Discovering genotype-phenotype relationships with machine learning and the Visual Physiology Opsin Database (VPOD).

BACKGROUND: Predicting phenotypes from genetic variation is foundational for fields as diverse as bioengineering and global change biology, highlighting the importance of efficient methods to predict gene functions. Linking genetic changes to phenotypic changes has been a goal of decades of experimental work, especially for some model gene families, including light-sensitive opsin proteins. Opsins can be expressed in vitro to measure light absorption parameters, including λmax-the wavelength of maximum absorbance-which strongly affects organismal phenotypes like color vision. Despite extensive research on opsins, the data remain dispersed, uncompiled, and often challenging to access, thereby precluding systematic and comprehensive analyses of the intricate relationships between genotype and phenotype. RESULTS: Here, we report a newly compiled database of all heterologously expressed opsin genes with λmax phenotypes that we call the Visual Physiology Opsin Database (VPOD). VPOD_1.0 contains 864 unique opsin genotypes and corresponding λmax phenotypes collected across all animals from 73 separate publications. We use VPOD data and deepBreaks to show regression-based machine learning (ML) models often reliably predict λmax, account for nonadditive effects of mutations on function, and identify functionally critical amino acid sites. CONCLUSION: The ability to reliably predict functions from gene sequences alone using ML will allow robust exploration of molecular-evolutionary patterns governing phenotype, will inform functional and evolutionary connections to an organism's ecological niche, and may be used more broadly for de novo protein design. Together, our database, phenotype predictions, and model comparisons lay the groundwork for future research applicable to families of genes with quantifiable and comparable phenotypes.

A link between evolution and society fostering the UN sustainable development goals.

Given the multitude of challenges Earth is facing, sustainability science is of key importance to our continued existence. Evolution is the fundamental biological process underlying the origin of all biodiversity. This phylogenetic diversity fosters the resilience of ecosystems to environmental change, and provides numerous resources to society, and options for the future. Genetic diversity within species is also key to the ability of populations to evolve and adapt to environmental change. Yet, the value of evolutionary processes and the consequences of their impairment have not generally been considered in sustainability research. We argue that biological evolution is important for sustainability and that the concepts, theory, data, and methodological approaches used in evolutionary biology can, in crucial ways, contribute to achieving the UN Sustainable Development Goals (SDGs). We discuss how evolutionary principles are relevant to understanding, maintaining, and improving Nature Contributions to People (NCP) and how they contribute to the SDGs. We highlight specific applications of evolution, evolutionary theory, and evolutionary biology's diverse toolbox, grouped into four major routes through which evolution and evolutionary insights can impact sustainability. We argue that information on both within-species evolutionary potential and among-species phylogenetic diversity is necessary to predict population, community, and ecosystem responses to global change and to make informed decisions on sustainable production, health, and well-being. We provide examples of how evolutionary insights and the tools developed by evolutionary biology can not only inspire and enhance progress on the trajectory to sustainability, but also highlight some obstacles that hitherto seem to have impeded an efficient uptake of evolutionary insights in sustainability research and actions to sustain SDGs. We call for enhanced collaboration between sustainability science and evolutionary biology to understand how integrating these disciplines can help achieve the sustainable future envisioned by the UN SDGs.

Pediatric urinary tract infections caused by poultry-associated Escherichia coli.

