title: Proteus mirabilis employs a contact-dependent killing system against competing Enterobacteriaceae

abstract:
Many bacterial species encode systems for interference competition with other microorganisms. Some systems are effective without contact (e.g. through secretion of toxins), while other systems (e.g. Type VI secretion system (T6SS)) require direct contact between cells. Here, we provide the initial characterization of a novel contact-dependent competition system for Proteus mirabilis. In neonatal mice, a commensal P. mirabilis strain apparently eliminated commensal Escherichia coli. We replicated the phenotype in vitro and showed that P. mirabilis efficiently reduced viability of several Enterobacteriaceae species, but not Gram-positive species or yeast cells. Importantly, P. mirabilis strains isolated from humans also killed E. coli. Reduction of viability occurred from early stationary phase to 24h of culture and was observed in shaking liquid media as well as on solid media. Killing required contact, but was independent of T6SS, the only contact-dependent killing system described for P. mirabilis. Expression of the killing system was regulated by osmolarity and components secreted into the supernatant. Stationary phase P. mirabilis culture supernatant itself did not kill but was sufficient to induce killing in an exponentially growing co-culture. In contrast, killing was largely prevented in media with low osmolarity. In summary, we provide the initial characterization of a potentially novel interbacterial competition system encoded in P. mirabilis.

IMPORTANCEThe study of bacterial competition systems has received significant attention in recent years. These systems collectively shape the composition of complex ecosystems like the mammalian gut. They are also being explored as narrow-spectrum alternatives to specifically eliminate problematic pathogenic species. However, many competition systems that effectively work in vitro do not show strong phenotypes in the gut. Our study was informed by an observation in infant mice. Further in vitro studies confirmed that P. mirabilis was able to kill several Enterobacteriaceae species. This killing system is novel for P. mirabilis and might represent a new function of a known system or even a novel system, as the observed characteristics do not fit with described contact-dependent competition systems. Competition systems are frequently present in multiple Enterobacteriaceae species. If present or transferred into a probiotic, it might be used in the future to reduce blooms of pathogenic Enterobacteriaceae associated with disease.


title: Application of HPMCAS-coated Ctx(Ile21)-Ha peptide microparticles as a potential use to prevent systemic infection caused by Salmonella Enteritidis in poultry

abstract: The transmission of Salmonella Enteritidis (SE) in poultry is most often by the fecal-oral route, which can be attributed to the population density. Consequently, the pathogen triggers stress response and virulence factors deploying it to survive in hosts. Therefore, this study proposed to evaluate HPMCAS-coated microparticles containing the Ctx(Ile21)-Ha antimicrobial peptide against SE in laying hens chicks infection model to determine whether Ctx(Ile21)-Ha-utilization confers a benefit in the intestinal lumen, as well as whether limits systemic infection. Importantly, while assessing whether AMP utilization confers reduction of SE in liver, it was noted that there was statistical significance between groups A (control, no Ctx(Ile21)-Ha peptide) and B (2.5 mg of Ctx(Ile21)-Ha/kg) at 2 dpi, potentially indicating the Ctx(Ile21)-Ha effectiveness in the first stage of infection by SE. Remarkably, it was also detected a statistical significance (p -value <0.0001) with lower counts of SE ([~] 0 CFU) in livers at 5, 7, and 14 dpi, regardless of Ctx(Ile21)-Ha dosage (2.5 mg or 5 mg/kg - group C). By using Chi-square test, the AMP effect on SE fecal excretion was evaluated. In this regard, it was noticed statistical significance (p < 0.05) among groups B and C in comparison with control group A, since those groups had lower bacterial excretion along 21 days. In summary, the role of HPMCAS-Ctx(Ile21)-Ha peptide microcapsules against S. Enteritidis in laying hen chicks infection model was unraveled, providing a satisfactory results against this pathogen.

category: microbiology


title: Coupling of spliceosome complexity to intron diversity

abstract: We determined that over 40 spliceosomal proteins are conserved between many fungal species and humans but were lost during the evolution of S. cerevisiae, an intron-poor yeast with unusually rigid splicing signals. We analyzed null mutations in a subset of these factors, most of which had not been investigated previously, in the intron-rich yeast Cryptococcus neoformans. We found they govern splicing efficiency of introns with divergent spacing between intron elements. Importantly, most of these factors also suppress usage of weak nearby cryptic/alternative splice sites. Among these, orthologs of GPATCH1 and the helicase DHX35 display correlated functional signatures and copurify with each other as well as components of catalytically active spliceosomes, identifying a conserved G-patch/helicase pair that promotes splicing fidelity. We propose that a significant fraction of spliceosomal proteins in humans and most eukaryotes are involved in limiting splicing errors, potentially through kinetic proofreading mechanisms, thereby enabling greater intron diversity.

category: molecular biology


title: A non-canonical microRNA derived from the snaR-A non-coding RNA targets a metastasis inhibitor

abstract: MicroRNAs (miRNAs) are small noncoding RNAs that function as critical post-transcriptional regulators in various biological processes. While most miRNAs are generated from processing of long primary transcripts via sequential Drosha and Dicer cleavage, some miRNAs that bypass Drosha cleavage can be transcribed as part of another small non-coding RNA. Here, we develop the Target-Oriented miRNA Discovery (TOMiD) bioinformatic analysis method to identify Drosha-independent miRNAs from Argonaute crosslinking and sequencing of hybrids (Ago-CLASH) datasets. Using this technique, we discovered a novel miRNA derived from a primate specific non-coding RNA, the small NF90 associated RNA A (snaR-A). The miRNA derived from snaR-A (miR-snaR) arises independent of Drosha processing, but requires Exportin-5 and Dicer for biogenesis. We identify that miR-snaR is concurrently upregulated with the full snaR-A transcript in cancer cells. Functionally, miR-snaR associates with Ago proteins and targets NME1, a key metastasis inhibitor, contributing to snaR-As role in promoting cancer cell migration. Our findings suggest a functional link between a novel miRNA and its precursor non-coding RNA.


title: Generation of Drosophila attP containing cell lines using CRISPR-Cas9

abstract: The generation of Drosophila stable cell lines have become invaluable for complementing in vivo experiments and as tools for genetic screens. Recent advances utilizing attP/PhiC31 integrase system has permitted the creation of Drosophila cells in which recombination mediated cassette exchange (RMCE) can be utilized to generate stably integrated transgenic cell lines that contain a single copy of the transgene at the desired locus. Current techniques, besides being laborious and introducing extraneous elements, are limited to a handful of cell lines of embryonic origin. Nonetheless, with well over 100 Drosophila cell lines available, including an ever-increasing number CRISPR/Cas9 modified cell lines, a more universal methodology is needed to generate a stably integrated transgenic line from any one of the available Drosophila melanogaster cell lines. Here we describe a toolkit and procedure that combines CRISPR/Cas9 and the PhiC31 integrase system. We have generated and isolated single cell clones containing an Actin5C::dsRed cassette flanked by attP sites into the genome of Kc167 and S2R+ cell lines that mimic the in vivo attP sites located at 25C6 and 99F8 of the Drosophila genome. Furthermore, we tested the functionality of the attP docking sites utilizing two independent GFP expressing constructs flanked by attB sites that permit RMCE and therefore the insertion of any DNA of interest. Lastly, to demonstrate the universality of our methodology and existing constructs, we have successfully integrated the Actin5C::dsRed cassette flanked by attP sites into two different CNS cell lines, ML-DmBG2-c2 and ML-DmBG3-c2. Overall, the reagents and methodology reported here permit the efficient generation of stable transgenic cassettes with minimal change in the cellular genomes in existing D. melanogaster cell lines.

category: genetics


title: Marchantia polymorpha model reveals conserved infection mechanisms in the vascular wilt fungal pathogen Fusarium oxysporum

abstract:
The non-vascular plant Marchantia polymorpha has emerged as a valuable model for studying evolutionarily conserved microbial infection strategies and plant immune responses. However, only a handful of fungal pathogens of Marchantia have been described so far. Here we establish a new pathosystem using the root-infecting vascular wilt fungus Fusarium oxysporum. On angiosperms, this fungus exhibits exquisite adaptation to the plant vascular niche and host-specific pathogenicity, both of which are conferred by lineage-specific effectors secreted during growth in the xylem. We show that F. oxysporum isolates with different lifestyles - pathogenic or endophytic - are able to infect this non-vascular liverwort causing tissue maceration and plant cell killing. Similar to bacterial pathogens, F. oxysporum induces a PAMP-triggered immune response in M. polymorpha. Analysis of isogenic fungal mutants established that infection of Marchantia requires conserved fungal pathogenicity mechanisms such as mitogen activated protein kinases, transcriptional regulators and cell wall remodeling enzymes. Remarkably, lineage-specific virulence effectors are dispensable for infection, most likely due to the absence of xylem tissue in this non-vascular plant. The F. oxysporum - M. polymorpha system provides new insights into the mechanism and evolution of pathogenic and endophytic fungus-plant interactions.

