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Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.

Abstract Bioethanol is a sustainable energy alternative and can contribute to global greenhouse-gas emission reductions by over 60%. Its industrial production faces various bottlenecks, including sub-optimal efficiency resulting from bacteria. Broad-spectrum removal of these contaminants results in negligible gains, suggesting that the process is shaped by ecological interactions within the microbial community. Here, we survey the microbiome across all process steps at two biorefineries, over three timepoints in a production season. Leveraging shotgun metagenomics and cultivation-based approaches, we identify beneficial bacteria and find improved outcome when yeast-to-bacteria ratios increase during fermentation. We provide a microbial gene catalogue which reveals bacteria-specific pathways associated with performance. We also show that Limosilactobacillus fermentum overgrowth lowers production, with one strain reducing yield by ~5% in laboratory fermentations, potentially due to its metabolite profile. Temperature is found to be a major driver for strain-level dynamics. Improved microbial management strategies could unlock environmental and economic gains in this US $ 60 billion industry enabling its wider adoption.

Summary: Infection is a commonplace, usually self-limiting, condition but can lead to sepsis, a severe life-threatening dysregulated host response. We investigate the individual phenotypic predisposition to developing uncomplicated infection or sepsis in a large cohort of non-infected patients undergoing major elective surgery. Whole-blood RNA sequencing analysis was performed on preoperative samples from 267 patients. These patients developed postoperative infection with (n = 77) or without (n = 49) sepsis, developed non-infectious systemic inflammatory response (n = 31), or had an uncomplicated postoperative course (n = 110). Machine learning classification models built on preoperative transcriptomic signatures predict postoperative outcomes including sepsis with an area under the curve of up to 0.910 (mean 0.855) and sensitivity/specificity up to 0.767/0.804 (mean 0.746/0.769). Our models, confirmed by quantitative reverse-transcription PCR (RT-qPCR), potentially offer a risk prediction tool for the development of postoperative sepsis with implications for patient management. They identify an individual predisposition to developing sepsis that warrants further exploration to better understand the underlying pathophysiology.

Abstract Background Enhancing our understanding of the underlying influences of medical interventions on the microbiome, resistome and mycobiome of preterm born infants holds significant potential for advancing infection prevention and treatment strategies. We conducted a prospective quasi-intervention study to better understand how antibiotics, and probiotics, and other medical factors influence the gut development of preterm infants. A controlled neonatal mice model was conducted in parallel, designed to closely reflect and predict exposures. Preterm infants and neonatal mice were stratified into four groups: antibiotics only, probiotics only, antibiotics followed by probiotics, and none of these interventions. Stool samples from both preterm infants and neonatal mice were collected at varying time points and analyzed by 16 S rRNA amplicon sequencing, ITS amplicon sequencing and whole genome shotgun sequencing. Results The human infant microbiomes showed an unexpectedly high degree of heterogeneity. Little impact from medical exposure (antibiotics/probiotics) was observed on the strain patterns, however, Bifidobacterium bifidum was found more abundant after exposure to probiotics, regardless of prior antibiotic administration. Twenty-seven antibiotic resistant genes were identified in the resistome. High intra-variability was evident within the different treatment groups. Lastly, we found significant effects of antibiotics and probiotics on the mycobiome but not on the microbiome and resistome of preterm infants. Conclusions Although our analyses showed transient effects, these results provide positive motivation to continue the research on the effects of medical interventions on the microbiome, resistome and mycobiome of preterm infants.

Background The importance of gut microbes in mediating the benefits of lifestyle intervention is increasingly recognized. However, compared to the bacterial microbiome, the role of intestinal fungi in exercise remains elusive. With our established randomized controlled trial of exercise intervention in Chinese males with prediabetes (n = 39, ClinicalTrials.gov:NCT03240978), we investigated the dynamics of human gut mycobiome and further interrogated their associations with exercise-elicited outcomes using multi-omics approaches.Methods Clinical variations and biological samples were collected before and after training. Fecal fungal composition was analyzed using the internal transcribed spacer 2 (ITS2) sequencing and integrated with paired shotgun metagenomics, untargeted metabolomics, and Olink proteomics.Results Twelve weeks of exercise training profoundly promoted fungal ecological diversity and intrakingdom connection. We further identified exercise-responsive genera with potential metabolic benefits, including Verticillium, Sarocladium, and Ceratocystis. Using multi-omics approaches, we elucidated comprehensive associations between changes in gut mycobiome and exercise-shaped metabolic phenotypes, bacterial microbiome, and circulating metabolomics and proteomics profiles. Furthermore, a machine-learning algorithm built using baseline microbial signatures and clinical characteristics predicted exercise responsiveness in improvements of insulin sensitivity, with an area under the receiver operating characteristic (AUROC) of 0.91 (95% CI: 0.85–0.97) in the discovery cohort and of 0.79 (95% CI: 0.74–0.86) in the independent validation cohort (n = 30).Conclusions Our findings suggest that intense exercise training significantly remodels the human fungal microbiome composition. Changes in gut fungal composition are associated with the metabolic benefits of exercise, indicating gut mycobiome is a possible molecular transducer of exercise. Moreover, baseline gut fungal signatures predict exercise responsiveness for diabetes prevention, highlighting that targeting the gut mycobiome emerges as a prospective strategy in tailoring personalized training for diabetes prevention.

Summary: Environmental change, coupled with alteration in human lifestyles, is profoundly impacting the microbial communities critical to the health of the Earth and its inhabitants. To identify bacteria and fungi that are resistant and susceptible to habitat change, we analyze thousands of genera detected in 1,580 host, soil, and aquatic samples. This large-scale analysis identifies 48 bacterial and 4 fungal genera that are abundant across the three biomes, demonstrating fitness in diverse environmental conditions. Samples containing these generalists have significantly higher alpha diversity. These generalists play a significant role in shaping cross-kingdom community structure, boasting larger genomes with more secondary metabolism and antimicrobial resistance genes. Conversely, 30 bacterial and 19 fungal genera are only found in a single habitat, suggesting a limited ability to adapt to different and changing environments. These findings contribute to our understanding of microbial niche breadth and its consequences for global biodiversity loss.

The opportunistic fungal pathogen Candida albicans thrives on human mucosal surfaces as a harmless commensal, but frequently causes infections under certain predisposing conditions. Translocation across the intestinal barrier into the bloodstream by intestine-colonizing C. albicans cells serves as the main source of disseminated candidiasis. However, the host and microbial mechanisms behind this process remain unclear. In this study we identified fungal and host factors specifically involved in infection of intestinal epithelial cells (IECs) using dual-RNA sequencing. Our data suggest that host-cell damage mediated by the peptide toxin candidalysin-encoding gene ECE1 facilitates fungal zinc acquisition. This in turn is crucial for the full virulence potential of C. albicans during infection. IECs in turn exhibit a filamentation- and damage-specific response to C. albicans infection, including NFκB, MAPK, and TNF signaling. NFκB activation by IECs limits candidalysin-mediated host-cell damage and mediates maintenance of the intestinal barrier and cell-cell junctions to further restrict fungal translocation. This is the first study to show that candidalysin-mediated damage is necessary for C. albicans nutrient acquisition during infection and to explain how IECs counteract damage and limit fungal translocation via NFκB-mediated maintenance of the intestinal barrier.

