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The Pathways Undergraduate Researchers Program is a paid, nine-week summer internship at the Fred Hutchinson Cancer Center. It targets rising first-, second-, and third-year college students from backgrounds underrepresented in biomedical research. This paper describes how the internship impacted students' awareness of biomedical careers, scientific identification, and sense of belonging in research. Interns reported an increased awareness of biomedical careers and how to attain them. The experience also challenged interns' career ideas. Interns described a mix of feelings on sense of belonging. All felt welcomed and confident in their abilities. Nonetheless, some noted they were different from the other researchers. A number were motivated by being in the minority and ready to become leaders in diversifying the workforce. Data gathered during the COVID-19 pandemic shed a different light on the internship's impact. The interns reported becoming "credible resources" on public health issues for their families and communities. The program supported this by building their confidence to understand and communicate science. This undergraduate program developed out of a longer running high school internship effort and many of the strategies described herein are used in both. These findings have implications for programs for underrepresented students at the high school and college level.

Background: Noise is omnipresent in the operating room. The average noise in the operating room generally ranges between 60 and 65 dB and can sometimes exceed 100 dB, despite the ARS (Agence Régionale de Santé) and WHO (World Health Organization) recommending levels of 35 dB(A). This study aimed to evaluate the effect of different kinds of background auditory stimuli on the performance of surgeons during an arthroscopic simulation task. Methods: Forty-seven surgeons with varying experience in arthroscopic surgery undertook different exercises under four different conditions: quiet, classical music, hard rock, and sustained chatter. All background auditory stimuli were set at 65 dB(A). Each participant underwent double randomization for the four sound stimuli and the four exercises to be performed. A musical questionnaire was also completed by each participant. Data related to each exercise included operating time in seconds, distance from the camera or instruments in centimeters, and an overall score automatically calculated by the simulator based on safety, economy of movement, and speed (scale: 0–20 points). Results: Operative time in an environment with classical music was significantly lower than in an environment with hard rock (95.9 s vs. 128.7 s, p = 0.0003). The overall rating in an environment with chatter was significantly lower than in a silent environment (11.7 vs. 15.7, p

The recent development of FYRE (French hYdroclimate REanalysis) Climate, a high-resolution ensemble daily reanalysis of precipitation and temperature covering the 1871–2012 period and the whole of France, offers the opportunity to derive streamflow series over the country from 1871 onwards. The FYRE Climate dataset has been used as input for hydrological modelling over a large sample of 661 near-natural French catchments using the GR6J (Génie Rural à 6 Paramètres Journaliers) lumped conceptual model. This approach led to the creation of the 25-member hydrological reconstructions, HydRE (Hydrological REconstruction), spanning the 1871–2012 period. Two sources of uncertainties have been taken into account: (1) the climate uncertainty using forcings from all 25 ensemble members provided by FYRE Climate and (2) the streamflow measurement error by perturbing observations used during the calibration. Further, the hydrological model error based on the relative discrepancies between observed and simulated streamflow has been added to derive the HydREM (Hydrological REconstruction with Model error) streamflow reconstructions. These two reconstructions are compared to other hydrological reconstructions with different meteorological inputs, hydrological reconstructions from a machine learning algorithm, and independent and dependent observations. Overall, the results show the added value of the HydRE and HydREM reconstructions in terms of quality, uncertainty estimation, and representation of extremes, therefore allowing us to better understand the variability in past hydrology over France.

Abstract Lobopodians represent a key step in the early history of ecdysozoans since they were the first animals to evolve legs within this clade. Their Cambrian representatives share a similar body plan with a typically cylindrical annulated trunk and a series of non-jointed legs. However, they do not form a monophyletic group and likely include ancestors of the three extant panarthropod lineages (Tardigrada, Onychophora, Euarthropoda). Some species display astonishing protective devices such as cuticular plates and spines. We describe here the armor and molting process of Microdictyon from the early Cambrian of China. Microdictyon secreted ovoid paired cuticular sclerites that were duplicated in a non-synchronous way along the animal’s body. The reticulated pattern and cuticular architecture of these sclerites have similarities to extant armored tardigrades that recently served in hypothesizing that tardigrades are possibly miniaturized lobopodians. Ecdysis and hard cuticular protection are now well documented in the whole spectrum of early Cambrian ecdysozoans such as soft-bodied scalidophorans, lobopodians and fully articulated euarthropods. We hypothesize that the secretion of sclerotized cuticular elements periodically renewed via ecdysis was a key innovation that opened large-scale evolutionary opportunities to invertebrate animal life, specifically ecdysozoans, both in terms of anatomical functionalities and ecological success.