Escherichia coli is the leading cause of urinary tract infections (UTIs) in children and adults. The gastrointestinal tract is the primary reservoir of uropathogenic E. coli, which can be acquired from a variety of environmental exposures, including retail meat. In the current study, we used a novel statistical-genomic approach to estimate the proportion of pediatric UTIs caused by foodborne zoonotic E. coli strains. E. coli urine isolates were collected from DC residents aged 2 months to 17 years from the Children's National Medical Center Laboratory, 2013-2014. During the same period, E. coli isolates were collected from retail poultry products purchased from 15 sites throughout DC. A total of 52 urine and 56 poultry isolates underwent whole-genome sequencing, core genome phylogenetic analysis, and host-origin prediction by a Bayesian latent class model that incorporated data on the presence of mobile genetic elements (MGEs) among E. coli isolates from multiple vertebrate hosts. A total of 56 multilocus sequence types were identified among the isolates. Five sequence types-ST10, ST38, ST69, ST117, and ST131-were observed among both urine and poultry isolates. Using the Bayesian latent class model, we estimated that 19% (10/52) of the clinical E. coli isolates in our population were foodborne zoonotic strains. These data suggest that a substantial portion of pediatric UTIs in the Washington DC region may be caused by E. coli strains originating in food animals and likely transmitted via contaminated poultry meat.IMPORTANCEEscherichia coli UTIs are a heavy public health burden and can have long-term negative health consequences for pediatric patients. E. coli has an extremely broad host range, including humans, chickens, turkeys, pigs, and cattle. E. coli derived from food animals is a frequent contaminant of retail meat products, but little is known about the risk these strains pose to pediatric populations. Quantifying the proportion of pediatric UTIs caused by food-animal-derived E. coli, characterizing the highest-risk strains, and identifying their primary reservoir species could inform novel intervention strategies to reduce UTI burden in this vulnerable population. Our results suggest that retail poultry meat may be an important vehicle for pediatric exposure to zoonotic E. coli strains capable of causing UTIs. Vaccinating poultry against the highest-risk strains could potentially reduce poultry colonization, poultry meat contamination, and downstream pediatric infections.

Genome sequence of white spot syndrome virus (WSSV) infecting cultured black tiger shrimp (Penaeus monodon) in Bangladesh.

The white spot syndrome virus (WSSV) is a causative agent of white spot disease (WSD) in crustaceans, especially in cultivated black tiger shrimp (Penaeus monodon), leading to significant economic losses in the aquaculture sector. The present study describes four whole genome sequences of WSSV obtained from coastal regions of Bangladesh.

Hospital antimicrobial stewardship: profiling the oral microbiome after exposure to COVID-19 and antibiotics.

Introduction: During the COVID-19 Delta variant surge, the CLAIRE cross-sectional study sampled saliva from 120 hospitalized patients, 116 of whom had a positive COVID-19 PCR test. Patients received antibiotics upon admission due to possible secondary bacterial infections, with patients at risk of sepsis receiving broad-spectrum antibiotics (BSA). Methods: The saliva samples were analyzed with shotgun DNA metagenomics and respiratory RNA virome sequencing. Medical records for the period of hospitalization were obtained for all patients. Once hospitalization outcomes were known, patients were classified based on their COVID-19 disease severity and the antibiotics they received. Results: Our study reveals that BSA regimens differentially impacted the human salivary microbiome and disease progression. 12 patients died and all of them received BSA. Significant associations were found between the composition of the COVID-19 saliva microbiome and BSA use, between SARS-CoV-2 genome coverage and severity of disease. We also found significant associations between the non-bacterial microbiome and severity of disease, with Candida albicans detected most frequently in critical patients. For patients who did not receive BSA before saliva sampling, our study suggests Staphylococcus aureus as a potential risk factor for sepsis. Discussion: Our results indicate that the course of the infection may be explained by both monitoring antibiotic treatment and profiling a patient's salivary microbiome, establishing a compelling link between microbiome and the specific antibiotic type and timing of treatment. This approach can aid with emergency room triage and inpatient management but also requires a better understanding of and access to narrow-spectrum agents that target pathogenic bacteria.

Consumption of sucralose- and acesulfame-potassium-containing diet soda alters the relative abundance of microbial taxa at the species level: findings of two pilot studies.

Sucralose and acesulfame-potassium consumption alters gut microbiota in rodents, with unclear effects in humans. We examined effects of three-times daily sucralose- and acesulfame-potassium-containing diet soda consumption for 1 (n = 17) or 8 (n = 8) weeks on gut microbiota composition in young adults. After 8 weeks of diet soda consumption, the relative abundance of Proteobacteria, specifically Enterobacteriaceae, increased; and, increased abundance of two Proteobacteria taxa was also observed after 1 week of diet soda consumption compared with sparkling water. In addition, three taxa in the Bacteroides genus increased following 1 week of diet soda consumption compared with sparkling water. The clinical relevance of these findings and effects of sucralose and acesulfame-potassium consumption on human gut microbiota warrant further investigation in larger studies. Clinical trial registration: NCT02877186 and NCT03125356.

