title: Generation of Infant-dedicated Fine-grained Functional Parcellation Maps of Cerebral Cortex

abstract: Infancy is a dynamic and immensely important period in human brain development. Studies of infant functional development using resting-state fMRI rely on precisely defined cortical parcellation maps. However, available adult-based functional parcellation maps are not applicable for infants due to their substantial differences in functional organizations. Fine-grained infant-dedicated cortical parcellation maps are highly desired but remain scarce, due to difficulties ranging from acquiring to processing of infant brain MRIs. In this study, leveraging 1,064 high-resolution longitudinal rs-fMRIs from 197 infants from birth to 24 months and advanced infant-dedicated processing tools, we create the first set of infant-specific, fine-grained cortical functional parcellation maps. Besides the conventional folding-based cortical registration, we specifically establish the functional correspondences across individuals using functional gradient densities and generate both age-specific and age-common fine-grained parcellation maps. The first set of comprehensive brain functional developmental maps are accordingly derived, and reveals a complex, hitherto unseen multi-peak fluctuation development pattern in temporal variations of gradient density, network sizes, and local efficiency, with more dynamic changes during the first 9 months than other ages. Our proposed method is applicable in generating fine-grained parcellations for the whole lifespan, and our parcellation maps will be available online to advance the neuroimaging field.


title: Association between plasma phospho-tau181 and cognitive change from age 73 to 82: Lothian Birth Cohort 1936

abstract:
INTRODUCTIONPlasma phospho-tau 181 (p-tau181) is a promising blood biomarker for Alzheimers disease. However, its predictive validity for age-related cognitive decline without dementia remains unclear. Several forms of p-tau have been shown to contribute to synapse degeneration, but it is unknown whether p-tau181 is present in synapses. Here, we tested whether plasma p-tau181predicts cognitive decline and whether it is present in synapses in human brain.

METHODSGeneral cognitive ability and plasma p-tau181 concentration were measured in 195 participants at ages 72 and 82. Levels of p-tau181 in total homogenate and synaptic fractions were compared with western blot (n=10-12 per group), and synaptic localisation was examined using array tomography.

RESULTSElevated baseline plasma p-tau181 and increasing p-tau181 over time predicted steeper general cognitive decline. We observe p-tau181 in neurites, presynapses, and post-synapses in the brain.

DISCUSSIONBaseline and subsequent change in plasma p-tau181 may represent rare biomarkers of differences in cognitive ageing across the 8th decade of life and may play a role in synaptic function in the brain.

category: neuroscience


title: Consequences of human Tau aggregation in the hippocampal formation of ageing mice in vivo

abstract: Intracellular aggregation of hyperphosphorylated Tau (pTau) in the brain is associated with cognitive and motor impairments, and ultimately neurodegeneration. We investigate how human pTau affects cells and network activity in the hippocampal formation of THY-Tau22 tauopathy model mice in vivo. We find that pTau preferentially accumulates in deep-layer pyramidal neurons, leading to neurodegeneration, and we establish that pTau spreads to oligodendrocytes. During goal-directed virtual navigation in aged transgenic mice, we detect fewer high-firing pyramidal cells, with the remaining cells retaining their coupling to theta oscillations. Analysis of network oscillations and firing patterns of pyramidal and GABAergic neurons recorded in head-fixed and freely-moving mice suggests preserved neuronal coordination. In spatial memory tests, transgenic mice have reduced short-term familiarity but spatial working and reference memory are surprisingly normal. We hypothesize that unimpaired subcortical network mechanisms implementing cortical neuronal coordination compensate for the widespread pTau aggregation, loss of high-firing cells and neurodegeneration.


title: Non-invasive real-time access to spatial attention information from 3T fMRI BOLD signals

abstract: Access to higher cognitive functions in real-time remains very challenging, because these functions are internally driven and their assessment is based onto indirect measures. In addition, recent finding show that these functions are highly dynamic. Previous studies using intra-cortical recordings in monkeys, succeed to access the (x,y) position of covert spatial attention, in real-time, using classification methods applied to monkey prefrontal multi-unit activity and local field potentials. In contrast, the direct access to attention with non-invasive methods is limited to predicting the attention localisation based on a quadrant classification. Here, we demonstrate the feasibility to track covert spatial attention localization using non-invasive fMRI BOLD signals, with an unprecedented spatial resolution. We further show that the errors produced by the decoder are not randomly distributed but concentrate on the locations neighbouring the cued location and that behavioral errors correlate with weaker decoding performance. Last, we also show that the voxels contributing to the decoder precisely match the visual retinotopic organization of the occipital cortex and that single trial access to attention is limited by the intrinsic dynamics of spatial attention. Taken together, these results open the way to the development of remediation and enhancement neurofeedback protocols targeting the attentional function.


title: A Unified Genomic Mechanism of Cell-Fate Change

abstract: The purpose of our studies is to elucidate the nature of massive control of whole genome expression with a particular emphasis on cell-fate change. Whole genome expression is coordinated by the emergence of a critical point (CP: a peculiar set of bi-phasic genes) through the genome-engine. In response to stimuli, the genome expression self-organizes three critical states, each exhibiting distinct collective behaviors with its center of mass acting as a local attractor, coexisting with whole genome attractor (GA). Genome-engine mechanism accounts for local attractors interaction in phase space. The CP acts as the organizing center of cell-fate change, and its activation makes local perturbation spread over the genome affecting GA. The activation of CP is in turn elicited by  hot-spots, genes with elevated temporal variance, normally in charge to keep genome expression at pace with microenvironment fluctuations. When hot-spots oscillation exceeds a given threshold, the CP synchronizes with the GA driving genome expression state transition. The expression synchronization wave invading the entire genome depends on the power law fusion-bursting dynamics of silencing pericentromere-associated heterochromatin domains and the consequent folding-unfolding status of transcribing euchromatin domains. The proposed mechanism is a unified step toward a time-evolutional transition theory of biological regulation.

category: cell biology


title: Evidence of positive and negative selection associated with DNA methylation

abstract: Signatures of negative selection are pervasive amongst complex traits and diseases. However, it is unclear whether such signatures exist for DNA methylation (DNAm) that has been proposed to have a functional role in disease. We estimate polygenicity, SNP-based heritability and model the joint distribution of effect size and minor allele frequency (MAF) to estimate a selection coefficient (S) for 2000 heritable DNAm sites in 1774 individuals from the Avon Longitudinal Study of Parents and Children. Additionally, we estimate S for meta stable epi alleles and DNAm sites associated with aging and mortality, birthweight and body mass index. Quantification of MAF-dependent genetic architectures estimated from genotype and DNAm reveal evidence of positive (S > 0) and negative selection (S < 0) and confirm previous evidence of negative selection for birthweight. Evidence of both negative and positive selection highlights the role of DNAm as an intermediary in multiple biological pathways with competing function.

category: genetics


title: The PAIR-R24M Dataset for Multi-animal 3D Pose Estimation

abstract: Understanding the biological basis of social and collective behaviors in animals is a key goal of the life sciences, and may yield important insights for engineering intelligent multi-agent systems. A critical step in interrogating the mechanisms underlying social behaviors is a precise readout of the 3D pose of interacting animals. While approaches for multi-animal pose estimation are beginning to emerge, they remain challenging to compare due to the lack of standardized training and benchmark datasets. Here we introduce the PAIR-R24M (Paired Acquisition of Interacting oRganisms - Rat) dataset for multi-animal 3D pose estimation, which contains 24.3 million frames of RGB video and 3D ground-truth motion capture of dyadic interactions in laboratory rats. PAIR-R24M contains data from 18 distinct pairs of rats and 24 different viewpoints. We annotated the data with 11 behavioral labels and 3 interaction categories to facilitate benchmarking in rare but challenging behaviors. To establish a baseline for markerless multi-animal 3D pose estimation, we developed a multi-animal extension of DANNCE, a recently published network for 3D pose estimation in freely behaving laboratory animals. As the first large multi-animal 3D pose estimation dataset, PAIR-R24M will help advance 3D animal tracking approaches and aid in elucidating the neural basis of social behaviors.

category: animal behavior and cognition


title: Flying In-formation: A computational method for the classification of host seeking mosquito flight patterns using path segmentation and unsupervised machine learning

abstract:
The rational design of effective vector control tools requires detailed knowledge of vector behaviour. Yet, behavioural observations, interpretations, evaluations and definitions by even the most experienced researcher are constrained by subjectivity and perceptual limits. Seeking an objective alternative to  expertise, we developed and tested an unsupervised method for the automatic identification of video-tracked mosquito flight behaviour. This method unites path-segmentation and unsupervised machine learning in an innovative workflow and is implemented using a combination of R and python. The workflow (1) records movement trajectories; (2) applies path-segmentation; (3) clusters path segments using unsupervised learning; and (4) interprets results. Analysis of the flight patterns of An. gambiae s.s., responding to human-baited insecticide-treated bednets (ITNs), by the new method identified four distinct behaviour modes: with  swooping and  approaching modes predominant at ITNs; increased  walking behaviours at untreated nets; similar rates of  reacting at both nets; and higher overall activity at treated nets. The methods validity was tested by comparing these findings with those from a similar setting using an expertise-based method. The level of correspondence found between the studies validated the accuracy of the new method. While researcher-defined behaviours are inherently subjective, and prone to corollary shortcomings, the new approachs mathematical method is objective, automatic, repeatable and a validated alternative for analysing complex vector behaviour. This method provides a novel and adaptable analytical tool and is freely available to vector biologists, ethologists and behavioural ecologists.