Abstract Background Aspergillus fumigatus is a major fungal pathogen that causes severe problems due to its increasing resistance to many therapeutic agents. Fludioxonil is a compound that triggers a lethal activation of the fungal-specific High Osmolarity Glycerol pathway. Its pronounced antifungal activity against A. fumigatus and other pathogenic molds renders this agent an attractive lead substance for the development of new therapeutics. The group III hydride histidine kinase TcsC and its downstream target Skn7 are key elements of the multistep phosphorelay that represents the initial section of the High Osmolarity Glycerol pathway. Loss of tcsC results in resistance to fludioxonil, whereas a Δskn7 mutant is partially, but not completely resistant. Results In this study, we compared the fludioxonil-induced transcriptional responses in the ΔtcsC and Δskn7 mutant and their parental A. fumigatus strain. The number of differentially expressed genes correlates well with the susceptibility level of the individual strains. The wild type and, to a lesser extend also the Δskn7 mutant, showed a multi-faceted stress response involving genes linked to ribosomal and peroxisomal function, iron homeostasis and oxidative stress. A marked difference between the sensitive wild type and the largely resistant Δskn7 mutant was evident for many cell wall-related genes and in particular those involved in the biosynthesis of chitin. Biochemical data corroborate this differential gene expression that does not occur in response to hyperosmotic stress. Conclusions Our data reveal that fludioxonil induces a strong and TcsC-dependent stress that affects many aspects of the cellular machinery. The data also demonstrate a link between Skn7 and the cell wall reorganizations that foster the characteristic ballooning and the subsequent lysis of fludioxonil-treated cells.

Abstract Background A growing body of evidence suggests that the gut microbiota is strongly linked to general human health. Microbiome-directed interventions, such as diet and exercise, are acknowledged as a viable and achievable strategy for preventing disorders and improving human health. However, due to the significant inter-individual diversity of the gut microbiota between subjects, lifestyle recommendations are expected to have distinct and highly variable impacts to the microbiome structure. Results Here, through a large-scale meta-analysis including 1448 shotgun metagenomics samples obtained longitudinally from 396 individuals during lifestyle studies, we revealed Bacteroides stercoris, Prevotella copri, and Bacteroides vulgatus as biomarkers of microbiota’s resistance to structural changes, and aromatic and non-aromatic amino acid biosynthesis as important regulator of microbiome dynamics. We established criteria for distinguishing between significant compositional changes from normal microbiota fluctuation and classified individuals based on their level of response. We further developed a machine learning model for predicting “responders” and “non-responders” independently of the type of intervention with an area under the curve of up to 0.86 in external validation cohorts of different ethnicities. Conclusions We propose here that microbiome-based stratification is possible for identifying individuals with highly plastic or highly resistant microbial structures. Identifying subjects that will not respond to generalized lifestyle therapeutic interventions targeting the restructuring of gut microbiota is important to ensure that primary end-points of clinical studies are reached. Video Abstract

Abstract Aspergillus fumigatus, an opportunistic human pathogen, frequently infects the lungs of people with cystic fibrosis and is one of the most common causes of infectious-disease death in immunocompromised patients. Here, we construct 252 strain-specific, genome-scale metabolic models of this important fungal pathogen to study and better understand the metabolic component of its pathogenic versatility. The models show that 23.1% of A. fumigatus metabolic reactions are not conserved across strains and are mainly associated with amino acid, nucleotide, and nitrogen metabolism. Profiles of non-conserved reactions and growth-supporting reaction fluxes are sufficient to differentiate strains, for example by environmental or clinical origin. In addition, shotgun metagenomics analysis of sputum from 40 cystic fibrosis patients (15 females, 25 males) before and after diagnosis with an A. fumigatus colonization suggests that the fungus shapes the lung microbiome towards a more beneficial fungal growth environment associated with aromatic amino acid availability and the shikimate pathway. Our findings are starting points for the development of drugs or microbiome intervention strategies targeting fungal metabolic needs for survival and colonization in the non-native environment of the human lung.

Abstract Currently, there is evidence that alteration in the gut ecosystem contributes to the development of liver diseases, however, the complex mechanisms involved are still unclear. We induced cholestasis in mice by bile duct ligation (BDL), mirroring the phenotype of a bile duct obstruction, to understand how gut microbiota alterations caused by an impaired flow of bile acid to the gut contribute to the pathogenesis and progression of liver disease. We performed longitudinal stool, heart, and liver sampling using mice receiving BDL and controls receiving sham operation (ShamOP). Shotgun metagenomics profiling using fecal samples taken before and on day 1, day 3, and day 7 after surgery was performed, and the cytokines and clinical chemistry profiles from heart blood, as well as the liver bile acids profile, were measured. The BDL surgery reshaped the microbiome of mice, resulting in highly distinct characteristics compared to the ShamOP. Our analysis of the microbiome pathways and ECs revealed that BDL reduces the production of hepatoprotective compounds in the gut, such as biotin, spermidine, arginine, and ornithine, which were negatively associated with inflammatory cytokines (IL-6, IL-23, MCP-1). The reduction of the functional potential of the gut microbiota in producing those hepatoprotective compounds is associated with the decrease of beneficial bacteria species from Anaerotruncus, Blautia, Eubacterium, and Lachnoclostridium genera, as well as the increase of disease-associated bacteria e.g., Escherichia coli and Entercoccus faecalis. Our findings advances our knowledge of the gut microbiome-bile acids-liver triangle, which may serve as a potential therapeutic strategy for liver diseases.

Abstract Innate immune responses vary by pathogen and host genetics. We analyze quantitative trait loci (eQTLs) and transcriptomes of monocytes from 215 individuals stimulated by fungal, Gram-negative or Gram-positive bacterial pathogens. We identify conserved monocyte responses to bacterial pathogens and a distinct antifungal response. These include 745 response eQTLs (reQTLs) and corresponding genes with pathogen-specific effects, which we find first in samples of male donors and subsequently confirm for selected reQTLs in females. reQTLs affect predominantly upregulated genes that regulate immune response via e.g., NOD-like, C-type lectin, Toll-like and complement receptor-signaling pathways. Hence, reQTLs provide a functional explanation for individual differences in innate response patterns. Our identified reQTLs are also associated with cancer, autoimmunity, inflammatory and infectious diseases as shown by external genome-wide association studies. Thus, reQTLs help to explain interindividual variation in immune response to infection and provide candidate genes for variants associated with a range of diseases.

Abstract Candida species overgrowth in the human gut is considered a prerequisite for invasive candidiasis, but our understanding of gut bacteria promoting or restricting this overgrowth is still limited. By integrating cross-sectional mycobiome and shotgun metagenomics data from the stool of 75 male and female cancer patients at risk but without systemic candidiasis, bacterial communities in high Candida samples display higher metabolic flexibility yet lower contributional diversity than those in low Candida samples. We develop machine learning models that use only bacterial taxa or functional relative abundances to predict the levels of Candida genus and species in an external validation cohort with an AUC of 78.6–81.1%. We propose a mechanism for intestinal Candida overgrowth based on an increase in lactate-producing bacteria, which coincides with a decrease in bacteria that regulate short chain fatty acid and oxygen levels. Under these conditions, the ability of Candida to harness lactate as a nutrient source may enable Candida to outcompete other fungi in the gut.

