A novel stem cell type at the basal side of the subventricular zone maintains adult neurogenesis According to the current consensus, neural stem cells (NSCs) apically contacting the lateral ventricle generate differentiated progenitors by rare asymmetric divisions or by relocating to the basal side of the ventricular-subventricular zone V-SVZ. Both processes will then ultimately lead to the generation of adult-born olfactory bulb (OB) interneurons. In contrast to this view, we here found that adult-born OB interneurons largely derive from an additional NSC type resident in the basal V-SVZ. Despite being both capable of self-renewal and long-term quiescence, apical and basal NSCs differ in Nestin expression, primary cilia extension and frequency of cell division. The expression of Notch-related genes also differed between the two NSC groups and Notch-activation was greatest in apical NSCs. Apical downregulation of Notch-effector Hes1 decreased Notch activation while increasing proliferation across the niche and neurogenesis from apical NSCs. Underscoring their different roles in neurogenesis, lactation-dependent increase in neurogenesis was paralleled by extra activation of basal but not apical NSCs. Thus, basal NSCs support OB neurogenesis whereas apical NSCs impart Notch-mediated lateral inhibition across the V-SVZ.
The NDP52/CALCOCO2 selective autophagy receptor controls processing body disassembly Kaposis sarcoma-associated herpesvirus (KSHV) causes the inflammatory and angiogenic endothelial cell neoplasm, Kaposis sarcoma (KS). We previously demonstrated that expression of the KSHV protein, Kaposin B (KapB), promoted inflammation via the disassembly of cytoplasmic ribonucleoprotein granules called processing bodies (PBs). Processing bodies (PBs) modify gene expression by silencing or degrading labile messenger RNAs (mRNAs) including many transcripts that encode inflammatory or angiogenic proteins that are associated with KS disease. Although our work implicated PB disassembly as one of the causes of inflammation during KSHV infection, the precise mechanism used by KapB to elicit PB disassembly was unclear. Here we reveal a new connection between the degradative process of autophagy and PB disassembly. We show that both latent KSHV infection and KapB expression enhanced autophagic flux via the phosphorylation of the autophagy regulatory protein, Beclin 1. KapB was necessary for this effect, as infection with a recombinant virus that does not express the KapB protein did not induce Beclin 1 phosphorylation or autophagic flux. Moreover, we reveal that PB disassembly mediated by KSHV or KapB depended on canonical autophagy genes and the selective autophagy receptor NDP52/CALCOCO2 and that the PB scaffolding protein, Pat1b, co-immunoprecipitated with NDP52. These studies reveal a new role for autophagy and the selective autophagy receptor NDP52 in promoting PB turnover and the concomitant synthesis of inflammatory molecules during KSHV infection.

Author SummaryKaposis sarcoma-associated herpesvirus (KSHV) is the causative agent of the inflammatory, endothelial cell cancer, Kaposis Sarcoma (KS). KSHV induces a pro-tumourigenic inflammatory environment which aids in the establishment and maintenance of the KS lesion. Processing bodies (PBs) are cellular structures that dampen inflammatory gene expression by suppression or decay of their cognate RNA molecules. We previously showed that the viral protein KapB caused PB disappearance during KSHV infection, identifying a new pathway used by KSHV to elicit inflammation. Now, we show that KSHV and KapB hijack the cellular degradative process of autophagy to promote PB disassembly and increase inflammatory gene expression. This places autophagy as central to the regulation of inflammation by KSHV and illustrates another remarkable strategy used by these viruses to create a tumourigenic microenvironment.
