Network Inference from Perturbation Time Course Data Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible.
Isotopically Nonstationary 13C Metabolic Flux Analysis in Resting and Activated Human Platelets Platelet metabolism is linked to platelet hyper- and hypoactivity in numerous human diseases. Developing a detailed understanding of the link between metabolic shifts and platelet activation state is integral to improving human health. Here, we show the first application of isotopically nonstationary 13C metabolic flux analysis to quantitatively measure carbon fluxes in both resting and thrombin activated platelets. Resting platelets primarily metabolize glucose to lactate via glycolysis, while acetate is oxidized to fuel the tricarboxylic acid cycle. Upon activation with thrombin, a potent platelet agonist, platelets increase their uptake of glucose 3-fold. This results in an absolute increase in flux throughout central metabolism, but when compared to resting platelets they redistribute carbon dramatically. Activated platelets decrease relative flux to the oxidative pentose phosphate pathway and TCA cycle from glucose and increase relative flux to lactate. These results provide the first report of reaction-level carbon fluxes in platelets and allow us to distinguish metabolic fluxes with much higher resolution than previous studies.
Fine-tuning the Spike: Role of the nature and topology of the glycan shield in the structure and dynamics of SARS-CoV-2 S The dense glycan shield is an essential feature of the SARS-CoV-2 spike (S) architecture, key to immune evasion and to the activation of the prefusion conformation. Recent studies indicate that the occupancy and structures of the SARS-CoV-2 S glycans depend not only on the nature of the host cell, but also on the structural stability of the trimer; a point that raises important questions about the relative competence of different glycoforms. Moreover, the functional role of the glycan shield in the SARS-CoV-2 pathogenesis suggests that the evolution of the sites of glycosylation is potentially intertwined with the evolution of the protein sequence to affect optimal activity. Our results from multi-microsecond molecular dynamics simulations indicate that the type of glycosylation at N234, N165 and N343 greatly affects the stability of the receptor binding domain (RBD) open conformation, and thus its exposure and accessibility. Furthermore, our results suggest that the loss of glycosylation at N370, a newly acquired modification in the SARS-CoV-2 S glycan shields topology, may have contributed to increase the SARS-CoV-2 infectivity as we find that N-glycosylation at N370 stabilizes the closed RBD conformation by binding a specific cleft on the RBD surface. We discuss how the absence of the N370 glycan in the SARS-CoV-2 S frees the RBD glycan binding cleft, which becomes available to bind cell-surface glycans, potentially increases host cell surface localization. A new method for the sampling and preservation of placental specimens in low-resource settings for the identification of P. falciparum and analysis of nucleic acids Collection, preservation, and shipment of histological specimens in low-resource settings is challenging. We present a novel method that achieved excellent preservation of placental specimens from rural Mali by using formalin fixation, ethanol dehydration, and long-term storage in a solar-powered freezer. Sample preservation success was 92%, permitting evaluation of current and past malaria infection, anemia, placental maturity, and inflammation. Using RNAscope(R) hybridization we were able to visualize cell-specific gene expression patterns in the formalin-fixed paraffin-embedded (FFPE) specimens. Additionally, our method entailed mirrored sampling from the two cut faces of a cotyledon, one for the FFPE workflows and the other for storage in RNAlater and RNA-seq. Non-invasive imaging of gene expression and protein secretion dynamics in living mice: identification of ectopic prothrombin expression as driver of thrombosis in cancer The topology of gene expression and protein localization is a crucial characteristic of life, where the spatiotemporal dynamic of secretory proteins instruct higher order organization, including the orchestration of developmental and adaptive programs. However tools to non-invasively interrogate the fate of secretory proteins in vivo are scarce. Here we introduce a genetic tagging strategy for in vivo imaging of the secretion and expression dynamics of secretory proteins in living animals. Applying this to a prototypical liver-derived secretory protein, we demonstrate that this approach, combined with