ABSTRACT Gut microbial dysbiosis has been observed in non-alcoholic fatty liver disease (NAFLD). The beneficial impact of exercise, the recommended lifestyle change for NAFLD patients, might be mediated by the gut microbiome (GM). However, the exact taxonomic and functional signatures associated with the host’s clinical and biochemical improvement during exercise in NAFLD patients have not been elucidated yet. To investigate the impact of exercise on GM and reveal GM structures associated with NAFLD improvement during exercise. Stool samples from a 12-week randomized controlled exercise study on NAFLD subjects (N = 39) were retrieved, and shotgun metagenomics was performed at baseline and endpoint. Differential correlation network and enrichment analysis were applied to characterize the GM taxonomic and functional changes during the exercise intervention and to associate GM changes with biomarkers of liver status and metabolic dysregulation. Network analysis demonstrated that exercise induced significant changes in the bacterial interactome, which were associated with waist circumference; resting metabolic rate; plasma fasting concentrations of triglyceride, glucose, insulin, and glycated hemoglobin A1c; and homeostasis model assessment for insulin resistance. Grouping the patients in the exercise group (N = 20) as responders (N = 13) and non-responders (N = 7) using their intrahepatic lipid content (IHL) change allowed us to identify bacteria consortia contributing to the levels of alanine fermentation, methanol-, creatinine-, and protocatechuate degradation and as a result to the plasma concentrations of liver injury markers alanine transaminase, gamma-glutamyl transaminase, and aspartate transaminase. We showed that even though exercise has not a significant impact on the alpha- and beta-diversity of NAFLD patients, it leads to a significant re-structuring of the gut bacteria interactome and that specific structural changes can be linked with improvements in IHL. IMPORTANCE Our study is applying a community-based approach to examine the influence of exercise on gut microbiota (GM) and discover GM structures linked with NAFLD improvements during exercise. The majority of microbiome research has focused on finding specific species that may contribute to the development of human diseases. However, we believe that complex diseases, such as NAFLD, would be more efficiently treated using consortia of species, given that bacterial functionality is based not only on its own genetic information but also on the interaction with other microorganisms. Our results revealed that exercise significantly changes the GM interaction and that structural alterations can be linked with improvements in intrahepatic lipid content and metabolic functions. We believe that the identification of these characteristics in the GM enhances the development of exercise treatment for NAFLD and will attract general interest in this field.

Candida species are a major cause of invasive fungal infections. While Candida albicans, C. glabrata, C. parapsilosis, and C. tropicalis are the most dominant species causing life-threatening candidiasis, C. auris recently emerged as a new species causing invasive infections with high rates of clinical treatment failures. To mimic initial phases of systemic Candida infections with dissemination via the bloodstream and to elucidate the pathogenic potential of C. auris, we used an ex vivo whole blood infection model. Similar to other clinically relevant Candida spp., C. auris is efficiently killed in human blood, but showed characteristic patterns of immune cell association, survival rates, and cytokine induction. Dual-species transcriptional profiling of C. auris-infected blood revealed a unique C. auris gene expression program during infection, while the host response proofed similar and conserved compared to other Candida species. C. auris-specific responses included adaptation and survival strategies, such as counteracting oxidative burst of immune cells, but also expression of potential virulence factors, (drug) transporters, and cell surface-associated genes. Despite comparable pathogenicity to other Candida species in our model, C. auris-specific transcriptional adaptations as well as its increased stress resistance and long-term environmental survival, likely contribute to the high risk of contamination and distribution in a nosocomial setting. Moreover, infections of neutrophils with pre-starved C. auris cells suggest that environmental preconditioning can have modulatory effects on the early host interaction. In summary, we present novel insights into C. auris pathogenicity, revealing adaptations to human blood and environmental niches distinctive from other Candida species.

ABSTRACT Candida auris, a multidrug-resistant human fungal pathogen that causes outbreaks of invasive infections, emerged as four distinct geographical clades. Previous studies identified genomic and proteomic differences in nutrient utilization on comparison to Candida albicans, suggesting that certain metabolic features may contribute to C. auris emergence. Since no high-throughput clade-specific metabolic characterization has been described yet, we performed a phenotypic screening of C. auris strains from all 4 clades on 664 nutrients, 120 chemicals, and 24 stressors. We identified common and clade- or strain-specific responses, including the preferred utilization of various dipeptides as nitrogen source and the inability of the clade II isolate AR 0381 to withstand chemical stress. Further analysis of the metabolic properties of C. auris isolates showed robust growth on intermediates of the tricarboxylic acid cycle, such as citrate and succinic and malic acids. However, there was reduced or no growth on pyruvate, lactic acid, or acetate, likely due to the lack of the monocarboxylic acid transporter Jen1, which is conserved in most pathogenic Candida species. Comparison of C. auris and C. albicans transcriptomes of cells grown on alternative carbon sources and dipeptides as a nitrogen source revealed common as well as species-unique responses. C. auris induced a significant number of genes with no ortholog in C. albicans, e.g., genes similar to the nicotinic acid transporter TNA1 (alternative carbon sources) and to the oligopeptide transporter (OPT) family (dipeptides). Thus, C. auris possesses unique metabolic features which could have contributed to its emergence as a pathogen. IMPORTANCE Four main clades of the emerging, multidrug-resistant human pathogen Candida auris have been identified, and they differ in their susceptibilities to antifungals and disinfectants. Moreover, clade- and strain-specific metabolic differences have been identified, but a comprehensive overview of nutritional characteristics and resistance to various stressors is missing. Here, we performed high-throughput phenotypic characterization of C. auris on various nutrients, stressors, and chemicals and obtained transcriptomes of cells grown on selected nutrients. The generated data sets identified multiple clade- and strain-specific phenotypes and induction of C. auris-specific metabolic genes, showing unique metabolic properties. The presented work provides a large amount of information for further investigations that could explain the role of metabolism in emergence and pathogenicity of this multidrug-resistant fungus.

Commensal bacteria such as Lactobacillus rhamnosus can inhibit the pathogenicity of the fungus Candida albicans. Here, Alonso-Roman et al. investigate the interplay between C. albicans, L. rhamnosus and intestinal epithelial cells, showing that changes in the metabolic environment, induced by the bacteria, trigger adaptations in C. albicans that reduce fungal pathogenicity.

Atopic dermatitis (AD) is a prevalent inflammatory skin disease that has been associated with changes in gut microbial composition in early life. However, there are limited longitudinal studies examining the gut microbiome in AD. This study aimed to explore taxonomy and metabolic functions across longitudinal gut microbiomes associated with AD in early childhood from 9 to 30 months of age using integrative data analysis within the Thai population. Our analysis revealed that gut microbiome diversity was not different between healthy and AD groups; however, significant taxonomic differences were observed. Key gut bacteria with short-chain fatty acids (SCFAs) production potentials, such as Anaerostipes, Butyricicoccus, Ruminococcus, and Lactobacillus species, showed a higher abundance in the AD group. In addition, metabolic alterations between the healthy and AD groups associated with vitamin production and host immune response, such as biosynthesis of menaquinol, succinate, and (Kdo)2-lipid A, were observed. This study serves as the first framework for monitoring longitudinal microbial imbalances and metabolic functions associated with allergic diseases in Thai children during early childhood.