Author summaryVector control targets the insects and arachnids that transmit 1 in every 6 communicable diseases worldwide. Since the effectiveness of many vector control tools depends on exploiting or changing vector behaviour, a firm understanding of this behaviour is required to maximise the impact of existing tools and design new interventions. However, current methods for identifying such behaviours are based primarily on expert knowledge, which can be inefficient, difficult to scale and limited by perceptual abilities. To overcome this, we present, detail and validate a new method for categorising vector behaviour. This method combines existing path segmentation and unsupervised machine learning algorithms to identify changes in vector movement trajectories and classify behaviours. The accuracy of the new method is demonstrated by replicating existing, expert-derived, findings covering the behaviour of host-seeking mosquitos around insecticide treated bednets, compared to nets without insecticide. As the method found the same changes in mosquito activity as previous research, it is said to be validated. The new method is significant, as it improves the analytical capabilities of biologists working to reduce the burden of vector-borne diseases, such as malaria, through an understanding of behaviour.


title: Use of Raman and Raman optical activity to extract atomistic details of saccharides in aqueous solution

abstract: Sugars are crucial components in biosystems and industrial applications. In aqueous environments, the natural state of short saccharides or charged glycosaminoglycans is floating and wiggling in solution. Therefore, tools to characterize their structure in a native aqueous environment are crucial but not always available. Here, we show that a combination of Raman/ROA and, on occasions, NMR experiments with Molecular Dynamics (MD) and Quantum Mechanics (QM) is a viable method to gain insights into structural features of sugars in solutions. Combining these methods provides information about accessible ring puckering conformers and their proportions. It also provides information about the conformation of the linkage between the sugar monomers, i.e., glycosidic bonds, allowing for identifying significantly accessible conformers and their relative abundance. For mixtures of sugar moieties, this method enables the deconvolution of the Raman/ROA spectra to find the actual amounts of its molecular constituents, serving as an effective analytical technique. For example, it allows calculating anomeric ratios for reducing sugars and analyzing more complex sugar mixtures to elucidate their real content. Altogether, we show that combining Raman/ROA spectroscopies with simulations is a versatile method applicable to saccharides. It allows for accessing many features with precision comparable to other methods routinely used for this task, making it a viable alternative. Furthermore, we prove that the proposed technique can scale up by studying the complicated Raffinose trisaccharide, and therefore, we expect its wide adoption to characterize sugar structural features in solution.

category: biophysics


title: Modeling the age distribution of retinoblastomas

abstract:
In this work, based on real data on the size of the eyeball (in a fetus, in a child, and in young people under 20), we constructed a model function of the growth of the retinal cell tissue.

We used this function to construct a theoretical age distribution of retinoblastomas. We constructed theoretical age distributions for four different models of retinoblastoma: a complex mutational model, a third mutational model, a model with a sequence of key events, and a model of a single oncogenic event with two different latencies (hereditary and non-hereditary retinoblastoma).

We compared the theoretical age distribution of retinoblastomas with the real age distribution based on SEER data (Surveillance Epidemiology and End Results; program of the American National Cancer Institute). In total, we examined 843 cases in women and 908 cases in men.

For all models (separately for women and men), we obtained estimates of the following cancer parameters: the specific frequency of key events (events that trigger cancer); the duration of the latency period of cancer; the number of key events required for cancer to occur.

For the composite age distributions, we calculated the theoretical mean age at diagnosis for hereditary and non-hereditary retinoblastomas.

The best approximation accuracy (for male and female forms of retinoblastoma) is shown by a model with a sequence of key events.

category: cancer biology


title: Reducing voltage-dependent potassium channel Kv3.4 levels ameliorates synapse loss in a mouse model of Alzheimers disease

abstract: Synapse loss is associated with cognitive decline in Alzheimers disease (AD) and owing to their plastic nature, synapses are an ideal target for therapeutic intervention. Oligomeric amyloid beta (A{beta}) around amyloid plaques is known to contribute to synapse loss in mouse models and is associated with synapse loss in human AD brain tissue, but the mechanisms leading from A{beta} to synapse loss remain unclear. Recent data suggest that the fast-activating and -inactivating voltagegated potassium channel subtype 3.4 (Kv3.4) may play a role in A{beta}-mediated neurotoxicity. Here, we tested whether this channel could also be involved in A{beta} synaptotoxicity. Using adeno-associated virus and CRISPR (clustered regularly interspaced short palindromic repeats) technology, we reduced Kv3.4 expression in neurons of the somatosensory cortex of APP/PS1 mice. These mice express human familial AD associated mutations in amyloid precursor protein and presenilin 1 and develop amyloid plaques and plaque-associated synapse loss similar to that observed in AD brain. We observe that reducing Kv3.4 levels ameliorates dendritic spine loss and changes spine morphology compared to control virus. In support of translational relevance, Kv3.4 protein was observed in human AD and control brain and is associated with synapses in human iPSC-derived cortical neurons. Interestingly, we observe a decrease in Kv3.4 expression in iPSC derived cortical neurons when they are challenged with human Alzheimers disease derived brain homogenate. These results suggest that approaches to reduce Kv3.4 expression and/or function could be protective against A{beta}-induced synaptic alterations.


title: An exploratory study of EEG connectivity during the first year of life in preterm and full-term infants

abstract:
AimTo evaluate electroencephalography (EEG) connectivity during the first year of age in healthy full-term infants and preterm infants with prenatal and perinatal risk factors for perinatal brain damage.

MethodsThree groups of infants were studied: healthy full-term infants (n = 71), moderate/late-preterm infants (n = 54), and very preterm infants (n = 56). All preterm infants had perinatal and/or perinatal risk factors for brain damage. EEG was obtained during phase II of natural nonrapid eye movement (NREM) sleep. EEG analysis was performed in 24 2.56-s artifact-free segments. For the calculation of EEG sources, spectral structured sparse Bayesian learning was used. Connectivity was computed by the phase-lag index.

ResultsIn healthy full-term infants, EEG interhemispheric connectivity in the different frequency bands followed similar trends with age to those reported in each frequency band: delta connectivity decreased, theta increased at the end of the year, the alpha band showed different trends based on the region studied, and beta interhemispheric connectivity decreased with age. EEG connectivity in preterm infants showed differences from the results of the term group.

DiscussionImportant structural findings may explain the differences observed in EEG connectivity between the term and preterm groups.

ConclusionThe study of EEG connectivity during the first year of age provides essential information on normal and abnormal brain development.


title: Stability criteria for the consumption and exchange of essential resources

abstract:
Models of pairwise interactions have informed our understanding of when ecological communities will have stable equilibria. However, these models do not explicitly include the effect of the resource environment, which has the potential to refine or modify our understanding of when a group of interacting species will coexist. Recent consumer-resource models incorporating the exchange of resources alongside competition exemplify this: such models can lead to either stable or unstable equilibria, depending on the resource supply. On the other hand, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebigs law, where species require and deplete multiple resources, but each consumers growth rate is only limited by a single one of these multiple resources. Consumed resources that do not lead to growth are leaked back into the environment, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, once again depending on the resource environment. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns we derive analytically apply to a broader class of network structures and resource inflow profiles, including cases in which species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when ecological mechanism is modeled directly.

Author summaryOne of the longstanding challenges in community ecology is to understand how diverse ecosystems assemble and stably persist. Microbial communities are a particularly acute example of this open problem, because thousands of different bacterial species can coexist in the same environment. Interactions between bacteria are of central importance across a wide variety of systems, from the dynamics of the human gut microbiome to the functioning of industrial bioreactors. As a result, a predictive understanding of which microbes can coexist together, and how they do it, will have far-reaching applications. In this paper, we incorporate a more realistic understanding of microbial metabolism into classic mathematical models of consumer-resource dynamics. In our model, bacteria deplete multiple abiotic nutrients but only grow on one of these resources. In addition, they recycle some of the nutrients they consume back into the environment as new resources. We analytically derive criteria which, if satisfied, guarantee that any number of microbes will coexist. We find that there are special types of interaction networks which remain stable even when resources are scarce. Our theory can be used in conjunction with experimentally determined interaction networks to predict which species assemblages are likely to stably coexist in a specified resource environment.

category: ecology


title: High-throughput tuning of ovarian cancer spheroids for on-chip invasion assays

abstract: We developed an invasion assay by using microfabricated culture devices. First, ovarian tumor spheroids were generated with a culture patch device consisting of an agarose membrane formed with a honeycomb microframe - the patch - and gelatin nanofiber backbone. By changing the dimensions of the honeycomb compartments we were able to control the number of cells and size of the spheroids. When the spheroids were placed on a patch coated with a thin membrane of fibrillary type I collagen, spheroid disruption was observed due to substrate induced cell migration. This process is straightforward and should be applicable to other cancer types, as well as assays under microfluidic conditions, thereby holding the potential for use in tumor modeling and anti-cancer drug development.

category: bioengineering


title: corral: Single-cell RNA-seq dimension reduction, batch integration, and visualization with correspondence analysis

abstract: Effective dimension reduction is an essential step in analysis of single cell RNA-seq (scRNAseq) count data, which are high-dimensional, sparse, and noisy. Principal component analysis (PCA) is widely used in analytical pipelines, and since PCA requires continuous data, it is often coupled with log-transformation in scRNAseq applications. However, log-transformation of scRNAseq counts distorts the data, and can obscure meaningful variation. We describe correspondence analysis (CA) for dimension reduction of scRNAseq data, which is a performant alternative to PCA. Designed for use with counts, CA is based on decomposition of a chi-squared residual matrix and does not require log-transformation of scRNAseq counts. We extend beyond standard CA (decomposition of Pearson residuals computed on the contingency table) and propose variations of CA, including an alternative chi-squared statistic, that address overdispersion and high sparsity in scRNAseq data. The performance of five variations of CA and standard CA are benchmarked on 10 datasets and compared to glmPCA. CA variations are fast, scalable, and outperform standard CA and glmPCA, to compute embeddings with more performant or comparable clustering accuracy in 8 out of 9 datasets. Of the variations we considered, we found that CA using the Freeman-Tukey chi-squared residual was most performant overall in scRNAseq data. Our analyses also showed that variance stabilizing transformations applied in conjunction with standard CA (using Pearson residuals) and the use of "power deflation" smoothing both improve performance in downstream clustering tasks, as compared to standard CA alone. CA has advantages including visual illustration of associations between genes and cell populations in a "CA biplot," and easy extension to multi-table analysis enabling integrative dimension reduction. We introduce corralm, a CA-based method for multi-table batch integration of scRNAseq data in shared latent space, and we propose a new approach for assessing batch integration. We implement CA for scRNAseq in the corral R/Bioconductor package (https://www.bioconductor.org/packages/corral) interfaces directly with widely used single cell classes in Bioconductor, allowing for easy integration into scRNAseq pipelines.