Novel MOG analogues to explore the MCT2 pharmacophore, α-ketoglutarate biology and cellular effects of N-oxalylglycine -ketoglutarate (KG) is a central metabolic node with a broad influence on cellular physiology. The KG analogue N-oxalylglycine (NOG) and its membrane-permeable pro-drug derivative dimethyl-oxalylglycine (DMOG) have been extensively used as tools to study prolyl hydroxylases (PHDs) and other KG-dependent processes. In cell culture media, DMOG is rapidly converted to MOG, which enters cells through monocarboxylate transporter MCT2, leading to intracellular NOG concentrations that are sufficiently high to inhibit glutaminolysis enzymes and cause cytotoxicity. Therefore, the degree of (D)MOG instability together with MCT2 expression levels determine the intracellular targets NOG engages with and, ultimately, its effects on cell viability. Here we designed and characterised a series of MOG analogues with the aims of improving stability and exploring the functional requirements for interaction with MCT2, a relatively understudied member of the SLC16 family. We report MOG analogues that maintain ability to enter cells via MCT2, and identify compounds that do not inhibit glutaminolysis or cause cytotoxicity but can still inhibit PHDs. We use these analogues to show that glutaminolysis-induced activation of mTORC1 can be uncoupled from PHD activity. Therefore, these new compounds can help deconvolute cellular effects that result from the polypharmacological action of NOG. Warmer temperatures result in maladaptive learning of sexual preferences O_LIEmpirical studies predicting the effects of the climate crisis on biodiversity loss that take into account learning ability and sexual selection are currently lacking.
C_LIO_LIUsing the African butterfly Bicyclus anynana, which shows strong phenotypic plasticity (i.e., polyphenism) in response to temperature, we find that learning produces a maladaptive mate preference under climate warming.
C_LIO_LIWe first modelled climate warming scenarios and then showed experimentally that as temperature becomes an unreliable cue to the onset of the dry season, adult butterflies displayed the wet season rather than the dry season form.
C_LIO_LIFemale learning further suppressed their innate, adaptive sexual preference for dry season males. Instead, females learned to prefer a phenotype transiently present during the seasonal transition.
C_LIO_LIFemale fertility and longevity were also indirectly affected by learning, likely reducing female fitness following climate warming.
C_LIO_LIOur results emphasize the importance of sexual selection, learning, and their fitness consequences for understanding (mal)adaptation of natural populations to climate warming.
C_LI 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. Presynaptic Stochasticity Improves Energy Efficiency and Helps Alleviate the Stability-Plasticity Dilemma When an action potential arrives at a synapse there is a large probability that no neurotransmitter is released. Surprisingly, simple computational models suggest that these synaptic failures enable information processing at lower metabolic costs. However, these models only consider information transmission at single synapses ignoring the remainder of the neural network as well as its overall computational goal. Here, we investigate how synaptic failures affect the energy efficiency of models of entire neural networks that solve a goal-driven task. We find that presynaptic stochasticity and plasticity improve energy efficiency and show that the network allocates most energy to a sparse subset of important synapses. We demonstrate that stabilising these synapses helps to alleviate the stability-plasticity dilemma, thus connecting a presynaptic notion of importance to a computational role in lifelong learning. Overall, our findings present a set of hypotheses for how presynaptic plasticity and stochasticity contribute to sparsity, energy efficiency and improved trade-offs in the stability-plasticity dilemma. Is Pisum sativum a good model species for the study of root responses to neighbours and barriers in soil? A bayesian hierarchical meta-analysis Plant-plant competition is ubiquitous in nature. However, studying below ground behaviour of roots has always posed certain difficulties. Pea (Pisum sativum L.) has become a sort of model species for ecological studies about how plant roots respond to neighbouring plant roots and barriers in soil. However, published results point in several different directions. This has sometimes been interpreted as pea having sophisticated context dependent responses that can change in complex ways depending on its surroundings. To explore this further, here, we combine the result of five new experiments with published results to examine 18 unique experiments from 7 different studies for a total of 254 replicates. We used a Bayesian hierarchical meta-analysis approach to estimating the likely effect size from the available data, as well as quantify heterogeneity among different experiments, studies and cultivars. The posterior distributions show that, at the coarsest possible scale of total root production, it is unlikely that P. sativum root growth is influenced by either neighbours or barriers to root growth imposed by the walls of pots that vary in volume. We suggest that further work should consider repeating experiments that reported finer scale root plasticity in pea at the rhizosphere scale, and also consider alternative model species for the study of plant root responses to external cues. De novo identification of maximally deregulated subnetworks based on multi-omics data with DeRegNet BackgroundWith a growing amount of (multi-)omics data being available, the extraction of knowledge from these datasets is still a difficult problem. Classical enrichment-style analyses require predefined pathways or gene sets that are tested for significant deregulation to assess whether the pathway is functionally involved in the biological process under study. De novo identification of these pathways can reduce the bias inherent in predefined pathways or gene sets. At the same time, the definition and efficient identification of these pathways de novo from large biological networks is a challenging problem.