Summary: Super killer (SKI) complex is a well-known cytoplasmic 3′–5′ mRNA decay complex that functions with the exosome to degrade excessive and aberrant mRNAs, is implicated with the extraction of mRNA at stalled ribosomes, tackling aberrant translation. Here, we show that SKIV2L and TTC37 of the hSKI complex are present within the nucleus, localize on chromatin and at some telomeres during the G2 cell cycle phase. In cells, SKIV2L prevents telomere replication stress, independently of its helicase domain, and increases the stability of telomere DNA-RNA hybrids in G2. We further demonstrate that purified hSKI complex binds telomeric DNA and RNA substrates in vitro and SKIV2L association with telomeres is dependent on DNA-RNA hybrids. Taken together, our results provide a nuclear function for SKIV2L of the hSKI complex in overcoming replication stress at telomeres mediated by its recruitment to DNA-RNA hybrid structures in G2 and thus maintaining telomere stability.

IntroductionThe marine microalga Isochrysis galbana is prolific producer of fucoxanthin, which is a xanthophyll carotenoid with substantial global market value boasting extensive applications in the food, nutraceutical, pharmaceutical, and cosmetic industries. This study presented a novel integrated experimental approach coupled with machine learning (ML) models to predict the fucoxanthin content in I. galbana by altering the type and concentration of phytohormone supplementation, thus overcoming the multiple methodological limitations of conventional fucoxanthin quantification.MethodsA novel integrated experimental approach was developed, analyzing the effect of varying phytohormone types and concentrations on fucoxanthin production in I. galbana. Morphological analysis was conducted to assess changes in microalgal structure, while growth rate and fucoxanthin yield correlations were explored using statistical analysis and machine learning models. Several ML models were employed to predict fucoxanthin content, with and without hormone descriptors as variables.ResultsThe findings revealed that the Random Forest (RF) model was highly significant with a high R2 of 0.809 and RMSE of 0.776 when hormone descriptors were excluded, and the inclusion of hormone descriptors further improved prediction accuracy to R2 of 0.839, making it a useful tool for predicting the fucoxanthin yield. The model that fitted the experimental data indicated methyl jasmonate (0.2 mg/L) as an effective phytohormone. The combined experimental and ML approach demonstrated rapid, reliable, and cost-efficient prediction of fucoxanthin yield.DiscussionThis study highlights the potential of machine learning models, particularly Random Forest, to optimize parameters influencing microalgal growth and fucoxanthin production. This approach offers a more efficient alternative to conventional methods, providing valuable insights into improving fucoxanthin production in microalgal cultivation. The findings suggest that leveraging diverse ML models can enhance the predictability and efficiency of fucoxanthin production, making it a promising tool for industrial applications.