category: bioinformatics


title: T-cell microvilli simulations show operation near packing limit and impact on antigen recognition.

abstract:
T-cells are immune cells that continuously scan for foreign-derived antigens on the surfaces of nearly all cells, termed antigen presenting cells (APCs). They do this by dynamically extending numerous protrusions called microvilli (MV) that contain T-cell receptors (TCRs) towards the APC surface in order to scan for antigens. The number, size, and dynamics of these MV, and the complex multi-scale topography that results, play a yet unknown role in antigen recognition. We develop an anatomically informed model of the T-cell/APC interface to elucidate the role of MV dynamics in antigen sensitivity and discrimination. We find that MV surveillance reduces antigen sensitivity compared to a completely flat interface unless MV are stabilized in an antigen-dependent manner and find that MV have only a modest impact on antigen discrimination. The model highlights that MV contacts optimise the competing demands of fast scanning speeds of the APC surface with antigen sensitivity and that T-cells operate their MV near the interface packing limit. Finally, we find that observed MV contact lifetimes can be largely influenced by conditions in the T-cell/APC interface with these lifetimes often being longer than the simulation or experimental observation period. The work highlights the role of MV in antigen recognition.

Significance StatementT-cells search for foreign-derived antigens on the surface of antigen presenting cells (APC) by dynamically extending tubular protrusions called microvilli (MV) which form membrane close-contacts. Although known for decades, their role in antigen recognition remains unclear. Guided by recent experiments, we built an anatomically informed stochastic model of MV scanning and compared with a topologically flat interface. We find that MV scanning modestly impacts antigen discrimination, yet it enables T-cells to balance the competing effects of maintaining sensitivity while conducting rapid APC surveillance. The model can reconcile discrepancies in observed MV lifetimes and demonstrates that observed area coverage fractions correspond to geometric packing limits. Our work suggests that MVs promote positive signaling outcomes despite anatomical constraints to close contact formation.


title: Long-Range Electrostatic Interactions Significantly Modulate the Affinity of Dynein for Microtubules

abstract:
The dynein family of microtubule minus-end directed motor proteins drives diverse functions in eukaryotic cells, including cell division, intracellular transport, and flagellar beating. Motor protein processivity, which characterizes how far a motor walks before detaching from its filament, depends on the interaction between its microtubule-binding domain (MTBD) and the microtubule. Dyneins MTBD switches between high- and low-binding affinity states as it steps. Significant structural and functional data show that specific salt bridges within the MTBD and between the MTBD and the microtubule govern these affinity state shifts. However, recent computational work suggests that non-specific, long-range electrostatic interactions between the MTBD and the microtubule may also play a significant role in the processivity of dynein. To investigate this hypothesis, we mutated negatively charged amino acids remote from the dynein MTBD-microtubule-binding interface to neutral residues and measured the binding affinity using microscale thermophoresis and optical tweezers. We found a significant increase in the binding affinity of the mutated MTBDs for microtubules. Furthermore, we found that charge screening by free ions in solution differentially affected the binding and unbinding rates of MTBDs to microtubules. Together, these results demonstrate a significant role for long-range electrostatic interactions in regulating dynein-microtubule affinity. Moreover, these results provide insight into the principles that potentially underlie the biophysical differences between molecular motors with various processivities and protein-protein interactions more generally.

Statement of SignificanceThe dynein family of motor proteins drives the motility of multiple cellular functions by walking toward the minus end of microtubules. The biophysical mechanisms of dynein rely on its ability to change affinity for the microtubule as it steps. Specific short-range electrostatic interactions acting at the microtubule-binding domain (MTBD)-microtubule interface are known to govern binding affinity. This study shows that non-specific longer-range electrostatic interactions due to charged amino acids remote from the binding interface also contribute significantly to the binding affinity mechanisms. Our results suggest that subtle differences in the electrostatic charge distribution within the MTBD significantly affect the molecular biophysical motility mechanisms in the dynein family of motors.


title: A new early-branching armoured dinosaur from the Lower Jurassic of southwestern China

abstract: The early evolutionary history of the armoured dinosaurs (Thyreophora) is obscured by its patchily distributed fossil record and by conflicting views on the relationships of its Early Jurassic representatives. Here, we describe an early-diverging thyreophoran from the Lower Jurassic Fengjiahe Formation of Yunnan Province, China, on the basis of an associated partial skeleton that includes skull, axial, limb and armour elements. It can be diagnosed as a new taxon based on numerous cranial and postcranial autapomorphies and is further distinguished from all other thyreophorans by a unique combination of character states. Although the robust postcranium is similar to that of more deeply nested ankylosaurs and stegosaurs, phylogenetic analysis recovers it as either the sister taxon of Emausaurus or of the clade Scelidosaurus+Eurypoda. This new taxon, XXXX XXXX, represents the first valid thyreophoran dinosaur to be described from the Early Jurassic of Asia and confirms the rapid geographic spread and diversification of the clade after its first appearance in the Hettangian. Its heavy build and distinctive armour also hint at previously unrealised morphological diversity early in the clades history.

category: paleontology


title: Septin-7 is indispensable for proper skeletal muscle architecture and function

abstract: Today septins are considered as the fourth component of the cytoskeleton with the Septin-7 isoform playing a critical role in the formation of higher order structures. While its importance has already been confirmed in several intracellular processes of different organs, very little is known about its role in skeletal muscle. Here, using Septin-7 conditional knock-down mouse model, the C2C12 cell line, and enzymatically isolated adult muscle fibers the organization and localization of septin filaments is revealed, and an ontogenesis-dependent expression of Septin-7 is demonstrated. KD mice displayed a characteristic hunchback phenotype with skeletal deformities, reduction in vivo and in vitro force generation, and disorganized mitochondrial networks. Furthermore, knock-out of Septin-7 in C2C12 cells resulted in complete loss of cell division while KD cells provided evidence that Septin-7 is essential in proper myotube differentiation. These and the transient increase in Septin-7 expression following muscle injury demonstrate its vital contribution to muscle regeneration and development.

category: physiology


title: The dynamics of HD-ZIP III - ZPR protein interactions play essential roles in embryogenesis, meristem function and organ development

abstract: Maintaining a stem cell population while developing lateral organs is a crucial aspect of plant development. Studies have shown that a family of micro proteins, the LITTLE ZIPPERS (ZPR), are involved in this process by repressing the activity of HD-ZIP III transcription factors. However, the unique role of each ZPR has not been thoroughly characterized. In this work, we use genetics, imaging, and biochemistry to create a detailed picture of ZPR family expression and their specific interactions with HD-ZIP IIIs. CRISPR/Cas9 was implemented to isolate single loss-of-function ZPR alleles as well as higher-order mutant combinations. A single mutation in ZPR1, ZPR3, and ZPR4 affects the development of the cotyledons during embryogenesis. Additionally, double mutant analyses indicates both unique roles for each ZPR protein as well as redundancy. Using ZPR tagged lines we show that while ZPR3 and ZPR4 have a similar pattern of accumulation as the HD-ZIP IIIs, ZPR1 and ZPR2 accumulation is more limited. Immuno-precipitations (IP) with tagged ZPR proteins are mainly enriched with the anticipated HD-ZIP III partners. Although ZPRs interact with all HD-ZIP IIIs, an apparent preference of heterodimer formation with REVOLUTA is observed. Our work highlights that the dynamics of ZPR protein accumulation together with the strength of ZPR-HD-ZIP III interactions provide an added layer of complexity to the regulation of HD-ZIP IIIs during plant development.

category: plant biology


title: CHIQUITA1 maintains temporal transition between proliferation and differentiation in Arabidopsis thaliana

abstract:
Body size varies widely among species, populations, and individuals depending on the environment. Transitioning between proliferation and differentiation is a crucial determinant of final organ size, but how the timing of this transition is established and maintained remains unknown. Using cell proliferation markers and genetic analysis, we show that CHIQUITA1 (CHIQ1) is required to maintain the timing of the transition from proliferation to differentiation in Arabidopsis thaliana. Combining kinematic and cell lineage tracking studies, we found that the number of actively dividing cells in chiquita1-1 plants decreases prematurely compared to wild type plants, suggesting CHIQ1 maintains the proliferative capacity in dividing cells and ensures that cells divide a certain number of times. CHIQ1 belongs to a plant-specific gene family of unknown molecular function and physically and genetically interacts with three close members of its family to control the timing of proliferation exit. Our work reveals the interdependency between cellular and organ-level processes underlying final organ size determination.