optical in-vivo imaging, uncovers extrahepatic prothrombin expression in multiple novel anatomical sites (including testes, placenta, brain, kidney, heart and lymphatic system) and in emerging tumors, resulting in significant amounts of tumor-derived prothrombin in the blood with procoagulant properties. Syngeneic cell lines from this mouse model enable unravelling regulatory mechanisms in high resolution, and in a scalable format ex vivo. Beyond discovering new functions of proteins in a targeted manner, this model allows identifying rheostats in the cross-talk between gene expression and availability of a secretory protein. It is also a valuable resource for uncovering novel (tissue-specific) therapeutic vulnerabilities. Conformist social learning inoculates against adverse risk aversion Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majoritys behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This  collective behavioural rescue, emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences. A new hypothesis-testing model for phyllochron based on a stochastic process - application to analysis of genetic and environment effects in maize The times between appearance of successive leaves or phyllochron characterize the vegetative development of annual plants. Hypothesis testing models, which enables to compare phyllochron between genetic groups or conditions, are usually based on regression of thermal time on the number of leaves, most of the time assuming a constant leaf appearance rate. However these models are both statistically biased and inappropriate in terms of modelling. We propose a stochastic process model in which the emergence of new leaves is considered as successive time-to-events, which provides a flexible and more accurate modelling as well as unbiased testing procedures. The model was applied on an original maize dataset collected in fields for three years on plants originating from two divergent selection experiments for flowering time conducted in two maize inbred lines. We showed that the main differences in phyllochron were not observed between selection populations (Early or Late), but rather between ancestral lines, years of experimentation, and leaf ranks. Our results highlight a strong departure from the assumption of a constant leaf appearance rate in one year that could be related to climate variations, even if the impact of each climatic variables individually was not clearly elucidated. A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles Increasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Multiple groups have produced recommendations for functions that biomedical repositories should support, with many using requirements of the FAIR data principles as guidelines. However, FAIR is but one set of principles that has arisen out of the open science community. They are joined by principles governing open science, data citation and trustworthiness, all of which are important aspects for biomedical data repositories to support. Together, these define a framework for data repositories that we call OFCT: Open, FAIR, Citable and Trustworthy. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and piloted the instrument by evaluating eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). Repositories included both specialist repositories that focused on a particular data type or domain, in this case diabetes and metabolomics, and generalist repositories that accept all data types and domains. The goal of this work was both to obtain a sense of how much the design of current biomedical data repositories align with these principles and to augment the dkNET listing with additional information that may be important to investigators trying to choose a repository, e.g., does the repository fully support data citation? The evaluation was performed from March to November 2020 through inspection of documentation and interaction with the sites by the authors. Overall, although there was little explicit acknowledgement of any of the OFCT principles in our sample, the majority of repositories provided at least some support for their tenets. Microbial colonization of tannin-rich tropical plants: interplay between degradability, methane production and tannin disappearance in the rumen AO_SCPLOWBSTRACTC_SCPLOWCondensed tannins in plants are found free and attached to protein and fibre but it is not known whether these fractions influence rumen degradation and microbial colonization. This study explored the rumen degradation of tropical tannins-rich plants and the relationship between condensed tannins fractions disappearance and microbial communities colonising plant