Significance statementRoot-infecting vascular fungi cause wilt diseases and provoke devastating losses in hundreds of crops. It is currently unknown how these pathogens evolved and whether they infect non-vascular plants, which diverged from vascular plants over 450 million years ago. Here we show that two strains of the fungus Fusarium oxysporum with opposed lifestyles, causing either wilting and death or beneficial protection on tomato, produce similar disease symptoms on the non-vascular plant Marchantia polymorpha. We define a set of core fungal pathogenicity factors required on both vascular and non-vascular plants and show that host-specific effectors contributing to disease on tomato are dispensable on Marchantia. These findings suggest that systemic wilt disease evolved in fungal pathogens after the emergence of vascular land plants.

category: plant biology


title: Effects of cover crops on beetle assemblages in tea plantations

abstract: Beetles are visible members of food webs in tea plantations, with high species richness and abundance. Many tea pests, as well as natural enemies, are members of this order, so a knowledge of how groundcovers affect beetles can aid pest management. We collected beetles in a replicated field experiment in the Wuyi Mountains, Fujian Province China. Tea was intercropped with Paspalum notatum or Chamaecrista rotundifolia, or rows were cleared to bare ground, or in the control they were left unmanaged to allow weeds to grow naturally. Sampling, done by sweep netting and vegetation beating, was conducted monthly, between May 2006 and April 2008, and Coleoptera abundance, biomass, species richness and assemblage structures were compared between groundcover treatments. Total beetle abundance and species richness were significantly higher in tea intercropped with C. rotundifolia and bare ground than in naturally grown weedy control. Whilst there was no difference between predator assemblages among treatments for any measure, herbivores were more abundant, weighed more, and were more diverse in C. rotundifolia treatments than in weedy control. Biomass and species richness were also greater in plots with P. notatum groundcover than those in weedy control. We found that beetle assemblages varied both seasonally and with ground cover treatment, but the potential pest control impact of more species-rich beetle assemblages was mixed, and further work is needed to gain information on trophic groups with potential benefits for use in non-insecticidal pest management.

category: ecology


title: Water yield modelling, sensitivity analysis and validation: a study for Portugal

abstract: The spatially explicit assessment of freshwater is key to introduce the ecosystem service (ES) concept into decision-making processes. Many tools are being developed to model water balance and to analyse the effects of meteorological conditions on water ES behaviours at multiple spatial scales. Nevertheless, there is a lack of studies that analyse the sensitivity of these models and estimate the models accuracy. The current research uses the InVEST Water Yield Model (WYM) to assess freshwater ES between 1990 and 2018 at River Basin District (RBD) level in mainland Portugal. The methodology included sensitivity analysis simulations to test different parameters of the model over two different sources of meteorological data. We validated the model with the European Environment Agency (EEA) database on the quantity of Europes freshwater resources. To evaluate the models sensitivity, Pearsons correlation coefficients and statistical methods were calculated for each simulation. The model which obtained the best performance in the sensitivity tests was retained for further analysis and calibration and its accuracy was assessed by comparing the mean estimated water yield (WY) with mean observed values for 2018. Results at the national level show a correlation coefficient of 0.803 with statistical significance for 0.01 one-tail. The WY in the RBDs of the North of the country was underestimated by 56.5 mm/ha/year and for the RBDs in the South of Portugal, the WY was overestimated by 58.1 mm/ha/year. This difference was explained through the spatial-temporal assessment of the main climatic variables used as input. This study contributes to a methodology to assess the level of confidence in WYM outputs and can be used to support the trustworthiness of water availability studies at sub-watershed, watershed, or RBD, using open access data and software.


title: A strategic sampling design revealed the local genetic structure of cold-water fluvial sculpin: a focus on groundwater-dependent water temperature heterogeneity

abstract: A key piece of information for ecosystem management is the relationship between the environment and population genetic structure. However, it is difficult to clearly quantify the effects of environmental factors on genetic differentiation because of spatial autocorrelation and analytical problems. In this study, we focused on stream ecosystems and the environmental heterogeneity caused by groundwater and constructed a sampling design in which geographic distance and environmental differences are not correlated. Using multiplexed ISSR genotyping by sequencing (MIG-seq) method, a fine-scale population genetics study was conducted in fluvial sculpin Cottus nozawae, for which summer water temperature is the determinant factor in distribution and survival. There was a clear genetic structure in the watershed. Although a significant isolation-by-distance pattern was detected in the watershed, there was no association between genetic differentiation and water temperature. Instead, asymmetric gene flow from relatively low-temperature streams to high-temperature streams was detected, indicating the importance of low-temperature streams and continuous habitats. The groundwater-focused sampling strategy yielded unexpected results and provided important insights for conservation.


title: Growth of Lahontan Cutthroat Trout from multiple sources re-introduced into Sagehen Creek, CA

abstract: Lahontan Cutthroat Trout Oncorhynchus clarkii henshawi have experienced massive declines in their native range and are now a threatened species under the US Endangered Species Act. A key management goal for this species is re-establishing extirpated populations using translocations and conservation hatcheries. In California USA, two broodstocks (Pilot Peak and Independence Lake) are available for translocation, in addition to potential wild sources. Yet suitability of these sources for re-introduction in different ecosystem types and regions remains an open and important topic. We conducted growth experiments using Lahontan Cutthroat Trout stocked into Sagehen Creek, CA USA. Experiments evaluated both available broodstocks and a smaller sample of wild fish translocated from a nearby creek. Fish from the Independence Lake source had significantly higher growth in weight and length compared to the other sources. Further, Independence Lake fish were the only stock that gained weight on average over the duration of the experiment. Our experiments suggest fish from the Independence Lake brood stock may be useful for re-introduction efforts into small montane headwater streams in California.


title: Multilevel selection favors fragmentation modes that maintain cooperative interactions in multispecies communities

abstract:
Reproduction is one of the requirements for evolution and a defining feature of life. Yet, across the tree of life, organisms reproduce in many different ways. Groups of cells (e.g., multicellular organisms, colonial microbes, or multispecies biofilms) divide by releasing propagules that can be single-celled or multicellular. What conditions determine the number and size of reproductive propagules? In multicellular organisms, existing theory suggests that single-cell propagules prevent the accumulation of deleterious mutations (e.g., cheaters). However, groups of cells, such as biofilms, sometimes contain multiple metabolically interdependent species. This creates a reproductive dilemma: small daughter groups, which prevent the accumulation of cheaters, are also unlikely to contain the species diversity that is required for ecological success. Here, we developed an individual-based, multilevel selection model to investigate how such multi-species groups can resolve this dilemma. By tracking the dynamics of groups of cells that reproduce by fragmenting into smaller groups, we identified fragmentation modes that can maintain cooperative interactions. We systematically varied the fragmentation mode and calculated the maximum mutation rate that communities can withstand before being driven to extinction by the accumulation of cheaters. We find that for groups consisting of a single species, the optimal fragmentation mode consists of releasing single-cell propagules. For multi-species groups we find various optimal strategies. With migration between groups, single-cell propagules are favored. Without migration, larger propagules sizes are optimal; in this case, group-size dependent fissioning rates can prevent the accumulation of cheaters. Our work shows that multi-species groups can evolve reproductive strategies that allow them to maintain cooperative interactions.

Author summaryIn order to reproduce, multicellular organisms and colonial bacteria fragment into offspring groups. Fragmentation modes in nature are very diverse: e.g. some organisms split into two halves, while others release single-celled propagules. These fragmentation modes can have fitness consequences, e.g. small propagules reduce the spread of deleterious mutants. However, the consequences of different fragmentation modes are not yet well understood for groups of cells containing several metabolically interdependent species, such as complex biofilms. We developed a multilevel selection model to investigate the effect of fragmentation mode on the accumulation of deleterious mutants when groups contain multiple species. In such groups, small propagules are not always a viable strategy, because they may harbor low species diversity. We find that alternative mechanisms, such as migration of cells between groups and group-size dependent fissioning rates, can prevent the accumulation of mutants. We also find that multilevel selection can lead to the evolution of fragmentation strategies that allow multi-species groups to thrive in the face of deleterious mutations.

category: evolutionary biology


title: APOE4 is associated with elevated blood lipids and lower levels of innate immune biomarkers in a tropical Amerindian subsistence population

abstract: In post-industrial settings, APOE4 is associated with increased cardiovascular and neurological disease risk. However, the majority of human evolutionary history occurred in environments with higher pathogenic diversity and low cardiovascular risk. We hypothesize that in high-pathogen and energy-limited contexts, the APOE4 allele confers benefits by reducing baseline innate inflammation when uninfected, while maintaining higher lipid levels that buffer costs of immune activation during infection. Among Tsimane forager-farmers of Bolivia (N=1266), APOE4 is associated with 30% lower C-reactive protein, and higher total cholesterol and oxidized-LDL. Blood lipids were either not associated, or negatively associated with inflammatory biomarkers, except for associations of oxidized-LDL and inflammation which were limited to obese adults. Further, APOE4 carriers maintain higher levels of total and LDL cholesterol at low BMIs. These results suggest the relationship between APOE4 and lipids is likely beneficial for pathogen-driven immune responses, and unlikely to increase cardiovascular risk in an active subsistence population.


title: Assortative Mating Biases Marker-based Heritability Estimators

abstract: Many complex traits are subject to assortative mating (AM), with recent molecular genetic findings confirming longstanding theoretical predictions that AM alters genetic architecture by inducing long range dependence across causal variants. However, all marker-based heritability estimators assume mating is random. We provide mathematical and simulation-based evidence demonstrating that both method-of-moments estimators and likelihood-based estimators produce biased estimates in the presence of AM and that common approaches to account for population structure fail to mitigate this bias. Then, examining height and educational attainment in the UK Biobank, we demonstrate that these biases affect real world traits. Finally, we derive corrected heritability estimators for traits under equilibrium AM.


title: Optogenetic manipulation of individual or whole population Caenorhabditis elegans worms with an under hundred-dollar tool: the OptoArm

abstract: AbstractOptogenetic tools have revolutionized the study of neuronal circuits in Caenorhabditis elegans. The expression of light-sensitive ion channels or pumps under specific promotors allows researchers to modify the behavior of excitable cells. Several optogenetic systems have been developed to spatially and temporally photoactivate light-sensitive actuators in C. elegans. Nevertheless, their high costs and low flexibility have limited wide access to optogenetics. Here, we developed an inexpensive, easy-to-build, and adjustable optogenetics device for use on different microscopes and worm trackers, called the OptoArm. The OptoArm allows for single- and multiple-worm illumination and is adaptable in terms of light intensity, lighting profiles and light-color. We demonstrate the OptoArms power in a population-based study on contributions of motor circuit cells to age-related motility decline. We find that functional decline of cholinergic neurons mirrors motor decline, while GABAergic neurons and muscle cells are relatively age-resilient, suggesting that rate-limiting cells exist and determine neuronal circuit aging.