Plasmodium parasites are reliant on the Apicomplexan AP2 (ApiAP2) transcription factor family to regulate gene expression programs. AP2 DNA binding domains have no homologs in the human or mosquito host genomes, making them potential antimalarial drug targets. Using an in-silico screen to dock thousands of small molecules into the crystal structure of the AP2-EXP (Pf3D7_1466400) AP2 domain (PDB:3IGM), we identified putative AP2-EXP interacting compounds. Four compounds were found to block DNA binding by AP2-EXP and at least one additional ApiAP2 protein. Our top ApiAP2 competitor compound perturbs the transcriptome of P. falciparum trophozoites and results in a decrease in abundance of log2 fold change > 2 for 50% (46/93) of AP2-EXP target genes. Additionally, two ApiAP2 competitor compounds have multi-stage anti-Plasmodium activity against blood and mosquito stage parasites. In summary, we describe a novel set of antimalarial compounds that interact with AP2 DNA binding domains. These compounds may be used for future chemical genetic interrogation of ApiAP2 proteins or serve as starting points for a new class of antimalarial therapeutics.

Patients suffering from coronavirus disease-2019 (COVID-19) are susceptible to deadly secondary fungal infections such as COVID-19-associated pulmonary aspergillosis and COVID-19-associated mucormycosis. Despite this clinical observation, direct experimental evidence for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-driven alterations of antifungal immunity is scarce. Using an ex-vivo whole blood stimulation assay, we challenged blood from twelve COVID-19 patients with Aspergillus fumigatus and Rhizopus arrhizus antigens and studied the expression of activation, maturation, and exhaustion markers, as well as cytokine secretion. Compared to healthy controls, T-helper cells from COVID-19 patients displayed increased expression levels of the exhaustion marker PD-1 and weakened A. fumigatus- and R. arrhizus-induced activation. While baseline secretion of proinflammatory cytokines was massively elevated, whole blood from COVID-19 patients elicited diminished release of T-cellular (e.g., IFN-γ, IL-2) and innate immune cell-derived (e.g., CXCL9, CXCL10) cytokines in response to A. fumigatus and R. arrhizus antigens. Additionally, samples from COVID-19 patients showed deficient granulocyte activation by mold antigens and reduced fungal killing capacity of neutrophils. These features of weakened anti-mold immune responses were largely decoupled from COVID-19 severity, the time elapsed since diagnosis of COVID-19, and recent corticosteroid uptake, suggesting that impaired anti-mold defense is a common denominator of the underlying SARS-CoV-2 infection. Taken together, these results expand our understanding of the immune predisposition to post-viral mold infections and could inform future studies of immunotherapeutic strategies to prevent and treat fungal superinfections in COVID-19 patients.

Wenyan Nong, Zhe Qu, Yiqian Li, Tom Barton-Owen, Annette Wong and colleagues provide genomes and small RNA transcriptomes for the mangrove horseshoe crab and the tri-spine horseshoe crab. They show that horseshoe crabs have undergone three rounds of whole genome duplication and shed light on how gene families and microRNAS evolved following this genome duplication event.

Invasive pulmonary aspergillosis (IPA) is a severe infection that is difficult to diagnose due to the ubiquitous presence of fungal spores, the underlying diseases of risk patients, and limitations of currently available markers. In this study, we performed a comprehensive liquid chromatography tandem mass spectrometry (LC-MS/MS)-based identification of host and fungal proteins expressed during IPA in mice and humans. The proteomic analysis of bronchoalveolar lavage samples of individual IPA and control cases allowed the description of common host factors that had significantly increased abundance in both infected animals and IPA patients compared to their controls. Although increased levels of these individual host proteins might not be sufficient to distinguish bacterial from fungal infection, a combination of these markers might be beneficial to improve diagnosis. We also identified 16 fungal proteins that were specifically detected during infection and may be valuable candidates for biomarker evaluation.

Protein kinases play a crucial role in regulating cellular processes such as growth, proliferation, environmental adaptation and stress responses. Serine-arginine (SR) protein kinases are highly conserved in eukaryotes and regulate fundamental processes such as constitutive and alternative splicing, mRNA processing and ion homeostasis. The Candida albicans genome encodes two (Sky1, Sky2) and the Candida glabrata genome has one homolog (Sky1) of the human SR protein kinase 1, but their functions have not yet been investigated. We used deletion strains of the corresponding genes in both fungi to study their cellular functions. C. glabrata and C. albicans strains lacking SKY1 exhibited higher resistance to osmotic stress and toxic polyamine concentrations, similar to Saccharomyces cerevisiae sky1Δ mutants. Deletion of SKY2 in C. albicans resulted in impaired utilization of various dipeptides as the sole nitrogen source. Subsequent phosphoproteomic analysis identified the di- and tripeptide transporter Ptr22 as a potential Sky2 substrate. Sky2 seems to be involved in Ptr22 regulation since overexpression of PTR22 in the sky2Δ mutant restored the ability to grow on dipeptides and made the cells more susceptible to the dipeptide antifungals Polyoxin D and Nikkomycin Z. Altogether, our results demonstrate that C. albicans and C. glabrata Sky1 protein kinases are functionally similar to Sky1 in S. cerevisiae, whereas C. albicans Sky2, a unique kinase of the CTG clade, likely regulates dipeptide uptake via Ptr22.

Abstract Background Antibiotic treatment has a well-established detrimental effect on the gut bacterial composition, but effects on the fungal community are less clear. Bacteria in the lumen of the gastrointestinal tract may limit fungal colonization and invasion. Antibiotic drugs targeting bacteria are therefore seen as an important risk factor for fungal infections and induced allergies. However, antibiotic effects on gut bacterial-fungal interactions, including disruption and resilience of fungal community compositions, were not investigated in humans. We analysed stool samples collected from 14 healthy human participants over 3 months following a 6-day antibiotic administration. We integrated data from shotgun metagenomics, metatranscriptomics, metabolomics, and fungal ITS2 sequencing. Results While the bacterial community recovered mostly over 3 months post treatment, the fungal community was shifted from mutualism at baseline to competition. Half of the bacterial-fungal interactions present before drug intervention had disappeared 3 months later. During treatment, fungal abundances were associated with the expression of bacterial genes with functions for cell growth and repair. By extending the metagenomic species approach, we revealed bacterial strains inhibiting the opportunistic fungal pathogen Candida albicans. We demonstrated in vitro how C. albicans pathogenicity and host cell damage might be controlled naturally in the human gut by bacterial metabolites such as propionate or 5-dodecenoate. Conclusions We demonstrated that antibacterial drugs have long-term influence on the human gut mycobiome. While bacterial communities recovered mostly 30-days post antibacterial treatment, the fungal community was shifted from mutualism towards competition. Video abstract.