particles. Leaves from Calliandra calothyrsus, Gliricidia sepium, and Leucaena leucocephala, pods from Acacia nilotica and the leaves of two agricultural by-products: Manihot esculenta and Musa spp. were incubated in situ in the rumen of dairy cows. An in vitro approach was also used to assess the effects of these plants on rumen fermentation parameters. All plants contained more than 100 g/kg of condensed tannins with a large proportion (32 to 61%) bound to proteins. Calliandra calothyrsus had the highest concentration of condensed tannins at 361 g/kg, whereas Acacia nilotica was particularly rich in hydrolysable tannins (350 g/kg). Hydrolysable and free condensed tannins from all plants completely disappeared after 24 h incubation in the rumen. Disappearance of protein-bound condensed tannins was variable with values ranging from 93% for Gliricidia sepium to 21% for Acacia nilotica. In contrast, fibre-bound condensed tannins disappearance averaged ~82% and did not vary between plants. Disappearance of bound fractions of condensed tannins was not associated with degradability of plant fractions. The presence of tannins interfered with the microbial colonisation of plants. Each plant had distinct bacterial and archaeal communities after 3 and 12 h of incubation in the rumen and distinct protozoal communities at 3 h. Adherent communities in tannin-rich plants had a lower relative abundance of fibrolytic microbes, notably Fibrobacter spp. Whereas, archaea diversity was reduced in high tannin-containing Calliandra calothyrsus and Acacia nilotica at 12 h of incubation. Concurrently, in vitro methane production was lower for Calliandra calothyrsus, Acacia nilotica and Leucaena leucocephala although for the latter total volatile fatty acids production was not affected and was similar to control. Here we show that the total amount of hydrolysable and condensed tannins contained in a plant govern the interaction with rumen microbes affecting degradability and fermentation. The effect of protein- and fibre-bound condensed tannins on degradability is less important. A Human-Immune-System (HIS) humanized mouse model (DRAGA: HLA-A2. HLA-DR4. Rag1 KO.IL-2Rγc KO. NOD) for COVID-19 We report the first Human Immune System (HIS)-humanized mouse model ("DRAGA": HLA-A2.HLA-DR4.Rag1KO.IL-2R{gamma}cKO.NOD) for COVID-19 research. This mouse is reconstituted with human cord blood-derived, HLA-matched hematopoietic stem cells. It engrafts human epi/endothelial cells expressing the human ACE2 receptor for SARS-CoV-2 and TMPRSS2 serine protease co-localized on lung epithelia. HIS-DRAGA mice sustained SARS-CoV-2 infection, showing deteriorated clinical condition, replicating virus in the lungs, and human-like lung immunopathology including T-cell infiltrates, microthrombi and pulmonary sequelae. Among T-cell infiltrates, lung-resident (CD103+) CD8+ T cells were sequestered in epithelial (CD326+) lung niches and secreted granzyme B and perforin, indicating cytotoxic potential. Infected mice also developed antibodies against the SARS-CoV-2 viral proteins. Hence, HIS-DRAGA mice showed unique advantages as a surrogate in vivo human model for studying SARS-CoV-2 immunopathology and for testing the safety and efficacy of candidate vaccines and therapeutics. What can cold-induced transcriptomes of Arctic Brassicaceae tell us about the evolution of cold tolerance? O_LILittle is known about the evolution of cold tolerance in polar plant species and how they differ from their temperate relatives. To gain insight into their biology and the evolution of cold tolerance, we compared the molecular basis of cold response in three Arctic Brassicaceae species.
C_LIO_LIWe conducted a comparative time series experiment to examine transcriptional responses to low temperature. RNA was sampled at 22 {degrees}C, and after 3h, 6h, and 24h at 2 {degrees}C. We then identified sets of genes that were differentially expressed in response to cold and compared them between species, as well as to published data from the temperate Arabidopsis thaliana.
C_LIO_LIMost differentially expressed genes were species-specific, but a significant portion of the cold response was also shared among species. Among thousands of differentially expressed genes, [~]200 were shared among the three Arctic species and A. thaliana, while [~]100 were exclusively shared among the three Arctic species.
C_LIO_LIOur results show that cold response differs markedly between Arctic Brassicaceae species, but likely builds on a conserved basis found across the family. They also confirm that highly polygenic traits such as cold tolerance may show little repeatability in their patterns of adaptation.
