are unable to detect all known types of SPs. We introduce SignalP 6.0, the first model capable of detecting all five SP types. Additionally, the model accurately identifies the positions of regions within SPs, revealing the defining biochemical properties that underlie the function of SPs in vivo. Results show that SignalP 6.0 has improved prediction performance, and is the first model to be applicable to metagenomic data.

SignalP 6.0 is available at https://services.healthtech.dtu.dk/service.php?SignalP-6.0


title: Assessment of deep learning algorithms for 3D instance segmentation of confocal image datasets

abstract:
Segmenting three dimensional microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed which claim to provide high accuracy segmentation of cellular images and are increasingly considered as the state-of-the-art for image segmentation problems. However, it remains difficult to define their relative performances as the concurrent diversity and lack of uniform evaluation strategies makes it difficult to know how their results compare. In this paper, we first made an inventory of the available DL methods for 3 dimensional (3D) cell segmentation. We next implemented and quantitatively compared a number of representative DL pipelines, alongside a highly efficient non-DL method named MARS. The DL methods were trained on a common dataset of 3D cellular confocal microscopy images. Their segmentation accuracies were also tested in the presence of different image artifacts. A specific method for segmentation quality evaluation was adopted which isolates segmentation errors due to under/over segmentation. This is complemented with a 3D visualization strategy for interactive exploration of segmentation quality. Our analysis shows that the DL pipelines have different levels of accuracy. Two of them, which are end to end 3D and were originally designed for cell boundary detection, show high performance, and offer clear advantages in terms of adaptability to new data.

Author summaryIn recent years a number of deep learning (DL) algorithms based on computational neural networks have been developed which claim to achieve high accuracy and automatic segmentation of 3D microscopy images. Although these algorithms have received considerable attention in the literature, it is difficult to evaluate their relative performances, while it remains unclear whether they really perform better than other, more classical segmentation methods.

To clarify these issues, we performed a detailed, quantitative analysis of a number of representative DL pipelines for cell instance segmentation from 3D confocal microscopy image datasets. We developed a protocol for benchmarking the performances of such DL based segmentation pipelines using common training and test datasets, evaluation metrics and visualizations. Using this protocol, we evaluated and compared four different DL pipelines to identify their strengths and limitations. A high performance non-DL method was also included in the evaluation. We show that DL pipelines may show significant differences in their performances depending on their model architecture and pipeline components but overall show excellent adaptability to unseen data. We also show that our benchmarking protocol could be extended to a variety of segmentation pipelines and datasets.


title: Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets


title: CANT-HYD: A curated database of phylogeny-derived Hidden Markov Models for annotation of marker genes involved in hydrocarbon degradation

abstract: Discovery of microbial hydrocarbon degradation pathways has traditionally relied on laboratory isolation and characterization of microorganisms. Although many metabolic pathways for hydrocarbon degradation have been discovered, the absence of tools dedicated to their annotation makes it difficult to identify the relevant genes and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Furthermore, sequence homology between hydrocarbon degradation genes and genes with other functions often results in misannotation. A tool that systematically identifies hydrocarbon metabolic potential is therefore needed. We present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database containing HMMs of 37 marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we show that hydrocarbon metabolic potential is widespread in the tree of life and identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate scalability by analyzing large metagenomic datasets for the prediction of hydrocarbon utilization in diverse environments. To the best of our knowledge, CANT-HYD is the first comprehensive tool for robust and accurate identification of marker genes associated with aerobic and anaerobic hydrocarbon degradation.


title: scSVAS: CNV clonal visualization online platform for large scale single-cell genomics

abstract: The recent advance of single-cell copy number variation analysis plays an essential role in addressing intra-tumor heterogeneity, identifying tumor subgroups, and restoring tumor evolving trajectories at single-cell scale. Pleasant visualization of copy number analysis results boosts productive scientific exploration, validation, and sharing. Several single-cell analysis figures have the effectiveness of visualizations for understanding single-cell genomics in published articles and software packages. However, they almost lack real-time interaction, and it is hard to reproduce them. Moreover, existing tools are time-consuming and memory-intensive when they reach large-scale single-cell throughputs. We present an online visualization platform, scSVAS, for real-time interactive single-cell genomics data visualization. scSVAS is specifically designed for large-scale single-cell analysis. Compared with other tools, scSVAS manifests the most comprehensive functionalities. After uploading the specified input files, scSVAS deploys the online interactive visualization automatically. Users may make scientific discoveries, share interactive visualization, and download high-quality publication-ready figures. scSVAS provides versatile utilities for managing, investigating, sharing, and publishing single-cell copy number variation profiles. We envision this online platform will expedite the biological understanding of cancer clonal evolution in single-cell resolution. All visualizations are publicly hosted at https://sc.deepomics.org.