ResultsWe present a novel algorithm, DeRegNet, for the identification of maximally deregulated subnetworks on directed graphs based on deregulation scores derived from (multi-)omics data. DeRegNet can be interpreted as maximum likelihood estimation given a certain probabilistic model for de-novo subgraph identification. We use fractional integer programming to solve the resulting combinatorial optimization problem. We can show that the approach outperforms related algorithms on simulated data with known ground truths. On a publicly available liver cancer dataset we can show that DeRegNet can identify biologically meaningful subgraphs suitable for patient stratification. DeRegNet is freely available as open-source software.

ConclusionThe proposed algorithmic framework and its available implementation can serve as a valuable heuristic hypothesis generation tool contextualizing omics data within biomolecular networks. 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. Water levels primarily drive variation in photosynthesis and nutrient use of scrub Red Mangroves in the southeastern Florida Everglades We investigated how mangrove-island micro-elevation (i.e., habitat: center vs. edge) affects tree physiology in a scrub mangrove forest of the southeastern Everglades. We measured leaf gas exchange rates of scrub Rhizophora mangle L. trees monthly during 2019, hypothesizing that CO2 assimilation (Anet) and stomatal conductance (gsw) would decline with increasing water levels and salinity, expecting more-considerable differences at mangrove-island edges than centers, where physiological stress is greatest. Water levels varied between 0 and 60 cm from the soil surface, rising during the wet season (May-October) relative to the dry season (November-April). Porewater salinity ranged from 15 to 30 ppt, being higher at mangrove-island edges than centers. Anet maximized at 15.1 {micro}mol m-2 s-1, and gsw was typically <0.2 mol m-2 s-1, both of which were greater in the dry than the wet season and greater at island centers than edges, with seasonal variability being roughly equal to variation between habitats. After accounting for season and habitat, water level positively affected Anet in both seasons but did not affect gsw. Our findings suggest that inundation stress (i.e., water level) is the primary driver of variation in leaf gas exchange rates of scrub mangroves in the Florida Everglades, while also constraining Anet more than gsw. The interaction between inundation stress due to permanent flooding and habitat varies with season as physiological stress is alleviated at higher-elevation mangrove-island center habitats during the dry season. Freshwater inflows during the wet season, increase water levels and inundation stress at higher-elevation mangrove-island centers, but also potentially alleviate salt and sulfide stress in soils. Thus, habitat heterogeneity leads to differences in nutrient and water acquisition and use between trees growing in island centers versus edges, creating distinct physiological controls on photosynthesis, which likely affect carbon flux dynamics of scrub mangroves in the Everglades. Unsupervised clustering analysis of SARS-Cov-2population structure reveals six major subtypes atearly stage across the world Identifying the population structure of the newly emerged coronavirus SARS-CoV-2 has significant potential to inform public health management and diagnosis. As SARS-CoV-2 sequencing data accrued, grouping them into clusters is important for organizing the landscape of the population structure of the virus. Due to the limited prior information on the newly emerged coronavirus, we utilized four different clustering algorithms to group 16,873 SARS-CoV-2 strains, which automatically enables the identification of spatial structure for SARS-CoV-2. A total of six distinct genomic clusters were identified using mutation profiles as input features. Comparison of the clustering results reveals that the four algorithms produced highly consistent results, but the state-of-the-art unsupervised deep learning clustering algorithm performed best and produced the smallest intra-cluster pairwise genetic distances. The varied proportions of the six clusters within different continents revealed specific geographical distributions. In particular, our analysis found that Oceania was the only continent on which the strains were dispersively distributed into six clusters. In summary, this study provides a concrete framework for the use of clustering methods to study the global population structure of SARS-CoV-2. In addition, clustering methods can be used for future studies of variant population structures in specific regions of these fast-growing viruses. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. A platform of patient-derived microtumors identifies individual treatment responses and therapeutic vulnerabilities in ovarian cancer. BackgroundIn light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease with complex microenvironment and high recurrence rates, we developed a 3D preclinical ovarian cancer model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) for identification of treatment vulnerabilities and validation of anti-cancer drug efficacy using immunohistochemistry, immune cell phenotyping, functional assays and protein profiling analyses.