Convergent adaptation of true crabs (Decapoda: Brachyura) to a gradient of terrestrial environments.

For much of terrestrial biodiversity, the evolutionary pathways of adaptation from marine ancestors are poorly understood, and have usually been viewed as a binary trait. True crabs, the decapod crustacean infraorder Brachyura, comprise over 7,600 species representing a striking diversity of morphology and ecology, including repeated adaptation to non-marine habitats. Here, we reconstruct the evolutionary history of Brachyura using new and published sequences of 10 genes for 344 tips spanning 88 of 109 brachyuran families. Using 36 newly vetted fossil calibrations, we infer that brachyurans most likely diverged in the Triassic, with family-level splits in the late Cretaceous and early Paleogene. By contrast, the root age is underestimated with automated sampling of 328 fossil occurrences explicitly incorporated into the tree prior, suggesting such models are a poor fit under heterogeneous fossil preservation. We apply recently defined trait-by-environment associations to classify a gradient of transitions from marine to terrestrial lifestyles. We estimate that crabs left the marine environment at least seven and up to 17 times convergently, and returned to the sea from non-marine environments at least twice. Although the most highly terrestrial- and many freshwater-adapted crabs are concentrated in Thoracotremata, Bayesian threshold models of ancestral state reconstruction fail to identify shifts to higher terrestrial grades due to the degree of underlying change required. Lineages throughout our tree inhabit intertidal and marginal marine environments, corroborating the inference that the early stages of terrestrial adaptation have a lower threshold to evolve. Our framework and extensive new fossil and natural history datasets will enable future comparisons of non-marine adaptation at the morphological and molecular level. Crabs provide an important window into the early processes of adaptation to novel environments, and different degrees of evolutionary constraint that might help predict these pathways.

Spatial diversity of the skin bacteriome.

The bacterial communities of the human skin impact its physiology and homeostasis, hence elucidating the composition and structure of the healthy skin bacteriome is paramount to understand how bacterial imbalance (i.e., dysbiosis) may lead to disease. To obtain an integrated view of the spatial diversity of the skin bacteriome, we surveyed from 2019 to 2023 five skin regions (belly button, behind ears, between toes, calves and forearms) with different physiological characteristics (dry, moist and sebaceous) in 129 healthy adults (579 samples - after data cleaning). Estimating bacterial diversity through 16S rRNA metataxonomics, we identified significant (p < 0.0001) differences in the bacterial relative abundance of the four most abundant phyla and 11 genera, alpha- and beta-diversity indices and predicted functional profiles (36 to 400 metabolic pathways) across skin regions and microenvironments. No significant differences, however, were observed across genders, ages, and ethnicities. As previously suggested, dry skin regions (forearms and calves) were more even, richer, and functionally distinct than sebaceous (behind ears) and moist (belly button and between toes) regions. Within skin regions, bacterial alpha- and beta-diversity also varied significantly for some of the years compared, suggesting that skin bacterial stability may be region and subject dependent. Our results, hence, confirm that the skin bacteriome varies systematically across skin regions and microenvironments and provides new insights into the internal and external factors driving bacterial diversity.

Major Revisions in Pancrustacean Phylogeny and Evidence of Sensitivity to Taxon Sampling.