title: Anti-GD2 antibody therapy alters the neuroblastoma tumor microenvironment and extends survival in TH-MYCN mice

abstract:
BackgroundNeuroblastoma is a commonly lethal solid tumor of childhood and intensive chemoradiotherapy treatment cures ~50% of children with high-risk disease. The addition of immunotherapy using dinutuximab, a monoclonal antibody directed against the GD2 disialoganglioside expressed on neuroblasts, improves survival when incorporated into front-line therapy and shows robust activity in regressing relapsed disease when combined with chemotherapy. Still, many children succumb to neuroblastoma despite receiving dinutuximab-based immunotherapy, and efforts to counteract the immune suppressive signals responsible are warranted. Animal models of human cancers provide useful platforms to study immunotherapies. TH-MYCN transgenic mice are immunocompetent and develop neuroblastomas at autochthonous sites due to enforced MYCN expression in developing neural crest tissues. However, GD2-directed immunotherapy in this model has been underutilized due to the prevailing notion that TH-MYCN neuroblasts express insufficient GD2 to be targeted.

MethodsTH-MYCN mice were treated with 14G2a (anti-GD2 antibody), isotype antibody, or phosphate buffered saline from day 14 of life until day 100 or signs of morbidity. Survival was recorded, and tumors were isolated in terminal surgeries for analysis of GD2 expression and immune cell frequencies. Tumors from untreated mice were explanted for generation into cell lines, and GD2 expression was recorded with serial passage in tissue culture. Immunocytology and immunoblotting were performed to evaluate for adrenergic and mesenchymal markers of neuroblasts. Survival curves compared using Kaplan-Meier method with a log-rank test for significance. Unpaired two-tailed Students t-tests used for comparison of groups in flow cytometry analysis.

Results14G2a markedly extends survival in such TH-MYCN mice. Additionally, neuroblasts in 14G2a-treated mice have reduced GD2 expression and fewer macrophage and myeloid-derived suppressor cells in their tumor microenvironments. Neuroblasts in TH-MYCN-driven tumors express GD2 at levels comparable to human neuroblastomas but rapidly lose GD2 expression when explanted ex vivo to establish tumor cell lines. The loss of GD2 expression ex vivo is associated with a transition from an adrenergic to mesenchymal state that is maintained when reimplanted in vivo.

ConclusionsOur findings support the utility of the TH-MYCN model to inform GD2-directed immunotherapy approaches for neuroblastoma as well as opportunities to investigate drivers of adrenergic to mesenchymal fate decisions.

category: cancer biology


title: Phenotyping the tumor-immune microenvironment (TiME) in vivo by cellular-level optical imaging reveals unique combination phenotypes with variable inflammation and endothelial anergy

abstract: Immunotherapies have shown unprecedented clinical benefits in several malignancies1-3. However, clinical responses remain variable and unpredictable, indicating the need to develop predictive platforms that can improve patient stratification4. Phenotyping of tumors into hot, altered, or cold5 based on assessment of only T-cell infiltration in static tumor biopsies provides suboptimal prediction of immunotherapy response6,7. In vivo dynamic mechanisms within the tumor microenvironment such as tumor angiogenesis and leukocyte trafficking5,8,9 also play a central role in modulating anti-tumor immunity and therefore immunotherapy response. Here, we report novel tumor immune microenvironment (TiME) phenotyping in vivo in patients with non-invasive spatially-resolved cellular-level imaging based on endogenous contrast. Investigating skin cancers as a model, with reflectance confocal microscopy (RCM) imaging10, we determined four major phenotypes with variable prevalence of vasculature (Vasc) and inflammation (Inf) features: VaschiInfhi, VaschiInflo, VascloInfhi and Vascmed/hiInflo. The VaschiInfhi phenotype correlates with high immune activation, exhaustion, and vascular signatures while VaschiInflo with endothelial anergy and immune exclusion. Automated quantification of TiME features demonstrates moderate-high accuracy and correlation with corresponding gene expression. Prospectively analyzed response to topical immunotherapy show highest response in VascloInfhi, and reveals the added value of vascular features in predicting treatment response. Our novel in vivo cellular-level imaging and phenotyping approach can potentially advance our fundamental understanding of TiME, develop robust predictors for immunotherapy outcomes and identify novel targetable pathways in future.