title: Tardigrades exhibit robust inter-limb coordination across walking speeds

abstract: Tardigrades must negotiate heterogeneous, fluctuating environments, and accordingly utilize locomotive strategies capable of dealing with variable terrain. We analyze the kinematics and inter-leg coordination of freely walking tardigrades (species: Hypsibius dujardini). We find that tardigrade walking replicates several key features of walking in insects despite disparities in size, skeleton, and habitat. To test the effect of environmental changes on tardigrade locomotor control circuits, we measure kinematics and inter-leg coordination during walking on two substrates of different stiffnesses. We find that the phase offset between contralateral leg pairs is flexible, while ipsilateral coordination is preserved across environmental conditions. This mirrors similar results in insects and crustaceans. We propose that these functional similarities in walking co-ordination between tardigrades and arthropods is either due to a generalized locomotor control circuit common to panarthropods, or to independent convergence onto an optimal strategy for robust multi-legged control in small animals with simple circuitry. Our results highlight the value of tardigrades as a comparative system towards understanding the mechanisms - neural and/or mechanical - underlying coordination in panarthropod locomotion.

category: animal behavior and cognition


title: Bumblebees can detect floral humidity

abstract:
Floral humidity, a region of elevated humidity proximal to the flower, occurs in many plant species and may add to their multimodal floral displays. So far, the ability to detect and respond to floral humidity cues has been only established for hawkmoths when they locate and extract nectar while hovering in front of some moth-pollinated flowers. To test whether floral humidity can be used by other more widespread generalist pollinators, we designed artificial flowers that presented biologically-relevant levels of humidity similar to those shown by flowering plants. Bumblebees showed a spontaneous preference for flowers which produced higher floral humidity. Furthermore, learning experiments showed that bumblebees are able to use differences in floral humidity to distinguish between rewarding and nonrewarding flowers. Our results indicate that bumblebees are sensitive to different levels of floral humidity. In this way floral humidity can add to the information provided by flowers and could impact pollinator behaviour more significantly than previously thought.

Summary statementWe demonstrate for the first time that bumblebees show a preference to elevated floral humidity and can learn to distinguish flowers that differ in floral humidity levels.


title: Multimodal characterization of Yucatan minipig behavior and physiology through maturation

abstract: Brain injuries that are induced by external forces are particularly challenging to model experimentally. In recent decades, the domestic pig has been gaining popularity as a highly relevant animal model to address the pathophysiological mechanisms and the biomechanics associated with head injuries. Understanding cognitive, motor, and sensory aspects of pig behavior throughout development is crucial for evaluating cognitive and motor deficits after injury. We have developed a comprehensive battery of tests to characterize the behavior and physiological function of the Yucatan minipig throughout maturation. Behavioral testing included assessments of learning and memory, executive functions, circadian rhythms, gait analysis, and level of motor activity. We applied traditional behavioral apparatus and analysis methods, as well as state-of-the-art sensor technologies to report on motion and activity, and artificial intelligent approaches to analyze behavior. We studied pigs from 16 weeks old through sexual maturity at 35 weeks old. The results show multidimensional characterization of minipig behavior, and how it develops and changes with age. This animal model may capitulate the biomechanical consideration and phenotype of head injuries in the developing brain and can drive forward the field of understanding pathophysiological mechanisms and developing new therapies to accelerate recovery in children who have suffered head trauma.


title: Platinized graphene fiber electrodes revealed differential activity in terminal splenic neurovascular plexi supporting a direct spleen-vagus communication

abstract: Neural interfacing nerve fascicles along the splenic neurovascular plexi (SNVP) is needed to better understand the spleen physiology, and for selective neuromodulation of this major organ. However, the small size and anatomical location have proven to be a significant challenge. Here, we use a reduced liquid crystalline graphene oxide (rGO) fiber coated with platinum (Pt) as a super-flexible suture-like electrode to interface multiple SNVP. The Pt-rGO fibers were used as handover knot electrodes over the small plexi, allowing sensitive recording from the splenic nerve (SN) terminal branches. Asymmetric defasciculation of the SN branches was revealed by electron microscopy, and the functional compartmentalization in spleen innervation was evidenced in response to hypoxia and pharmacological modulation of mean arterial pressure. We demonstrate that electrical stimulation of cervical and subdiaphragmatic vagus nerve (VN), evoked direct activity in a subset of SN terminal branches, providing evidence for a direct VN control over the spleen. This notion was supported by tract-tracing of SN branches, revealing an unconventional direct spleen-VN projection. High-performance Pt-rGO fiber electrodes, may be used for the fine neural modulation of other small neurovascular plexi at the point of entry of the organs as a bioelectronic medical alternative.

category: bioengineering


title: An equine tendon model for studying intra-tendinous shear in tendons that have more than one muscle contribution

abstract: Human Achilles tendon is composed of three smaller sub-tendons and exhibits non-uniform internal displacements, which decline with age and after injury, suggesting a potential role in the development of tendinopathies. Studying internal sliding behaviour is therefore important but difficult in human Achilles tendon. Here we propose the equine deep digital flexor tendon (DDFT) and its accessory ligament (AL) as a model to understand the sliding mechanism. The AL-DDFT has a comparable sub-bundle structure, is subjected to high and frequent asymmetric loads and is a natural site of injury similar to human Achilles tendons. Equine AL-DDFT were collected and underwent whole tendon level (n=7) and fascicle level (n=7) quasi-static mechanical testing. Whole tendon level testing was performed by sequentially loading through the proximal AL and subsequently through the proximal DDFT and recording regional strain in the free structures and joined DDFT and AL. Fascicle level testing was performed with focus on the inter-sub-bundle matrix between the two structures at the junction. Our results demonstrate a significant difference in the regional strain between the joined DDFT and AL and a greater transmission of force from the AL to the DDFT than vice versa. These results can be partially explained by the mechanical properties and geometry of the two structures and by differences in the properties of the interfascicular matrices. In conclusion, this tendon model successfully demonstrates that high displacement discrepancy occurs between the two structures and can be used as an easy-access model for study intra-tendinous shear mechanics at the sub-tendon level.


title: Asc-Seurat - Analytical single-cell Seurat-based web application

abstract:
SummarySingle-cell RNA sequencing (scRNA-seq) has become a popular approach for studying the transcriptome, providing a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data processing and uncover relevant biological information. We present Asc-Seurat, a feature rich workbench, providing a user-friendly and easy-to-install web application encapsulating the necessary tools for an all-encompassing and fluid scRNA-seq data analysis.

Availability and implementationAsc-Seurat is available at https://github.com/KirstLab/asc_seurat/ and released under GNU 3 license.

Contactmkirst@ufl.edu

Supplementary informationSupplementary data are available at Bioinformatics online.

category: bioinformatics


title: Convergent Usage of Amino Acids in Human Cancers as a Reversed Process of Tissue Development

abstract: Genome and transcriptome-wide amino acid usage preference across different species is a well-studied phenomenon in molecular evolution, but its characteristics and implication in cancer evolution and therapy remain largely unexplored. Here, we analyzed large-scale transcriptome/proteome profiles such as TCGA, GTEx, and CPTAC and found that compared to normal tissues, different cancer types showed a convergent pattern towards using biosynthetically low-cost amino acids. Such a pattern can be accurately captured by a single index based on the average biosynthetic energy cost of amino acids, termed Energy Cost Per Amino Acid (ECPA). With this index, we further compared the trends of amino acid usage and the contributing genes in cancer and tissue development and revealed their reversed patterns. Finally, focusing on the liver, a tissue with a dramatic increase in ECPA during development, we found that EPCA represented a powerful biomarker that could distinguish liver tumors from normal liver samples consistently across 11 independent patient cohorts (AUROC = ~0.99) and outperformed any index based on single genes. Our study reveals an important principle underlying cancer evolution and suggests the global amino acid usage as a system-level biomarker for cancer diagnosis.


title: Representation learning of RNA velocity reveals robust cell transitions

abstract: AO_SCPLOWBSTRACTC_SCPLOWRNA velocity is a promising technique to reveal transient cellular dynamics among a heterogeneous cell population and quantify their transitions from single-cell transcriptome experiments. However, the cell transitions estimated from high dimensional RNA velocity are often unstable or inaccurate, partly due to the high technical noise and less informative projection. Here, we present VeloAE, a tailored representation learning method to learn a low-dimensional representation of RNA velocity on which cell transitions can be robustly estimated. From various experimental datasets, we show that VeloAE can both accurately identify stimulation dynamics in time-series designs and effectively capture the expected cellular differentiation in different biological systems. VeloAE therefore enhances the usefulness of RNA velocity for studying a wide range of biological processes.


title: Cellar: Interactive single cell data annotation tool

abstract:
Several recent technologies and platforms enable the profiling of various molecular signals at the single-cell level. A key question for all studies using such data is the assignment of cell types. To improve the ability to correctly assign cell types in single and multi-omics sequencing and imaging single-cell studies, we developed Cellar. This interactive software tool supports all steps in the analysis and assignment process. We demonstrate the advantages of Cellar by using it to annotate several HuBMAP datasets from multi-omics single-cell sequencing and spatial proteomics studies. Cellar is freely available and includes several annotated reference HuBMAP datasets.

