Identification of a Golgi-localized altORF peptide reveals a minimal Golgi targeting motif Prior work has identified signal sequences and motifs that are necessary and sufficient to target proteins to specific subcellular regions and organelles such as the plasma membrane, nucleus, Endoplasmic Reticulum, and mitochondria. In contrast, minimal sequence motifs that are sufficient for Golgi localization remain largely elusive. In this work, we identified a 37 amino acid alternative open reading frame (altORF) within the mRNA of the centromere protein, CENP-R. This altORF peptide localizes specifically to the cytoplasmic surface of the Golgi apparatus. Through mutational analysis, we identify a minimal 10 amino acid sequence and a critical cysteine residue that are necessary and sufficient for Golgi localization. Pharmacological perturbations suggest that this peptide is modified through palmitoylation to promote its localization. Together, our work defines a minimal sequence that is sufficient for Golgi targeting and provide a valuable Golgi marker for live cell imaging.
A novel sodium signaling complex regulates uterine activity Depolarization of the myometrial smooth muscle cell (MSMC) resting membrane potential is necessary for the transition of the uterus from a quiescent state to a contractile state. The molecular mechanisms involved in this transition are not completely understood. Here, we report a novel coupled system between the Na+-activated K+ channel (SLO2.1) and the non-selective Na+ leak channel (NALCN) which determines the MSMC membrane potential. We show that SLO2.1 currents are activated by an inward Na+ leak current carried by the NALCN channel leading to MSMC hyperpolarization. These results show an unanticipated role for the Na+ leak currents in activating a negative feedback system countering the excitable effects of Na+ currents. This is a novel role for the NALCN channel in which Na+ acts as an intracellular signaling molecule. In fact, we report here that the net effect of Na+ entry through NALCN channels is a hyperpolarization of the MSMCs plasma membrane because of the activation of SLO2.1 K channel. Importantly, we also report that a decrease in NALCN/SLO2.1 activity triggers both Ca2+ entries through VDCCs, promoting myometrial contraction. Consistently, with a functional coupling, our data show that NALCN and SLO2.1 are in proximity to one another in human MSMCs. We propose that the spatial arrangement of SLO2.1 and NALCN permits these channels to functionally interact in order to regulate human MSMC membrane potential and cell excitability to modulate uterine contractile activity.
NPEPPS regulates intracellular import and sensitivity to cisplatin by interaction with volume regulated anion channels Despite routine use of platinum-based chemotherapeutics in cancer treatment, there remains a need to improve efficacy and patient selection. Multi-omic assessment of human bladder cancer cell lines and their cisplatin resistant derivatives and whole-genome CRISPR screens identified NPEPPS, the puromycin-sensitive aminopeptidase as a novel driver of cisplatin resistance. NPEPPS depletion increased cisplatin import and sensitization of resistant cells in vitro and in vivo. Pharmacologic inhibition of NPEPPS in cells and chemoresistant, patient-derived tumor organoids improved response to cisplatin. NPEPPS was found in complex with volume regulated anion channel (VRAC) subunits LRRC8A and LRRC8D, whose loss is known to enhance resistance to cisplatin. Depletion of LRRC8A the only obligate subunit for normal VRAC function abrogated the effect of NPEPPS-mediated cisplatin import. Our findings describe the first mechanism by which VRACs can be targeted for therapeutic benefit.