title: Cellular-level phenotyping of tumor-immune microenvironment (TiME) in patients in vivo reveals distinct inflammation and endothelial anergy signatures


title: Identification of novel pulmonary vein nodes as generators of ectopic arrhythmic foci for atrial fibrillation: An immuno-histochemical proof

abstract:
IntroductionThe atrial muscle sleeve (AMS) of the pulmonary vein is the most common source of the arrhythmogenic triggers in atrial fibrillation (AF). Anatomical substrate generating these ectopic currents is still elusive. The present study was designed to study the AMS of pulmonary veins with an emphasis on the structural basis which might govern AF initiation and perpetuation.

Materials and MethodsThe study was conducted on longitudinal tissue section of pulmonary vein, taken from 15 human cadaveric non-diseased hearts. Tissue was studied histologically using H&E and Gomori trichrome stain. The pacemaker channels were identified by immunohistochemistry using monoclonal HCN4 and HCN1 antibodies.

ResultsThe AMS was identified in each pulmonary vein, located between the tunica adventitia and tunica media. A node like arrangement of myocytes was seen within the AMS in 30% of veins. It had a compact zone limited by a fibrous capsule and contained much smaller, paler and interconnected myocytes. Outside the capsule there was a zone of dispersed, singly placed myocytes separating the compact zone from the working myocytes of the AMS. HCN4 and HCN1 antibodies were expressed on the cell membrane of nodal myocytes, while the working myocytes demonstrated none to minimal staining.

ConclusionPulmonary veins nodes are similar to the specialized cardiac conductive tissue in, histological arrangement of compact and transitional zones, cellular characteristics, and the presence of pacemaker channels. They might be the anatomical basis of ectopic arrhythmogenic foci. To our knowledge these nodes are being described for the first time in human.

category: pathology


title: A robust field-based method to screen heat tolerance in wheat

abstract: Wheat is highly sensitive to elevated temperatures, particularly during pollen meiosis and early-to-mid grain filling. The impact of heat stress greatly depends on the plant developmental stage. Thus, germplasm ranking for heat tolerance in field trials may be confounded by variations in developmental phase between genotypes at the time of heat events. A photoperiod-extension method (PEM) was developed allowing screening of 35 diverse genotypes at matched developmental phase despite phenological variations. Paired trials were conducted to compare the new PEM against conventional field screening in plots. In the PEM, plants were sown in single rows or small plots. Artificial lighting was installed at one end of each row or plot to extend day length, inducing a gradient of flowering times with distance from the lights. Individual stems or plot quadrats of each genotype were tagged at flowering. Late-sown plants received more heat shocks during early to mid grain filling than earlier sowings, suffering reductions in both individual grain weight (IGW) and yield. IGW was reduced by 1.5 mg for each additional post-flowering day with temperature > 30{degrees}C. Significant genotypic differences in heat tolerance ranking were observed between PEM versus conventional plot screening. Strong correlations between trials experiencing similar degree of heat were found both for IGW and for total grain weight with the PEM either with individual-stem tagging (e.g. average r of 0.59 and 0.54, respectively for environments with moderate postflowering heat) or quadrat tagging (r of 0.53 and 0.47). However, correlations for IGW and yield in these environments were either poor or negative for conventional trials (e.g. average r of 0.11 and 0.12, respectively for environments with moderate postflowering heat). Accordingly, a PCA grouped genotypes consistently for heir performance across environments with similar heat stress in PEM trials but not in conventional trials. In this study, most consistent genotype ranking for heat tolerance was achieved with the PEM with tagging and harvesting individual spikes at matched developmental phase. The PEM with quadrat sampling provided slightly less consistent rankings but appears overall more suitable for high-throughput phenotyping. The method promises to improve the efficiency of heat tolerance field screening, particularly when comparing genotypes of different maturity types.