C_LI Quantifying the effect of caloric and non-caloric sweeteners in the brain response using EEG and convolutional neural network Sweetener type can influence sensory properties and consumers acceptance and preference for low-calorie products. An ideal sweetener does not exist, and each sweetener must be used in situations to which it is best suited. Aspartame and sucralose can be good substitutes for sucrose in passion fruit juice. Despite the interest in artificial sweeteners, little is known about how artificial sweeteners are processed in the human brain. Here, we evaluated brain signals of 11 healthy subjects when they tasted passion fruit juice equivalently sweetened with sucrose (9.4 g/100 g), sucralose (0.01593 g/100 g), or aspartame (0.05477 g/100 g). Electroencephalograms were recorded for two sites in the gustatory cortex (i.e., C3 and C4). Data with artifacts were disregarded, and the artifact-free data were used to feed a CNN. Our results indicated that the brain responses distinguish juice sweetened with different sweeteners with an average accuracy of 0.823.

Practical ApplicationsFinding sweeteners that best fit consumer preferences evolves understanding how the gustatory cortex processes sweeteners. Ideal equivalence will occur when the brain is no longer able to distinguish stimuli that are consciously perceived. This study presents a method of signal acquisition using a single channel and an open-source processing environment. This would allow, for example, to disregard the use of a commercial electroencephalograph and expand the studies in this area and offering to food industry additional tools in the development of products sweetened with non-caloric sweeteners. To knot or not to knot: Multiple conformations of the SARS-CoV-2 frameshifting RNA element The SARS-CoV-2 frameshifting RNA element (FSE) is an excellent target for therapeutic intervention against Covid-19. This small gene element employs a shifting mechanism to pause and backtrack the ribosome during translation between Open Reading Frames 1a and 1b, which code for viral polyproteins. Any interference with this process has profound effect on viral replication and propagation. Pinpointing the structures adapted by the FSE and associated structural transformations involved in frameshifting has been a challenge. Using our graph-theory-based modeling tools for representing RNA secondary structures, "RAG" (RNA-As-Graphs), and chemical structure probing experiments, we show that the 3-stem H-type pseudoknot (3_6 dual graph), long assumed to be the dominant structure has a viable alternative, an HL-type 3-stem pseudoknot (3_3) for longer constructs. In addition, an unknotted 3-way junction RNA (3_5) emerges as a minor conformation. These three conformations share Stems 1 and 3, while the different Stem 2 may be involved in a conformational switch and possibly associations with the ribo-some during translation. For full-length genomes, a stem-loop motif (2_2) may compete with these forms. These structural and mechanistic insights advance our understanding of the SARS-CoV-2 frameshifting process and concomitant virus life cycle, and point to three avenues of therapeutic intervention. Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. Bacterial H-NS contacts DNA at the same irregularly spaced sites in both bridged and hemi-sequestered linear filaments Gene silencing in bacteria is mediated by chromatin proteins, of which Escherichia coli H-NS is a paradigmatic example. H-NS forms nucleoprotein filaments with either one or two DNA duplexes. However, the structures, arrangements of DNA-binding domains (DBDs), and positions of DBD-DNA contacts in linear and bridged filaments are uncertain. To characterize the contacts that silence transcription by RNA polymerase, we combined {middle dot}OH footprinting, molecular dynamics, statistical modeling, and DBD mapping using a chemical nuclease (Fe2+-EDTA) tethered to the DBDs (TEN-map). We find that H-NS DBDs contact DNA at indistinguishable locations in bridged or linear filaments and that the DBDs vary in orientation and position with ~10-bp average spacing. Our results support a hemi-sequestration model of linear-to-bridged H-NS switching in which linear filaments able to inhibit only transcription initiation switch to bridged filaments able to inhibit both initiation and elongation using the same irregularly spaced DNA contact sites.