Availabilityhttps://data.test.hubmapconsortium.org/app/cellar


title: GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

abstract: Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further adapt a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data dependent acquisition (DDA) based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.


title: Isolation, Molecular identification, Molecular docking  In Vitro and In Silico Evaluation study against Fusarium oxysporum sp. Lactucae

abstract: bioRxiv has withdrawn this preprint as it was submitted and made public without the full consent of all the contributing authors.


title: Machine learning prediction of Antibody-Antigen binding: dataset, method and testing

abstract:
DNA sequencing technologies are providing new insights into the immune response by allowing the large scale sequencing of rearranged immunoglobulin gene present in an individual, however the applications of this approach are limited by the lack of methods for determining the antigen(s) that an immunoglobulin encoded by a given sequence binds to. Computational methods for predicting antibody-antigen interactions that leverage structure prediction and docking have been proposed, however these methods require knowledge of the 3D structures.

As a step towards the development of a machine learning method suitable for predicting antibody-antigen binding affinities from sequence data, a weighted nearest neighbor machine learning approach was applied to the problem. A prediction program was coded in Python and evaluated using cross-validation on a dataset of 600 antibodies interacting with 50 antigens. The classification predicting accuracy was around 76% for this dataset. These results provide a useful frame of reference as well as protocols and considerations for machine learning and dataset creation in this area.

Both the dataset (in csv format) and the machine learning program (coded in python) are freely available for download.


title: Correcting for Background Noise Improves Phenotype Prediction from Human Gut Microbiome Data

abstract: The ability to predict human phenotypes accurately from metagenomic data is crucial for developing biomarkers and therapeutics for diseases. However, metagenomic data is commonly affected by technical or biological variables, unrelated to the phenotype of interest, such as sequencing protocol or host sex, which can greatly reduce or, when correlated to the phenotype of interest, inflate prediction accuracy. We perform a comparative analysis of the ability of different data transformations and existing supervised and unsupervised methods to correct microbiome data for background noise. We find that supervised methods are limited because they cannot account for unmeasured sources of variation. In addition, we observe that unsupervised approaches are often superior in addressing these issues, but existing methods developed for other  omic data types, e.g., gene expression and methylation, are restricted by parametric assumptions unsuitable for microbiome data, which is typically compositional, highly skewed, and sparse. We show that application of the centered log-ratio transformation prior to correction with unsupervised approaches improves prediction accuracy for many phenotypes while simultaneously reducing variance due to unwanted sources of variation. As new and larger metagenomic datasets become increasingly available, background noise correction will become essential for generating reproducible microbiome analyses.


title: Predicting TCR-epitope Binding Specificity Using Deep Metric Learning and Multimodal Learning

abstract: Understanding the recognition of specific epitopes by cytotoxic T cells is a central problem in immunology. Although predicting binding between peptides and the class I Major Histocompatibility Complex (MHC) has had success, predicting interactions between T cell receptors (TCRs) and MHC class I-peptide complexes (pMHC) remains elusive. This paper utilizes a convolutional neural network model employing deep metric learning and multimodal learning to perform two critical tasks in TCR-epitope binding prediction: identifying the TCRs that bind a given epitope from a TCR repertoire, and identifying the binding epitope of a given TCR from a list of candidate epitopes. Our model can perform both tasks simultaneously and reveals that inconsistent preprocessing of CDR3B sequences can confound binding prediction. Applying a neural network interpretation method identifies key amino acid sequence patterns and positions within the TCR important for binding specificity. Contrary to the common assumption, known crystal structures of TCR-pMHC complexes show that the predicted salient amino acid positions are not necessarily the closest to the epitopes, implying that physical proximity may not be a good proxy for importance in determining TCR-epitope specificity. Our work thus provides insight into the learned predictive features of TCR-epitope binding specificity and advances associated classification tasks.


title: Predicting activatory and inhibitory drug-target interactions based on mol2vec and genetically perturbed transcriptomes

abstract: A computational approach to identifying drug-target interactions (DTIs) is a credible strategy for accelerating drug development and understanding the mechanisms of action of small molecules. However, current methods are limited to providing simple DTIs without mode of action (MoA), or they show unsatisfactory performance for a limited range of compounds and targets. Here, we propose AI-DTI, a novel method that predicts activatory and inhibitory DTIs by combining the mol2vec and genetically perturbed transcriptomes. We trained the model on large-scale DTIs with MoA and found that our model outperformed a previous model that predicted activatory and inhibitory DTIs. To extend the applicability, we applied the inferential method for the target vector so that our method can learn and predict a wider range of targets. Our method achieved satisfactory performance in an independent dataset where the target was unseen in the training set and a high-throughput screening dataset where positive and negative samples were explicitly defined. Finally, our method successfully rediscovered approximately half of the DTIs for drugs used in the treatment of COVID-19. These results indicate that AI-DTI is a practically useful tool for guiding drug discovery processes and generating plausible hypotheses that can reveal unknown mechanisms of drug action.


title: The Aliment to Bodily Condition knowledgebase (ABCkb): A database connecting plants and human health

abstract:
ObjectiveOverconsumption of processed foods has led to an increase in chronic diet-related diseases such obesity and type 2 diabetes. Although diets high in fresh fruits and vegetables are linked with healthier outcomes, the specific mechanisms for these relationships are poorly understood. Experiments examining plant phytochemical production and breeding programs, or separately on the health effects of nutritional supplements have yielded results that are sparse, siloed, and difficult to integrate between the domains of human health and agriculture. To connect plant products to health outcomes through their molecular mechanism an integrated computational resource is necessary.

ResultsWe created the Aliment to Bodily Condition Knowledgebase (ABCkb) to connect plants to human health by creating a stepwise path from plant [->] plant product [->] human gene [->] pathways [->] indication. ABCkb integrates 11 curated sources as well as relationships mined from Medline abstracts by loading into a graph database which is deployed via a Docker container. This new resource, provided in a queryable container with a user-friendly interface connects plant products with human health outcomes for generating nutritive hypotheses. All scripts used are available on github (https://github.com/atrautm1/ABCkb) along with basic directions for building the knowledgebase.


title: Membrane-MEDYAN: Simulating Deformable Vesicles Containing Complex Cytoskeletal Networks

abstract: The plasma membrane defines the shape of the cell and plays an indispensable role in bridging intra- and extra-cellular environments. Mechanochemical interactions between plasma membrane and cytoskeleton are vital for cell biomechanics and mechanosensing. A computational model that comprehensively captures the complex, cell-scale cytoskeleton-membrane dynamics is still lacking. In this work, we introduce a triangulated membrane model that accounts for membranes elastic properties, as well as for membrane-filament steric interactions. The corresponding force-field was incorporated into the active biological matter simulation platform, MEDYAN ("Mechanochemical Dynamics of Active Networks"). Simulations using the new model shed light on how actin filament bundling affects generation of tubular membrane protrusions. In particular, we used membrane-MEDYAN simulations to investigate protrusion initiation and dynamics while varying geometries of filament bundles, membrane rigidities and local G-Actin concentrations. We found that bundles protrusion propensities sensitively depend on the synergy between bundle thickness and inclination angle at which the bundle approaches the membrane. The new model paves the way for simulations of biological systems involving intricate membrane-cytoskeleton interactions, such as occurring at the leading edge and the cortex, eventually helping to uncover the fundamental principles underlying the active matter organization in the vicinity of the membrane.

category: biophysics


title: Loss of Endothelial HIF-Prolyl hydroxylase 2 (PHD2) Induces Cardiac Hypertrophy and Fibrosis

abstract:
BackgroundCardiac hypertrophy and fibrosis are common adaptive responses to injury and stress, eventually leading to heart failure. Hypoxia signaling is important to the (patho)physiological process of cardiac remodeling. However, the role of endothelial Prolyl-4 hydroxylase 2 (PHD2)/hypoxia inducible factors (HIFs) signaling in the pathogenesis of heart failure remains elusive.

Methods and ResultsMice with Tie2-Cre-mediated deletion of Egln1 (encoding PHD2) (Egln1Tie2Cre) exhibited left ventricular (LV) hypertrophy evident by increased thickness of anterior and posterior wall and LV mass, as well as cardiac fibrosis. Tamoxifen-induced endothelial Egln1 deletion in adult mice also induced LV hypertrophy and fibrosis. Additionally, we observed a marked decrease of PHD2 expression in heart tissues and cardiovascular endothelial cells from patients with cardiomyopathy. Moreover, genetic ablation of Hif2a but not Hif1a in Egln1Tie2Cre mice normalized cardiac size and function. RNA sequencing analysis also demonstrated HIF-2 as a critical mediator of signaling related to cardiac hypertrophy and fibrosis. Pharmacological inhibition of HIF-2 attenuated cardiac hypertrophy and fibrosis in Egln1Tie2Cre mice.