category: plant biology


title: Underwater CAM photosynthesis elucidated by Isoetes genome

abstract: To conserve water in arid environments, numerous plant lineages have independently evolved Crassulacean Acid Metabolism (CAM). Interestingly, Isoetes, an aquatic lycophyte, can also perform CAM as an adaptation to low CO2 availability underwater. However, little is known about the evolution of CAM in aquatic plants and the lack of genomic data has hindered comparison between aquatic and terrestrial CAM. Here, we investigated the underwater CAM in Isoetes taiwanensis by generating a high-quality genome assembly and RNA-seq time course. Despite broad similarities between CAM in Isoetes and terrestrial angiosperms, we identified several key differences. Notably, for carboxylation of PEP, Isoetes recruited the lesser-known "bacterial-type" PEPC, along with the "plant-type" exclusively used in other terrestrial CAM and C4 plants. Furthermore, we found that circadian control of key CAM pathway genes has diverged considerably in Isoetes relative to flowering plants. This suggests the existence of more evolutionary paths to CAM than previously recognized.


title: Calcium-permeable cation channels are involved in uranium uptake in Arabidopsis thaliana

abstract: Uranium (U) is a non-essential and toxic element that is taken up by plants from the environment. The assimilation pathway of U is still unknown in plants and any other organism. In this study, we provide several evidences that U is taken up by the roots of Arabidopsis thaliana through Ca2+-permeable cation channels. First, we showed that deprivation of Arabidopsis plants with calcium induced a 1.5-fold increase in the capacity of roots to accumulate U, suggesting that calcium deficiency promoted the radionuclide import pathway. Second, we showed that external calcium inhibits U accumulation in roots, suggesting a common route for the uptake of both cations. Third, we found that gadolinium, nifedipine and verapamil inhibit the absorption of U, suggesting that different types of Ca2+-permeable channels serve as a route for U uptake. Last, we showed that U bioaccumulation in Arabidopsis mutants deficient for the Ca2+-permeable channels MCA1 and ANN1 was decreased by 40%. This suggests that MCA1 and ANN1 contribute to the absorption of U in different zones and cell layers of the root. Together, our results describe for the first time the involvement of Ca2+-permeable cation channels in the cellular uptake of U.


title: Quantitative and population genomics suggest a broad role of staygreen loci in the drought adaptation of sorghum

abstract:
O_LIDrought is a major constraint on plant productivity globally. Sorghum (Sorghum bicolor) landraces have evolved in drought-prone regions, but the genetics of their adaptation is not yet understood. Loci underlying stay-green post-flowering drought tolerance (Stg), have been identified in a temperate breeding line, but their role in drought adaptation of tropical sorghum is to be elucidated.
C_LIO_LIWe phenotyped 590 diverse sorghum accessions from West Africa under field-based managed drought stress, pre-flowering (WS1) and post-flowering (WS2) over several years and conducted genome-wide association studies (GWAS).
C_LIO_LIBroad-sense heritability for grain and biomass yield components was high (33-92%) across environments. There was a significant correlation between stress tolerance index (STI) for grain weight across WS1 and WS2. GWAS revealed that SbZfl1 and SbCN12, orthologs of maize flowering genes, likely underlie flowering time variation under these conditions. GWAS further identified associations (n = 134) for STI and drought effects on yield components, including 16 putative pleiotropic associations. Thirty of the associations colocalized with Stg1-4 loci and had large effects. Seven lead associations, including some within Stg1, overlapped with positive selection outliers.
C_LIO_LIOur findings reveal natural genetic variation for drought tolerance-related traits, and suggest a broad role of Stg loci in drought adaptation of sorghum.
C_LI


title: Scalable and Automated CRISPR-Based Strain Engineering Using Droplet Microfluidics

abstract: We present a droplet-based microfluidic system that enables CRISPR-based gene editing and high-throughput screening on chip. The microfluidic device contains a 10 x 10 element array, each element containing sets of electrodes for two electric field actuated operations-electrowetting for merging droplets to mix reagents and electroporation for transformation. It can perform up to 100 genetic modifications in parallel, providing a scalable platform for generating the large number of engineered strains required for combinatorial optimization of genetic pathways and predictable bioengineering. We demonstrate the systems capabilities through CRISPR-based engineering of two test cases-1) disruption of the function of enzyme galactokinase (galK) in E. coli and 2) targeted engineering of glutamine synthetase gene (glnA) and blue-pigment synthetase (bpsA) enzyme to improve indigoidine production in E. coli.