The clade Pancrustacea, comprising crustaceans and hexapods, is the most diverse group of animals on earth, containing over 80% of animal species and half of animal biomass. It has been the subject of several recent phylogenomic analyses, yet relationships within Pancrustacea show a notable lack of stability. Here, the phylogeny is estimated with expanded taxon sampling, particularly of malacostracans. We show small changes in taxon sampling have large impacts on phylogenetic estimation. By analyzing identical orthologs between two slightly different taxon sets, we show that the differences in the resulting topologies are due primarily to the effects of taxon sampling on the phylogenetic reconstruction method. We compare trees resulting from our phylogenomic analyses with those from the literature to explore the large tree space of pancrustacean phylogenetic hypotheses and find that statistical topology tests reject the previously published trees in favor of the maximum likelihood trees produced here. Our results reject several clades including Caridoida, Eucarida, Multicrustacea, Vericrustacea, and Syncarida. Notably, we find Copepoda nested within Allotriocarida with high support and recover a novel relationship between decapods, euphausiids, and syncarids that we refer to as the Syneucarida. With denser taxon sampling, we find Stomatopoda sister to this latter clade, which we collectively name Stomatocarida, dividing Malacostraca into three clades: Leptostraca, Peracarida, and Stomatocarida. A new Bayesian divergence time estimation is conducted using 13 vetted fossils. We review our results in the context of other pancrustacean phylogenetic hypotheses and highlight 15 key taxa to sample in future studies.

Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data.

Most experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.

Locus specific endogenous retroviral expression associated with Alzheimer's disease.

Introduction: Human endogenous retroviruses (HERVs) are transcriptionally-active remnants of ancient retroviral infections that may play a role in Alzheimer's disease. Methods: We combined two, publicly available RNA-Seq datasets with a third, novel dataset for a total cohort of 103 patients with Alzheimer's disease and 45 healthy controls. We use telescope to perform HERV quantification for these samples and simultaneously perform gene expression analysis. Results: We identify differentially expressed genes and differentially expressed HERVs in Alzheimer's disease patients. Differentially expressed HERVs are scattered throughout the genome; many of them are members of the HERV-K superfamily. A number of HERVs are correlated with the expression of dysregulated genes in Alzheimer's and are physically proximal to genes which drive disease pathways. Discussion: Dysregulated expression of ancient retroviral insertions in the human genome are present in Alzheimer's disease and show localization patterns that may explain how these elements drive pathogenic gene expression.

Oncogenic Transformation Drives DNA Methylation Loss and Transcriptional Activation at Transposable Element Loci.

Transposable elements (TE) are typically silenced by DNA methylation and repressive histone modifications in differentiated healthy human tissues. However, TE expression increases in a wide range of cancers and is correlated with global hypomethylation of cancer genomes. We assessed expression and DNA methylation of TEs in fibroblast cells that were serially transduced with hTERT, SV40, and HRASR24C to immortalize and then transform them, modeling the different steps of the tumorigenesis process. RNA sequencing and whole-genome bisulfite sequencing were performed at each stage of transformation. TE expression significantly increased as cells progressed through transformation, with the largest increase in expression after the final stage of transformation, consistent with data from human tumors. The upregulated TEs were dominated by endogenous retroviruses [long terminal repeats (LTR)]. Most differentially methylated regions (DMR) in all stages were hypomethylated, with the greatest hypomethylation in the final stage of transformation. A majority of the DMRs overlapped TEs from the RepeatMasker database, indicating that TEs are preferentially demethylated. Many hypomethylated TEs displayed a concordant increase in expression. Demethylation began during immortalization and continued into transformation, while upregulation of TE transcription occurred in transformation. Numerous LTR elements upregulated in the model were also identified in The Cancer Genome Atlas datasets of breast, colon, and prostate cancer. Overall, these findings indicate that TEs, specifically endogenous retroviruses, are demethylated and transcribed during transformation. SIGNIFICANCE: Analysis of epigenetic and transcriptional changes in a transformation model reveals that transposable element expression and methylation are dysregulated during oncogenic transformation.

Amphibian myelopoiesis.