MethodsPDM and TILs were isolated from fresh primary ovarian cancer tissue specimen using mechanical disruption and limited enzymatic digestion and were subsequently cultured in suspension in defined media in the absence of serum. The heterogeneous cellular composition of isolated PDM as well as autologous TILs was analyzed by FFPE immunohistochemistry and multi-color flow cytometry, respectively. For in-depth protein profiling of PDM we established Reverse Phase Protein Array (RPPA) analyses of >110 total and phospho-proteins. Treatment efficacy in response to chemotherapeutics as well as immunotherapeutic compounds was assessed in PDM and PDM-TIL co-cultures using a functional viability assay in microplate format.

ResultsThe enzymatic digestion of primary ovarian cancer tissue and suspension culture in defined serum-free media allowed fast and efficient recovery of patient-derived microtumors (PDM). Immunohistochemical analyses demonstrated histopathological comparability of ovarian cancer PDM with corresponding patient tumor tissue. Reverse Phase Protein Array (RPPA)-based analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Finally, combining PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated the potential for patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach.

Conclusion3D patient-derived ovarian cancer microtumors represent a preclinical, ex vivo tumor model that reflects intertumoral heterogeneity and represent the cellular complexity of individual patient tumors. Combining protein pathway analysis and anti-cancer drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision-making and personalizing cancer treatment. Construction of a new chromosome-scale, long-read reference genome assembly for the Syrian hamster, Mesocricetus auratus BackgroundThe Syrian hamster (Mesocricetus auratus) has been suggested as a useful mammalian model for a variety of diseases and infections, including infection with respiratory viruses such as SARS-CoV-2. The MesAur1.0 genome assembly was generated in 2013 using whole-genome shotgun sequencing with short-read sequence data. Current more advanced sequencing technologies and assembly methods now permit the generation of near-complete genome assemblies with higher quality and greater continuity.

FindingsHere, we report an improved assembly of the M. auratus genome (BCM_Maur_2.0) using Oxford Nanopore Technologies long-read sequencing to produce a chromosome-scale assembly. The total length of the new assembly is 2.46 Gbp, similar to the 2.50 Gbp length of a previous assembly of this genome, MesAur1.0. BCM_Maur_2.0 exhibits significantly improved continuity with a scaffold N50 that is 6.7 times greater than MesAur1.0. Furthermore, 21,616 protein coding genes and 10,459 noncoding genes are annotated in BCM_Maur_2.0 compared to 20,495 protein coding genes and 4,168 noncoding genes in MesAur1.0. This new assembly also improves the unresolved regions as measured by nucleotide ambiguities, where approximately 17.11% of bases in MesAur1.0 were unresolved compared to BCM_Maur_2.0 in which the number of unresolved bases is reduced to 3.00%.

ConclusionsAccess to a more complete reference genome with improved accuracy and continuity will facilitate more detailed, comprehensive, and meaningful research results for a wide variety of future studies using Syrian hamsters as models. Muscle Activation Profile During Perturbed Walking is Modulated According to Body State During an unexpected loss of balance, avoiding a fall requires people to readjust their footing rapidly and effectively. We investigated the activation patterns of the ankle and knee muscles, and muscle fiber type recruitment resulting from unannounced, medio-lateral (i.e., right/left) horizontal-surface walking perturbations in twenty healthy adults (27.00{+/-}2.79 years, 10 females). Surface electromyography (sEMG) total spectral power for specific frequency bands (40-60Hz, 60-150Hz, 150-250Hz, 250-400Hz and 400-1000Hz), from tibialis anterior (TA) and vastus lateralis (VL) muscles were analyzed. Compared to non-perturbed walking, we found a significant increase in the total spectral power of lower-extremity muscles during the first 3 seconds after perturbation. When two feet were on the ground in time of perturbation we found a different muscle fiber type recruitment pattern between VL and TA muscles. This was not significant for perturbations implemented when one foot was on the ground. Our findings suggest that muscle operating frequency is modulated in real time to fit body state and somatosensory input in the context of functional goal requirements such as a rapid change of footing in response to unexpected loss of balance in single and double-support phases of gait.