category: synthetic biology


title: Systems analysis reveals ageing-related perturbations in retinoids and sex hormones in Alzheimer's and Parkinson's diseases

abstract: Neurodegenerative diseases (NDDs), including Alzheimers (AD) and Parkinsons diseases (PD), are complex heterogeneous diseases with highly variable patient responses to treatment. Due to the growing evidence for ageing-related clinical and pathological commonalities between AD and PD, these diseases have recently been studied in tandem. In this study, we analyse transcriptomic data from AD and PD patients, and stratify these patients into three subclasses with distinct gene expression and metabolic profiles. Through integrating transcriptomic data with a genome-scale metabolic model and validating our findings by network exploration and co-analysis using a zebrafish ageing model, we identify retinoids as a key ageing-related feature in all subclasses of AD and PD. We also demonstrate that the dysregulation of androgen metabolism by three different independent mechanisms is a source of heterogeneity in AD and PD. Taken together, our work highlights the need for stratification of AD/PD patients and development of personalised and precision medicine approaches based on the detailed characterisation of these subclasses.

category: systems biology


title: Monod model is insufficient to explain biomass growth in nitrogen-limited yeast fermentation

abstract:
The yeast Saccharomyces cerevisiae is an essential microorganism in food biotechnology; particularly, in wine and beer making. During wine fermentation, yeasts transform sugars present in the grape juice into ethanol and carbon dioxide. The process occurs in batch conditions and is, for the most part, an anaerobic process. Previous studies linked limited-nitrogen conditions with problematic fermentations, with negative consequences for the performance of the process and the quality of the final product. It is, therefore, of the highest interest to anticipate such problems through mathematical models. Here we propose a model to explain fermentations under nitrogen-limited anaerobic conditions. We separated the biomass formation into two phases: growth and carbohydrate accumulation. Growth was modelled using the well-known Monod equation while carbohydrate accumulation was modelled by an empirical function, analogous to a proportional controller activated by the limitation of available nitrogen. We also proposed to formulate the fermentation rate as a function of the total protein content when relevant data are available. The final model was used to successfully explain experiments taken from the literature, performed under normal and nitrogen-limited conditions. Our results revealed that Monod model is insufficient to explain biomass formation kinetics in nitrogen-limited fermentations of S. cerevisiae. The goodness-of-fit of the herewith proposed model is superior to that of previously published models, offering the means to predict, and thus control fermentations.

ImportanceProblematic fermentations still occur in the winemaking industrial practise. Problems include sluggish rates of fermentation, which have been linked to insufficient levels of assimilable nitrogen. Data and relevant models can help anticipate poor fermentation performance. In this work, we proposed a model to predict biomass growth and fermentation rate under nitrogen-limited conditions and tested its performance with previously published experimental data. Our results show that the well-known Monod equation does not suffice to explain biomass formation.


title: The long arm of childhood socioeconomic deprivation on mid- to later-life cognitive trajectories : A cross-cohort analysis

abstract:
INTRODUCTIONEarlier studies of the effects of childhood socioeconomic status (SES) on later life cognitive function consistently report a social gradient in later life cognitive function. Evidence for their effects on cognitive decline is, however, less clear.

METHODSThe sample consists of 5,324 participants in the Whitehall II Study, 8,572 in the Health and Retirement Study, and 1,413 in the Kame Project, who completed self-report questionnaires on their early-life experiences and underwent repeated cognitive assessments. We characterised cognitive trajectories using latent class mixed models, and explored associations between childhood SES and latent class membership using logistic regressions.

RESULTSWe identified distinct trajectories classes for all cognitive measures examined. Childhood socioeconomic deprivation was associated with an increased likelihood of being in a lower trajectory class.

DISCUSSIONOur findings support the notions that cognitive ageing is a heterogeneous process and early-life circumstances may have lasting effects on cognition across the life-course.