OBJECTIVE: Major obstacles to data harmonization in neuropsychology include lack of consensus about what constructs and tests are most important and invariant across healthy and clinical populations. This study addressed these challenges using data from the National Neuropsychology Network (NNN). METHOD: Data were obtained from 5,000 NNN participants and Pearson standardization samples. Analyses included variables from four instruments: Wechsler Adult Intelligence Scale, 4th Edition (WAIS-IV); Wechsler Memory Scale, 4th Edition (WMS-IV); California Verbal Learning Test, 3rd Edition (CVLT3); and Delis-Kaplan Executive Function System (D-KEFS). We used confirmatory factor analysis to evaluate models suggested by prior work and examined fit statistics and measurement invariance across samples. We examined relations of factor scores to demographic and clinical characteristics. RESULTS: For each instrument, we identified four first-order and one second-order factor. Optimal models in patients generally paralleled the best-fitting models in the standardization samples, including task-specific factors. Analysis of the NNN data prompted specification of a Recognition-Familiarity factor on the WMS-IV and an Inhibition-Switching factor on the D-KEFS. Analyses showed strong to strict factorial invariance across samples with expected differences in factor means and variances. The Recognition-Familiarity factor correlated with age more strongly in NNN than in the standardization sample. CONCLUSIONS: Factor models derived from healthy groups generally fit well in patients. NNN data helped identify novel Recognition-Familiarity and Inhibition-Switching factors that were also invariant across samples and may be clinically useful. The findings support efforts to identify evidence-based and optimally efficient measurements of neuropsychological constructs that are valid across groups. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Abstract Given high costs of Oncotype DX (ODX) testing, widely used in recurrence risk assessment for early-stage breast cancer, studies have predicted ODX using quantitative clinicopathologic variables. However, such models have incorporated only small cohorts. Using a cohort of patients from the National Cancer Database (NCDB, n = 53,346), we trained machine learning models to predict low-risk (0-25) or high-risk (26-100) ODX using quantitative estrogen receptor (ER)/progesterone receptor (PR)/Ki-67 status, quantitative ER/PR status alone, and no quantitative features. Models were externally validated on a diverse cohort of 970 patients (median follow-up 55 months) for accuracy in ODX prediction and recurrence. Comparing the area under the receiver operating characteristic curve (AUROC) in a held-out set from NCDB, models incorporating quantitative ER/PR (AUROC 0.78, 95% CI 0.77–0.80) and ER/PR/Ki-67 (AUROC 0.81, 95% CI 0.80–0.83) outperformed the non-quantitative model (AUROC 0.70, 95% CI 0.68–0.72). These results were preserved in the validation cohort, where the ER/PR/Ki-67 model (AUROC 0.87, 95% CI 0.81–0.93, p = 0.009) and the ER/PR model (AUROC 0.86, 95% CI 0.80–0.92, p = 0.031) significantly outperformed the non-quantitative model (AUROC 0.80, 95% CI 0.73–0.87). Using a high-sensitivity rule-out threshold, the non-quantitative, quantitative ER/PR and ER/PR/Ki-67 models identified 35%, 30% and 43% of patients as low-risk in the validation cohort. Of these low-risk patients, fewer than 3% had a recurrence at 5 years. These models may help identify patients who can forgo genomic testing and initiate endocrine therapy alone. An online calculator is provided for further study.

Abstract Diazotrophs provide a significant reactive nitrogen source in the ocean. Increased warming and stratification may decrease nutrient availability in the future, forcing microbial communities toward using dissolved organic matter (DOM). Not depending on reactive nitrogen availability, diazotrophs may be “winners” in a nutrient‐depleted ocean. However, their ability to exploit DOM may influence this success. We exposed cultures of the widespread Crocosphaera to low (26°C, pH 8.1), moderate (28°C, pH 8.0), and extreme (30°C, pH 7.9) climate change scenarios, under control or DOM‐amended conditions. Growth was suboptimal in the low and extreme treatments and favored in the moderate treatment. DOM was preferred as a carbon source regardless of the treatment and promoted N2 fixation in extreme conditions. This was reflected in the increased expression of photosynthesis genes to obtain energy. DOM provides Crocosphaera with a key ecological advantage, possibly dictating diazotroph‐derived nitrogen inputs in the future ocean.

Abstract Glucocorticoid (GC) resistance in childhood relapsed B-cell acute lymphoblastic leukemia (B-ALL) represents an important challenge. Despite decades of clinical use, the mechanisms underlying resistance remain poorly understood. Here, we report that in B-ALL, GC paradoxically induce their own resistance by activating a phospholipase C (PLC)-mediated cell survival pathway through the chemokine receptor, CXCR4. We identify PLC as aberrantly activated in GC-resistant B-ALL and its inhibition is able to induce cell death by compromising several transcriptional programs. Mechanistically, dexamethasone (Dex) provokes CXCR4 signaling, resulting in the activation of PLC-dependent Ca2+ and protein kinase C signaling pathways, which curtail anticancer activity. Treatment with a CXCR4 antagonist or a PLC inhibitor improves survival of Dex-treated NSG mice in vivo. CXCR4/PLC axis inhibition significantly reverses Dex resistance in B-ALL cell lines (in vitro and in vivo) and cells from Dex resistant ALL patients. Our study identifies how activation of the PLC signalosome in B-ALL by Dex limits the upfront efficacy of this chemotherapeutic agent.