SignificanceTiming of the transition between proliferation and differentiation is fundamental for determining the final size of organs and organisms. In agriculture, controlling organ and organism size can influence key agronomic traits such as yield and biomass. Dwarfism prevents lodging and was the trait responsible for the Green Revolution. Today, more sophisticated traits are needed for generating crops that are both resilient and sustainable. Revealing the molecular mechanisms that control the temporal transition between proliferation and differentiation will help unlock the potential of next-generation crops. Here, we report that CHIQUITA 1 in Arabidopsis thaliana is needed to maintain the proper timing of the transition between proliferation and differentiation in leaves and roots.


title: Mesoscopic Quantification of Cortical Architecture in the Living Human Brain

abstract: Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for a comprehensive understanding of brain structure and function. However, in vivo techniques for mesoscopic imaging have been hampered by the sensitivity challenges of acquiring data at very high resolutions and the lack of analysis tools that can retain fine-scale detail while also accurately positioning measurements relative to the complex folded structure of the cerebral cortex. Here, we present an experimental dataset in which we image the anatomical structure of the visual and auditory cortices of five participants at 0.35 x 0.35 x 0.35 mm3 resolution. To analyze this challenging dataset, we design and implement two sets of novel methodology: a method for mitigating imaging artifacts related to blood motion and a suite of software tools for accurate quantification and visualization of the mesoscopic structure of the cortical surface. Applying these methods, we demonstrate the ability to clearly identify structures that are visible only at the mesoscopic scale, including cortical layers and intracortical blood vessels. We freely share our dataset and tools with the research community, thereby enabling investigations of fine-scale neurobiological structures in both the current and future datasets. Overall, our results demonstrate the viability of mesoscopic imaging as a quantitative tool for studying the living human brain.


title: Population-level asymmetry of the cerebral cortex: reproducibility, lifespan changes, heritability, and individual differences

abstract:
Cortical asymmetry is a ubiquitous feature of brain organization that is altered in neurodevelopmental disorders and aging. Achieving consensus on cortical asymmetries in humans is necessary to uncover the genetic-developmental mechanisms that shape them and factors moderating cortical lateralization. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in 7 datasets and chart asymmetry trajectories across life (4-89 years; observations = 3937; 70% longitudinal). We reveal asymmetry interrelationships, heritability, and test associations in UK Biobank (N=~37,500). Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in development and declines in aging. Areal asymmetry correlates in specific regions, whereas thickness asymmetry is globally interrelated across cortex and suggests high directional variability in global thickness lateralization. Areal asymmetry is moderately heritable (max h2SNP ~19%), and phenotypic correlations are reflected by high genetic correlations, whereas heritability of thickness asymmetry is low. Finally, we detected an asymmetry association with cognition and confirm recently-reported handedness links. Results suggest areal asymmetry is developmentally stable and arises in early life, whereas developmental changes in thickness asymmetry may lead to directional variability of global thickness lateralization. Our results bear enough reproducibility to serve as a standard for future brain asymmetry studies.

SignificanceCortical asymmetry is reduced in neurodevelopmental disorders, yet we lack knowledge of how cortical asymmetry development proceeds across life in health. We provide a definitive reference for asymmetry in the cerebral cortex. We find areal asymmetry is stable from childhood to old age, and specific areal asymmetries are formed under common genetic-developmental influence. In contrast, thickness asymmetry shows developmental growth, and is globally interrelated in a pattern suggesting highly left-lateralized individuals tend towards left-lateralization also in right-asymmetric regions (and vice versa). Heritability mapping also supported a prenatal-postnatal developmental dichotomy for areal and thickness asymmetry, and we find reduced asymmetry in the most lateralized brain region associates with reduced cognition. Our results provide novel insights into normal brain organization and development.


title: Interaction between theta-phase and spike-timing dependent plasticity simulates theta induced memory effects

abstract:
Rodent studies suggest that spike timing relative to hippocampal theta activity determines whether potentiation or depression of synapses arise. Such changes also depend on spike timing between pre- and post-synaptic neurons, known as spike-timing-dependent plasticity (STDP). STDP, together with theta-phase-dependent learning, has inspired several computational models of learning and memory. However, evidence to elucidate how these mechanisms directly link to human episodic memory is lacking. In a computational model, we modulate long-term potentiation (LTP) and long-term depression (LTD) of STDP, by opposing phases of a simulated theta rhythm. We fit parameters to a hippocampal cell culture study in which LTP and LTD were observed to occur in opposing phases of a theta rhythm. Further, we modulated two inputs by cosine waves with synchronous and asynchronous phase offsets and replicate key findings in human episodic memory. Learning advantage was found for the synchronous condition, as compared to the asynchronous conditions, and was specific to theta modulated inputs. Importantly, simulations with and without each mechanism suggest that both STDP and theta-phase-dependent plasticity are necessary to replicate the findings. Together, the results indicate a role for circuit-level mechanisms, which bridges the gap between slice preparation studies and human memory.

Author SummaryLong-lasting changes in synaptic connectivity between neurons have been suggested to support learning and memory processes at the cellular level in the brain. Such synaptic modifications depend on synchronous activation of neurons, which leads to generate brain oscillations. Human memory studies focus on the relationships between brain oscillations and memory processes. Direct evidence on how the cellular mechanism links to human memory behaviour is lacking. To investigate the direct link between synaptic plasticity mechanisms and human memory formation, we built a computational neural network that implements two synaptic plasticity mechanisms, which are well-established in the rodents hippocampus. One mechanism shows that strengthening or weakening in synaptic connectivity depends on the phases of ongoing brain oscillation at theta frequency (4 - 8 Hz), which is a dominant signal in the hippocampus. The other mechanism suggests that synaptic modification depends on the precise timing of action potentials between two neurons. Our model successfully reproduces results from rodents, as well as several human episodic memory studies which demonstrated that human associative memory performance depends on phase synchronisation in theta frequency. These findings suggest a link between specific learning mechanisms at cellular level and human memory behaviour.


title: Activation of LH GABAergic inputs counteracts fasting-induced changes in tVTA/RMTG neurons.

abstract:
Dopamine neurons in the ventral tegmental area (VTA) are strongly innervated by GABAergic neurons in the  tail of the VTA (tVTA), also known as the rostralmedial tegmental nucleus (RMTg). Disinhibition of dopamine neurons through firing of the GABAergic neurons projecting from the lateral hypothalamus (LH) leads to reward seeking and consumption through dopamine release in the nucleus accumbens. VTA dopamine neurons respond to changes in motivational state, yet less is known of whether tVTA/RMTg GABAergic neurons or the LH GABAergic neurons that project to them are also affected by changes in motivational state, such as fasting. An acute 16 h overnight fast decreased the excitability of tVTA/RMTg GABAergic neurons of male and female mice. In addition, fasting decreased synaptic strength at LH GABA to tVTA/RMTg GABAergic synapses, indicated by reduced amplitude of optically evoked currents, decreased readily releasable pool (RRP) size and replenishment. Optical stimulation of LH GABA terminals suppressed evoked action potentials of tVTA/RMTg GABAergic neurons in unfasted mice, but this effect decreased following fasting. Furthermore, during fasting, LH GABA inputs to tVTA/RMTg neurons maintained functional connectivity during depolarization, as depolarization block was reduced following fasting. Taken together, inhibitory synaptic transmission from LH GABA inputs onto tVTA/RMTg GABAergic neurons decreases following fasting, however ability to functionally inhibit tVTA/RMTg GABAergic neurons is preserved, allowing for possible disinhibition of dopamine neurons and subsequent foraging.

Key PointsO_LIWhile dopamine neuronal activity changes with motivational state, it is unknown if fasting influences tVTA/RMTg GABAergic neurons, a major inhibitory input to VTA dopamine neurons.
C_LIO_LIIn unfasted mice, there were sex differences in inhibitory synaptic transmission onto tVTA/RMTg GABAergic neurons.
C_LIO_LIActivation of LH GABAergic neurons decreases firing of tVTA/RMTg GABAergic neurons through a monosynaptic input.
C_LIO_LIAn acute fast decreased the excitability of tVTA/RMTg GABAergic neurons.
C_LIO_LIAn acute fast decreases inhibitory synaptic transmission of the LH GABA input to tVTA/RMTg GABAergic neurons in both male and female mice.
C_LI


title: Milk Exosomes Cross the Blood-Brain Barrier in Murine Cerebral Cortex Endothelial Cells and Promote Dendritic Complexity in the Hippocampus and Brain Function in C57BL/6J Mice

abstract:
BackgroundHuman milk contains large amounts of exosomes (MEs) and their regulatory microRNA cargos, whereas infant formulas contain only trace amounts of MEs and microRNAs. Breastfeeding has been implicated in optimal brain development but experimental evidence linking ME intake with brain development is limited.

ObjectivesWe assessed the transport of MEs across the blood-brain barrier (BBB) and ME accumulation in distinct regions of the brain in brain endothelial cells and suckling mice. We further assessed BME-dependent gene expression profiles and effects on the dendritic complexity of hippocampal granule cells and phenotypes of BME depletion in neonate, juvenile and adult mice.

MethodsThe transfer of MEs across the BBB was assessed by using bovine MEs labeled with FM4-64 or loaded with IRDye-labeled miR-34a in murine brain endothelial bEnd.3 cell monolayers and dual chamber systems, and in wild-type newborn pups fostered to exosome and cargo tracking (ECT) dams that express MEs endogenously labeled with a CD63-eGFP fusion protein for subsequent analysis by serial two-photon tomography and staining with anti-eGFP antibodies. Effects of MEs on gene expression and dendritic architecture of granule cells was analyzed in hippocampi from juvenile mice fed exosome and RNA-depleted (ERD) and exosome and RNA-sufficient (ERS) diets by using RNA-sequencing analysis and Golgi-Cox staining followed by integrated neuronal tracing and morphological analysis of neuronal dendrites, respectively. Spatial learning and severity of kainic acid-induced seizures were assessed in mice fed ERD and ERS diets.