Abstract Clofarabine is active in refractory/relapsed acute myeloid leukemia (AML). In this phase 2 study, we treated 18‐ to 65‐year‐old AML patients refractory to first‐line 3 + 7 daunorubicin/cytarabine induction or relapsing after 3 + 7 induction and high‐dose cytarabine consolidation, with clofarabine (30 mg/m2/d, Days 1‐5), cytarabine (750 mg/m2/d, Days 1‐5), and mitoxantrone (12 mg/m2/d, Days 3‐5) (CLAM). Patients achieving remission received up to two consolidation cycles of 50% CLAM, with eligible cases bridged to allogeneic hematopoietic stem cell transplantation (allo‐HSCT). The mutational profile of a 69‐gene panel was evaluated. Twenty‐six men and 26 women at a median age of 46 (22‐65) years were treated. The overall response rate after the first cycle of CLAM was 90.4% (complete remission, CR: 69.2%; CR with incomplete hematologic recovery, CRi: 21.2%). Twenty‐two CR/CRi patients underwent allo‐HSCT. The 2‐year overall survival (OS), relapse‐free survival (RFS), and event‐free survival (EFS) were 65.8%, 45.7%, and 40.2%, respectively. Multivariate analyses showed that superior OS was associated with CR after CLAM (P = .005) and allo‐HSCT (P = .005), and superior RFS and EFS were associated with allo‐HSCT (P

Abstract The gut microbiota has the potential to influence the efficacy of cancer therapy. Here, we investigated the contribution of the intestinal microbiome on treatment outcomes in a heterogeneous cohort that included multiple cancer types to identify microbes with a global impact on immune response. Human gut metagenomic analysis revealed that responder patients had significantly higher microbial diversity and different microbiota compositions compared to non-responders. A machine-learning model was developed and validated in an independent cohort to predict treatment outcomes based on gut microbiota composition and functional repertoires of responders and non-responders. Specific species, Bacteroides ovatus and Bacteroides xylanisolvens, were positively correlated with treatment outcomes. Oral gavage of these responder bacteria significantly increased the efficacy of erlotinib and induced the expression of CXCL9 and IFN-γ in a murine lung cancer model. These data suggest a predictable impact of specific constituents of the microbiota on tumor growth and cancer treatment outcomes with implications for both prognosis and therapy.

Abstract Background Roux-en-Y gastric bypass (RYGB) surgery is a last-resort treatment to induce substantial and sustained weight loss in cases of severe obesity. This anatomical rearrangement affects the intestinal microbiota, but so far, little information is available on how it interferes with microbial functionality and microbial-host interactions independently of weight loss. Methods A rat model was employed where the RYGB-surgery cohort is compared to sham-operated controls which were kept at a matched body weight by food restriction. We investigated the microbial taxonomy and functional activity using 16S rRNA amplicon gene sequencing, metaproteomics, and metabolomics on samples collected from theileum, the cecum, and the colon, and separately analysed the lumen and mucus-associated microbiota. Results Altered gut architecture in RYGB increased the relative occurrence of Actinobacteria, especially Bifidobacteriaceae and Proteobacteria, while in general, Firmicutes were decreased although Streptococcaceae and Clostridium perfringens were observed at relative higher abundances independent of weight loss. A decrease of conjugated and secondary bile acids was observed in the RYGB-gut lumen. The arginine biosynthesis pathway in the microbiota was altered, as indicated by the changes in the abundance of upstream metabolites and enzymes, resulting in lower levels of arginine and higher levels of aspartate in the colon after RYGB. Conclusion The anatomical rearrangement in RYGB affects microbiota composition and functionality as well as changes in amino acid and bile acid metabolism independently of weight loss. The shift in the taxonomic structure of the microbiota after RYGB may be mediated by the resulting change in the composition of the bile acid pool in the gut and by changes in the composition of nutrients in the gut. Video abstract.

Purpose: Visceral fat is an independent risk factor for metabolic and cardiovascular disease. The study aimed to investigate the associations between gut microbiome and visceral fat. Methods: We recruited 32 obese adults and 30 healthy controls at baseline. Among the obese subjects, 14 subjects underwent laparoscopic sleeve gastrectomy (LSG) and were followed 6 months after surgery. Abdominal visceral fat area (VFA) and subcutaneous fat area (SFA) were measured by magnetic resonance imaging. Waist, hipline, waist-to-hip ratio (WHR) and body mass index (BMI) were included as simple obese parameters. Gut microbiome was analyzed by metagenomic sequencing. Results: Among the obese parameters, VFA had the largest number of correlations with the species that were differentially enriched between obese and healthy subjects, following by waist, WHR, BMI, hipline, and SFA. Within the species negatively correlated with VFA, Eubacterium eligens had the strongest correlation, following by Clostridium citroniae, C. symbiosum, Bacteroides uniformis, E. ventriosum, Ruminococcaceae bacterium D16, C. hathewayi, etc. C. hathewayi and C. citroniae were increased after LSG. Functional analyses showed that among all the obese parameters, VFA had strongest correlation coefficients with the obesity-related microbial pathways. Microbial pathways involved in carbohydrate fermentation and biosynthesis of L-glutamate and L-glutamine might contribute to visceral fat accumulation. Conclusions: Visceral fat was more closely correlated with gut microbiome compared with subcutaneous fat, suggesting an intrinsic connection between gut microbiome and metabolic cardiovascular diseases. Specific microbial species and pathways which were closely associated with visceral fat accumulation might contribute to new targeted therapies for metabolic disorders.

Sepsis remains a major cause of death despite advances in medical care. Metabolic deregulation is an important component of the survival process. Metabolomic analysis allows profiling of critical metabolic functions with the potential to classify patient outcome. Our prospective longitudinal characterization of 33 septic and non-septic critically ill patients showed that deviations, independent of direction, in plasma levels of lipid metabolites were associated with sepsis mortality. We identified a coupling of metabolic signatures between liver and plasma of a rat sepsis model that allowed us to apply a human kinetic model of mitochondrial beta-oxidation to reveal differing enzyme concentrations for medium/short-chain hydroxyacyl-CoA dehydrogenase (elevated in survivors) and crotonase (elevated in non-survivors). These data suggest a need to monitor cellular energy metabolism beyond the available biomarkers. A loss of metabolic adaptation appears to be reflected by an inability to maintain cellular (fatty acid) metabolism within a “corridor of safety”.

Trillions of microbes representing all kingdoms of life are resident in, and on, humans holding essential roles for the host development and physiology. The last decade over a dozen online tools and servers, accessible via public domain, have been developed for the analysis of bacterial sequences; however, the analysis of fungi is still in its infancy. Here, we present a web server dedicated to the comprehensive analysis of the human mycobiome for (i) translating raw sequencing reads to data tables and high-standard figures, (ii) integrating statistical analysis and machine learning with a manually curated relational database and (iii) comparing the user’s uploaded datasets with publicly available from the Sequence Read Archive. Using 1,266 publicly available Internal transcribed spacers (ITS) samples, we demonstrated the utility of DAnIEL web server on large scale datasets and show the differences in fungal communities between human skin and soil sites.

Abstract Although obesity occurs in most of the patients with type 2 diabetes (T2D), a fraction of patients with T2D are underweight or have normal weight. Several studies have linked the gut microbiome to obesity and T2D, but the role of gut microbiota in lean individuals with T2D having unique clinical characteristics remains unclear. A metagenomic and targeted metabolomic analysis is conducted in 182 lean and abdominally obese individuals with and without newly diagnosed T2D. The abundance of Akkermansia muciniphila (A. muciniphila) significantly decreases in lean individuals with T2D than without T2D, but not in the comparison of obese individuals with and without T2D. Its abundance correlates inversely with serum 3β‐chenodeoxycholic acid (βCDCA) levels and positively with insulin secretion and fibroblast growth factor 15/19 (FGF15/19) concentrations. The supplementation with A. muciniphila is sufficient to protect mice against high sucrose‐induced impairment of glucose intolerance by decreasing βCDCA and increasing insulin secretion and FGF15/19. Furthermore, βCDCA inhibits insulin secretion and FGF15/19 expression. These findings suggest that decreased abundance of A. muciniphila is linked to the impairment of insulin secretion and glucose homeostasis in lean T2D, paving the way for new therapeutic options for the prevention or treatment of diabetes.