Macrophage-lineage cells are indispensable to immunity and physiology of all vertebrates. Amongst these, amphibians represent a key stage in vertebrate evolution and are facing decimating population declines and extinctions, in large part due to emerging infectious agents. While recent studies indicate that macrophages and related innate immune cells are critically involved during these infections, much remains unknown regarding the ontogeny and functional differentiation of these cell types in amphibians. Accordingly, in this review we coalesce what has been established to date about amphibian blood cell development (hematopoiesis), the development of key amphibian innate immune cells (myelopoiesis) and the differentiation of amphibian macrophage subsets (monopoiesis). We explore the current understanding of designated sites of larval and adult hematopoiesis across distinct amphibian species and consider what mechanisms may lend to these species-specific adaptations. We discern the identified molecular mechanisms governing the functional differentiation of disparate amphibian (chiefly Xenopus laevis) macrophage subsets and describe what is known about the roles of these subsets during amphibian infections with intracellular pathogens. Macrophage lineage cells are at the heart of so many vertebrate physiological processes. Thus, garnering greater understanding of the mechanisms responsible for the ontogeny and functionality of these cells in amphibians will lend to a more comprehensive view of vertebrate evolution.

Abnormalities in intron retention characterize patients with systemic lupus erythematosus.

Regulation of intron retention (IR), a form of alternative splicing, is a newly recognized checkpoint in gene expression. Since there are numerous abnormalities in gene expression in the prototypic autoimmune disease systemic lupus erythematosus (SLE), we sought to determine whether IR was intact in patients with this disease. We, therefore, studied global gene expression and IR patterns of lymphocytes in SLE patients. We analyzed RNA-seq data from peripheral blood T cell samples from 14 patients suffering from systemic lupus erythematosus (SLE) and 4 healthy controls and a second, independent data set of RNA-seq data from B cells from16 SLE patients and 4 healthy controls. We identified intron retention levels from 26,372 well annotated genes as well as differential gene expression and tested for differences between cases and controls using unbiased hierarchical clustering and principal component analysis. We followed with gene-disease enrichment analysis and gene-ontology enrichment analysis. Finally, we then tested for significant differences in intron retention between cases and controls both globally and with respect to specific genes. Overall decreased IR was found in T cells from one cohort and B cells from another cohort of patients with SLE and was associated with increased expression of numerous genes, including those encoding spliceosome components. Different introns within the same gene displayed both up- and down-regulated retention profiles indicating a complex regulatory mechanism. These results indicate that decreased IR in immune cells is characteristic of patients with active SLE and may contribute to the abnormal expression of specific genes in this autoimmune disease.

Therapeutic beta-lactam dosages and broad-spectrum antibiotics are associated with reductions in microbial richness and diversity in persons with cystic fibrosis.

Persons with cystic fibrosis (PwCF) suffer from pulmonary exacerbations (PEx) related in part to lung infection. While higher microbial diversity is associated with higher lung function, the data on the impact of short-term antibiotics on changes in microbial diversity is conflicting. Further, Prevotella secretes beta-lactamases, which may influence recovery of lung function. We hypothesize that sub-therapeutic and broad spectrum antibiotic exposure leads to decreasing microbial diversity. Our secondary aim was to evaluate the concerted association of beta-lactam pharmacokinetics (PK), antibiotic spectrum, microbial diversity, and antibiotic resistance on lung function recovery using a pathway analysis. This was a retrospective observational study of persons with CF treated with IV antibiotics for PEx between 2016 and 2020 at Children's National Hospital; respiratory samples and clinical information were collected at hospital admission for PEx (E), end of antibiotic treatment (T), and follow-up (F). Metagenomic sequencing was performed; PathoScope 2.0 and AmrPlusPlus were used for taxonomic assignment of sequences to bacteria and antibiotic resistance genes (ARGs). M/W Pharm was used for PK modeling. Comparison of categorical and continuous variables and pathway analysis were performed in STATA. Twenty-two PwCF experienced 43 PEx. The study cohort had a mean age of 14.6 years. Only 12/43 beta-lactam courses had therapeutic PK, and 18/43 were broad spectrum. A larger decrease in richness between E and T was seen in the therapeutic PK group (sufficient - 20.1 vs. insufficient - 1.59, p = 0.025) and those receiving broad spectrum antibiotics (broad - 14.5 vs. narrow - 2.8, p = 0.030). We did not detect differences in the increase in percent predicted forced expiratory volume in one second (ppFEV1) at end of treatment compared to PEx based on beta-lactam PK (sufficient 13.6% vs. insufficient 15.1%) or antibiotic spectrum (broad 11.5% vs. narrow 16.6%). While both therapeutic beta-lactam PK and broad-spectrum antibiotics decreased richness between PEx and the end of treatment, we did not detect longstanding changes in alpha diversity or an association with superior recovery of lung function compared with subtherapeutic PK and narrow spectrum antimicrobials.