ResultsbEnd.3 cells internalized MEs by using a saturable transport mechanism and secreted miR-34a across the basal membrane. MEs penetrated the entire brain in fostering experiments; major regions of accumulation included the hippocampus, cortex and cerebellum. Two hundred ninety-five genes were differentially expressed in hippocampi from male mice fed ERD and ERS diets; high-confidence gene networks included pathways implicated in axon guidance and calcium signaling. Only one gene was differentially expressed in females fed the experimental diets. Juvenile pups fed the ERD diet had reduced dendritic complexity of dentate granule cells in the hippocampus, scored nine-fold lower in the Barnes maze test of spatial learning and memory (P < 0.01), and the severity of seizures was 5-fold higher following kainic acid administration in adult mice fed the ERD diet compared to mice fed the ERS diet (P < 0.01).

ConclusionsMEs cross the BBB and contribute toward optimal neuronal development, spatial learning and memory, and resistance to kainic acid-induced seizures in mice.


title: A scale-invariant perturbative approach to study information communication in dynamic brain networks

abstract: How communication among neuronal ensembles shapes functional brain dynamics at the large scale is a question of fundamental importance to Neuroscience. To date, researchers have primarily relied on two alternative ways to address this issue 1) in-silico neurodynamical modelling of functional brain dynamics by choosing biophysically inspired non-linear systems, interacting via a connection topology driven by empirical data; and 2) identifying topological measures to quantify network structure and studying them in tandem with functional metrics of interest, e.g. co-variation of time series in brain regions from fast (EEG/ MEG) and slow (fMRI) timescales. While the modelling approaches are limited in scope to only scales of the nervous system for which dynamical models are well defined, the latter approach does not take into account how the network architecture and intrinsic regional node dynamics contribute together to inter-regional communication in the brain. Thus, developing a generalized scale-invariant measure of interaction between network topology and constituent regional dynamics can potentially resolve how transmission of perturbations in brain networks alter function e.g. by neuropathologies, or the intervention strategies designed to mitigate them. In this work, we introduce a recently developed theoretical perturbative framework in network science into a neuroscientific framework, to conceptualize the interaction of regional dynamics and network architecture in a quantifiable manner. This framework further provides insights into the information communication contributions of putative regions and sub-networks in the brain, irrespective of the observational scale of the phenomenon (firing rates to BOLD fMRI time series). The proposed approach can directly quantify network-dynamical interactions without reliance on a specific class of models or response characteristics: linear/nonlinear. By simply gauging the asymmetries in responses to perturbations, we obtain insights into the significance of regions in communication and their influence over the rest of the network. Moreover, coupling perturbations with functional lesions can also answer which regions contribute the most to information spread: a quantity termed Flow. The simplicity of the proposed technique allows translation to an experimental setting where the response asymmetries and flow can inversely act as a window into the dynamics of regions. For proof-of-concept, we apply the perturbative approach on in-silico data generated for human resting state network dynamics, using different established dynamical models that mimic empirical observations. We also apply the perturbation approach at the level of large scale Resting State Networks (RSNs) to gauge the range of network-dynamical interactions in mediating information flow across brain regions.


title: Systematic Evaluation of Machine Learning Algorithms for Neuroanatomically-Based Age Prediction in Youth

abstract: Application of machine learning algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain-age). The choice of the machine learning approach in estimating brain-age in children and adolescents is important because age-related brain changes in these age-groups are dynamic. However, the comparative performance of the multiple machine learning algorithms available has not been systematically appraised. To address this gap, the present study evaluated the accuracy (Mean Absolute Error; MAE) and computational efficiency of 21 machine learning algorithms using sMRI data from 2,105 typically developing individuals aged 5 to 22 years from five cohorts. The trained models were then tested in two independent holdout datasets, comprising 4,078 pre-adolescents aged 9-10 years and another sample of 594 individuals aged 5-21 years. The algorithms encompassed parametric and nonparametric, Bayesian, linear and nonlinear, tree-based, and kernel-based models. Sensitivity analyses were performed for parcellation scheme, number of neuroimaging input features, number of cross-validation folds, number of extreme outliers, and sample size. The best performing algorithms were Extreme Gradient Boosting (MAE of 1.49), Random Forest Regression (MAE of 1.58) and Support Vector Regression with Radial Basis Function Kernel (MAE of 1.64) which had acceptable and comparable computational efficiency. Findings of the present study could be used as a guide for optimizing methodology when quantifying age-related changes in youth.


title: Directionality of PYD filament growth determined by the transition of NLRP3 nucleation seeds to ASC elongation

abstract: Inflammasomes sense intrinsic and extrinsic danger signals to trigger inflammatory responses and pyroptotic cell death. Homotypic pyrin domain (PYD) interactions of inflammasome forming Nod-like receptors with the adaptor protein ASC mediate oligomerization into helical filamentous assemblies. These supramolecular organizing centers recruit and activate caspase-1, which results in IL-1{beta} family cytokine maturation and pyroptotic cell death. The molecular details of the critical step in signal transduction of inflammasome signaling, however, remain ill-defined. Here, we describe the cryo-EM structure of the human NLRP3 PYD filament at 3.6 [A] resolution. We identify a unique pattern of highly polar interface residues that form the homomeric interactions leading to characteristic filament ends that we designate as A- and B-end, respectively. Coupling a titration polymerization assay to cryo-EM, we demonstrate that the ASC adaptor protein elongation on NLRP3 PYD filament seeds is unidirectional, associating exclusively to the B-end of the NLRP3 filament. Notably, NLRP3 and ASC PYD filaments exhibit the same symmetry in rotation and axial rise per subunit, allowing for a continuous transition between NLRP3 as the nucleation seed and ASC as the elongator. Integrating the directionality of filament growth, we present a molecular model of the ASC speck consisting of active NLRP3-NEK7, ASC, and Caspase-1 proteins.

category: immunology


title: A glycosylphosphatidylinositol-anchored α-amylase encoded by amyD contributes to a decrease in the molecular mass of cell wall α-1,3-glucan in Aspergillus nidulans

abstract: -1,3-Glucan is one of the main polysaccharides in the cell wall of Aspergillus nidulans. We previously revealed that it plays a role in hyphal aggregation in liquid culture, and that its molecular mass (MM) in an agsA-overexpressing (agsAOE) strain was larger than that in an agsB-overexpressing (agsBOE) strain. The mechanism that regulates the MM of -1,3-glucan is poorly understood. Although the gene amyD, which encodes glycosyl-phosphatidylinositol (GPI)-anchored -amylase (AmyD), is involved in the biosynthesis of -1,3-glucan in A. nidulans, how it regulates this biosynthesis remains unclear. Here we constructed strains with disrupted amyD ({Delta}amyD) or overexpressed amyD (amyDOE) in the genetic background of the ABPU1 (wild-type), agsAOE, or agsBOE strain, and characterized the chemical structure of -1,3-glucans in the cell wall of each strain, focusing on their MM. The MM of -1,3-glucan from the agsBOE amyDOE strain was smaller than that in the parental agsBOE strain. In addition, the MM of -1,3-glucan from the agsAOE {Delta}amyD strain was greater than that in the agsAOE strain. These results suggest that AmyD is involved in decreasing the MM of -1,3-glucan. We also found that the C-terminal GPI-anchoring region is important for these functions.

category: microbiology


title: A Novel Approach Towards Less Invasive Multi 'Omics Gut Analyses: A Pilot Study

abstract:
Newer  omics approaches such as metatranscriptomics and metabolomics allow functional assessments of the interaction(s) between the gut microbiome and the human host. In order to generate meaningful data with these approaches, though, the method of sample collection is critical. Prior studies have relied upon expensive and invasive means towards sample acquisition such as intestinal biopsy, while other studies have relied upon easier methods of collection such as fecal samples that do not necessarily represent those microbes in contact with the host. In this pilot study, we attempt to characterize a novel, minimally invasive method towards sampling the human microbiome using mucosal cytology brush sampling compared to intestinal gut biopsy on 5 healthy participants undergoing routine screening colonoscopy. We compared metatranscriptomic analyses between the two collection methods, identifying increased taxonomic evenness and beta diversity in the cytology brush samples, and similar community transcriptional profiles between the two methods. Metabolomics assessment demonstrated striking differences between the two methods, implying a difference in bacterial-derived versus human absorbed metabolites. Put together, this study supports the use of a less invasive method of microbiome sampling with cytology brushes, but caution must be exercised when performing metabolomics assessment as this represents differential metabolite production but not absorption by the host.