ConclusionsThe present studies define for the first time an unexpected role of endothelial PHD2 deficiency in inducing cardiac hypertrophy and fibrosis in a HIF-2 dependent manner. PHD2 was markedly decreased in cardiovascular endothelial cells in patients with cardiomyopathy. Thus, targeting PHD2/HIF-2 signaling may represent a novel therapeutic approach for the treatment of pathological cardiac hypertrophy and failure.

category: physiology


title: EffectorO: motif-independent prediction of effectors in oomycete genomes using machine learning and lineage specificity

abstract: Oomycete plant pathogens cause a wide variety of diseases, including late blight of potato, sudden oak death, and downy mildew of many plants. These pathogens are major contributors to losses in many food crops. Oomycetes secrete "effector" proteins to manipulate their hosts to the advantage of the pathogen. Plants have evolved to recognize effectors, resulting in an evolutionary cycle of defense and counter-defense in plant-microbe interactions. This selective pressure results in highly diverse effector sequences that can be difficult to computationally identify using sequence similarity. We developed a pipeline, EffectorO, that uses two complementary approaches to predict effectors in oomycete pathogen genomes: (1) a machine learning-based pipeline that predicts effector probability based on the biochemical properties of the N-terminal amino acid sequence of a protein and is trained on experimentally verified oomycete effectors and (2) a pipeline based on lineage-specificity to find proteins that are unique to one species or genus, a sign of evolutionary divergence due to adaptation to the host. We tested EffectorO on Bremia lactucae, which causes lettuce downy mildew, and Phytophthora infestans, which causes late blight of potato and tomato, and predicted many novel effector candidates, while still recovering the majority of known effector candidates. EffectorO will be useful for discovering novel families of oomycete effectors without relying on sequence similarity to known effectors.


title: JASMONIC ACID PRIMING OF POTATO USES HYPERSENSITIVE RESPONSE-DEPENDENT DEFENSE AND DELAYS NECROTROPHIC PHASE CHANGE AGAINST PHYTOPHTHORA INFESTANS

abstract: One of the most important diseases affecting potato is late blight, caused by the oomycete Phtytophthora infestans. The use of jasmonic acid has been reported to reduce the progression of the disease in potato, but the defense mechanisms involved in this response are unknown. In this study we described the effect of jasmonic acid as a priming agent over time in the defense response of potato against the invasion of P. infestans. We observed that the initial stimulus generated by the exogenous application of jasmonic acid had an effect on the stomatal conductance of the treated tissue and activated StMYC2 expression. Results reveal a priming effect in plants inoculated 11 days after treatment with jasmonic acid, evidenced by an increased transcriptional induction of defense-associated genes, decrease in the number of necrotic lesions and an evident reduction of lesion area (72.23%). Furthermore, in this study, we show that the tested concentration of jasmonic acid does not have an adverse effect at the physiological level in plants, since variation in stomatal conductance was transient, no change in chlorophyll a fluorescence and no early senescence in leaves was observed.


title: Inferring causality in biological oscillators

abstract: A fundamental goal of biological study is to identify regulatory interactions among components. The recent surge in time-series data collection in biology provides a unique opportunity to infer regulatory networks computationally. However, when the components oscillate, model-free inference methods, while easily implemented, struggle to distinguish periodic synchrony and causality. Alternatively, model-based methods test whether time series are reproducible with a specific model but require inefficient simulations and have limited applicability. Here, we develop an inference method based on a general model of molecular, neuronal, and ecological oscillatory systems that merges the advantages of both model-based and model-free methods, namely accuracy, broad applicability, and usability. Our method successfully infers the positive and negative regulations of various oscillatory networks, including the repressilator and a network of cofactors of pS2 promoter, outperforming popular inference methods. We also provide a computational package, ION (Inferring Oscillatory Networks), that users can easily apply to noisy, oscillatory time series to decipher the mechanisms by which diverse systems generate oscillations.

category: systems biology


title: Optimal Transport improves cell-cell similarity inference in single-cell omics data

abstract:
The recent advent of high-throughput single-cell molecular profiling is revolutionizing biology and medicine by unveiling the diversity of cell types and states contributing to development and disease. The identification and characterization of cellular heterogeneity is typically achieved through unsupervised clustering, which crucially relies on a similarity metric.

We here propose the use of Optimal Transport (OT) as a cell-cell similarity metric for single-cell omics data. OT defines distances to compare, in a geometrically faithful way, high-dimensional data represented as probability distributions. It is thus expected to better capture complex relationships between features and produce a performance improvement over state-of-the-art metrics. To speed up computations and cope with the high-dimensionality of single-cell data, we consider the entropic regularization of the classical OT distance. We then extensively benchmark OT against state-of-the-art metrics over thirteen independent datasets, including simulated, scRNA-seq, scATAC-seq and single-cell DNA methylation data. First, we test the ability of the metrics to detect the similarity between cells belonging to the same groups (e.g. cell types, cell lines of origin). Then, we apply unsupervised clustering and test the quality of the resulting clusters.

In our in-depth evaluation, OT is found to improve cell-cell similarity inference and cell clustering in all simulated and real scRNA-seq data, while its performances are comparable with Pearson correlation in scATAC-seq and single-cell DNA methylation data. All our analyses are reproducible through the OT-scOmics Jupyter notebook available at https://github.com/ComputationalSystemsBiology/OT-scOmics.


title: Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations

abstract:
Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, the models simulating individual cells behavior are needed. Here, we provided a link between the average data value recorded for radiologic image voxels and the cellular and vascular architecture of the tissue that fills these voxels. Using hybrid agent-based modeling, we generated a set of tissue morphologies capable of reproducing tissue oxygenation levels observed in radiologic images. We applied this approach to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies showed that intravascular changes in oxygen supply can reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, large magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in biologically feasible manner. Additionally, we developed a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications this approach can be used to generate a set of tissues representative for radiology images and to simulate tumor response to various anti-cancer treatments on the tissue-scale level.

Authors SummaryLow levels of oxygen, called hypoxia, are observable in many solid tumors. They are associated with more aggressive malignant cells which are resistant to chemo-, radio- and immunotherapies. Recently developed imaging techniques provide a way to measure the magnitude of frequent short-term oxygen fluctuation, however they operate on a macro-scale voxel level. To examine the causes of rapid oxygen fluctuations on the cell level, we developed a hybrid agent-based mathematical model. We tested two different mechanisms that could be responsible for these cyclic effects in tissue oxygenation: variations in vascular influx of oxygen and modulations in cellular oxygen absorption. Additionally, we developed a procedure to identify plausible tissue morphologies from data collected from radiological images. This will also provide a bridge between the micro-scale simulations with individual cells and the longitudinal medical images containing average voxel values. In the future applications, this approach can be used to generate a set of tissues representative of radiology images and to simulate tumor response to various anticancer treatments on the cell-scale level.


title: Vision-to-value transformations in artificial network and human brains

abstract: Humans and now computers can derive subjective valuations from sensory events although such transformation process is essentially unknown. In this study, we elucidated unknown neural mechanisms by comparing convolutional neural networks (CNNs) to their corresponding representations in humans. Specifically, we optimized CNNs to predict aesthetic valuations of paintings and examined the relationship between the CNN representations and brain activity via multivoxel pattern analysis. Primary visual cortex and higher association cortex activities were similar to computations in shallow CNN layers and deeper layers, respectively. The vision-to-value transformation is hence proved to be a hierarchical process which is consistent with the principal gradient that connects unimodal to transmodal brain regions (i.e. default mode network). The activity of the frontal and parietal cortices was approximated by goal-driven CNN. Consequently, representations of the hidden layers of CNNs can be understood and visualized by their correspondence with brain activity-facilitating parallels between artificial intelligence and neuroscience.

category: neuroscience


title: Vision-to-value transformations in artificial neural networks and human brain


title: A digitization theory of the Weber-Fechner law

abstract: Ever since the publication of Shannons article about information theory, there have been many attempts to apply information theory to the neuroscience field. Meanwhile, the Weber-Fechner law of psychophysics states that the magnitude of a subjective sensation of a person increases in proportion to the logarithm of the intensity of the external physical-stimulus. It is hardly surprising that we assign the amount of information to the response in the Weber-Fechner law. But to date no one has succeeded in applying information theory directly to that law: the direct links between information theory and that response in the Weber-Fechner law have not yet been found. The proposed theory unveils a link between information theory and that response, and differs subtly from the field such as neural coding that involves complicated calculations and models. Because my theory targets the Weber-Fechner law which is a macroscopic phenomenon, this theory does not involve complicated calculations. My theory is expected to mark a new era in the fields of sensory perception research. My theory must be studied in parallel with the fields of microscopic scale such as neural coding. This article ultimately aims to provide the fundamental concepts and their applications so that a new field of research on stimuli and responses can be created.


title: Auditory mismatch responses are differentially sensitive to changes in muscarinic acetylcholine versus dopamine receptor function

abstract:
The auditory mismatch negativity (MMN) has been proposed as a biomarker of NMDA receptor (NMDAR) dysfunction in schizophrenia. Pathophysiological theories suggest that such dysfunction might be partially caused by aberrant interactions of different modulatory neurotransmitters with NMDARs, which could explain heterogeneity among patients with schizophrenia and their treatment response. Understanding the differential impact of different neuromodulators on readouts of NMDAR function is therefore of high clinical relevance.

Here, we report results from two studies (N=81 each) which systematically tested whether the MMN is sensitive to diminishing and enhancing cholinergic vs. dopaminergic function. Both studies used a double-blind, placebo-controlled between-subject design and monitored individual drug plasma levels. Using a novel variant of the auditory oddball paradigm, we contrasted phases with stable versus volatile probabilities of tone switches. In the first study, we found that the muscarinic acetylcholine receptor antagonist biperiden reduced and/or delayed mismatch responses, particularly during stable phases of the experiment, whereas this effect was absent for amisulpride, a dopamine D2/D3 receptor antagonist. The direct comparison between biperiden and amisulpride indicated a significant drug x mismatch interaction. In the second study, neither elevating acetylcholine nor dopamine levels via administration of galantamine and levodopa, respectively, exerted significant effects on MMN.