New & NoteworthyTo study muscle spectral profiles in response to loss of balance, we investigated the dynamics of muscle spectral power changes, across different frequency bands after unannounced mechanical perturbations during walking. We showed increased activation of high-frequency motor units of the lower-limb muscles, subside 3 seconds after perturbation. Differences in power increase of specific frequency bands suggest that muscle activation is modulated in real time to fit body state in the context of functional goal requirements. Effect of Adolescent Stress on Adult Morphine-Induced Behavioral Sensitization is Dependent Upon Genetic Background 1Deaths related to opioid use have skyrocketed in the United States, leading to a public health epidemic. Research has shown that both biological (genes) and environmental (stress) precursors are linked to opioid use. In particular, stress during adolescence - a critical period of frontal lobe development - influences the likelihood of abusing drugs. However, little is known about the biological mechanisms through which adolescent stress leads to long-term risk of opioid use, or whether genetic background moderates this response. Male and female C57BL/6J and BALB/cJ mice were exposed to chronic variable social stress (CVSS) or control conditions throughout adolescence and then tested for morphine locomotor sensitization or morphine consumption in adulthood. To examine possible mechanisms that underlie stress-induced changes in morphine behaviors, we assessed physiological changes in response to acute stress exposure and prefrontal cortex miRNA gene expression. Adolescent stress did not influence morphine sensitization or consumption in BALB/cJ animals, and there was limited evidence of stress effects in female C57BL/6J mice. In contrast, male C57BL/6J mice exposed to adolescent CVSS had blunted morphine sensitization compared to control animals; no differences were observed in the acute locomotor response to morphine administration or morphine consumption. Physiologically, C57BL/6J mice exposed to CVSS had an attenuated corticosterone recovery following an acute stressor and downregulation of twelve miRNA in the prefrontal cortex compared to control mice. The specificity of the effects for C57BL/6J versus BALB/cJ mice provides evidence of a gene by environmental interaction influencing opioid behaviors. Long-term differences in stress reactivity or miRNA expression suggests two possible biological mechanisms to evaluate in future research. Ineffectual AEC1 differentiation from KRT8hi transitional state without fibrosis is associated with fatal COVID-19 ARDS ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Multi-omic meta-analysis of transcriptomes and the bibliome uncovers novel hypoxia-inducible genes Hypoxia is a condition in which cells, tissues, or organisms are deprived of sufficient oxygen supply. Aerobic organisms have a hypoxic response system, represented by hypoxia-inducible factor 1- (HIF1A), to adapt to this condition. Due to publication bias, there has been little focus on genes other than well-known signature hypoxia-inducible genes. Therefore, in this study, we performed a meta-analysis to identify novel hypoxia-inducible genes. We searched publicly available transcriptome databases to obtain hypoxia-related experimental data, retrieved the metadata, and manually curated it. We selected the genes that are differentially expressed by hypoxic stimulation, and evaluated their relevance in hypoxia by performing enrichment analyses. Next, we performed a bibliometric analysis using gene2pubmed data to examine genes that have not been well studied in relation to hypoxia. Gene2pubmed data that provides information about the relationship between gene and publication. We calculated and evaluated the number of reports and similarity coefficients of each gene to HIF1A, which is a representative gene in hypoxia studies. In this data-driven study, we report that several genes that were not known to be associated with hypoxia, including the G protein-coupled receptor 146 gene, are upregulated by hypoxic stimulation. Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias. LY-CoV1404 (bebtelovimab) potently neutralizes SARS-CoV-2 variants SARS-CoV-2 neutralizing monoclonal antibodies (mAbs) can reduce the risk of hospitalization when administered early during COVID-19 disease. However, the emergence of variants of concern has negatively impacted the therapeutic use of some authorized mAbs. Using a high throughput B-cell screening pipeline, we isolated a highly potent SARS-CoV-2 spike glycoprotein receptor binding domain (RBD)-specific antibody called LY-CoV1404 (also known as bebtelovimab). LY-CoV1404 potently neutralizes authentic SARS-CoV-2 virus, including the prototype, B.1.1.7, B.1.351 and B.1.617.2). In pseudovirus neutralization studies, LY-CoV1404 retains potent neutralizing activity against numerous variants including B.1.1.7, B.1.351, B.1.617.2, B.1.427/B.1.429, P.1, B.1.526, B.1.1.529, and the BA.2 subvariant and retains binding to spike proteins with a variety of underlying RBD mutations including K417N, L452R, E484K, and N501Y. Structural analysis reveals that the contact residues of the LY-CoV1404 epitope are highly conserved with the exception of N439 and N501. Notably, the binding and neutralizing activity of LY-CoV1404 is unaffected by the most common mutations at these positions (N439K and N501Y). The breadth of reactivity to amino acid substitutions present among current VOC together with broad and potent neutralizing activity and the relatively conserved epitope suggest that LY-CoV1404 has the potential to be an effective therapeutic agent to treat all known variants causing COVID-19.