HighlightsO_LITethered-nuclease mapping (TEN-map) of H-NS DNA-binding domains detects DNA contacts
C_LIO_LIBridged and linear H-NS filaments use the same DNA contact sites
C_LIO_LIH-NS-DNA contacts are unevenly spaced with ~10 bp average separation
C_LIO_LIAT-steps, minor groove width, and electrostatic potential best predict contact sites
C_LI A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information. Distinct cellular origins and differentiation process account for distinct oncogenic and clinical behaviors of leiomyosarcomas Differentiated phenotypes in solid tumors mostly lead to a better outcome than in their more immature counterparts. In leiomyosarcoma (LMS), a very aggressive tumor for which neither chemotherapy nor targeted or immune therapies have demonstrated efficacy, a relatively transcriptionally uniform subgroup of well differentiated tumors has been described and is associated with poor survival. In this disease, differentiation does not systematically hinder tumor progression, so it is a good model for studying the relation between these two mechanisms. By applying ad hoc bioinformatic methods, we conducted a comprehensive analysis in order to detect subgroups of leiomyosarcoma and finely investigate their transcriptomic and genomic profiles. We first used unsupervised hierarchical clustering to identify the most transcriptionally homogeneous LMS subgroup, which we named  hLMS. We derived a transcriptional signature that could consistently stratify patients with similar clinical and genomic characteristics in TCGA and ICGC cohorts. Functional analysis of the signature showed over-expression of SRF and E2Fs targets harboring histone modifications that were specifically identified in smooth muscles in hLMS. By integrating multi-omics data, we identified punctual and structural variations as well as the potential cellular origins of each group of LMS using GTEX normal tissue gene expression. Altogether, our results suggest that hLMS, but not oLMS (other LMS), may originate from vascular smooth muscle cells in which oncogenesis is driven by the MYOCD/SRF axis, which is essential for hLMS survival. We propose that the phenotypic plasticity of vascular smooth muscle cells coupled with MYOCD/SRF pathway overactivation could explain how hLMS balance this uncommon interplay between differentiation and aggressiveness. Disentangling five dimensions of animacy in human brain and behaviour The perception of animate things is of great behavioural importance to humans. Despite the prominence of the distinct brain and behavioural responses to animate and inanimate things, however, it remains unclear which of several commonly confounded properties underlie these observations. Here, we investigate the importance of five dimensions of animacy: "being alive", "looking like an animal", "having agency", "having mobility", and "being unpredictable" in brain (fMRI, EEG) and behaviour (property and similarity judgments) of 19 subjects using a stimulus set of 128 images that disentangles the five dimensions (optimized by a genetic algorithm). The living/non-living distinction ("being alive") was prominent in subjects judgments, but despite its prominence in the neuroscience literature, did not explain variance in brain representations. The other dimensions of animacy explained variance in both brain and behaviour. The "having agency" dimension explained more variance in higher-level visual areas, consistent with higher cognitive contributions. The "being unpredictable" dimension was reflected in representations in both lower and higher-level visual cortex, possibly because unpredictable things require attention. We conclude that the multiple dimensions commonly conflated in the notion of animacy are distinctly reflected in different brain and behavioural responses. Robust and annotation-free analysis of alternative splicing across diverse cell types in mice Although alternative splicing is a fundamental and pervasive aspect of gene expression in higher eukaryotes, it is often omitted from single-cell studies due to quantification challenges inherent to commonly used short-read sequencing technologies. Here, we undertake the analysis of alternative splicing across numerous diverse murine cell types from two large-scale single-cell datasets--the Tabula Muris and BRAIN Initiative Cell Census Network--while accounting for understudied technical artifacts and unannotated isoforms. We find strong and general cell-type-specific alternative splicing, complementary to total gene expression but of similar discriminatory value, and identify a large volume of novel isoforms. We specifically highlight splicing variation across different cell types in primary motor cortex neurons, bone marrow B cells, and various epithelial cells; and show that the implicated transcripts include many genes which do not display total expression differences. To elucidate the regulation of alternative splicing, we build a custom predictive model based on splicing factor activity, recovering several known interactions while generating new hypotheses, including potential regulatory roles for novel alternative splicing events in critical genes including Khdrbs3 and Rbfox1. We make our results available using public interactive browsers to spur further exploration by the community. SkewDB: A comprehensive database of GC and 10 other skews for over 28,000 chromosomes and plasmids GC skew denotes the relative excess of G nucleotides over C nucleotides on the leading versus the lagging replication strand of eubacteria. While the effect is small, typically around 2.5%, it is robust and pervasive. GC skew and the analogous TA skew are a localized deviation from Chargaffs second parity rule, which states that G and C, and T and A occur with (mostly) equal frequency even within a strand.