HIGHLIGHTSO_LIMulti-omic screening found NPEPPS is a driver of cisplatin resistance in cancer
C_LIO_LINPEPPS is in protein complex with LRRC8A and D, volume regulated anion channel (VRAC) subunits
C_LIO_LILRRC8A and D loss increases cisplatin resistance and reduce its intracellular levels
C_LIO_LINPEPPS regulates cisplatin import and sensitivity through VRACs
C_LIO_LINPEPPS function is inhibited by small molecules offering potential for clinical translation
C_LI Non-specific effects of a CINNAMATE-4-HYDROXYLASE inhibitor on auxin homeostasis Chemical inhibitors are often implemented for the functional characterization of genes to overcome the limitations associated with genetic approaches. Although being a powerful tool, off-target effects of these inhibitors are easily overlooked in a complex biological setting. Here we illustrate the implications of such secondary effects by focusing on piperonylic acid (PA), an inhibitor of CINNAMATE-4-HYDROXYLASE (C4H) that is often used to investigate the involvement of lignin during plant growth and development. When supplied to plants, we found that PA is recognized as a substrate by GRETCHEN HAGEN 3.6 (GH3.6), an amido synthetase involved in the formation of the auxin catabolite indole-3-acetic acid (IAA)-Asp. By competing for the same enzyme, PA interferes with auxin conjugation, resulting in an increase in cellular auxin concentrations. These increased auxin levels likely further contribute to an increase in adventitious rooting previously observed upon PA-treatment. Despite the focus on GH3.6 in this report, PA is conjugated by an array of enzymes and their subsequent reduced activity on native substrates could potentially affect a whole set of physiological processes in the plant. We conclude that surrogate occupation of the endogenous conjugation machinery in the plant by exogenous compounds is likely a more general phenomenon that is rarely considered in pharmacological studies. Our results hereby provide an important basis for future reference in studies using chemical inhibitors. Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors. Physiological Substrates and Ontogeny-Specific Expression of the Ubiquitin Ligases MARCH1 and MARCH8 MARCH1 and MARCH8 are ubiquitin ligases that control the expression and trafficking of critical immunoreceptors. Understanding of their function is hampered by three major knowledge gaps: (i) it is unclear which cell types utilize these ligases; (ii) their level of redundancy is unknown; and (iii) most of their putative substrates have been described in cell lines, often overexpressing MARCH1 or MARCH8, and it is unclear which substrates are regulated by either ligase in vivo. Here we address these questions by systematically analyzing the immune cell repertoire of MARCH1- or MARCH8-deficient mice, and applying unbiased proteomic profiling of the plasma membrane of primary cells to identify MARCH1 and MARCH8 substrates. Only CD86 and MHC II were unequivocally identified as immunoreceptors regulated by MARCH1 and MARCH8, but each ligase carried out its function in different tissues. MARCH1 regulated MHC II and CD86 in professional and "atypical" antigen presenting cells of hematopoietic origin, whereas MARCH8 only operated in non-hematopoietic cells. Our results reveal that the range of cells constitutively endowed with antigen-presentation capacity is wider than generally appreciated. They also establish MARCH1 and MARCH8 as specialized regulators of CD4+ T cell immunity in two ontogenically distinct cellular compartments. Propionate ameliorates diabetes-induced neurological dysfunction through regulating the PI3K/Akt/eNOS signaling pathway A large body of research has established diabetes-related cognitive deterioration, sometimes known as "diabetic encephalopathy." Current evidence supports that oxidative stress, neuronal apoptosis, and cerebral microcirculation weakness are associated with cognition deficits induced by diabetes. The present study explores the effect of propionate on neurological deficits, cerebral blood flow, and oxidative stress in diabetic mice. Propionate can markedly improve neurological function, which is correlated with its capabilities of stimulating nitric oxide (NO) production, increasing cerebral microcirculation, suppressing oxidative stress and reducing neuron loss in the hippocampus. In addition, the results of Western Blotting indicated that the brain-protective function of propionate in streptozocin (STZ)-induced insulin-dependent diabetes mellitus (IDDM) mice is related to phosphoinositide 3-kinase (PI3K)/serine-threonine protein kinase (Akt)/endothelial nitric oxide synthase(eNOS) signaling pathway. In a diabetic mouse model, propionate reduces cerebral microcirculation, hippocampus apoptosis, and neurological impairment. Thus, propionate, now employed as a food preservative, may also help slow diabetes-induced cognitive loss.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/464493v2_ufig1.gif" ALT="Figure 1">
View larger version (27K):
org.highwire.dtl.DTLVardef@81fa09org.highwire.dtl.DTLVardef@1469451org.highwire.dtl.DTLVardef@b37fa1org.highwire.dtl.DTLVardef@8037e7_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIPropionate ameliorates diabetic-induced depression-like behavior, spatial learning and memory deficits.