ImportanceIn order to generate meaningful metabolomic and microbiome data, the method of sample collection is critical. This study utilizes and compares two methods to intestinal tissue collection for evaluation of metabolites and microbiome, finding that using a brush to sample the microbiome is superior to tissue biopsy. However, for metabolomics assessment, biopsy may still be required.


title: Particle-associated and free-living microbial assemblages are distinct in a permanently redox-stratified freshwater lake

abstract: Microbial assemblages associated with biogenic particles are phylogenetically distinct from free-living counterparts, yet biogeochemically coupled. Compositions may vary with organic carbon and inorganic substrate availability and with redox conditions, which determine reductant and oxidant availability. To explore microbial assemblage compositional responses to steep oxygen and redox gradients and seasonal variability in particle and substrate availability, we analyzed taxonomic compositions of particle-associated (PA) and free-living (FL) bacteria and archaea in permanently redox-stratified Fayetteville Green Lake. PA and FL assemblages (> 2.7 {micro}m and 0.2 - 2.7 {micro}m) were surveyed at the peak (July) and end (October) of concurrent cyanobacteria, purple and green sulfur bacteria blooms that result in substantial vertical fluxes of particulate organic carbon. Assemblage compositions varied significantly among redox conditions and size fractions (PA or FL). Temporal differences were only apparent among samples from the mixolimnion and oxycline, coinciding with seasonal hydrographic changes. PA assemblages of the mixolimnion and oxycline shifted from aerobic heterotrophs in July to fermenters, iron-reducers, and denitrifiers in October, likely reflecting seasonal variability in photoautotroph biomass and inorganic nitrogen. Within a light-scattering layer spanning the lower oxycline and upper monimolimnion, photoautotrophs were more abundant in July than in October, when Desulfocapsa, a sulfate-reducing and sulfur-disproportionating bacterium, and Chlorophyte chloroplasts were abundant in PA assemblages. In this layer, microbial activity and cell concentrations were also highest. Below, the most abundant resident taxa were sulfate-reducing bacteria and anaerobic respirers. Results suggest PA and FL assemblage niche partitioning interconnects multiple elemental cycles that involve particulate and dissolved phases.


title: Prediction of molecular markers of bovine mastitis by meta-analysis of differentially expressed genes using combined p-value and robust rank aggregation

abstract: Bovine mastitis causes significant economic loss to the dairy industry by affecting milk quality and quantity. E.coli and S.aureus are the two common mastitis-causing bacteria among the consortia of mastitis pathogens, wherein E.coli is an opportunistic environmental pathogen, and S.aureus is a contagious pathogen. This study was designed to predict molecular markers of bovine mastitis by meta-analysis of differentially expressed genes (DEG) in E.coli or S.aureus infected mammary epithelial cells (MECs) using p-value combination and robust rank aggregation (RRA) methods. High throughput transcriptome of bovine (MECs, infected with E.coli or S.aureus, were analyzed, and correlation of z-scores were computed for the expression datasets to identify the lineage profile and functional ontology of DEGs. Key pathways enriched in infected MECs were deciphered by Gene Set Enrichment Analysis (GSEA), following which combined p-value and RRA were used to perform DEG meta-analysis to limit type I error in the analysis. The miRNA-Gene networks were then built to uncover potential molecular markers of mastitis. Lineage profiling of MECs showed that the gene expression levels were associated with mammary tissue lineage. The up-regulated genes were enriched in immune-related pathways whereas down-regulated genes influenced the cellular processes. GSEA analysis of DEGs deciphered the involvement of Toll-like receptor (TLR), and NF- Kappa B signalling pathway during infection. Comparison after meta-analysis yielded with genes ZC3H12A, RND1 and MAP3K8 having significant expression levels in both E.coli and S.aureus dataset and on evaluating miRNA-Gene network 7 pairs were common to both sets identifying them as potential molecular markers.

category: molecular biology


title: Expression of mini-G proteins specifically halt cognate GPCR trafficking and intracellular signalling

abstract: Mini-G proteins are engineered thermostable variants of G subunits designed to specifically stabilise G protein-coupled receptors (GPCRs) in their active conformation for structural analyses. Due to their smaller size and ease of use, they have become popular tools in recent years to assess specific GPCR behaviours in cells, both as reporters of receptor coupling to each G protein subtype and for in-cell assays designed to quantify compartmentalised receptor signalling from a range of subcellular locations. Here, we describe a previously unappreciated consequence of the co-expression of mini-G proteins with their cognate GPCRs, namely a profound disruption in GPCR trafficking and intracellular signalling caused by the co-expression of the specific mini-G subtype coupled to the affected receptor. We studied the Gs-coupled pancreatic beta cell class B GPCR glucagon-like peptide-1 receptor (GLP-1R) as a model to describe in detail the molecular consequences derived from this effect, including a complete halt in {beta}-arrestin-2 recruitment and receptor internalisation, despite near-normal levels of receptor GRK2 recruitment and lipid nanodomain segregation, as well as the disruption of endosomal GLP-1R signalling by mini-Gs co-expression. We also extend our analysis to a range of other prototypical GPCRs covering the spectrum of G subtype coupling preferences, to unveil a widely conserved phenomenon of GPCR internalisation blockage by specific mini-G proteins coupled to a particular receptor. Our results have important implications for the design of methods to assess intracellular GPCR signalling. We also present an alternative adapted bystander intracellular signalling assay for the GLP-1R in which we substitute the mini-Gs by a nanobody, Nb37, with specificity for active Gs:GPCR complexes and no deleterious effect on the capacity for GLP-1R internalisation.


title: A high-density lineage tree reveals dynamics of expression differences accumulation in nondifferentiating clonal expansion

abstract: Differences in gene expression levels among genetically identical cells naturally accumulate during cellular proliferation, forming the basis of expression noise or differentiation. Nevertheless, how transcriptome-wide noise accumulation is constrained to maintain homeostasis during continuous cell divisions has remained largely unresolved. We developed a novel method named "single-cell transcriptome and dense tree" (STADT) to simultaneously determines the transcriptomes and lineage tree of >50% single cells in a single-cell-seeded colony. This lineage tree revealed gradual accumulation of transcriptome differences that became saturated upon four cell divisions, reduced expression noise for sub-tree/sub-colonies closer to inferred expression boundaries, and transcriptionally modulated co-fluctuations among genes. These results collectively showed, for the first time, constrained dynamics of expression noise in the context of cell division.


title: Measurements and simulations of microtubule growth imply strong longitudinal interactions and reveal a role for GDP on the elongating end

abstract: Microtubule polymerization dynamics result from the biochemical interactions of {beta}-tubulin with the polymer end, but a quantitative understanding has been challenging to establish. We used interference reflection microscopy to make improved measurements of microtubule growth rates and growth fluctuations in the presence and absence of GTP hydrolysis. In the absence of GTP hydrolysis, microtubules grew steadily with very low fluctuations. These data were best described by a computational model implementing slow assembly kinetics, such that the rate of microtubule elongation is primarily limited by the rate of {beta}-tubulin associations. With GTPase present, microtubules displayed substantially larger growth fluctuations than expected based on the no GTPase measurements. Our modeling showed that these larger fluctuations occurred because exposure of GDP-tubulin on the microtubule end transiently  poisoned growth, yielding a wider range of growth rate compared to GTP only conditions. Our experiments and modeling point to slow association kinetics (strong longitudinal interactions), such that drugs and regulatory proteins that alter microtubule dynamics could do so by modulating either the association or dissociation rate of tubulin from the microtubule tip. By causing slower growth, exposure of GDP tubulin at the growing microtubule end may be an important early event determining catastrophe.


title: Age-specific survival in an English Twite population.

abstract: Like many bird species associated with agricultural habitats in the UK, the Twite Linaria flavirostris has undergone severe declines over recent decades due to habitat degradation, with populations in England, Wales and Ireland now restricted to a few small pockets. However, the demographic drivers of these declines are still largely unresolved. We estimated the survival of Twite from a small population at the southernmost edge of the English range in Derbyshire using capture-mark-recapture data from 2016-2019. Annual apparent survival for juveniles (0.14-0.34) was lower than for adults (0.29-0.56) and less than that of other Cardueline finches. Our results suggest that low juvenile survival may be one demographic driver underpinning the recent decline of the Derbyshire Twite population, although we also cannot rule out the possibility that differences in emigration of juveniles and adults from the population also contribute to the observed age-specific apparent survival rates.


title: Gene conversion explains elevated diversity in the immunity modulating APL1 gene of the malaria vector Anopheles funestus

abstract: The leucine rich repeat gene APL1 is a key component of immunity to Plasmodium and other microbial pathogens in Anopheles mosquitoes. In the malaria vector Anopheles funestus the APL1 gene has four paralogues which occur along the same chromosome arm. We show that APL1 has exceptional levels of non-synonymous polymorphism across the range of An. funestus with an average {pi}n of 0.027 versus a genome-wide average of 0.002, and {pi}n (and {pi}s) is consistently high in populations across Africa. The pattern of APL1 diversity was consistent between independent pooled-template and target-enrichment datasets, however no link between APL1 diversity and insecticide-resistance was observed with the phenotyped target-enrichment dataset. Two further innate immunity genes of the gambicin anti-microbial peptide family had {pi}n/{pi}s ratios greater than one, possibly driven by either positive or balancing selection. Cecropin antimicrobial peptides were expressed much more highly than other anti-microbial peptide genes, an observation discordant with current models of anti-microbial peptide activity. The observed APL1 diversity likely results from gene conversion between paralogs, as evidenced by shared polymorphisms, overlapping read mappings, and recombination events among paralogues. Gene conversion at APL1 versus alternative explanations is concordant with similarly elevated diversity in APL1 and TEP1 loci in An. gambiae. In contrast, the more closely related An. stephensi which also encodes a single-copy of APL1 does not show this elevated diversity. We hypothesise that a more open chromatin formation at the APL1 locus due to higher gene expression than its paralogues enhances gene conversion, and therefore increased polymorphism, at APL1.

category: evolutionary biology


title: Nutrigonometry I: using right-angle triangles to quantify nutritional trade-offs in multidimensional performance landscapes

abstract: Animals regulate their diet in order to maximise the expression of fitness traits that often have different nutritional needs. These nutritional trade-offs have been experimentally uncovered using the Geometric framework for nutrition (GF). However, current analytical methods to measure such responses rely on either visual inspection or complex models applied to multidimensional performance landscapes, making these approaches subjective, or conceptually difficult, computationally expensive, and in some cases inaccurate. This limits our ability to understand how animal nutrition evolved to support life-histories within and between species. Here, we introduce a simple trigonometric model to measure nutritional trade-offs in multidimensional landscapes ( Nutrigonometry). Nutrigonometry is both conceptually and computationally easier than current approaches, as it harnesses the trigonometric relationships of right-angle triangles instead of vector calculations. Using landmark GF datasets, we first show how polynomial (Bayesian) regressions can be used for precise and accurate predictions of peaks and valleys in performance landscapes, irrespective of the underlying structure of the data (i.e., individual food intakes vs fixed diet ratios). Using trigonometric relationships, we then identified the known nutritional trade-off between lifespan and reproductive rate both in terms of nutrient balance and concentration. Nutrigonometry enables a fast, reliable and reproducible quantification of nutritional trade-offs in multidimensional performance landscapes, thereby broadening the potential for future developments in comparative research on the evolution of animal nutrition.