Overall, our results indicate differential sensitivity of the MMN to changes in cholinergic (muscarinic) versus dopaminergic receptor function. This finding may prove useful for developments of future tools for predicting individual treatment responses in disorders that show abnormal MMN, such as schizophrenia.


title: A Weighted Network Analysis Framework for the Hourglass Effect - and its Application in the C. Elegans Connectome

abstract: Understanding hierarchy and modularity in natural as well as technological networks is of utmost importance. A major aspect of such analysis involves identifying the nodes that are crucial to the overall processing structure of the network. More recently, the approach of hourglass analysis has been developed for the purpose of quantitatively analyzing whether only a few intermediate nodes mediate the information processing between a large number of inputs and outputs of a network. We develop a new framework for hourglass analysis that takes network weights into account while identifying the core nodes and the extent of hourglass effect in a given weighted network. We use this framework to study the structural connectome of the C. elegans and identify intermediate neurons that form the core of sensori-motor pathways in the organism. Our results show that the neurons forming the core of the connectome show significant differences across the male and hermaphrodite sexes, with most core nodes in the male concentrated in sex-organs while they are located in the head for the hermaphrodite. Our work demonstrates that taking weights into account for network analysis framework leads to emergence of different network patterns in terms of identification of core nodes and hourglass structure in the network, which otherwise would be missed by unweighted approaches.


title: Impact of anaesthesia on static and dynamic functional connectivity in mice

abstract:
A few studies have compared the static functional connectivity between awake and anaesthetized states in rodents by resting-state fMRI. However, impact of anaesthesia on static and dynamic fluctuations in functional connectivity has not been fully understood. Here, we developed a resting-state fMRI protocol to perform awake and anaesthetized functional MRI in the same mice. Static functional connectivity showed a widespread decrease under anaesthesia, such as when under isoflurane or a mixture of isoflurane and medetomidine. Several interhemispheric connections were key connections for anaesthetized condition from awake. Dynamic functional connectivity demonstrates the shift from frequent broad connections across the cortex, the hypothalamus, and the auditory-visual cortex to frequent local connections within the cortex only. Fractional amplitude of low frequency fluctuation in the thalamic nuclei decreased under both anaesthesia. These results indicate that typical anaesthetics for functional MRI alters the spatiotemporal profile of the dynamic brain network in subcortical regions, including the thalamic nuclei and limbic system.

HighlightsO_LIResting-state fMRI was compared between awake and anaesthetized in the same mice.
C_LIO_LIAnaesthesia induced a widespread decrease of static functional connectivity.
C_LIO_LIAnaesthesia strengthened local connections within the cortex.
C_LIO_LIfALFF in the thalamus was decreased by anaesthesia.
C_LI


title: Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0 identifies proteins enriched within inflammatory lesions in tissue sections and human clinical biopsies.

abstract: Tissue microenvironment properties like blood flow, extracellular matrix or proximity to immune infiltrate are important regulators of cell biology. However, methods to study regional protein expression in context of the native tissue environment are limited. To address this need we have developed a novel approach to visualize, purify and measure proteins in situ using Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0. We previously implemented AutoSTOMP to identify proteins localized to the vacuoles of obligate intracellular microbes at the 1-2 m scale within infected host cells1. Here we report custom codes in SikuliX to specify regions of heterogeneity in a tissue section and then biotin tag and identify proteins belonging to specific cell types or structures within those regions. To enrich biotinylated targets from fixed tissue samples we developed a biochemical protocol compatible with LC-MS. These tools were applied to a) identify inflammatory proteins expressed by CD68+ macrophages in rat cardiac infarcts and b) characterize inflammatory proteins enriched in IgG4+ lesions in esophageal tissue. These data indicate that AutoSTOMP is a flexible approach to determine regional protein expression in situ on a range of primary tissues and clinical biopsies where current tools are limited.

category: immunology


title: γδ-Thymocyte Maturation and Emigration

abstract: The thymus is the site of both {beta} and {gamma}{delta}-T cell development. After several unique waves of {gamma}{delta}-T cells are generated in, and exported from, the fetal/neonatal thymus, the adult thymus continues to produce a stream of {gamma}{delta}-T cells throughout life. One intriguing feature of {gamma}{delta} T cell development is the coordination of differentiation and acquisition of effector function within the fetal thymus, however, it is less clear whether this paradigm holds true in adult animals. To investigate the relationship between maturation and time since V(D)J recombination in adult-derived {gamma}{delta}-thymocytes, we used the Rag2pGFP model. Immature (CD24+) {gamma}{delta}-thymocytes expressed high levels of GFP while only a small minority of mature (CD24-) {gamma}{delta}-thymocytes were GFP+. Similarly, most GFP+ {gamma}{delta}-splenocytes were immature, while some were mature. Analysis of {gamma}{delta}-recent thymic emigrants (RTEs) indicated that most {gamma}{delta}-T cell RTEs were CD24+ and GFP+ and adoptive transfer experiments showed that immature {gamma}{delta}-thymocytes could be maintained in the periphery for at least 3 days over which time they matured. With respect to the mature {gamma}{delta}-thymocytes that were GFP-, parabiosis experiments demonstrated that mature {gamma}{delta}-T cells did not recirculate from the periphery. Instead, a population of mature {gamma}{delta}-thymocytes remained resident in the thymus for at least 60 days while mature {gamma}{delta}-thymocytes derived solely from adult hematopoiesis were mostly lost from the thymus within 60 days. Collectively, these data demonstrate two streams of actively developing {gamma}{delta}-T cells in adult mice: an immature subset that quickly leaves the thymus and matures in the periphery, and one that completes maturation within the thymus over a longer period of time. Furthermore, there is a fetal-derived and heterogeneous population of resident {gamma}{delta}-thymocytes of unknown functional importance.


title: Internal microbial zonation assists in the massive growth of marimo, a lake ball of Aegagropila linnaei in Lake Akan

abstract: Marimo (lake ball) is an uncommon ball-like aggregation of the green alga, Aegagropila linnaei. Although A. linnaei is broadly distributed in fresh and brackish waters in the northern hemisphere, marimo colonies are found only in particular habitats. The colonies have been gradually shrinking in recent years. Nevertheless, it is not clear how and why A. linnaei forms such massive spherical aggregations. Here, we report the bacterial microbiomes inside various sizes and aggregating structures of natural marimo collected from Lake Akan, Japan. We observed multi-layers composed of sediment particles only in the sizeable radial-type marimo with a >20 cm diameter, not in the tangled-type marimo. The deeper layers were enriched by Nitrospira, potential novel sulphur-oxidizing bacteria, and sulphate-reducing Desulfobacteraceae bacteria. The sulphur cycle-related bacteria are unique to Lake Akan due to sulphur deposits from the nearby volcanic mountains. Some of them were also recovered from lake sediments. Microorganisms of the multi-layers would form biofilms incorporating nearby sediment, which would function as microbial "seals" within large radial-type marimo. We propose that the layer structure provides habitats for diverse bacterial communities, promotes airtightness of the marimo, and finally contributes to the massive growth of the aggregation. These findings provide a clue to deciphering the massive growth of endangered marimo aggregates.


title: More pests but less treatments: ambivalent effect of landscape complexity on Conservation Biological Control

abstract: In agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and auxiliary species, the underlying landscape structure, and their interaction may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that SNH boost predator population, but predator movement from hedges to fields is fundamental for an efficient pest regulation by auxiliaries and to decrease pesticide treatments. Moreover landscape elements may lead to different effects on pest reduction depending on the considered scale. Integration of species behaviors and traits with landscape structure at multiple scales are needed to provide useful insights for CBC.


title: Foxes facilitate other wildlife through ecosystem engineering activities on the Arctic tundra

abstract: Top predators largely affect ecosystems through trophic interactions, but they also can have indirect effects by altering nutrient dynamics and acting as ecosystem engineers. Arctic foxes (Vulpes lagopus) are ecosystem engineers that concentrate nutrients around their dens, creating biogeochemical hotspots with lush vegetation on the nutrient-limited tundra. Red foxes (V. vulpes) similarly engineer subarctic environments through their denning behavior, and have recently expanded onto the tundra where they now often occupy historically Arctic fox dens. We evaluated the impact of Arctic and red fox denning behavior on other tundra wildlife by comparing predator and herbivore visits to dens and adjacent control areas using camera traps in northeastern Manitoba, where both fox species are sympatric. Both the capture rates and species richness of wildlife were significantly greater at fox dens relative to control sites. Predators were detected almost exclusively on dens occupied by foxes, suggesting carcass or fox presence attracts predators to den sites. This is supported by observations of predators investigating and scavenging prey remains (carrion, feathers) from the dens. Caribou (Rangifer tarandus) visited dens more often than control areas, and we hypothesize they are attracted to the enhanced vegetation typically found on dens. Our results suggest Arctic fox ecosystem engineering has a prolonged, indirect effect on caribou by enriching vegetation at dens, whereas both Arctic and red foxes directly facilitate predators by provisioning resources. Understanding how predators affect other organisms via non-trophic interactions provides an enriched view of their functional roles within ecosystems.


title: Evolutionary conserved protein motifs drive attachment of the plant nucleoskeleton at nuclear pores

abstract: The nucleoskeleton forms a filamentous meshwork under the nuclear envelope and contributes to the regulation of nuclear morphology and gene expression. To understand how the Arabidopsis nucleoskeleton physically connects to the nuclear periphery, we investigated the nucleoskeleton protein KAKU4 and sought for functional regions responsible for its localization at the nuclear periphery. Computational predictions identified three evolutionary conserved peptide motifs within the N-terminal region of KAKU4. Functional analysis revealed that these motifs are required for homomerization of KAKU4, interaction with the nucleoskeleton proteins CROWDED NUCLEI (CRWN) and localization at the nuclear periphery. We find that similar protein motifs are present in NUP82 and NUP136, two plant specific nucleoporins from the Nuclear Pore Complex (NPC) basket. These conserved motifs allow the two nucleoporins to bind CRWN proteins, thus revealing a physical link between the nucleoskeleton and nuclear pores in plants. Finally, whilst NUP82, NUP136 and KAKU4 have a common evolutionary history predating non-vascular land plants, KAKU4 mainly localizes outside the NPC suggesting neofunctionalization of an ancient nucleoporin into a new nucleoskeleton component.