Strontium ions can be removed from wastewater in fixed-bed reactors by adsorption on hierarchical materials (different pore sizes and phases). A detailed understanding of the materials multiscale structure is therefore crucial to optimize their sorption properties. This article presents a multi-technique approach developed to characterize the relationship between microstructure and adsorption in a range of Linde-type A (LTA) zeolite-geopolymer composites,. Two-dimensional scanning electron microscopy and 3D X-ray tomography were used to image the porous and solid phases at different length scales. Advanced numerical methods involving machine learning were applied to segment the images and provide quantitative morphological values describing the porous network geometry and the location and accessibility of the zeolite particles in the geopolymer. These results were then correlated with the materials sorption properties, measured in batch and column processes. Increasing the materials zeolite content (from 0 to 27 wt%) slowed down their adsorption kinetics but increased their maximal adsorption capacities from 20 to 49 mg.g−1 and Sr2+-selectivity at equilibrium. In breakthrough experiments, the material with highest zeolite content had a much higher breakthrough volume passing from 169 to 478 ml in the presented experimental conditions (much higher wastewater decontamination capacity), but a shallower breakthrough curve (lower column efficiency).

Extant ecdysozoans (moulting animals) are represented by a great variety of soft-bodied or articulated organisms that may or may not have appendages. However, controversies remain about the vermiform nature (i.e. elongated and tubular) of their ancestral body plan. We describe here Beretella spinosa gen. et sp. nov. a tiny (maximal length 3 mm) ecdysozoan from the lowermost Cambrian, Yanjiahe Formation, South China, characterized by an unusual sack-like appearance, single opening, and spiny ornament. Beretella spinosa gen. et sp. nov has no equivalent among animals, except Saccorhytus coronarius, also from the basal Cambrian. Phylogenetic analyses resolve both fossil species as a sister group (Saccorhytida) to all known Ecdysozoa, thus suggesting that ancestral ecdysozoans may have been non-vermiform animals. Saccorhytids are likely to represent an early off-shot along the stem-line Ecdysozoa. Although it became extinct during the Cambrian, this animal lineage provides precious insight into the early evolution of Ecdysozoa and the nature of the earliest representatives of the group.

Abstract The identification of processes activated by specific microbes during microbiota colonization of plant roots has been hampered by technical constraints in metatranscriptomics. These include lack of reference genomes, high representation of host or microbial rRNA sequences in datasets, or difficulty to experimentally validate gene functions. Here, we recolonized germ-free Arabidopsis thaliana with a synthetic, yet representative root microbiota comprising 106 genome-sequenced bacterial and fungal isolates. We used multi-kingdom rRNA depletion, deep RNA-sequencing and read mapping against reference microbial genomes to analyse the in planta metatranscriptome of abundant colonizers. We identified over 3,000 microbial genes that were differentially regulated at the soil-root interface. Translation and energy production processes were consistently activated in planta, and their induction correlated with bacterial strains’ abundance in roots. Finally, we used targeted mutagenesis to show that several genes consistently induced by multiple bacteria are required for root colonization in one of the abundant bacterial strains (a genetically tractable Rhodanobacter). Our results indicate that microbiota members activate strain-specific processes but also common gene sets to colonize plant roots.

Elucidation of pathways regulating parasite cell death is believed to contribute to identification of novel therapeutic targets for protozoan diseases, and in this context, apoptosis-like cell death has been reported in different groups of protozoa, in which metacaspases seem to play a role. In the genus Plasmodium, apoptotic markers have been detected in P. falciparum and P. berghei, and no study focusing on P. vivax cell death has been reported so far. In the present study, we investigated the susceptibility of P. vivax to undergo apoptotic cell death after incubating mature trophozoites with the classical apoptosis inducer staurosporine. As assessed by flow cytometry assays, staurosporine inhibited parasite intraerythrocytic development, which was accompanied by a decrease in cell viability, evidenced by reduced plasmodial mitochondrial activity. However, typical signs of apoptosis, such as DNA fragmentation, chromatin condensation, and nuclear segregation, were not detected in the parasites induced to cell death, and no significant alteration in metacaspase gene expression (PvMCA1) was observed under cell death stimulus. Interestingly, dying parasites positively modulated cell death (eryptosis) of host erythrocytes, which was marked by externalization of phosphatidylserine and cell shrinkage. Our study shows for the time that P. vivax blood stages may not be susceptible to apoptosis-like processes, while they could trigger eryptosis of parasitized cells by undergoing cell death. Further studies are required to elucidate the cellular machinery involved in cell death of P. vivax parasites as well as in the modulation of host cell death.