Abstract Background Coastal marine environments are one of the most productive ecosystems on Earth. However, anthropogenic impacts exert significant pressure on coastal marine biodiversity, contributing to functional shifts in microbial communities and human health risk factors. However, relatively little is known about the impact of eutrophication—human-derived nutrient pollution—on the marine microbial biosphere. Results Here, we tested the hypothesis that benthic microbial diversity and function varies along a pollution gradient, with a focus on human pathogens and antibiotic resistance genes. Comprehensive metagenomic analysis including taxonomic investigation, functional detection, and ARG annotation revealed that zinc, lead, total volatile solids, and ammonia nitrogen were correlated with microbial diversity and function. We propose several microbes, including Planctomycetes and sulfate-reducing microbes as candidates to reflect pollution concentration. Annotation of antibiotic resistance genes showed that the highest abundance of efflux pumps was found at the most polluted site, corroborating the relationship between pollution and human health risk factors. This result suggests that sediments at polluted sites harbor microbes with a higher capacity to reduce intracellular levels of antibiotics, heavy metals, or other environmental contaminants. Conclusions Our findings suggest a correlation between pollution and the marine sediment microbiome and provide insight into the role of high-turnover microbial communities as well as potential pathogenic organisms as real-time indicators of water quality, with implications for human health and demonstrate the inner functional shifts contributed by the microcommunities.

Abstract Background Viruses are important components of microbial communities modulating community structure and function; however, only a couple of tools are currently available for phage identification and analysis from metagenomic sequencing data. Here we employed the random forest algorithm to develop VirMiner, a web-based phage contig prediction tool especially sensitive for high-abundances phage contigs, trained and validated by paired metagenomic and phagenomic sequencing data from the human gut flora. Results VirMiner achieved 41.06% ± 17.51% sensitivity and 81.91% ± 4.04% specificity in the prediction of phage contigs. In particular, for the high-abundance phage contigs, VirMiner outperformed other tools (VirFinder and VirSorter) with much higher sensitivity (65.23% ± 16.94%) than VirFinder (34.63% ± 17.96%) and VirSorter (18.75% ± 15.23%) at almost the same specificity. Moreover, VirMiner provides the most comprehensive phage analysis pipeline which is comprised of metagenomic raw reads processing, functional annotation, phage contig identification, and phage-host relationship prediction (CRISPR-spacer recognition) and supports two-group comparison when the input (metagenomic sequence data) includes different conditions (e.g., case and control). Application of VirMiner to an independent cohort of human gut metagenomes obtained from individuals treated with antibiotics revealed that 122 KEGG orthology and 118 Pfam groups had significantly differential abundance in the pre-treatment samples compared to samples at the end of antibiotic administration, including clustered regularly interspaced short palindromic repeats (CRISPR), multidrug resistance, and protein transport. The VirMiner webserver is available at http://sbb.hku.hk/VirMiner/. Conclusions We developed a comprehensive tool for phage prediction and analysis for metagenomic samples. Compared to VirSorter and VirFinder—the most widely used tools—VirMiner is able to capture more high-abundance phage contigs which could play key roles in infecting bacteria and modulating microbial community dynamics. Trial registration The European Union Clinical Trials Register, EudraCT Number: 2013-003378-28. Registered on 9 April 2014

Despite the documented antibiotic-induced disruption of the gut microbiota, the impact of antibiotic intake on strain-level dynamics, evolution of resistance genes, and factors influencing resistance dissemination potential remains poorly understood. To address this gap we analyzed public metagenomic datasets from 24 antibiotic treated subjects and controls, combined with an in-depth prospective functional study with two subjects investigating the bacterial community dynamics based on cultivation-dependent and independent methods. We observed that short-term antibiotic treatment shifted and diversified the resistome composition, increased the average copy number of antibiotic resistance genes, and altered the dominant strain genotypes in an individual-specific manner. More than 30% of the resistance genes underwent strong differentiation at the single nucleotide level during antibiotic treatment. We found that the increased potential for horizontal gene transfer, due to antibiotic administration, was ∼3-fold stronger in the differentiated resistance genes than the non-differentiated ones. This study highlights how antibiotic treatment has individualized impacts on the resistome and strain level composition, and drives the adaptive evolution of the gut microbiota. Keywords: Antibiotics, Resistome, Gut microbiome, Strain, Evolution, Horizontal gene transfer

Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.

Impaired exercise tolerance and lung function is a marker for increased mortality in lung cancer patients undergoing lung resection surgery. Recent data suggest that the gut-lung axis regulates systemic metabolic and immune functions, and microbiota might alter exercise tolerance. Here, we aimed to evaluate the associations between gut microbiota and outcomes in lung cancer patients who underwent lung resection surgery. We analysed stool samples, from 15 early-stage lung cancer patients, collected before and after surgical resection using shotgun metagenomic and Internal Transcribed Spacer (ITS) sequencing. We analysed microbiome and mycobiome associations with post-surgery lung function and cardiopulmonary exercise testing (CPET) to assess the maximum level of work achieved. There was a significant difference, between pre- and post-surgical resection samples, in microbial community functional profiles and several species from Alistipes and Bacteroides genus, associated with the production of SCFAs, increased significantly in abundance. Interestingly, an increase in VO2 coincides with an increase in certain species and the "GABA shunt" pathway, suggesting that treatment outcome might improve by enriching butyrate-producing species. Here, we revealed associations between specific gut bacteria, fungi, and their metabolic pathways with the recovery of lung function and exercise capacity.

Oral antibiotics are commonly prescribed to non-hospitalized adults. However, antibiotic-induced changes in the human gut microbiome are often investigated in cohorts with preexisting health conditions and/or concomitant medication, leaving the effects of antibiotics not completely understood. We used a combination of omic approaches to comprehensively assess the effects of antibiotics on the gut microbiota and particularly the gut resistome of a small cohort of healthy adults. We observed that 3 to 19 species per individual proliferated during antibiotic treatment and Gram-negative species expanded significantly in relative abundance. While the overall relative abundance of antibiotic resistance gene homologs did not significantly change, antibiotic-specific gene homologs with presumed resistance toward the administered antibiotics were common in proliferating species and significantly increased in relative abundance. Virome sequencing and plasmid analysis showed an expansion of antibiotic-specific resistance gene homologs even 3 months after antibiotic administration, while paired-end read analysis suggested their dissemination among different species. These results suggest that antibiotic treatment can lead to a persistent expansion of antibiotic resistance genes in the human gut microbiota and provide further data in support of good antibiotic stewardship. Abbreviation: ARG – Antibiotic resistance gene homolog; AsRG – Antibiotic-specific resistance gene homolog; AZY – Azithromycin; CFX – Cefuroxime; CIP – Ciprofloxacin; DOX – Doxycycline; FDR – False discovery rate; GRiD – Growth rate index value; HGT – Horizontal gene transfer; NMDS – Non-metric multidimensional scaling; qPCR – Quantitative polymerase chain reaction; RPM – Reads per million mapped reads; TA – Transcriptional activity; TE – Transposable element; TPM – Transcripts per million mapped reads

Antibiotics are commonly used in the Intensive Care Unit (ICU); however, several studies showed that the impact of antibiotics to prevent infection, multi-organ failure, and death in the ICU is less clear than their benefit on course of infection in the absence of organ dysfunction. We characterized here the compositional and metabolic changes of the gut microbiome induced by critical illness and antibiotics in a cohort of 75 individuals in conjunction with 2,180 gut microbiome samples representing 16 different diseases. We revealed an “infection-vulnerable” gut microbiome environment present only in critically ill treated with antibiotics (ICU+). Feeding of Caenorhabditis elegans with Bifidobacterium animalis and Lactobacillus crispatus, species that expanded in ICU+ patients, revealed a significant negative impact of these microbes on host viability and developmental homeostasis. These results suggest that antibiotic administration can dramatically impact essential functional activities in the gut related to immune responses more than critical illness itself, which might explain in part untoward effects of antibiotics in the critically ill.