title: Analysis of correlation and trail coefficients for componentperformance s in nine experimental tomato lines

abstract: The objective of the research was to analyze the main variables related to tomato yield, and guide the selection of materials for the INIAF vegetable improvement program. The experiment was carried out in the open field using nine tomato lines on the grounds of the National Vegetable Seed Production Center, during the 2017-2018 agricultural campaign. A randomized complete block experimental design was used, with three repetitions and 10 plants per experimental unit. For the analysis of the data, the variable yield was considered as dependent and the variables number of flowers per inflorescence, number of clusters per plant, number of fruits per plant, weight of fruit, equatorial and polar diameter as independent variables. Analysis of variance, phenotypic correlations and path coefficients were performed. The performance of the L015 line was 80. 79 t ha-1 higher than the L014, L019 and Rio Grande lines. The fruit yield had a significant correlation with the weight of fruit per plant followed by the polar diameter, equatorial diameter, number of fruits per plant and weight of fruit. The analysis of path coefficients showed that the number of fruits per plant had the highest direct positive effect on the fruit yield, fruit weight and equatorial diameter that have a significant correlation and a direct effect on the fruit yield, emerged as the components with coefficients of 0.96 and 0.52 respectively. These characters may be relevant within the selection criteria in the development of new varieties. number of fruits per plant and weight of fruit. The analysis of path coefficients showed that the number of fruits per plant had the highest direct positive effect on the fruit yield, fruit weight and equatorial diameter that have a significant correlation and a direct effect on the fruit yield, emerged as the components with coefficients of 0.96 and 0.52 respectively. These characters may be relevant within the selection criteria in the development of new varieties. number of fruits per plant and weight of fruit. The analysis of path coefficients showed that the number of fruits per plant had the highest direct positive effect on the fruit yield, fruit weight and equatorial diameter that have a significant correlation and a direct effect on the fruit yield, emerged as the components with coefficients of 0.96 and 0.52 respectively. These characters may be relevant within the selection criteria in the development of new varieties.


title: ChromWave: Deciphering the DNA-encoded competition between transcription factors and nucleosomes with deep neural networks

abstract: Transcription factors (TFs) regulate gene expression by recognising and binding specific DNA sequences. At times, these regulatory elements may be occluded by nucleosomes, making them inaccessible for TF-binding. The competition for DNA occupancy between TFs and nucleosomes, and associated gene regulatory outputs, are important consequences of the cis-regulatory information encoded in the genome. However, these sequence patterns are subtle and remain difficult to interpret. Here, we introduce ChromWave, a deep-learning model that, for the first time, predicts the competing profiles for TF and nucleosomes occupancies with remarkable accuracy. Models trained using short- and long-fragment MNase-Seq data successfully learn the sequence preferences underlying TF and nucleosome occupancies across the entire yeast genome. They recapitulate nucleosome evictions from regions containing "strong" TF binding sites and knock-out simulations show nucleosomes gaining occupancy in the absence of these TFs, accompanied by lateral rearrangement of adjacent nucleosomes. At a local level, models anticipate with high accuracy the outcomes of detailed experimental analysis of partially unwrapped nucleosomes at the GAL4 UAS locus. Finally, we trained a ChromWave model that successfully predicts nucleosome positions at promoters in the human genome. We find that human promoters generally contain few sites at which simple sequence changes can alter nucleosome occupancies and that these positions align well with causal variants linked to DNase hypersensitivity. ChromWave is readily combined with diverse genomic datasets and can be trained to predict any output that is linked to the underlying genomic sequence.

category: genomics


title: SC1: A Tool for Interactive Web-Based Single Cell RNA-Seq Data Analysis

abstract: Single cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. Here, we present SC1 a web-based highly interactive scRNA-Seq data analysis tool publicly accessible at https://sc1.engr.uconn.edu. The tool presents an integrated workflow for scRNA-Seq analysis, implements a novel method of selecting informative genes based on Term-Frequency Inverse-Document-Frequency (TF-IDF) scores, and provides a broad range of methods for clustering, differential expression analysis, gene enrichment, interactive visualization, and cell cycle analysis. The tool integrates other single cell omics data modalities like TCR-Seq and supports several single cell sequencing technologies. In just a few steps, researchers can generate a comprehensive analysis and gain powerful insights from their scRNA-Seq data.


title: Seqpac: A New Framework for small RNA analysis in R using Sequence-Based Counts

abstract: Small RNA sequencing (sRNA-seq) has become important for studying regulatory mechanisms in many cellular processes. Data analysis remains challenging, mainly because each class of sRNA--such as miRNA, piRNA, tRNA- and rRNA-derived fragments (tRFs/rRFs)--needs special considerations. Analysis therefore involves complex workflows across multiple programming languages, which can produce research bottlenecks and transparency issues. To make analysis of sRNA more accessible and transparent we present seqpac: a tool for advanced group-based analysis of sRNA completely integrated in R. This opens advanced sRNA analysis for Windows users--from adaptor trimming to visualization. Seqpac provides a framework of functions for analyzing a PAC object, which contains 3 standardized tables: sample phenotypic information (P), sequence annotations (A), and a counts table with unique sequences across the experiment (C). By applying a sequence-based counting strategy that maintains the integrity of the fastq sequence, seqpac increases flexibility and transparency compared to other workflows. It also contains an innovative targeting system allowing sequence counts to be summarized and visualized across sample groups and sequence classifications. Reanalyzing published data, we show that seqpacs fastq trimming performs equal to standard software outside R and demonstrate how sequence-based counting detects previously unreported bias. Applying seqpac to new experimental data, we discovered a novel rRF that was down-regulated by RNA pol I inhibition (anticancer treatment), and up-regulated in previously published data from tumor positive patients. Seqpac is available on github (https://github.com/Danis102/seqpac), runs on multiple platforms (Windows/Linux/Mac), and is provided with a step-by-step vignette on how to analyze sRNA-seq data.


title: A bispecific monomeric nanobody induces SARS-COV-2 spike trimer dimers

abstract: Antibodies binding to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike have therapeutic promise, but emerging variants show the potential for virus escape. This emphasizes the need for therapeutic molecules with distinct and novel neutralization mechanisms. Here we isolated a nanobody that interacts simultaneously with two RBDs from different spike trimers of SARS-CoV-2, rapidly inducing the formation of spike trimer-dimers leading to the loss of their ability to attach to the host cell receptor, ACE2. We show that this nanobody potently neutralizes SARS-CoV-2, including the B.1.351 variant, and cross-neutralizes SARS-CoV. Furthermore, we demonstrate the therapeutic potential of the nanobody against SARS-CoV-2 and the B.1.351 variant in a human ACE2 transgenic mouse model. This naturally elicited bispecific monomeric nanobody establishes a novel strategy for potent inactivation of viral antigens and represents a promising antiviral against emerging SARS-CoV-2 variants.


title: A bispecific monomeric nanobody induces spike trimer dimers and neutralizes SARS-CoV-2 in vivo


title: Interferon Resistance of Emerging SARS-CoV-2 Variants

abstract:
The emergence of SARS-CoV-2 variants with enhanced transmissibility, pathogenesis and resistance to vaccines presents urgent challenges for curbing the COVID-19 pandemic. While Spike mutations that enhance virus infectivity or neutralizing antibody evasion may drive the emergence of these novel variants, studies documenting a critical role for interferon responses in the early control of SARS-CoV-2 infection, combined with the presence of viral genes that limit these responses, suggest that interferons may also influence SARS-CoV-2 evolution. Here, we compared the potency of 17 different human interferons against multiple viral lineages sampled during the course of the global outbreak, including ancestral and four major variants of concern. Our data reveal increased interferon resistance in emerging SARS-CoV-2 variants, suggesting that evasion of innate immunity may be a significant, ongoing driving force for SARS-CoV-2 evolution. These findings have implications for the increased lethality of emerging variants and highlight the interferon subtypes that may be most successful in the treatment of early infections.

Author SummaryIn less than 2 years since its spillover into humans, SARS-CoV-2 has infected over 220 million people, causing over 4.5 million COVID-19 deaths. High infection rates provided substantial opportunities for the virus to evolve, as variants with enhanced transmissibility, pathogenesis, and resistance to vaccine-elicited neutralizing antibodies have emerged. While much focus has centered on the Spike protein which the virus uses to infect target cells, mutations were also found in other viral proteins that might inhibit innate immune responses. Specifically, viruses encounter a potent innate immune response mediated by the interferons, two of which, IFN2 and IFN{beta}, are being repurposed for COVID-19 treatment. Here, we compared the potency of human interferons against ancestral and emerging variants of SARS-CoV-2. Our data revealed increased interferon resistance in emerging SARS-CoV-2 strains that included the alpha, beta, gamma and delta variants of concern, suggesting a significant, but underappreciated role for innate immunity in driving the next phase of the COVID-19 pandemic.


title: Circadian regulation of SARS-CoV-2 infection in lung epithelial cells

abstract: The COVID-19 pandemic, caused by SARS-CoV-2 coronavirus, is a global health issue with unprecedented challenges for public health. SARS-CoV-2 primarily infects cells of the respiratory tract, via Spike glycoprotein binding angiotensin-converting enzyme (ACE2). Circadian rhythms coordinate an organisms response to its environment and can regulate host susceptibility to virus infection. We demonstrate a circadian regulation of ACE2 in lung epithelial cells and show that silencing BMAL1 or treatment with a synthetic REV-ERB agonist SR9009 reduces ACE2 expression and inhibits SARS-CoV-2 entry. Treating infected cells with SR9009 limits viral replication and secretion of infectious particles, showing that post-entry steps in the viral life cycle are influenced by the circadian system. Transcriptome analysis revealed that Bmal1 silencing induced a wide spectrum of interferon stimulated genes in Calu-3 lung epithelial cells, providing a mechanism for the circadian pathway to dampen SARS-CoV-2 infection. Our study suggests new approaches to understand and improve therapeutic targeting of SARS-CoV-2.