Most bacteria also show the analogous TA skew. Different phyla show different kinds of skew and differing relations between TA and GC skew.

This article introduces an open access database (https://skewdb.org) of GC and 10 other skews for over 28,000 chromosomes and plasmids. Further details like codon bias, strand bias, strand lengths and taxonomic data are also included. The SkewDB database can be used to generate or verify hypotheses. Since the origins of both the second parity rule, as well as GC skew itself, are not yet satisfactorily explained, such a database may enhance our understanding of microbial DNA. Plasmodium DDI1 is a potential dual-therapeutic target and essential chromatin-associated protein DDI1 proteins are involved in a variety of cellular processes, including proteasomal degradation of specific proteins. All DDI1 proteins contain a ubiquitin-like (UBL) domain and a retroviral aspartyl protease (RVP) domain. Some DDI1 proteins also contain a ubiquitin-associated (UBA) domain. The three domains confer distinct activities to DDI1 proteins. The presence of RVP domain makes DDI1 a potential target of HIV protease inhibitors, which also block the development of malaria parasites. Hence, we investigated the DDI1 of malaria parasites to identify its roles during parasite development and potential as a therapeutic target. DDI1 proteins of Plasmodium and other Apicomplexan parasites share the UBL-RVP domain architecture, and some also contain the UBA domain. Plasmodium DDI1 is expressed across all the major life cycle stages and is essential, as conditional depletion of DDI1 protein in the mouse malaria parasite Plasmodium berghei and the human malaria parasite Plasmodium falciparum compromised parasite development. Infection of mice with DDI1 knock-down P. berghei was self-limiting and protected the recovered mice from subsequent infection with homologous as well as heterologous parasites, indicating potential of DDI1 knock-down parasites as a whole organism vaccine. P. falciparum DDI1 (PfDDI1) is associated with chromatin and DNA-protein crosslinks. PfDDI1-depleted parasites accumulated DNA-protein crosslinks and showed enhanced susceptibility to DNA damaging chemicals, indicating a role of PfDDI1 in removal of DNA-protein crosslinks. Knock-down of PfDDI1 increased susceptibility to the retroviral protease inhibitor lopinavir and antimalarial artemisinin, which suggests that simultaneous inhibition of DDI1 could potentiate antimalarial activity of these drugs. Hence, Plasmodium DDI1 could be a dual-therapeutic target for malaria control. Linking plankton size spectra and community composition to carbon export and its efficiency The magnitude and efficiency of particulate carbon export from the ocean surface depends not only on net primary production (NPP) but also on how carbon is consumed, respired, and repackaged by organisms. We contend that several of these processes can be captured by the size spectrum of the plankton community. However, most global models have relatively simple food-web structures that are unable to generate plankton sizespectra. Moreover, the life-cycles of multicellular zooplankton are typically not resolved, restricting the ability of models to represent time-lags that are known to impact carbon export and its efficiency (pe-ratio). Here, we use a global mechanistic size-spectrum model of the marine plankton community to investigate how particulate export and pe-ratio relate to the community size spectrum, community composition, and time-lags between predators and prey. The model generates emergent food-webs with associated size distributions for organisms and detrital particles. To resolve time-lags between phytoplankton and zooplankton, we implement the life-cycle of multicellular zooplankton (here represented by copepods). The simulation successfully captures observed patterns in biomass and energy fluxes across regions. We find that carbon export correlates best with copepod biomass and trophic level, whereas the pe-ratio correlates best with the exponent of the size spectrum and sea surface temperature (SST). Community metrics performed better than NPP or SST for both deep export and pe-ratio. Time-lags between phytoplankton and copepods did not strongly affect export or pe-ratio. We conclude by discussing how can we reconcile size-spectrum theory with field sampling.