Published by Érès with the support of the Centre national du livre, the simple review of the introduction to this collection would already be satisfying. Not that the “revised and expanded” texts proposed by Jean-Claude Maleval are of limited interest. Quite the contrary. However, the dozen or so pages that open these Psychoanalytical Conversations with Ordinary and Extraordinary Psychotics contain assertions and other clinical innovations capable of shaking the doctrinal tree. Certainly, there is no surprise in this author''s constant and incisive criticism of the “dead end of the descriptive strategy” adopted by successive DSMs and reduced to independent of human history and cultural variations”. Moreover, this in an environment characterized by a “spectacular” increase in requests for psychoanalysis by subjects with a psychotic structure. The clinician briefly explains the reasons: the introduction of the diagnosis of ordinary psychosis, the sharpening of its identification and a better knowledge of the conduct of the treatment. A trend reinforced a contrario by the negative effects of a “deterioration of the conditions in which patients receive in psychiatric institutions”.

Objectives To estimate prevalence, incidence and mortality rates, and annual healthcare costs of primary Sjögren’s syndrome (pSS) and SS associated with other autoimmune disorders (SS+AID) in France.Methods French national healthcare claims-based study within the prospective Système National des Données de Santé database that includes the majority of the French population. An algorithm was developed to identify patients with SS and SS-related healthcare claims were analysed between 2011 and 2018.Results Overall, 23 848 patients with pSS and 14 809 with SS+AID were identified. From 2011 to 2018, the prevalence rate increased slightly for pSS (23–32 per 100000) and SS+AID (16–20 per 100 000), with females comprising 90%–91% and 92%–93% of cases, respectively. The incidence rate of SS per 100 000 persons decreased from 2012 (pSS: 4.3; SS+AID: 2.0) to 2017 (pSS: 0.7; SS+AID: 0.3). Mortality rates per 100 000 persons increased from 2012 to 2018 in patients with pSS (0.2–0.8) or SS+AID (0.1–0.5); mean age of death also increased. Artificial tears and hydroxychloroquine were the most common drug reimbursements. Less than half of patients received annual specialist care from a dentist or ophthalmologist. Healthcare costs associated with SS increased from 2011 to 2018 and exceeded the national estimate of expected costs for chronic diseases.Conclusion In this large French population database study, the low prevalence of pSS confirms that it is an orphan disease. SS is clinically and economically burdensome; these findings may help clinicians better understand routine healthcare received by patients.

Lynch syndrome is the most common autosomal dominant inherited cancer predisposing syndrome, due to mutations in DNA mismatch repair genes. The key feature of cancers in Lynch syndrome is microsatellite instability and a high risk of developing mainly colorectal and uterine cancers. However, cancers with microsatellite instability outside this spectrum, for example, lung cancer, are extremely rare. Here, we report a case of squamous cell carcinoma of the lung with microsatellite instability in a patient with Lynch syndrome.

Abstract Background Precision oncology, defined as treatment of patients with targeted therapies matched to specific molecular alterations, has entered routine clinical practice. Particularly in patients with advanced cancer or hematologic malignancies, for whom no further standard therapies are available, this approach is increasingly applied as last resort option outside of the approved indication. However, data on patient outcomes are not systematically collected, analyzed, reported, and shared. We have initiated the INFINITY registry to provide evidence from routine clinical practice to fill this knowledge gap. Methods INFINITY is a retrospective, non-interventional cohort study conducted at approximately 100 sites in Germany (office-based oncologists/hematologists and hospitals). We aim to include 500 patients with advanced solid tumors or hematologic malignancies who received a non-standard targeted therapy based on potentially actionable molecular alterations or biomarkers. INFINITY aims to provide insights into the use of precision oncology in routine clinical practice within Germany. We systematically collect details on patient and disease characteristics, molecular testing, clinical decision-making, treatment, and outcome. Discussion INFINITY will provide evidence on the current biomarker landscape driving treatment decisions in routine clinical care. It will also provide insights on effectiveness of precision oncology approaches in general, and of specific drug class/alteration matches used outside their approved indications. Trial registration The study is registered at ClinicalTrials.gov, NCT04389541.