Impact of Fecal Microbiota Transplantation on Gut Bacterial Bile Acid Metabolism in Humans.

Fecal microbiota transplantation (FMT) is a promising therapeutic modality for the treatment and prevention of metabolic disease. We previously conducted a double-blind, randomized, placebo-controlled pilot trial of FMT in obese metabolically healthy patients in which we found that FMT enhanced gut bacterial bile acid metabolism and delayed the development of impaired glucose tolerance relative to the placebo control group. Therefore, we conducted a secondary analysis of fecal samples collected from these patients to assess the potential gut microbial species contributing to the effect of FMT to improve metabolic health and increase gut bacterial bile acid metabolism. Fecal samples collected at baseline and after 4 weeks of FMT or placebo treatment underwent shotgun metagenomic analysis. Ultra-high-performance liquid chromatography-mass spectrometry was used to profile fecal bile acids. FMT-enriched bacteria that have been implicated in gut bile acid metabolism included Desulfovibrio fairfieldensis and Clostridium hylemonae. To identify candidate bacteria involved in gut microbial bile acid metabolism, we assessed correlations between bacterial species abundance and bile acid profile, with a focus on bile acid products of gut bacterial metabolism. Bacteroides ovatus and Phocaeicola dorei were positively correlated with unconjugated bile acids. Bifidobacterium adolescentis, Collinsella aerofaciens, and Faecalibacterium prausnitzii were positively correlated with secondary bile acids. Together, these data identify several candidate bacteria that may contribute to the metabolic benefits of FMT and gut bacterial bile acid metabolism that requires further functional validation.

Source and acquisition of rhizosphere microbes in Antarctic vascular plants.

Rhizosphere microbial communities exert critical roles in plant health, nutrient cycling, and soil fertility. Despite the essential functions conferred by microbes, the source and acquisition of the rhizosphere are not entirely clear. Therefore, we investigated microbial community diversity and potential source using the only two native Antarctic plants, Deschampsia antarctica (Da) and Colobanthus quitensis (Cq), as models. We interrogated rhizosphere and bulk soil microbiomes at six locations in the Byers Peninsula, Livingston Island, Antarctica, both individual plant species and their association (Da.Cq). Our results show that host plant species influenced the richness and diversity of bacterial communities in the rhizosphere. Here, the Da rhizosphere showed the lowest richness and diversity of bacteria compared to Cq and Da.Cq rhizospheres. In contrast, for rhizosphere fungal communities, plant species only influenced diversity, whereas the rhizosphere of Da exhibited higher fungal diversity than the Cq rhizosphere. Also, we found that environmental geographic pressures (i.e., sampling site, latitude, and altitude) and, to a lesser extent, biotic factors (i.e., plant species) determined the species turnover between microbial communities. Moreover, our analysis shows that the sources of the bacterial communities in the rhizosphere were local soils that contributed to homogenizing the community composition of the different plant species growing in the same sampling site. In contrast, the sources of rhizosphere fungi were local (for Da and Da.Cq) and distant soils (for Cq). Here, the host plant species have a specific effect in acquiring fungal communities to the rhizosphere. However, the contribution of unknown sources to the fungal rhizosphere (especially in Da and Da.Cq) indicates the existence of relevant stochastic processes in acquiring these microbes. Our study shows that rhizosphere microbial communities differ in their composition and diversity. These differences are explained mainly by the microbial composition of the soils that harbor them, acting together with plant species-specific effects. Both plant species acquire bacteria from local soils to form part of their rhizosphere. Seemingly, the acquisition process is more complex for fungi. We identified a significant contribution from unknown fungal sources due to stochastic processes and known sources from soils across the Byers Peninsula.