title: Recombination of standing variation in a multi-hybrid swarm drove adaptive radiation in a fungal pathogen and gave rise to two pandemic plant diseases

abstract:
Adaptive radiations fuel speciation and are characterized by rapid genetic diversification and expansion into new ecological niches. Historically, these processes were believed to be driven by selection on novel mutations but genomic analyses now indicate that standing variation and gene flow often have prominent roles. How "old" variation is combined, however, and its resulting genetic architecture within newly-adapted populations is not well understood. We reconstructed a recent radiation in the fungus, Pyricularia oryzae, that spawned a population pathogenic to eleven grass genera, and caused two new plant diseases: wheat blast - already a serious threat to global agriculture - and gray leaf spot of ryegrasses. We show that the new population evolved in a multi-hybrid swarm using only the standing variation that was present in seven individuals from five distinct, host-specialized lineages. Sexual and parasexual recombination within the swarm reassorted key host-specificity factors and generated more diversity in possibly just a few weeks than existing lineages had accumulated over hundreds to thousands of years. We suggest that the process was initiated by sexual opportunity arising when a fertile fungal strain was imported into Brazil on Urochloa introduced as forage for beef production; and we further contend that the host range expansion was largely fortuitous, with host selection playing little, if any, role in driving the process. Finally, we believe that our findings point to an overlooked role for happenstance in creating situations that allow organisms to skirt rules that would normally hold evolution in check.

Commercial Endorsement DisclaimerMention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.

Equal Opportunity/Non-Discrimination StatementUSDA is an equal opportunity provider and employer.


title: Spatial charting of single cell transcriptomes in tissues

abstract: Single cell RNA sequencing (scRNA-seq) methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics (ST) assays can profile spatial regions in tissue sections, but do not have single cell genomic resolution. Here, we developed a computational approach called CellTrek that combines these two datasets to achieve single cell spatial mapping. We benchmarked CellTrek using a simulation study and two in situ datasets. We then applied CellTrek to reconstruct cellular spatial structures in existing datasets from normal mouse brain and kidney tissues. We also performed scRNA-seq and ST experiments on two ductal carcinoma in situ (DCIS) tissues and applied CellTrek to identify tumor subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data shows that CellTrek can accurately map single cells in diverse tissue types to resolve their spatial organization.

category: genomics


title: NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

abstract: Nucleosome positioning is involved in many gene regulatory processes happening in the cell and it may change as cells differentiate or respond to the changing microenvironment in a healthy or diseased organism. One important implication of nucleosome positioning in clinical epigenetics is its use in the "nucleosomics" analysis of cell-free DNA (cfDNA) for the purpose of patient diagnostics in liquid biopsies. The rationale for this is that the apoptotic nucleases that digest chromatin of the dying cells mostly cut DNA between nucleosomes. Thus, the short pieces of DNA in body fluids reflect the positions of nucleosomes in the cells of origin. Here we report a systematic nucleosomics database - NucPosDB, curating published nucleosome positioning datasets in vivo as well as datasets of sequenced cell-free DNA (cfDNA) that reflect nucleosome positioning in situ in the cells of origin. Users can select subsets of the database by a number of criteria and then obtain raw or processed data. NucPosDB also reports the originally determined regions with stable nucleosome occupancy across several individuals with a given condition. An additional section provides a catalogue of computational tools for the analysis of nucleosome positioning or cfDNA experiments and theoretical algorithms for the prediction of nucleosome positioning from DNA sequence. We provide an overview of the field, describe the structure of the database in this context and demonstrate data variability using examples of different medical conditions. NucPosDB is useful both for analysis of fundamental gene regulation processes and training computational models for patient diagnostics based on cfDNA. The database currently curates [~]400 publications on nucleosome positioning in cell lines and in situ as well as cfDNA from >10,000 patients and healthy volunteers. For open-access cfDNA datasets as well as key MNase-seq datasets in human cells, NucPosDB allows downloading processed mapped data in addition to the stable-nucleosome regions. NucPosDB is available at https://generegulation.org/nucposdb/.


title: Analysis of transcriptional changes associated with pubertal development

abstract:
Puberty is an important developmental period marked by hormonal, metabolic and immune changes, which have been implicated in predisposition to immune diseases later in life. Yet, little is known about the gene expression changes in immune cells that occur during pubertal development. In a longitudinal cohort of 251 children we assessed pubertal development and leukocyte gene expression. We identified largely overlapping gene expression changes in boys and girls for thousands of genes over a short time period. For 108 genes we detected gene expression changes associated with pubertal development. Substantial transcriptional changes were detected between pre- and post-menarcheal girls, which suggested a shift from predominantly innate to adaptive immunity as girls sexually matured.

We identified genetic effects on gene expression that dynamically change during pubertal development for IGKV1-27 and PGAP1 in males, DSC1 and TRBV30 in females. We discovered that menarche is associated with a change in sign of a genetic effect on the expression of the asthma-associated gene FLOT2. Using a Transcriptome-Wide Association Study approach, we discovered that in girls, gene expression changes during puberty are associated with age at menarche. For example, expression of the endometrial cancer risk gene EEFSEC increases as girls become older, suggesting a link between age at menarche, transcriptional changes happening during puberty and poor health outcomes. These findings shed light on immune gene expression processes accompanying puberty and can advance the understanding of the molecular mechanisms through which pubertal development relates to immune diseases later in life.


title: Social preference in rats not impacted by posterior parietal activity despite overall changes in familiarity-based social behavior

abstract: Recent literature points to a potential link between the evolution of complex social behavior and the posterior parietal cortex (PPC) in primates including humans (Parkinson & Wheatley, 2013). Thus far, this theory has been overlooked in other highly social animals that may have also evolved due to social selective pressures. In rodents, there is limited knowledge on the involvement of the PPC on sociality, and most studies of such behavior are limited to understanding social preference. We investigated the role of the PPC through two experiments using the 3-Chamber Sociability and Social Novelty test in rats (Crawley, 2004). In Experiment 1, we used a standard 3-Chamber paradigm, which included two novel demonstrators. In Experiment 2, this paradigm was altered to increase the difference in familiarity between demonstrators such that one demonstrator was highly familiar to the subject and the other was entirely novel. Rats with pre-testing permanent neurotoxic lesions were compared to sham surgery control rats, and the same rats were used for both experiments. Experiments 1 and 2 showed that both groups of rats preferred general social interaction, suggesting no deficit in sociability following PPC damage, regardless of demonstrator identity. Further, experimental and control rats showed similar levels of novelty preference following PPC damage, with novelty preferences increasing in Experiment 2. We argue that heightened novelty preference in Experiment 2 may reflect the increased difference in familiarity between demonstrators. Within the confines of the 3-Chamber task, our results suggest that PPC function was not required for general sociability or social novelty recognition. Because the PPC is implicated in abstract cognition, we argue that existing social tests in rodents may not adequately measure the complex cognitive capacities thought to be supported by the PPC. Future studies should investigate the role of the PPC in social cognition by employing behavioral tasks that require higher cognitive demand rather than testing inherent preference for social partners. Outside of our investigation of the PPC, these results show that social novelty preference can be manipulated through changes in familiarity of demonstrators, and that rats can discriminate others social identities.


title: Brain monoaminergic activity during predator inspection in the Trinidadian guppy (Poecilia reticulata)

abstract:
To understand the processes underpinning social decision-making, we need to determine how internal states respond to information gathered from the social environment. Brain monoamine neurotransmitters are key in the appraisal of the social environment and can reflect the internal state underlying behavioural responses to social stimuli. Here we determined the effects of conspecific partner cooperativeness during predator inspection on brain monoamine metabolic activity in Trinidadian guppies (Poecilia reticulata). We quantified the concentration of dopamine, serotonin and their metabolites across brain sections sampled immediately after ostensibly experiencing cooperation or defection from social partners whilst inspecting a predator model. Our results indicate dopaminergic and serotonergic activity differs with the cooperativeness experienced; these different neurotransmission profiles are likely to affect the expression and regulation of downstream behaviours that ultimately contribute to the patterning of cooperative interactions among individuals in the population.