Abstract Phytoplankton play a crucial role in the marine food web and are sensitive indicators of environmental change. Iceland is at the center of a contrasting hydrography, with cold Arctic water coming in from the north and warmer Atlantic water from the south, making this geographical location very sensitive to climate change. We used DNA metabarcoding to determine the biogeography of phytoplankton in this area of accelerating change. Seawater samples were collected in spring (2012–2018), summer (2017) and winter (2018) together with corresponding physico-chemical metadata around Iceland. Amplicon sequencing of the V4 region of the 18S rRNA gene indicates that eukaryotic phytoplankton community composition is different between the northern and southern water masses, with some genera completely absent from Polar Water masses. Emiliania was more dominant in the Atlantic-influenced waters and in summer, and Phaeocystis was more dominant in the colder, northern waters and in winter. The Chlorophyta picophytoplankton genus, Micromonas, was similarly dominant to the dominant diatom genus, Chaetoceros. This study presents an extensive dataset which can be linked with other 18s rRNA datasets for further investigation into the diversity and biogeography of marine protists in the North Atlantic.

Abstract Background Rice is the second most produced crop worldwide, but is highly susceptible to drought. Micro-organisms can potentially alleviate the effects of drought. The aim of the present study was to unravel the genetic factors involved in the rice-microbe interaction, and whether genetics play a role in rice drought tolerance. For this purpose, the composition of the root mycobiota was characterized in 296 rice accessions (Oryza sativa L. subsp. indica) under control and drought conditions. Genome wide association mapping (GWAS) resulted in the identification of ten significant (LOD > 4) single nucleotide polymorphisms (SNPs) associated with six root-associated fungi: Ceratosphaeria spp., Cladosporium spp., Boudiera spp., Chaetomium spp., and with a few fungi from the Rhizophydiales order. Four SNPs associated with fungi-mediated drought tolerance were also found. Genes located around those SNPs, such as a DEFENSIN-LIKE (DEFL) protein, EXOCYST TETHERING COMPLEX (EXO70), RAPID ALKALINIZATION FACTOR-LIKE (RALFL) protein, peroxidase and xylosyltransferase, have been shown to be involved in pathogen defense, abiotic stress responses and cell wall remodeling processes. Our study shows that rice genetics affects the recruitment of fungi, and that some fungi affect yield under drought. We identified candidate target genes for breeding to improve rice-fungal interactions and hence drought tolerance.

Abstract The capillary-venous pathology cerebral cavernous malformation (CCM) is caused by loss of CCM1/Krev interaction trapped protein 1 (KRIT1), CCM2/MGC4607, or CCM3/PDCD10 in some endothelial cells. Mutations of CCM genes within the brain vasculature can lead to recurrent cerebral hemorrhages. Pharmacological treatment options are urgently needed when lesions are located in deeply-seated and in-operable regions of the central nervous system. Previous pharmacological suppression screens in disease models of CCM led to the discovery that treatment with retinoic acid improved CCM phenotypes. This finding raised a need to investigate the involvement of retinoic acid in CCM and test whether it has a curative effect in preclinical mouse models. Here, we show that components of the retinoic acid synthesis and degradation pathway are transcriptionally misregulated across disease models of CCM. We complemented this analysis by pharmacologically modifying retinoic acid levels in zebrafish and human endothelial cell models of CCM, and in acute and chronic mouse models of CCM. Our pharmacological intervention studies in CCM2-depleted human umbilical vein endothelial cells (HUVECs) and krit1 mutant zebrafish showed positive effects when retinoic acid levels were increased. However, therapeutic approaches to prevent the development of vascular lesions in adult chronic murine models of CCM were drug regiment-sensitive, possibly due to adverse developmental effects of this hormone. A treatment with high doses of retinoic acid even worsened CCM lesions in an adult chronic murine model of CCM. This study provides evidence that retinoic acid signaling is impaired in the CCM pathophysiology and suggests that modification of retinoic acid levels can alleviate CCM phenotypes.

Fate specification in the mammalian epiblast rely on complex interactions between morphogens and tissue organization. Here, the authors highlight epithelial integrity as a key determinant of TGF-β activity and a mechanism guiding morphogen sensing and spatial cell fate change.