Plain Language SummaryPlankton are tiny but extremely abundant aquatic organisms. Plankton lock CO2 away from the atmosphere as they sink to the deep ocean, where carbon can be stored for hundreds of years. However, how much carbon is locked away and for how long depends on how organisms eat, defecate, and respire. We argue that these processes are reflected in the size composition of the plankton community. The size composition shows a clear relationship between the number of organisms and their body-size. The steepness of this "size-abundance relationship" describes the balance between small vs. large organisms, and has been argued to reflect how energy is transferred from small to large organisms. Since large organisms create fast-sinking particles, the size-abundance relationship could be used to estimate how much carbon is being stored in the deep ocean. Here we use a computer simulation of the global plankton community to investigate how the removal of carbon relates to the plankton community and the steepness of the sizeabundance relationship. The model successfully captures patterns observed in nature. We found that the size-abundance relationship, together with the quantity of large zooplankton better explained carbon export than other measures typically used, such as photosynthesis and temperature.

Key PointsO_LIWe use a global mechanistic size-spectrum model to investigate the relation between particulate export and plankton community metrics.
C_LIO_LIWe find a good correlation between export efficiency and the exponent of the size spectrum.
C_LIO_LITotal carbon export correlated well with copepod biomass and trophic level of active copepods in the model.
C_LI A phenomics approach for in vitro antiviral drug discovery BackgroundThe current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties.

ResultsWe show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state.

ConclusionsThe method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. Protein Complex Structure Prediction Powered by Multiple Sequence Alignments of Interologs from Multiple Taxonomic Ranks and AlphaFold2 AlphaFold2 is expected to be able to predict protein complex structures as long as a multiple sequence alignment (MSA) of the interologs of the target protein-protein interaction (PPI) can be provided. However, preparing the MSA of protein-protein interologs is a non-trivial task due to the existence of paralogs. In this study, a simplified phylogeny-based approach was applied to generate the MSA of interologs, which was then used as the input to AlphaFold2 for protein complex structure prediction. Extensively benchmarked this protocol on non-redundant PPI dataset including 107 bacterial PPIs and 442 eukaryotic PPIs, we show complex structures of 79.5% of the bacterial PPIs and 49.8% of the eukaryotic PPIs can be successfully predicted. Considering PPIs may not be conserved in species with long evolutionary distances, we further restricted interologs in the MSA to different taxonomic ranks of the species of the target PPI in protein complex structure prediction. We found the success rates can be increased to 87.9% for the bacterial PPIs and 56.3% for the eukaryotic PPIs if interologs in the MSA are restricted to a specific taxonomic rank of the species of each target PPI. Finally, we show the optimal taxonomic ranks for protein complex structure prediction can be selected with the application of the recalculated predicted TM-scores of the output models. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Tracheal tube fusion in Drosophila involves release of exosomes from multivesicular bodies Extracellular vesicles (EVs) comprise diverse types of cell-released membranous structures that are thought to play important roles in intercellular communication. Despite extensive work on the formation and functions of EVs in cultured cells, studies of EVs in vivo have remained scarce. We report here that EVs are present in the developing lumen of tracheal tubes in Drosophila embryos. We defined two distinct EV subpopulations, one of which contains the Munc13-4 homologue Staccato (Stac) and is spatially and temporally associated with tracheal tube fusion events. The formation of Stac-positive luminal EVs depends on the tip-cell-specific GTPase Arl3, which is also required for the formation of Stac-positive multivesicular bodies, suggesting that Stac-EVs derive from fusion of Stac-MVBs with the luminal membrane in tip cells during anastomosis formation. The GTPases Rab27 and Rab35 cooperate downstream of Arl3 to promote Stac-MVB formation and tube fusion. We propose that Stac-MVBs act as membrane reservoirs that facilitate tracheal lumen fusion in a process regulated by Arl3, Rab27, Rab35, and Stac/Munc13-4.