C_LIO_LIPropionate increases cerebral microcirculation by enhancing NO production in diabetic mice.
C_LIO_LIPropionate suppresses oxidative stress and reduces neuron loss in the hippocampus.
C_LIO_LIThe brain-protective function of propionate is related to PI3K/Akt/eNOS signaling pathway.
C_LI Is a Ring-arranged Vascular Pattern Unique to Stems? A Three Dimensional Reconstruction of Anaxagorea (Annonaceae) Carpel Vasculature and its Evolutionary Implications Elucidating the origin of carpel has been a challenge in botany for a long time. The Unifying Theory suggested that the carpel originate from a composite organ comprising an ovule-bearing shoot and a foliar part enclosing the shoot. A logical inference from this theory is that placenta in angiosperms should have radiosymmetrical vasculature, just like that in a young branch. Anaxagorea is the most basal genus of the primitive angiosperm family, Annonaceae. The conspicuous carpel stipe makes it an ideal material for exploring the carpel vasculature. In this study, serial sections of flower and carpel were delineated in Anaxagorea luzonensis and A. javanica, and a three-dimensional model of the carpel vasculature was reconstructed. The results show that (1) vascular bundles at both the carpel stipe and the ovule/placenta are in a radiosymmetrical pattern, (2) the amphicribral bundles would develop into ring-arranged bundle complex with the carpel maturation, (3) the ovule/placenta bundles were separated from the bundles of the carpel wall, and, (4) all the radiosymmetrical vasculature (including amphicribral bundles and ring-arranged bundle complexes) in the carpel were fed by a larger radiosymmetrical bundle system. These results suggest that the radiosymmetrical pattern of carpel vasculature are in line with the Unifying Theory. A pilot study on the home range and movement patterns of the Andean Fox Lycalopex culpaeus (Molina 1782) in Cotopaxi National Park, Ecuador This study reports movement patterns and home range estimates of an Andean fox (Lycalopex culpaeus) in Cotopaxi National Park in Ecuador, representing the first GPS-tagging of the species. The GPS functioned well during the 197-day tracking period. Home range sizes ranged between 4.9 - 8.1 km2, depending on the estimation method. Movement speeds averaged 0.17 km/hr at day vs. 0.87 km/hr. at night, and distance traveled averaged 0.23 km at day vs. 0.89 km at night. These preliminary results highlight the importance of collecting unbiased, high-quality data which enables an enhanced understanding on mammal behavior and human/animal interaction. ABPP-HT* - Deep meets fast for activity-based profiling of deubiquitylating enzymes using advanced DIA mass spectrometry methods Activity-based protein profiling (ABPP) uses a combination of activity-based chemical probes with mass spectrometry (MS) to selectively characterise a particular enzyme or enzyme class. ABPP has proven invaluable for profiling enzymatic inhibitors in drug discovery. When applied to cell extracts and cells, challenging the ABP-enzyme complex formation with a small molecule can simultaneously inform on potency, selectivity, reversibility/binding affinity, permeability, and stability. ABPP can also be applied to pharmacodynamic studies to inform on cellular target engagement within specific organs when applied to in vivo models. Recently, we established separate high depth and high throughput ABPP (ABPP-HT) protocols for the profiling of deubiquitylating enzymes (DUBs). However, the combination of the two, deep and fast, in one method has been elusive. To further increase the sensitivity of the current ABPP-HT workflow we implemented state-of-the-art data-independent acquisition (DIA) and data-dependent acquisition (DDA) MS analysis tools. Hereby, we describe an improved methodology, ABPP-HT* (enhanced high-throughput-compatible activity-based protein profiling), that in combination with DIA MS methods allowed for the consistent profiling of 35-40 DUBs and provided a reduced number of missing values, whilst maintaining a throughput of 100 samples per day. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. The Neural Basis of Delayed Gratification Balancing instant gratification versus delayed, but better gratification is important for optimizing survival and reproductive success. Although psychologists and neuroscientists have long attempted to study delayed gratification through human psychological and brain activity monitoring, and animal research, little is known about its neural basis. We successfully trained mice to perform a waiting-and-water-reward delayed gratification task and used these animals in physiological recording and optical manipulation of neuronal activity during the task to explore its neural basis. Our results showed that the activity of DA neurons in ventral tegmental area (VTA) increases steadily during the waiting period. Optical activation vs. silencing of these neurons, respectively, extends or reduces the duration of waiting. To interpret this data, we developed a reinforcement learning (RL) model that reproduces our experimental observations. In this model, steady increases in DAergic activity signal the value of waiting and support the hypothesis that delayed gratification involves real-time deliberation.