In BriefLY-CoV1404 is a potent SARS-CoV-2-binding antibody that neutralizes all known variants of concern and whose epitope is rarely mutated.

HighlightsO_LILY-CoV1404 potently neutralizes SARS-CoV-2 authentic virus and known variants of concern including the B.1.1.529 (Omicron), the BA.2 Omicron subvariant, and B.1.617.2 (Delta) variants
C_LIO_LINo loss of potency against currently circulating variants
C_LIO_LIBinding epitope on RBD of SARS-CoV-2 is rarely mutated in GISAID database
C_LIO_LIBreadth of neutralizing activity and potency supports clinical development
C_LI Lifespan prolonging mechanisms and insulin upregulation without fat accumulation in long-lived reproductives of a higher termite Kings and queens of eusocial termites can live for decades, while queens sustain a nearly maximal fertility. To investigate the molecular mechanisms underlying their long lifespan, we carried out transcriptomics, lipidomics and metabolomics in Macrotermes natalensis on sterile short-lived workers, long-lived kings and five stages spanning twenty years of adult queen maturation. Reproductives share gene expression differences from workers in agreement with a reduction of several aging-related processes, involving upregulation of DNA damage repair and mitochondrial functions. Anti-oxidant gene expression is downregulated, while peroxidability of membranes in queens decreases. Against expectations, we observed an upregulated gene expression in fat bodies of reproductives of several components of the IIS pathway, including an insulin-like peptide, Ilp9. This pattern does not lead to deleterious fat storage in physogastric queens, while simple sugars dominate in their hemolymph and large amounts of resources are allocated towards oogenesis. Our findings support the notion that all processes causing aging need to be addressed simultaneously in order to prevent it. Conserved organ-specific microbial assemblages in different populations of a terrestrial crab Brachyuran crabs originated in the oceans and evolved specific morphological and physiological adaptations to live in freshwater, intertidal and even terrestrial habitats but the role of a selection mechanism involving symbiotic microorganisms long these colonization processes are not known. In this work we investigated the associated microbiota of three populations of a terrestrial brachyuran crab, Chiromantes haematocheir, to find evidence of a conserved crab-specific microbiome unrelated to the population of origin and dissimilar from environmental microbial assemblages. Bacterial 16S rRNA gene and fungal ITS sequences were obtained from selected crab organs and environmental matrices to profile microbial communities. In spite of the presence of truly marine larval stages and no gregarious behaviour, favouring microbiota exchanges, we found common, organ-specific microbiota, associated to the gut and the gills of the crabs (with more than 15% of the genera detected specifically enriched only in one organ). Our results suggest an early establishment of a new common, stable microbiota in the transition from water to land. Bespoke data augmentation and network construction enable developmental morphological classification on limited microscopy datasets Deep learning is a powerful tool for image classification, yet training deep learning models often requires large datasets, which are not always available in biological research. Here we use a small dataset to train an accurate classifier by employing data augmentation regimes and Bayesian optimisation. We establish a new staging system for the Hamburger-Hamilton stage 10 chick embryo brain, based on morphology, identifying three sub-stages uncoupled from somite number, the usual metric used to stage chick embryos. Incorporating biologically informed, data-driven preprocessing, we train a deep convolutional neural network to classify our sub-stages. We find that augmenting our images with a combination of rotation, blur, shear, and cutout transformations is effective in training an accurate classifier on a small microscopy dataset. We then apply our approach to an unrelated small microscopy dataset comprising images of limb buds, finding good agreement with the results from brain classification. Through saliency analysis, we ensure that relevant features are being used by our classifier, gain insight into the efficacy of different data augmentations, and identify sub-stage specific features. In summary, we apply biological domain expertise to design effective data augmentation regimes for training a neural network-based image classifier on small, specialised datasets, classifying the developing brains and limbs with up to 90.9% and 94.4% accuracy respectively. These reliable classifiers can inform future experiments. Development of antibiotic resistance reveals diverse evolutionary pathways to face the complex