Research in contextO_LISystematic review: We reviewed the literature on childhood socioeconomic status (SES) as a predictor for cognitive decline in mid- to later-life using PubMed. Studies generally reported lower childhood SES is associated with poorer baseline cognition, but not a faster rate of decline. These studies generally focused on the mean rate of decline in the population; no study to date has explored associations between childhood SES and different cognitive trajectories. Relevant studies have been appropriately cited.
C_LIO_LIInterpretation: Our findings suggest that cognitive trajectories differ between individuals and across cognitive domains. Individuals of lower childhood SES were more likely to be in a lower cognitive trajectory class, which may or may not involve more rapid decline.
C_LIO_LIFuture directions: Future studies should include more cognitive outcomes and longer follow-ups, as well as investigate the impact of social mobility to further improve our understanding on how early-life circumstances influence cognitive decline.
C_LI


title: Toward a More Accurate 3D Atlas of C. elegans Neurons

abstract: Determining cell identity in volumetric images of tagged neuronal nuclei is an ongoing challenge in contemporary neuroscience. Frequently, cell identity is determined by aligning and matching tags to an "atlas" of labeled neuronal positions and other identifying characteristics. Previous analyses of such C. elegans datasets have been hampered by the limited accuracy of such atlases, especially for neurons present in the ventral nerve cord, and also by time-consuming manual elements of the alignment process. We present a novel automated alignment method for sparse and incomplete point clouds of the sort resulting from typical C. elegans fluorescence microscopy datasets. This method involves a tunable learning parameter and a kernel that enforces biologically realistic deformation. We also present a pipeline for creating alignment atlases from datasets of the recently developed NeuroPAL transgene. In combination, these advances allow us to label neurons in volumetric images with confidence much higher than previous methods. We release, to the best of our knowledge, the most complete C. elegans 3D positional neuron atlas, encapsulating positional variability derived from 7 animals, for the purposes of cell-type identity prediction for myriad applications (e.g., imaging neuronal activity, gene expression, and cell-fate).


title: CREB repressor in mushroom body enhances Drosophila LTM formation

abstract: Long-term memory (LTM) requires learning-induced synthesis of new proteins allocated to specific neurons and synapses in a neural circuit. Not all learned information, however, becomes permanent memory. How the brain gates relevant information into LTM remains unclear. In Drosophila adults, a single training session in an olfactory aversive task is not sufficient to induce protein synthesis-dependent LTM. Instead, multiple spaced training sessions are required. Here, we report that initial learning induces neural activity in the early /{beta} subset of Kenyon cells of the mushroom body (MB), and output from these neurons inhibits LTM formation. Specifically in response to spaced training, Schnurri activates CREBB expression which then appears to suppress the inhibitory output from MB. One training session can enhance LTM formation when this inhibitory effect is relieved. We propose that learning-induced protein synthesis and spaced training-induced CREBB act antagonistically to modulate output from early /{beta} MB neurons during LTM formation.


title: Phase-specific pooling of sparse assembly activity by respiration-related brain oscillations

abstract: Nasal breathing affects cognitive functions, but it has remained largely unclear how respiration-driven inputs shape information processing in neuronal circuits. Current theories emphasize the role of neuronal assemblies, coalitions of transiently active pyramidal cells, as the core unit of cortical network computations. Here, we show that respiration-related oscillations (RROs) directly pace the activation of neuronal assemblies in the medial prefrontal cortex (mPFC) of mice. Neuronal assemblies are more efficiently entrained than single neurons and activate preferentially during the descending phase of RROs. At the same time, overlap between individual assemblies is minimized during descending RRO due to the efficient recruitment of GABAergic neurons by assemblies. Our results thus suggest the RROs support cortical operations by defining time windows of enhanced yet segregated assembly activity.


title: Nonlinear transient amplification in recurrent neural networks with short-term plasticity

abstract: To rapidly process information, neural circuits have to amplify specific activity patterns transiently. How the brain performs this nonlinear operation remains elusive. Hebbian assemblies are one possibility whereby symmetric excitatory connections boost neuronal activity. However, such Hebbian amplification is often associated with dynamical slowing of network dynamics, non-transient attractor states, and pathological run-away activity. Feedback inhibition can alleviate these effects but typically linearizes responses and reduces amplification gain. At the same time, other alternative mechanisms rely on asymmetric connectivity, in conflict with the Hebbian doctrine. Here we propose nonlinear transient amplification (NTA), a plausible circuit mechanism that reconciles symmetric connectivity with rapid amplification while avoiding the above issues. NTA has two distinct temporal phases. Initially, positive feedback excitation selectively amplifies inputs that exceed a critical threshold. Subsequently, short-term plasticity quenches the run-away dynamics into an inhibition-stabilized network state. By characterizing NTA in supralinear network models, we establish that the resulting onset transients are stimulus selective and well-suited for speedy information processing. Further, we find that excitatory-inhibitory co-tuning widens the parameter regime in which NTA is possible. In summary, NTA provides a parsimonious explanation for how excitatory-inhibitory co-tuning and short-term plasticity collaborate in recurrent networks to achieve transient amplification.