TEASERSustained ramping dopaminergic activation helps individuals to resist impulsivity and wait for laerger but later return. A Positive Correlation between Bacterial GC Content and Growth Temperature BackgroundGC pairs are generally more stable than AT pairs; GC-rich genomes were proposed to be more adapted to high temperatures than AT-rich genomes. Previous studies consistently showed positive correlations between growth temperature and the GC contents of structural RNA genes. However, for the whole genome sequences and the silent sites of the codons in protein-coding genes, the relationship between GC content and growth temperature is in a long-lasting debate.

ResultsWith a dataset much larger than previous studies (681 bacteria and 155 archaea with completely assembled genomes), our phylogenetic comparative analyses showed positive correlations between optimal growth temperature (Topt) and GC content both in bacterial and archaeal structural RNA genes and in bacterial whole genome sequences, chromosomal sequences, plasmid sequences, core genes, and accessory genes. However, in the 155 archaea, we did not observe a significant positive correlation of Topt with whole-genome GC content (GCw) or GC content at four-fold degenerate sites. We randomly drew 155 samples from the 681 bacteria for 1000 rounds. In most cases (> 95%), the positive correlations between Topt and genomic GC contents became statistically nonsignificant (P > 0.05). This result suggested that the small sample sizes might account for the lack of positive correlations between growth temperature and genomic GC content in the 155 archaea and the bacterial samples of previous studies. Comparing the GC content among four categories (psychrophiles/psychrotrophiles, mesophiles, thermophiles, and hyperthermophiles) also revealed a positive correlation between GCw and growth temperature in bacteria. By including the GCw of incompletely assembled genomes, we expanded the sample size of archaea to 303. Positive correlations between GCw and Topt appear especially after excluding the halophilic archaea whose GC contents might be are strongly shaped by intense UV radiation.

ConclusionsThis study explains the previous contradictory observations and ends a long debate. Prokaryotes growing in high temperatures have higher GC contents. Thermal adaptation is one possible explanation for the positive association. Meanwhile, we propose that the elevated efficiency of DNA repair in response to heat mutagenesis might have the by-product of increasing GC content like that happens in intracellular symbionts and marine bacterioplankton. 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. RNA-guided Cas12a and Cas9 knockout and knockin of the omega-1 locus of Schistosoma mansoni We compared the efficiency of gene knockout (KO) and precision of insertion (knock-in, KI) of the RNA-guided AsCas12a nuclease of Acidaminococcus sp. with that of SpCas9 from Streptococcus pyogenes, aiming to enhance the functional genomics toolkit for Schistosoma mansoni. Programmed DNA cleavages catalyzed by Cas12a and Cas9 result in staggered and blunt ended strand breaks, respectively. TTTV, the optimal protospacer adjacent motif for AsCas12a would occur frequently within the AT-rich genome of this platyhelminth. We deployed optimized conditions for the ratio of guide RNAs to the nuclease, donor templates, and electroporation parameters, to target a key enzyme termed omega-1 that is secreted by the schistosome egg. AsCas12a was more efficient than SpCas9 for gene knockout of omega-1 as determined by tracking of indels by decomposition (P < 0.001). Resulting from CRISPREsso2 analysis, most mutations were deletions; SpCas9 induced short deletions of 3 nt in length whereas AsCas12a induced deletions of 2 to 26 nt. Knockout efficiency of both nucleases markedly increased in the presence of short, single stranded oligodeoxynucleotide (ssODN) donor templates. With AsCas12a, ssODNs representative of both the non-CRISPR target (NT) and target (T) strands of the targeted gene were tested, resulting in KO efficiencies of 15.67, 28.71 and 21.43% in the SpCas9 plus donor ssODN, AsCas12a plus NT-ssODN, and AsCas12a plus T-ssODN groups, respectively. Trans cleavage activity against the ssODNs by activated AsCas12a was not apparent in vitro. Programmed SpCas9 editing led to more precise transgene insertion than AsCas12a, with KI efficiencies of 17.07% for the KI_SpCas9 group, 14.58% for KI_AsCas12a-NT-ssODN and 12.37% for KI_AsCas12a-T-ssODN. Although AsCas12a induced fewer mutations per genome than SpCas9, the phenotypic impact on transcription and expression of omega-1 was similar for both nucleases. These findings revealed that AsCas12a and SpCas9 both provide tractable routes for RNA-guided programmed mutation of the genome of the schistosome egg. Evaluation of US state pollinator plans using 3 evidence-based policymaking frameworks After the US federal