ABSTRACT Antibiotic resistance is an increasing threat to human health. In the case of Aspergillus fumigatus, which is both an environmental saprobe and an opportunistic human fungal pathogen, resistance is suggested to arise from fungicide use in agriculture, as the azoles used for plant protection share the same molecular target as the frontline antifungals used clinically. However, limiting azole fungicide use on crop fields to preserve their activity for clinical use could threaten the global food supply via a reduction in yield. In this study, we clarify the link between azole fungicide use on crop fields and resistance in a prototypical human pathogen through systematic soil sampling on farms in Germany and surveying fields before and after fungicide application. We observed a reduction in the abundance of A. fumigatus on fields following fungicide treatment in 2017, a finding that was not observed on an organic control field with only natural plant protection agents applied. However, this finding was less pronounced during our 2018 sampling, indicating that the impact of fungicides on A. fumigatus population size is variable and influenced by additional factors. The overall resistance frequency among agricultural isolates is low, with only 1 to 3% of isolates from 2016 to 2018 displaying resistance to medical azoles. Isolates collected after the growing season and azole exposure show a subtle but consistent decrease in susceptibility to medical and agricultural azoles. Whole-genome sequencing indicates that, despite the alterations in antifungal susceptibility, fungicide application does not significantly affect the population structure and genetic diversity of A. fumigatus in fields. Given the low observed resistance rate among agricultural isolates as well the lack of genomic impact following azole application, we do not find evidence that azole use on crops is significantly driving resistance in A. fumigatus in this context. IMPORTANCE Antibiotic resistance is an increasing threat to human health. In the case of Aspergillus fumigatus, which is an environmental fungus that also causes life-threatening infections in humans, antimicrobial resistance is suggested to arise from fungicide use in agriculture, as the chemicals used for plant protection are almost identical to the antifungals used clinically. However, removing azole fungicides from crop fields threatens the global food supply via a reduction in yield. In this study, we survey crop fields before and after fungicide application. We find a low overall azole resistance rate among agricultural isolates, as well as a lack of genomic and population impact following fungicide application, leading us to conclude azole use on crops does not significantly contribute to resistance in A. fumigatus.

Summary: High-throughput RNA sequencing (RNA-seq) is routinely applied to study diverse biological processes; however, when performed separately on interacting organisms, systemic noise intrinsic to RNA extraction, library preparation, and sequencing hampers the identification of cross-species interaction nodes. Here, we develop triple RNA-seq to simultaneously detect transcriptomes of monocyte-derived dendritic cells (moDCs) infected with the frequently co-occurring pulmonary pathogens Aspergillus fumigatus and human cytomegalovirus (CMV). Comparing expression patterns after co-infection with those after single infections, our data reveal synergistic effects and mutual interferences between host responses to the two pathogens. For example, CMV attenuates the fungus-mediated activation of pro-inflammatory cytokines through NF-κB (nuclear factor κB) and NFAT (nuclear factor of activated T cells) cascades, while A. fumigatus impairs viral clearance by counteracting viral nucleic acid-induced activation of type I interferon signaling. Together, the analytical power of triple RNA-seq proposes molecular hubs in the differential moDC response to fungal/viral single infection or co-infection that contribute to our understanding of the etiology and, potentially, clearance of post-transplant infections.

Rhinovirus (RV) and influenza virus are the most frequently detected respiratory viruses among adult patients with community acquired pneumonia. Previous clinical studies have identified major differences in the clinical presentations and inflammatory or immune response during these infections. A systematic transcriptomic analysis directly comparing influenza and RV is lacking. Here, we sought to compare the transcriptomic response to these viral infections. Human airway epithelial Calu-3 cells were infected with contemporary clinical isolates of RV, influenza A virus (IAV), or influenza B virus (IBV). Host gene expression was determined using RNA-seq. Differentially expressed genes (DEGs) with respect to mock-infected cells were identified using the overlapping gene-set of four different statistical models. Transcriptomic analysis showed that RV-infected cells have a more blunted host response with fewer DEGs than IAV or IBV-infected cells. IFNL1 and CXCL10 were among the most upregulated DEGs during RV, IAV, and IBV infection. Other DEGs that were highly expressed for all 3 viruses were mainly genes related to type I or type III interferons (RSAD2, IDO1) and chemokines (CXCL11). Notably, ICAM5, a known receptor for enterovirus D68, was highly expressed during RV infection only. Gene Set Enrichment Analysis (GSEA) confirmed that pathways associated with interferon response, innate immunity, or regulation of inflammatory response, were most perturbed for all three viruses. Network analysis showed that steroid-related pathways were enriched. Taken together, our data using contemporary virus strains suggests that genes related to interferon and chemokine predominated the host response associated with RV, IAV, and IBV infection. Several highly expressed genes, especially ICAM5 which is preferentially-induced during RV infection, deserve further investigation.

Pathogenic microorganisms exploit host metabolism for sustained survival by rewiring its metabolic interactions. Therefore, several metabolic changes are induced in both pathogen and host cells in the course of infection. A systems-based approach to elucidate those changes includes the integrative use of genome-scale metabolic networks and molecular omics data, with the overall goal of better characterizing infection mechanisms for novel treatment strategies. This review focuses on novel aspects of metabolism-oriented systems-based investigation of pathogen-human interactions. The reviewed approaches are the generation of dual-omics data for the characterization of metabolic signatures of pathogen-host interactions, the reconstruction of pathogen-host integrated genome-scale metabolic networks, which has a high potential to be applied to pathogen-gut microbiota interactions, and the structure-based analysis of enzymes playing role in those interactions. The integrative use of those approaches will pave the way for the identification of novel biomarkers and drug targets for the prediction and prevention of infectious diseases.

Despite available diagnostic tests and recent advances, diagnosis of pulmonary invasive aspergillosis (IPA) remains challenging. We performed a longitudinal case-control pilot study to identify host-specific, novel, and immune-relevant molecular candidates indicating IPA in patients post allogeneic stem cell transplantation (alloSCT). Supported by differential gene expression analysis of six relevant in vitro studies, we conducted RNA sequencing of three alloSCT patients categorized as probable IPA cases and their matched controls without Aspergillus infection (66 samples in total). We additionally performed immunoassay analysis for all patient samples to gain a multi-omics perspective. Profiling analysis suggested LGALS2, MMP1, IL-8, and caspase-3 as potential host molecular candidates indicating IPA in investigated alloSCT patients. MMP1, IL-8, and caspase-3 were evaluated further in alloSCT patients for their potential to differentiate possible IPA cases and patients suffering from COVID-19-associated pulmonary aspergillosis (CAPA) and appropriate control patients. Possible IPA cases showed differences in IL-8 and caspase-3 serum levels compared with matched controls. Furthermore, we observed significant differences in IL-8 and caspase-3 levels among CAPA patients compared with control patients. With our conceptual work, we demonstrate the potential value of considering the human immune response during Aspergillus infection to identify immune-relevant molecular candidates indicating IPA in alloSCT patients. These human host candidates together with already established fungal biomarkers might improve the accuracy of IPA diagnostic tools.