title: pySuStaIn: a Python implementation of the Subtype and Stage Inference algorithm

abstract:
Progressive disorders are highly heterogeneous. Symptom-based clinical classification of these disorders may not reflect the underlying pathobiology. Data-driven subtyping and staging of patients has the potential to disentangle the complex spatiotemporal patterns of disease progression. Tools that enable this are in high demand from clinical and treatment-development communities. Here we describe the pySuStaIn software package, a Python-based implementation of the Subtype and Stage Inference (SuStaIn) algorithm. SuStaIn unravels the complexity of heterogeneous diseases by inferring multiple disease progression patterns (subtypes) and individual severity (stages) from cross-sectional data. The primary aims of pySuStaIn are to enable widespread application and translation of SuStaIn via an accessible Python package that supports simple extension and generalization to novel modelling situations within a single, consistent architecture.

Code metadataCurrent code version v1.0

Permanent link to code/repository used of this code version https://github.com/ucl-pond/pySuStaIn

Legal Code License MIT

Code versioning system used git

Software code languages, tools, and services used Python

Compilation requirements, operating environments & dependencies Linux, Mac, Windows

Support email for questions leon.aksman@loni.usc.edu, p.wijeratne@ucl.ac.uk, alexandra.young@kcl.ac.uk


title: Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography

abstract: The pial arterial vasculature of the human brain is the only blood supply to the neocortex, but quantitative data on the morphology and topology of these mesoscopic arteries (diameter 50- 300 {micro}m) remains scarce. Because it is commonly assumed that blood flow velocities in these vessels are prohibitively slow, non-invasive time-of-flight MRI angiography (TOF-MRA)--which is well-suited to high 3D imaging resolutions--has not been applied to imaging the pial arteries. Here, we provide a theoretical framework that outlines how TOF-MRA can visualize small pial arteries in vivo, by employing extremely small voxels at the size of individual vessels. We then provide evidence for this theory by imaging the pial arteries at 140-{micro}m isotropic resolution using a 7T MRI scanner and prospective motion correction, and show that pial arteries one voxel-width in diameter can be detected. We conclude that imaging pial arteries is not limited by slow blood flow, but instead by achievable image resolution. This study represents the first targeted, comprehensive account of imaging pial arteries in vivo in the human brain. This ultra-high-resolution angiography will enable the characterization of pial vascular anatomy across the brain to investigate patterns of blood supply and relationships between vascular and functional architecture.


title: Dietary modulation alters susceptibility to Listeria monocytogenes and Salmonella typhimurium in a gut microbiota-independent manner

abstract:
Food safety has considerably improved worldwide, yet infections with food-borne human enteric pathogens, such as Listeria spp. and Salmonella spp., still cause numerous hospitalizations and fatalities. Thus, the need to shed more light on the mechanisms of enteropathogenesis is apparent. Since dietary alterations, including fiber deficiency, might impact the colonization resistance by the gut microbiota, studying diet-microbiota-pathogen axis holds promise in further understanding the pathogenesis mechanisms. Using a gnotobiotic mouse model containing a 14-member synthetic human gut microbiota (14SM), we have previously shown that dietary fiber deprivation promotes proliferation of mucin-degrading bacteria leading to a microbiota-mediated erosion of the colonic mucus barrier, which results in an increased susceptibility towards the rodent enteric pathogen Citrobacter rodentium. Here, we sought to understand how low-fiber diet affects susceptibility to Listeria monocytogenes and Salmonella typhimurium infections in our 14SM gnotobiotic mouse model, in BALB/c and C57BL/6N backgrounds, respectively. Intriguingly and in contrast to our results with C. rodentium, we observe that depriving mice of dietary fiber protected them from infections with the pathogens compared to mice fed a standard chow. The microbiota delayed the overall pathogenicity as compared to the onset of disease observed in germ-free control mice; nevertheless, we observe the same effect of diet in germ-free mice, suggesting that the susceptibility is microbiota independent. Our study points out an important observation that dietary fiber plays a crucial role on either the host susceptibility, the virulence of these pathogens, or both, which would be judicious to design and interpret future studies.