government created a national pollinator protection plan in 2015, many states followed with their own. Since their goal is to promote pollinating insect conservation, we wanted to know whether the state plans are using best practices for evidence-based science policy. In early 2019 we found and downloaded every existing, publicly available US state pollinator protection plan. We then used content analysis to assess the goals, scope, and implementation of state-level pollinator protection plans across the US. This analysis was conducted using three distinct frameworks for evidence-based policymaking: US Department of Interior Adaptive Resources Management (ARM), US Environmental Protection Agency management pollinator protection plan (MP3) guidance, and Pew Trusts Pew-MacAthur Results First Project elements of evidence-based state policymaking (PEW) framework. Then we scored them using the framework criteria, to assess whether the plans were using known best practices for evidence based policymaking. Of the 31 states with a state pollinator plan, Connecticut was the state with the lowest total score across the three evaluation frameworks. The state with the highest overall scores, across the three frameworks, was Missouri. Most states did not score highly on the majority of the frameworks. Overall, many state plans were lacking policy elements that address monitoring, evaluation, and adjustment. These missing elements impact states ability to achieve their conservation goals. Our results indicate that states can improve their pollinator conservation policies to better match evidence-based science policy guidance, regardless of which framework is used. 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. Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism-targeting as a promising antiviral strategy. 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. 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. LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2 The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length, and are thus infeasible for coronaviruses, which possess the longest genomes ([~]30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurbo-Folds purely in silico prediction not only is close to experimentally-guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5 and 3 UTRs ([~]29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies novel conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, siRNAs, CRISPR-Cas13 guide RNAs and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies, and will be a useful tool in fighting the current and future pandemics.

Significance StatementConserved RNA structures are critical for designing diagnostic and therapeutic tools for many diseases including COVID-19. However, existing algorithms are much too slow to model the global structures of full-length RNA viral genomes. We present LinearTurboFold, a linear-time algorithm that is orders of magnitude faster, making it the first method to simultaneously fold and align whole genomes of SARS-CoV-2 variants, the longest known RNA virus ([~]30 kilobases). Our work enables unprecedented global structural analysis and captures long-range interactions that are out of reach for existing algorithms but crucial for RNA functions. LinearTurboFold is a general technique for full-length genome studies and can help fight the current and future pandemics. First evidence of in vitro cytotoxic effects of marine microlitter on Merluccius merluccius and Mullus barbatus, two Mediterranean commercial fish species Marine litter is composed mainly of plastics and is recognized as a serious threats to marine ecosystems. Ecotoxicological approaches have started elucidating the potential severity of microplastics (MPs) in controlled laboratory studies with pristine materials but no information exist on marine environmental microlitter as a whole. Here, we characterized the litter in the coastal Northern Tyrrhenian sea and in the stomach of two fish species of socio-economic importance, and exposed primary cell cultures of mucosal and lymphoid organs to marine microlitter for evaluating possible cytotoxic effects. An average of 0.30 {+/-} 0.02 microlitter items m-3 was found in water samples. FT-IR analysis revealed that plastic particles, namely HDPE, polyamide and polypropylene were present in 100% and 83.3% of Merluccius merluccius and Mullus barbatus analyzed, which overall ingested 14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual, respectively. Moreover, microlitter was confirmed as a vector of microorganisms. Lastly, the apical end-point of viability was found to be significantly reduced in splenic cells exposed in vitro to two microlitter conditions. Considering the role of the spleen in the mounting of adaptive immune responses, our results warrant more in-depth investigations for clarifying the actual susceptibility of these two species to anthropogenic microlitter.