title: The circadian clock component BMAL1 regulates SARS-CoV-2 entry and replication in lung epithelial cells


title: Critical interactions for SARS-CoV-2 spike protein binding to ACE2 identified by machine learning

abstract: Both SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor. Based on high-resolution structures, the two viruses bind in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Here we have used molecular dynamics (MD) simulations, machine learning (ML), and free energy perturbation (FEP) calculations to elucidate the differences in RBD binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.


title: Structural and energetic profiling of SARS-CoV-2 antibody recognition and the impact of circulating variants

abstract: The SARS-CoV-2 pandemic highlights the need for a detailed molecular understanding of protective antibody responses. This is underscored by the emergence and spread of SARS-CoV-2 variants, including B.1.1.7, P1, and B.1.351, some of which appear to be less effectively targeted by current monoclonal antibodies and vaccines. Here we report a high resolution and comprehensive map of antibody recognition of the SARS-CoV-2 spike receptor binding domain (RBD), which is the target of most neutralizing antibodies, using computational structural analysis. With a dataset of nonredundant experimentally determined antibody-RBD structures, we classified antibodies by RBD residue binding determinants using unsupervised clustering. We also identified the energetic and conservation features of epitope residues and assessed the capacity of viral variant mutations to disrupt antibody recognition, revealing sets of antibodies predicted to effectively target recently described viral variants. This detailed structure-based reference of antibody RBD recognition signatures can inform therapeutic and vaccine design strategies.


title: A New Old Tale: Dopamine Transporter implications in an animal model of Attention-Deficit Hyperactivity Disorder

abstract: Attention deficit/Hyperactivity disorder (ADHD) is one of the most diagnosed psychiatric disorders nowadays. The core symptoms of the condition include hyperactivity, impulsiveness and inattention. The main pharmacological treatment consists of psychostimulant drugs affecting Dopamine Transporter (DAT) function. We have previously shown that genetically modified mice lacking p35 protein (p35KO), which have reduced Cdk5 activity, present key hallmarks resembling those described in animal models useful for studying ADHD. The p35KO mouse displays spontaneous hyperactivity and shows a calming effect of methylphenidate or amphetamine treatment. Interestingly, dopaminergic neurotransmission is altered in these mice as they have an increased Dopamine (DA) content together with a low DA turnover. This led us to hypothesize that the lack of Cdk5 activity affects DAT expression and/or function in this animal model. In this study, we performed biochemical assays, cell-based approaches, quantitative fluorescence analysis and functional studies that allowed us to demonstrate that p35KO mice exhibit decreased DA uptake and reduced cell surface DAT expression levels in the striatum (STR). These findings are supported by in vitro observations in which the inhibition of Cdk5 activity in N2a cells induced a significant increase in constitutive DAT endocytosis with a concomitant increase in DAT localization to recycling endosomes. Taken together, these data provide evidences regarding the role of Cdk5/p35 in DAT expression and function, thus contributing to the knowledge of DA neurotransmission physiology and also providing therapeutic options for the treatment of DA pathologies such as ADHD.


title: Lack of Cdk5 activity is involved on Dopamine Transporter expression and function: Evidences from an animal model of Attention-Deficit Hyperactivity Disorder


title: Non-REM sleep in major depressive disorder

abstract:
Disturbed sleep is a key symptom in major depressive disorder (MDD). REM sleep alterations are well described in the current fliterature, but little is known about non-REM sleep alterations. Additionally, sleep disturbances relate to a variety of cognitive symptoms in MDD, but which features of non-REM sleep EEG contribute to this, remains unknown. We comprehensively analyzed non-REM sleep EEG features in three independently collected datasets (N=284). These included MDD patients with a broad age range, varying duration and severity of depression, unmedicated or medicated, age- and gender-matched to healthy controls. We explored changes in sleep architecture including sleep stages and cycles, spectral power, sleep spindles, slow waves (SW), and SW-spindle coupling. Next, we analyzed the association of these sleep features with acute measures of depression severity and overnight consolidation of procedural memory. Overall, no major systematic alterations in non-REM sleep architecture were found in patients compared to controls. For the microstructure of non-REM sleep, we observed a higher spindle amplitude in unmedicated patients compared to controls, and after the start of antidepressant medication longer SWs with lower amplitude and a more dispersed SW-spindle coupling. In addition, long-term, but not short-term medication seemed to lower spindle density. Overnight procedural memory consolidation was impaired in medicated patients and associated with lower sleep spindle density. Our results suggest that alterations in non-REM sleep EEG might be more subtle than previously reported. We discuss these findings in the context of antidepressant medication intake and age.

Statement of SignificanceDepression affects large and diverse populations worldwide, including their sleep. Most sleep is non-REM sleep, which is vital to cognitive function, including memory. How non-REM is affected during a depression or medical treatment remains poorly investigated. We classified non-REM sleep of depressive patients against healthy controls in unprecedented analysis detail and confidence using the largest dataset published so far while also test sleep alterations associations with impaired memory. Surprisingly, severe depression alone did not alter sleep. We observed severe non-REM sleep alterations only worsening under patient medication, which ultimately coincided with 24-hour memory impairments. Though causal influences of medication on sleep in depressive patients remains to be investigated, this cautions common clinical practice in long-term treatment with antidepressants.


title: UNC-45A is Highly Expressed in the Proliferative Cells of the Mouse Genital Tract and in the Microtubule-Rich Areas of the Mouse Nervous System

abstract: UNC-45A is a cytoskeletal-associated protein with a dual and non-mutually exclusive role as a regulator of the acto-myosin system and as a Microtubule (MT)-destabilizing protein. UNC-45A is overexpressed in human cancers including in ovarian cancer patients resistant to the MT-stabilizing drug Paclitaxel. Mapping of UNC-45A in the mouse upper genital tract and central nervous system reveals its enrichment in highly proliferating and prone to remodeling cells and in microtubule-rich areas of in the ovaries and in neurons respectively. In both apparatuses UNC-45A is also abundantly expressed in the ciliated epithelium. Because regulators of acto-myosin contractility and MT stability are essential for the physiopathology of the female reproductive tract and of neuronal development our findings suggest that UNC-45A may have a role in ovarian cancer initiation and development and in neurodegeneration.


title: Dram1 confers resistance to Salmonella infection

abstract: Dram1 is a stress and infection inducible autophagy modulator that functions downstream of transcription factors p53 and NF{kappa}B. Using a zebrafish embryo infection model, we have previously shown that Dram1 provides protection against the intracellular pathogen Mycobacterium marinum by promoting the p62-dependent xenophagy of bacteria that have escaped into the cytosol. However, the possible interplay between Dram1 and other anti-bacterial autophagic mechanisms remains unknown. Recently, LC3-associated phagocytosis (LAP) has emerged as an important host defense mechanism that requires components of the autophagy machinery and targets bacteria directly in phagosomes. Our previous work established LAP as the main autophagic mechanism by which macrophages restrict growth of Salmonella Typhimurium in a systemically infected zebrafish host. We therefore employed this infection model to investigate the possible role of Dram1 in LAP. Morpholino knockdown or CRISPR/Cas9-mediated mutation of Dram1 led to reduced host survival and increased bacterial burden during S. Typhimurium infections. In contrast, overexpression of dram1 by mRNA injection curtailed Salmonella replication and reduced mortality of the infected host. During the early response to infection, GFP-Lc3 levels in transgenic zebrafish larvae correlated with the dram1 expression level, showing over two-fold reduction of GFP-Lc3-Salmonella association in dram1 knockdown or mutant embryos and an approximately 30% increase by dram1 overexpression. Since LAP is known to require the activity of the phagosomal NADPH oxidase, we used a Salmonella biosensor strain to detect bacterial exposure to reactive oxygen species (ROS) and found that the ROS response was largely abolished in the absence of dram1. Together, these results demonstrate the host protective role of Dram1 during S. Typhimurium infection and suggest a functional link between Dram1 and the induction of LAP.


title: Ion transport modulators differentially modulate inflammatory responses in THP-1 derived macrophages

abstract: Ion transport modulators are most commonly used to treat various non-communicable diseases including diabetes and hypertension. They are also known to bind to receptors on various immune cells, but the immunomodulatory properties of most ion transport modulators have not been fully elucidated. We assessed the effects of thirteen FDA approved ion transport modulators namely ambroxol HCl, amiloride HCl, diazoxide, digoxin, furosemide, hydrochlorothiazide, metformin, omeprazole, pantoprazole, phenytoin, verapamil, drug X and drug Y on superoxide production, nitric oxide production and cytokine expression by THP-1 derived macrophages that had been stimulated with ethanol-inactivated Mycobacterium bovis BCG. Ambroxol HCl, diazoxide, digoxin, furosemide, hydrochlorothiazide, metformin, pantoprazole, phenytoin, verapamil and drug Y had an inhibitory effect on nitric oxide production, while all the test drugs had an inhibitory effect on superoxide production. Amiloride HCl, diazoxide, digoxin, furosemide, phenytoin, verapamil, drug X and drug Y enhanced the expression of IL-1{beta} and TNF-. Unlike most immunomodulatory compounds currently in clinical use, most of the test drugs inhibited some inflammatory processes while promoting others. Ion pumps and ion channels could therefore serve as targets for more selective immunomodulatory agents which do not cause overt immunosupression.