ImportanceHuman enteric pathogens Listeria monocytogenes and Salmonella typhimurium are employed as classical models in rodent hosts to understand the pathogenesis mechanisms of food-borne pathogens. Research in the past decade has stressed importance of the composition of the gut microbiota in modulating susceptibility to these pathogens. Our results--using gnotobiotic mice and germ-free control animals--additionally suggest that the dietary fiber components dominate the impact of enteropathogenic virulence over the pathogenicity-modulating properties of the gut microbiota. The significance of our research is in the need to carefully choose a certain chow when performing the enteropathogen-associated mouse experiments and to cautiously match the rodent diets when trying to replicate experiments across different laboratories. Finally, our data underscore the importance of germ-free control animals to study these pathogens, as our findings would have been prone to misinterpretation in the absence of these controls.


title: High-affinity iron and calcium transport pathways are involved in U(VI) uptake in the budding yeast Saccharomyces cerevisiae

abstract:
Uranium (U) is a naturally-occurring radionuclide toxic for living organisms that can take it up. To date, the mechanisms of U uptake are far from being understood. Here, we used the yeast Saccharomyces cerevisiae as a unicellular eukaryote model to identify U assimilation pathways. Thus, we have identified, for the first time, transport machineries capable of transporting U in a living organism. First, we evidenced a metabolism-dependent U transport in yeast. Then, competition experiments with essential metals allowed us to identify calcium, iron and copper entry pathways as potential routes for U uptake. The analysis of various metal transport mutants revealed that mid1{Delta}, cch1{Delta} and ftr1{Delta} mutants, affected in calcium (Mid1/Cch1 channel) and Fe(III) (Ftr1/Fet3 complex) transport, respectively, exhibited highly reduced U uptake rates and accumulation, demonstrating the implication of these import systems in U uptake. Finally, expression of the Mid1 gene into the mid1{Delta} mutant restored U uptake levels of the wild type strain, underscoring the central role of the Mid1/Cch1 calcium channel in U absorption process in yeast. Our results also open up the opportunity for rapid screening of U-transporter candidates by functional expression in yeast, before their validation in more complex higher eukaryote model systems.

HighlightsO_LILiving yeast Saccharomyces cerevisiae is able to take up U
C_LIO_LIAvailability of a metabolizable substrate stimulates U uptake
C_LIO_LICalcium, iron and copper inhibit U uptake
C_LIO_LIStrains deleted in Mid1/Cch1 calcium channel and Ftr1 iron permease are affected in U uptake
C_LIO_LIExpression of MID1 gene in mid1{Delta} strain restore wild type levels of U uptake
C_LI

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/447839v1_ufig1.gif" ALT="Figure 1">
View larger version (27K):
org.highwire.dtl.DTLVardef@153dbe0org.highwire.dtl.DTLVardef@8874bcorg.highwire.dtl.DTLVardef@a7f353org.highwire.dtl.DTLVardef@57feb1_HPS_FORMAT_FIGEXP  M_FIG Graphical Abstract

C_FIG


title: A high content microscopy screening identifies genes involved in cell width control in Bacillus subtilis

abstract: How cells control their shape and size is a fundamental question of biology. In most bacteria, cell shape is imposed by the peptidoglycan (PG) polymeric meshwork that surrounds the cell. Thus, bacterial cell morphogenesis results from the coordinated action of the proteins assembling and degrading the PG shell. Remarkably, during steady-state growth, most bacteria maintain a defined shape along generations, suggesting that error-proof mechanisms tightly control the process. In the rod-shaped model for Gram-positive bacteria Bacillus subtilis, the average cell length varies as a function of the growth rate but the cell diameter remains constant throughout the cell cycle and across growth conditions. Here, in an attempt to shed light on the cellular circuits controlling bacterial cell width, we developed a screen to identify genetic determinants of cell width in B. subtilis. Using high-content screening (HCS) fluorescence microscopy and semi-automated measurement of single-cell dimensions, we screened a library of ~ 4000 single knockout mutants. We identified 13 mutations significantly altering cell diameter, in genes that belong to several functional groups. In particular, our results indicate that metabolism plays a major role in cell width control in B. subtilis.


title: A high content microscopy screening identifies new genes involved in cell width control in Bacillus subtilis