Impact of Antibiotics on the Lung Microbiome and Lung Function in Children With Cystic Fibrosis 1 Year After Hospitalization for an Initial Pulmonary Exacerbation.

Background: Cystic fibrosis (CF) is characterized by recurrent pulmonary exacerbations (PEx) and lung function decline. PEx are frequently treated with antibiotics. However, little is known about the effects of antibiotics on the airway microbiome of persons with CF over time. The purpose of this study was to evaluate changes in the microbiome and lung function in persons with CF over 1 year following an initial study pulmonary exacerbation (iPEx). Methods: Twenty children aged ≤18 years with CF were enrolled in the study, which occurred prior to the routine administration of highly effective modulator therapy. Respiratory samples and spirometry were obtained at a minimum of quarterly visits and up to 1 year after an iPEx. Metagenomic sequencing was performed, and bacterial taxa were assigned using MetaPhlAn 2.0. Paired t test, analysis of variance, and generalized least squares regression were used to compare outcome variables. Results: The mean age of study participants at the time of the iPEx was 10.6 years. There were 3 ± 1.6 PEx treated with antibiotics per person during the study period. Bacterial richness was similar at 1 year compared to iPEx (40.3 vs 39.3, P = .852), whereas the mean Shannon diversity index was significantly higher at 1 year (2.84 vs 1.62, P < .001). The number of PEx treated with antibiotics was not associated with changes in microbial diversity but was associated with changes in lung function. Conclusions: In our 1-year prospective study, we found that microbial diversity increased despite decreases in lung function associated with repeated PEx events requiring antibiotic therapy.

Host taxonomy determines the composition, structure, and diversity of the earthworm cast microbiome under homogenous feeding conditions.

Host evolutionary history is a key factor shaping the earthworm cast microbiome, although its effect can be shadowed by the earthworm's diet. To untangle dietary from taxon effects, we raised nine earthworm species on a uniform diet of cow manure and compared cast microbiome across species while controlling for diet. Our results showed that, under controlled laboratory conditions, earthworm microbiomes are species-specific, more diverse than that of the controlled diet, and mainly comprised of native bacteria (i.e. not acquired from the diet). Furthermore, diet has a medium to large convergence effect on microbiome composition since earthworms shared 16%-74% of their bacterial amplicon sequence variants (ASV). The interspecies core microbiome included 10 ASVs, while their intraspecies core microbiomes were larger and varied in ASV richness (24%-48%) and sequence abundance across earthworm species. This specificity in core microbiomes and variable degree of similarity in bacterial composition suggest that phylosymbiosis could determine earthworm microbiome assembly. However, lack of congruence between the earthworm phylogeny and the microbiome dendrogram suggests that a consistent diet fed over several generations may have weakened potential phylosymbiotic effects. Thus, cast microbiome assembly in earthworms seem to be the result of an interplay among host phylogeny and diet.

Metabolite, protein, and tissue dysfunction associated with COVID-19 disease severity.

Proteins are direct products of the genome and metabolites are functional products of interactions between the host and other factors such as environment, disease state, clinical information, etc. Omics data, including proteins and metabolites, are useful in characterizing biological processes underlying COVID-19 along with patient data and clinical information, yet few methods are available to effectively analyze such diverse and unstructured data. Using an integrated approach that combines proteomics and metabolomics data, we investigated the changes in metabolites and proteins in relation to patient characteristics (e.g., age, gender, and health outcome) and clinical information (e.g., metabolic panel and complete blood count test results). We found significant enrichment of biological indicators of lung, liver, and gastrointestinal dysfunction associated with disease severity using publicly available metabolite and protein profiles. Our analyses specifically identified enriched proteins that play a critical role in responses to injury or infection within these anatomical sites, but may contribute to excessive systemic inflammation within the context of COVID-19. Furthermore, we have used this information in conjunction with machine learning algorithms to predict the health status of patients presenting symptoms of COVID-19. This work provides a roadmap for understanding the biochemical pathways and molecular mechanisms that drive disease severity, progression, and treatment of COVID-19.