and dynamic environment of a long-term treated patient Antibiotic resistance development has been studied using approaches that range from laboratory experimental evolution, surveillance and epidemiology, to clinical isolate sequencing. However, evolutionary trajectories depend on the environment in which selection takes place, compelling to address evolutionary analyses in antibiotic-treated patients, to embrace the whole inherent environmental complexities as well as their dynamics over time. Herein, we address the complexity of the bacterial adaptive response to changing antibiotic selective pressures by studying the long-term in-patient evolution of a broad diversity of {beta}-lactam resistant Pseudomonas aeruginosa clones. By using mutational and ultra-deep amplicon sequencing, we analyzed multiple generations of a P. aeruginosa hypermutator strain persisting for more than 26 years of chronic infection in the airways of a cystic fibrosis (CF) patient. We identified the accumulation of multiple alterations targeting the chromosomally encoded class C {beta}-lactamase (blaPDC), providing structural and functional protein changes that resulted in a continuous enhancement of its catalytic efficiency and high level of cephalosporin resistance. This evolution was linked to the persistent treatment with ceftazidime, which we demonstrate selected for variants with robust catalytic activity against this expanded-spectrum cephalosporin. Surprisingly, "a gain of function" of collateral resistance towards ceftolozane, a more recently introduced cephalosporin that was not prescribed to this patient, was also observed and the biochemical basis of this cross-resistance phenomenon was elucidated. This work unveils the diversity of evolutionary trajectories driven by bacteria in the natural CF environmental setting, towards a multidrug resistant phenotype after years of antibiotic treatment against a formidable pathogen. Python-Microscope: A new open source Python library for the control of microscopes Custom built microscopes often require control of multiple hardware devices and precise hardware coordination. It is also desirable to have a solution that is scalable to complex systems and translatable between components from different manufacturers. Here we report Python-Microscope, a free and open source Python library for high performance control of arbitrarily complex and scalable custom microscope systems. Python-Microscope offers simple to use Python-based tools, abstracting differences between physical devices by providing a defined interface for different device types. Concrete implementations are provided for a range of specific hardware and a framework exists for further expansion. Python-Microscope supports the distribution of devices over multiple computers while maintaining synchronisation via highly precise hardware triggers. We discuss the architecture choices of Python-Microscope that overcome the performance problems often raised against Python and demonstrate the different use cases that drove its design: its integration in user facing projects, namely in the Microscope-Cockpit project; in controlling complex microscopes at high speed while using the Python programming language; and as a microscope simulation tool for software development. Chemomechanically voxelated niches for programmable histogenesis Stem-cell derived tissue models are commonly cultured under globally-delivered stimuli that trigger histogenesis via self-organizing activity. However, the culture of such tissue models is prone to stochastic behavior, limiting the reproducibility of cellular composition and resulting in non-physiological architectures. To overcome these shortcomings, we developed a method for printing cell niche microenvironments with microstructured cues that mediate local histogenic processes, including mechanosensing and differentiation of selected cell types. Microstructured cues include independently tunable mechano-chemical properties, with conjugated peptides, proteins, and morphogens across a range of Youngs moduli. By rationally designing niches, we mediate the structure of tissues derived from stem-cell-progenitor sources, including a bone-fat assembly from stromal mesenchyme, and embryonic tissues derived from hiPSC. We show that microstructured cues can recapitulate mechano-chemical signals resembling early embryonic histogenesis. This outcome includes a role for niche mechanics in human embryonic organization, where soft niche mechanics bias markers of mesendodermal differentiation and epithelial-to-mesenchymal-transition (EMT), as well as a demonstration of a material-mediated morphogen signaling centers able to induce foci of mesenchymal and EMT differentiation. Thus, microstructured materials can mediate local histogenic processes to enhance the structure and composition of tissue models.