HighlightsO_LI0.30 {+/-} 0.02 microlitter items m-3 were found at the surface of coastal Northern Tyrrhenian sea
C_LIO_LI14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual were retrieved from the stomach of hakes and mullets
C_LIO_LIThe ingested microlitter contained plastic items
C_LIO_LIMicrolitter was validated as a carrier of bacteria, fungi and flagellates
C_LIO_LISplenic cells exposed to two microlitter conditions for 72 hours suffered cytotoxicity
C_LI The glycocalyx affects the mechanotransductive perception of the topographical microenvironment The cell/microenvironment interface is the starting point of integrin-mediated mechanotransduction, but many details of mechanotransductive signal integration remain elusive due to the complexity of the involved (extra)cellular structures, such as the glycocalyx.

We used nano-bio-interfaces reproducing the complex nanotopographical features of the extracellular matrix to analyse the glycocalyx impact on PC12 cell mechanosensing at the nanoscale (e.g., by force spectroscopy with functionalised probes). Our data demonstrates that the glycocalyx configuration affects spatio-temporal nanotopography-sensitive mechanotransductive events at the cell/microenvironment interface. Opposing effects of glycocalyx removal were observed, when comparing flat and specific nanotopographical conditions. The excessive retrograde actin flow speed and force loading are strongly reduced on certain nanotopographies upon removal of the native glycocalyx, while on the flat substrate we observe the opposite trend.

Our results highlight the importance of the glycocalyx configuration in a molecular clutch force loading-dependent cellular mechanism for mechanosensing of microenvironmental nanotopographical features. 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. A Histoplasma capsulatum lipid metabolic map identifies antifungal targets Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here we built a comprehensive map of the Histoplasma capsulatum lipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression of H. capsulatum genes in Saccharomyces cerevisiae to validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide and the fatty acid analog 10-thiastearic acid inhibit H. capsulatum growth in nanomolar to low micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development. A Novel Paradigm for Deep Reinforcement Learning of Biomimetic Systems Mechanisms behind neural control of movement have been an active area of research. Goal-directed movement is a common experimental setup used to understand these mechanisms and relevant neural pathways. On the one hand, optimal feedback control theory is used to model and make quantitative predictions of the coordinated activations of the effectors, such as muscles, joints or limbs. While on the other hand, evidence shows that higher centres such as Basal Ganglia and Cerebellum are involved in activities such as reinforcement learning and error correction. In this paper, we provide a framework to build a digital twin of relevant sections of the human spinal cord using our NEUROiD platform. The digital twin is anatomically and physiologically realistic model of the spinal cord at cellular, spinal networks and system level. We then build a framework to learn the supraspinal activations necessary to perform a simple goal directed movement of the upper limb. The NEUROiD model is interfaced to an Opensim model for all the musculoskeletal simulations. We use Deep Reinforcement Learning to obtain the supraspinal activations necessary to perform the goal directed movement. As per our knowledge, this is the first time an attempt is made to learn the stimulation pattern at the spinal cord level, especially by limiting the observation space to only the afferent feedback received on the Ia, II and Ib fibers. Such a setup results in a biologically realistic constrained environment for learning. Our results show that (1) Reinforcement Learning algorithm converges naturally to the triphasic response observed during goal directed movement (2) Increasing the complexity of the goal gradually helped to accelerate learning (3) Modulation of the afferent inputs were sufficient to execute tasks which were not explicitly learned, but were closely related to the learnt task.