In Hong Kong, cattle were traditionally raised by farmers as draft animals to plough rice fields. Due to urbanization in the 20th century, they were gradually abandoned and became wild cattle straying in suburban Hong Kong. Recently, these cattle were observed to have become omnivorous by eating leftover barbeque food waste in country parks. Microbiome analysis was performed on fecal samples of the omnivorous cattle using deep sequencing and the resulting microbiome was compared with that of traditional herbivorous cattle in Southern China. A more diverse gut microbiome was observed in the omnivorous cattle, suggesting that microbiota diversity increases as diet variation increases. At the genus level, the relative abundance of Anaeroplasma, Anaerovorax, Bacillus, Coprobacillus and Solibacillus significantly increased and those of Anaerofustis, Butyricimonas, Campylobacter, Coprococcus, Dehalobacterium, Phascolarctobacterium, rc4.4, RFN20, Succinivibrio and Turicibacter significantly decreased in the omnivorous group. The increase in microbial community levels of Bacillus and Anaerovorax likely attributes to the inclusion of meat in the diet; while the decrease in relative abundance of Coprococcus, Butyricimonas, Succinivibrio, Campylobacter and Phascolarctobacterium may reflect the reduction in grass intake. Furthermore, an increased consumption of resistant starch likely resulted in the increase in abundance of Anaeroplasma. In conclusion, a significant change in the gut microbial community was observed in the omnivorous cattle, suggesting that diet may be one of the factors that may signal an adaptation response by the cattle to maintain feed efficiency as a consequence of the change in environment. Keywords: Cattle, Microbiome, Diet, Omnivore, Microbial diversity

Occupational mold exposure can lead to Aspergillus-associated allergic diseases including asthma and hypersensitivity pneumonitis. Elevated IL-17 levels or disbalanced T-helper (Th) cell expansion were previously linked to Aspergillus-associated allergic diseases, whereas alterations to the Th cell repertoire in healthy occupationally exposed subjects are scarcely studied. Therefore, we employed functional immunoassays to compare Th cell responses to A. fumigatus antigens in organic farmers, a cohort frequently exposed to environmental molds, and non-occupationally exposed controls. Organic farmers harbored significantly higher A. fumigatus-specific Th-cell frequencies than controls, with comparable expansion of Th1- and Th2-cell frequencies but only slightly elevated Th17-cell frequencies. Accordingly, Aspergillus antigen-induced Th1 and Th2 cytokine levels were strongly elevated, whereas induction of IL-17A was minimal. Additionally, increased levels of some innate immune cell-derived cytokines were found in samples from organic farmers. Antigen-induced cytokine release combined with Aspergillus-specific Th-cell frequencies resulted in high classification accuracy between organic farmers and controls. Aspf22, CatB, and CipC elicited the strongest differences in Th1 and Th2 responses between the two cohorts, suggesting these antigens as potential candidates for future bio-effect monitoring approaches. Overall, we found that occupationally exposed agricultural workers display a largely balanced co-expansion of Th1 and Th2 immunity with only minor changes in Th17 responses.

Background: A range of computational methods that rely on the analysis of genome-wide expression datasets have been developed and successfully used for drug repositioning. The success of these methods is based on the hypothesis that introducing a factor (in this case, a drug molecule) that could reverse the disease gene expression signature will lead to a therapeutic effect. However, it has also been shown that globally reversing the disease expression signature is not a prerequisite for drug activity. On the other hand, the basic idea of significant anti-correlation in expression profiles could have great value for establishing diet-disease associations and could provide new insights into the role of dietary interventions in disease.Methods: We performed an integrated analysis of publicly available gene expression profiles for foods, diseases and drugs, by calculating pairwise similarity scores for diet and disease gene expression signatures and characterizing their topological features in protein-protein interaction networks.Results: We identified 485 diet-disease pairs where diet could positively influence disease development and 472 pairs where specific diets should be avoided in a disease state. Multiple evidence suggests that orange, whey and coconut fat could be beneficial for psoriasis, lung adenocarcinoma and macular degeneration, respectively. On the other hand, fructose-rich diet should be restricted in patients with chronic intermittent hypoxia and ovarian cancer. Since humans normally do not consume foods in isolation, we also applied different algorithms to predict synergism; as a result, 58 food pairs were predicted. Interestingly, the diets identified as anti-correlated with diseases showed a topological proximity to the disease proteins similar to that of the corresponding drugs.Conclusions: In conclusion, we provide a computational framework for establishing diet-disease associations and additional information on the role of diet in disease development. Due to the complexity of analyzing the food composition and eating patterns of individuals our in silico analysis, using large-scale gene expression datasets and network-based topological features, may serve as a proof-of-concept in nutritional systems biology for identifying diet-disease relationships and subsequently designing dietary recommendations.

ABSTRACT As diet is considered the major regulator of the gut ecosystem, the overall objective of this work was to demonstrate that a detailed knowledge of the phytochemical composition of food could add to our understanding of observed changes in functionality and activity of the gut microbiota. We used metatranscriptomic data from a human dietary intervention study to develop a network that consists of >400 compounds present in the administered plant-based diet linked to 609 microbial targets in the gut. Approximately 20% of the targeted bacterial proteins showed significant changes in their gene expression levels, while functional and topology analyses revealed that proteins in metabolic networks with high centrality are the most “vulnerable” targets. This global view and the mechanistic understanding of the associations between microbial gene expression and dietary molecules could be regarded as a promising methodological approach for targeting specific bacterial proteins that impact human health. IMPORTANCE It is a general belief that microbiome-derived drugs and therapies will come to the market in coming years, either in the form of molecules that mimic a beneficial interaction between bacteria and host or molecules that disturb a harmful interaction or proteins that can modify the microbiome or bacterial species to change the balance of “good” and “bad” bacteria in the gut microbiome. However, among the numerous factors, what has proven the most influential for modulating the microbial composition of the gut is diet. In line with this, we demonstrate here that a systematic analysis of the interactions between the small molecules present in our diet and the gut bacterial proteome holds great potential for designing dietary interventions to improve human health.

Recent research has demonstrated that consumption of food -especially fruits and vegetables- can alter the effects of drugs by interfering either with their pharmacokinetic or pharmacodynamic processes. Despite the recognition of such drug-food associations as an important element for successful therapeutic interventions, a systematic approach for identifying, predicting and preventing potential interactions between food and marketed or novel drugs is not yet available. The overall objective of this work was to sketch a comprehensive picture of the interference of ∼ 4,000 dietary components present in ∼1800 plant-based foods with the pharmacokinetics and pharmacodynamics processes of medicine, with the purpose of elucidating the molecular mechanisms involved. By employing a systems chemical biology approach that integrates data from the scientific literature and online databases, we gained a global view of the associations between diet and dietary molecules with drug targets, metabolic enzymes, drug transporters and carriers currently deposited in DrugBank. Moreover, we identified disease areas and drug targets that are most prone to the negative effects of drug-food interactions, showcasing a platform for making recommendations in relation to foods that should be avoided under certain medications. Lastly, by investigating the correlation of gene expression signatures of foods and drugs we were able to generate a completely novel drug-diet interactome map.