List of abbreviations used


title: Hyperspectral Counting of Multiplexed Nanoparticle Emitters in Single Cells and Organelles

abstract: Nanomaterials are the subject of a range of biomedical, commercial, and environmental investigations involving measurements in living cells and tissues. Accurate quantification of nanomaterials, at the tissue, cell, and organelle levels, is often difficult, however, in part due to their inhomogeneity. Here, we propose a method that uses the diverse optical properties of a nanomaterial preparation in order to improve quantification at the single-cell and organelle level. We developed  hyperspectral counting, which employs diffraction-limited imaging via hyperspectral microscopy of a diverse set of nanomaterial emitters, to estimate nanomaterial counts in live cells and sub-cellular structures. A mathematical model was developed, and Monte Carlo simulations were employed, to improve the accuracy of these estimates, enabling quantification with single-cell and single-endosome resolution. We applied this nanometrology technique to identify an upper-limit of the rate of uptake into cells - approximately 3,000 particles endocytosed within 30 minutes. In contrast, conventional ROI counting results in a 230% undercount. The method identified significant heterogeneity and a broad non-Gaussian distribution of carbon nanotube uptake within cells. For example, while a particular cell contained an average of 1 nanotube per endosome, the heterogenous distribution resulted in over 7 nanotubes localizing within some endosomes, substantially changing the accounting of subcellular nanoparticle concentration distributions. This work presents a method to quantify cellular and subcellular concentrations of a heterogeneous carbon nanotube reference material, with implications for nanotoxicology, drug/gene delivery, and nanosensor fields.


title: Annotation of Spatially Resolved Single-cell Data with STELLAR

abstract: Spatial protein and RNA imaging technologies have been gaining rapid attention but current computational methods for annotating cells are based on techniques established for dissociated single-cell technologies and thus do not take spatial organization into account. Here we present STELLAR, a geometric deep learning method that utilizes spatial and molecular cell information to automatically assign cell types from an annotated reference set as well as discover new cell types and cell states. STELLAR transfers annotations across different dissection regions, tissues, and donors and detects higher-order tissue structures with dramatic time savings.


title: ECLIPSER: identifying causal cell types and genes for complex traits through single cell enrichment of e/sQTL-mapped genes in GWAS loci

abstract:
SummaryECLIPSER was developed to identify pathogenic cell types and cell type-specific genes that may affect complex disease susceptibility and trait variation by integrating single cell data with known GWAS loci. ECLIPSER maps genes to GWAS loci for a given complex trait based on expression and splicing quantitative trait loci (e/sQTLs) and other functional data, and tests whether the mapped genes are enriched for cell type-specific expression in particular cell types using single-cell/nucleus RNA-seq data from one or more tissues of interest. A Bayesian Fishers exact test is used to compute fold-enrichment significance. We demonstrate the application of ECLIPSER on various skin diseases and traits using snRNA-seq of healthy human skin samples.

Availability and ImplementationThe source code and documentation for ECLIPSER and a Jupyter notebook for generating output tables and figures are available at https://github.com/segrelabgenomics/ECLIPSER. The source code for GWASvar2gene that maps genes to GWAS loci based on e/sQTLs is available at https://github.com/segrelabgenomics/GWASvar2gene. The analysis presented here used data from GTEx (https://gtexportal.org/home/datasets) and Open Targets Genetics (https://genetics-docs.opentargets.org/data-access/graphql-api), but can also be applied to other GWAS variant lists and QTL studies. Data used to reproduce the results of the paper are available in Supplementary data.


title: On the reproductive mechanism of Gram-negative protocells

abstract: One of the major challenges of understanding early life or a bottom-up approach of building a synthetic cell is to drive the process of reproduction. To achieve reproduction completely independent of molecular biological processes, here we worked with bacterial protoplasts under environmental conditions of early Earth. Rather than reproducing in a chaotic manner due to the loss of molecular biological co-ordination, cells in our study reproduced in a defined sequence of steps. Lifecycle of cells in our study was either similar to lipid vesicles undergoing osmotic shrinkage or to lipid vesicles undergoing expansion when placed in an elongational flow path. Fission of parent cell into multiple daughter cells was achieved via forces intrinsic to cell like the Brownian motion of intracellular constituents, asymmetric conditions on either side of the membrane or induced by membrane phase-separation. In short, our study demonstrates how cells reproduced prior to the evolution of molecular biological processes.


title: Day length-dependent thermal COP1 dynamics integrate conflicting seasonal cues in the control of Arabidopsis elongation

abstract: As the summer approaches, plants experience enhanced light inputs and elevated temperatures, two environmental cues with an opposite morphogenic impact. How plants integrate this conflicting information throughout seasons remains unclear. Key components of the plant response to light and temperature include phytochrome B (phyB), PHYTOCROME INTERACTING FACTOR 4 (PIF4), EARLY FLOWERING 3 (ELF3) and CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1). Here, we used hypocotyl lengths of single and double mutant/over-expression lines to fit a mathematical model incorporating known interactions of these genes. The fitted model recapitulates day length-dependent thermoelongation of all lines studied, and correctly predicts temperature responsiveness of new genotypes. Whilst previous works pointed to a lightindependent thermal function of COP1, simulations of our model suggested that COP1 has a role in temperature-signaling only during daytime. Based on by this prediction, we show that COP1 overexpression increases thermal response in continuous white light, while it has little effect in darkness. Defective thermal response of cop1-4 mutants is epistatic to phyB-9 and elf3-8, indicating that COP1 activity is essential to the transduction of phyB and ELF3 thermosensory function. Our model accurately captures phyB, ELF3 and PIF4 dynamics, providing an excellent toolbox for identification of best allelic combinations towards optimized crops resilience to climate change at different geographical latitudes.


title: Intact double stranded RNA is mobile and triggers RNAi against viral and fungal plant pathogens

abstract: Topical application of double-stranded RNA (dsRNA) as RNA interference(RNAi) based biopesticides represents a sustainable alternative to traditional transgenic, breeding-based or chemical crop protection strategies. A key feature of RNAi is its ability to act non-cell autonomously, a process that plays a critical role in plant protection. However, the uptake of dsRNA upon topical application, and its ability to move and act non-cell autonomously remains debated and largely unexplored. Here we show that when applied to a leaf, unprocessed full-length dsRNA enters the vasculature and rapidly moves to multiple distal below ground, vegetative and reproductive tissue types in several model plant and crop hosts. Intact unprocessed dsRNA was detected in the apoplast of leaves, roots and flowers after leaf application and maintained in subsequent new growth. Furthermore, we show mobile dsRNA is functional against root infecting fungal and foliar viral pathogens. Our demonstration of the uptake and maintained movement of intact and functional dsRNA stands to add significant benefit to the emerging field of RNAi-based plant protection.


title: A Scalable and Modular Automated Pipeline for Stitching of Large Electron Microscopy Datasets

abstract: Serial-section electron microscopy (ssEM) is the method of choice for studying macroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so called connectomes. In order to use this data, consisting of up to 108 individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render [18] services used in the volume assembly of the brain of adult Drosophila melanogaster [2]. It achieves high throughput by operating on the meta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP is modular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous processing of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex [1, 25] at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

category: neuroscience


title: Altered neurogenic pathways in experimental rat models of ischemic cerebral stroke: A transcriptome based meta-analysis

abstract:
1)ObjectivesPromoting neurogenesis mediated recovery is one of the most sought after strategies in recovery after cerebral stroke. In this paper we elucidate how neurogenesis related genes are altered in the early stroke environment, to hint at potential pathways for therapeutic recovery.

Materials and MethodsAround 97 microarray datasets derived from stroke affected rat brains were collected from NCBI-GEO. Datasets were normalized and subjected to meta-analysis in Network Analyst to identify differentially expressed genes. Gene enrichment analyses were carried out using GSEA, and WebGestalt, and results were visualized using Cytoscape Enrichment mapping.

ResultsNearly 939 differentially expressing genes were identified in the cerebral stroke group. Among them 30 neurogenesis related genes were identified through enrichment mapping analysis, and 35 genes through Protein- Protein Interaction analysis. Highest upregulated neurogenesis genes were found to be TSPO, GFAP, VIM, and TGFB1. Highest Downregulated neurogenesis genes were found to be THY1, NR1D1, CDK5, STX1B, and NOG.

ConclusionsThrough this study, we have identified that during the acute time frame after stroke, majority of the neurogenesis genes related to neural proliferation and neural differentiation are downregulated, while the majority of the genes related to neuronal migration were upregulated. Single or combined therapeutic approach against the identified dysregulated genes could greatly aid neural restoration and functional recovery during the postischemic stage.


title: Automated methodology for optimal selection of the minimum electrode subset for accurate EEG source localization based on Genetic Algorithm optimization

abstract:
High-density Electroencephalography (HD-EEG) has been proven to be the most accurate option to estimate the neural activity inside the brain. Multiple studies report the effect of electrode number on source localization for specific sources and specific electrode configurations. The electrodes for these configurations have been manually selected to uniformly cover the entire head, going from 32 to 128 electrodes, but electrodes were not selected according to their contribution to accuracy. In this work, an optimization-based study is proposed to determine the minimum number of electrodes and identify optimal combinations of electrodes that can retain the localization accuracy of HD-EEG reconstructions. This optimization approach incorporates scalp landmark positions of widely used EEG montages. In this way, a systematic search for the minimum electrode subset is performed for single and multiple source localization problems. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) combined with source reconstruction methods is used to formulate a multi-objective optimization problem that concurrently minimizes 1) the localization error for each source and 2) the number of required EEG electrodes. The method can be used for evaluating the source localization quality of low-density EEG systems (e.g. consumer-grade wearable EEG). We performed an evaluation over synthetic and real EEG dataset with known ground-truth. The experimental results show that optimal subsets with 6 electrodes can obtain an equal or better accuracy than HD-EEG (with more than 200 channels) for a single source case. This happened when reconstructing a particular brain activity in more than 88% of the cases (in synthetic signals) and 63% (in real signals), and in more than 88% and 73% of the cases when considering optimal combinations with 8 channels. For a multiple-source case of three sources (only with synthetic signals), it was found that optimized combinations of 8, 12 and 16 electrodes attained an equal or better accuracy than HD-EEG with 231 electrodes in at least 58%, 76%, and 82% of the cases respectively. Additionally, for such electrode numbers, a lower mean error and standard deviation than with 231 electrodes were obtained.

HighlightsO_LIThe number of EEG electrodes and their locations can be optimized for reconstructing the brain source activity.
C_LIO_LIOptimally selected EEG electrodes can retain the accuracy of high density montages (256, 128 chs) for brain source estimation, when electrodes are selected according to their contribution to accuracy.
C_LIO_LIWith optimization, selected combinations of EEG electrodes will flexibilize the estimation of the source activity.
C_LI


title: Automated methodology for optimal selection of the minimum electrode subset for accurate EEG source estimation based on Genetic Algorithm optimization