Abstract Background From a theoretical ecology point of view, microbiomes are far more complex than expected. Besides competition and competitive exclusion, cooperative microbe-microbe interactions have to be carefully considered. Metabolic dependencies among microbes likely explain co-existence in microbiota. Methodology In this in silico study, we explored genome-scale metabolic models (GEMs) of 193 bacteria isolated from Arabidopsis thaliana roots. We analyzed their predicted producible metabolites under simulated nutritional constraints including “root exudate-mimicking growth media” and assessed the potential of putative metabolic exchanges of by- and end-products to avoid those constraints. Results We found that the genome-encoded metabolic potential is quantitatively and qualitatively clustered by phylogeny, highlighting metabolic differentiation between taxonomic groups. Random, synthetic combinations of increasing numbers of strains (SynComs) indicated that the number of producible compounds by GEMs increased with average phylogenetic distance, but that most SynComs were centered around an optimal phylogenetic distance. Moreover, relatively small SynComs could reflect the capacity of the whole community due to metabolic redundancy. Inspection of 30 specific end-product metabolites (i.e., target metabolites: amino acids, vitamins, phytohormones) indicated that the majority of the strains had the genetic potential to produce almost all the targeted compounds. Their production was predicted (1) to depend on external nutritional constraints and (2) to be facilitated by nutritional constraints mimicking root exudates, suggesting nutrient availability and root exudates play a key role in determining the number of producible metabolites. An answer set programming solver enabled the identification of numerous combinations of strains predicted to depend on each other to produce these targeted compounds under severe nutritional constraints thus indicating a putative sub-community level of functional redundancy. Conclusions This study predicts metabolic restrictions caused by available nutrients in the environment. By extension, it highlights the importance of the environment for niche potential, realization, partitioning, and overlap. Our results also suggest that metabolic dependencies and cooperation among root microbiota members compensate for environmental constraints and help maintain co-existence in complex microbial communities. Video Abstract

Antibodies to SARS-CoV-2 are central to recovery and immunity from COVID-19. However, the relationship between disease severity and the repertoire of antibodies against specific SARS-CoV-2 epitopes an individual develops following exposure remains incompletely understood. Here, we studied seroprevalence of antibodies to specific SARS-CoV-2 and other betacoronavirus antigens in a well-annotated, community sample of convalescent and never-infected individuals obtained in August 2020. One hundred and twenty-four participants were classified into five groups: previously exposed but without evidence of infection, having no known exposure or evidence of infection, seroconverted without symptoms, previously diagnosed with symptomatic COVID-19, and recovered after hospitalization with COVID-19. Prevalence of IgGs specific to the following antigens was compared between the five groups: recombinant SARS-CoV-2 and betacoronavirus spike and nucleocapsid protein domains, peptides from a tiled array of 22-mers corresponding to the entire spike and nucleocapsid proteins, and peptides corresponding to predicted immunogenic regions from other proteins of SARS-CoV-2. Antibody abundance generally correlated positively with severity of prior illness. A number of specific immunogenic peptides and some that may be associated with milder illness or protection from symptomatic infection were identified. No convincing association was observed between antibodies to Receptor Binding Domain(s) (RBDs) of less pathogenic betacoronaviruses HKU1 or OC43 and COVID-19 severity. However, apparent cross-reaction with SARS-CoV RBD was evident and some predominantly asymptomatic individuals had antibodies to both MERS-CoV and SARS-CoV RBDs. Findings from this pilot study may inform development of diagnostics, vaccines, and therapeutic antibodies, and provide insight into viral pathogenic mechanisms.

Summary: Severe acute malnutrition (SAM) is a multifactorial disease affecting millions of children worldwide. It is associated with changes in intestinal physiology, microbiota, and mucosal immunity, emphasizing the need for multidisciplinary studies to unravel its full pathogenesis. We established an experimental model in which weanling mice fed a high-deficiency diet mimic key anthropometric and physiological features of SAM in children. This diet alters the intestinal microbiota (less segmented filamentous bacteria, spatial proximity to epithelium), metabolism (decreased butyrate), and immune cell populations (depletion of LysoDC in Peyer’s patches and intestinal Th17 cells). A nutritional intervention leads to a fast zoometric and intestinal physiology recovery but to an incomplete restoration of the intestinal microbiota, metabolism, and immune system. Altogether, we provide a preclinical model of SAM and have identified key markers to target with future interventions during the education of the immune system to improve SAM whole defects.