Metagenomic Prediction Research Articles

Taxonomic Diversity, Predicted Metabolic Pathway, and Interaction Pattern of Bacterial Community in Sea Urchin Anthocidaris crassispina.

Bacterial assemblages associated with sea urchin are critical to their physiology and ecology within marine ecosystems. In this study, we characterized the bacterial communities in wild sea urchin Anthocidaris crassispina captured in Daya Bay, South China Sea. A total of 363 amplicon sequence variants belonging to nine phyla and 141 genera were classified from intestine, body surface, and surrounding seawater samples. Proteobacteria, Firmicutes, and Bacteroidetes were the dominant bacteria phyla found in this study. A network analysis of bacterial interspecies interactions revealed varying complexity, stability, connectivity, and relationship patterns across the samples, with the most intricate network observed in the surrounding seawater. Metagenomic predictions highlighted the distinct bacterial metabolic pathways, with significant differences between intestine and seawater samples. Notably, pathways associated with polysaccharide degradation, including chitin derivatives, starch, and CoM biosynthesis, were markedly abundant, underscoring the gut microbiota's key role in digesting algae. In addition, other metabolic pathways in intestine samples were linked to immune response regulation of sea urchins. Overall, this study provides a comprehensive overview of the bacterial community structure and potential functional roles in A. crassispina.

Key Chemical Soil Parameters for the Assembly of Rhizosphere Bacteria Associated with Avocado Cv Hass Grafted on Landrace Rootstocks

Avocado cultivation holds significant economic importance in many countries, ranking Colombia as the fifth largest global producer. Particularly, the Hass cultivar plays a pivotal role in Colombia’s avocado industry, especially in the Department of Antioquia, the primary export region. This cultivar is grown under diverse soil and climate conditions and exhibits considerable genetic polymorphism due to the hybridization of varieties of agronomic significance, leading to a diverse array of landrace rootstocks. However, the role of soil conditions and rootstock genotype in structuring rhizosphere bacterial communities is still lacking. In addressing this knowledge gap, we investigated the influence of two soil conditions on the structure of rhizosphere bacterial communities associated with two landrace genotypes of Persea americana cv. Hass, utilizing 16S rRNA sequencing. Notably, no significant differences related to genotypes were observed. This study reports that the rhizosphere bacterial microbiome remains consistent across avocado landrace rootstocks, while variations in key parameters such as phosphorus, pH, Mg, and Ca drive distinct rhizosphere effects. Our results reveal that despite the soils having similar management, increases in these crucial parameters can lead to bacterial communities with lower alpha diversity and a more complex co-occurrence network. In addition, we found substantial variations in beta diversity, bacterial composition, and metagenome predictions between the two farms, underscoring the role of soil variables in shaping the bacterial microbiome. These findings provide valuable insights into the factors influencing the bacterial communities that may play a role in the health and productivity of crops with agro-industrial potential, such as Hass avocado.

Disclosing the key role of Fe/As/Cu in community co-occurrence and microbial recruitment in metallurgical ruins

Mining activities have led to the persistent presence of substantial heavy metals at metallurgical sites. However, the impact of long-term and complex heavy metal pollution in metallurgical ruins on the structure and spatial shift of microbiome remains unclear. In this study, we focused on various types of metallurgical sites to uncover the occurrence of heavy metals in abandoned mines and the response patterns of microbial communities. The results indicate that mining activities have caused severe exceedances of multiple heavy metals, with AsBio, CuBio, and FeBio being the primary factors affecting community structure and function. Co-occurrence network analyses suggest that several genera, including Ellin6515, Cupriavidus, Acidobacteria genus RB41, Vicinamibacteraceae, Blastococcus, and Sphingomonas, may play significant roles in the synergistic metabolism of communities responding to Fe-Cu-As stress. Although random dispersal contributed to community migration, null models emphasized that variable selection predominates in the spatial turnover of community composition. Additionally, metagenomic prediction (PICRUSt2) identified key genes involved in stress and detoxification strategies of heavy metals. The composite heavy metal stress strengthened the relationship between network structure and the potential function of the community, along with critical ecosystem functions. Our findings demonstrated that microbial interactions were crucial for ecosystem management and the ecological consequences of heavy metal pollution remediation.

Fecal microbiome and functional prediction profiles of horses with and without crib-biting behavior: A comparative study

Crib-biting is a stereotyped oral behavior with poorly understood etiology and pathophysiology. The relationship between the gut microbiome and brain function has been described in behavioral disorders such as schizophrenia, depression and anxiety in humans. In horses, studies of behavioral problems and the microbiome are very limited. This study aimed to characterize the fecal microbiome and the predicted functional profile of horses with and without aerophagia. Fecal samples were collected from 12 Colombian Creole Horses of both sexes, divided into two groups: group 1, composed of six horses with crib-biting (3 females and 3 males), average body weight of 330 ± 10 kg, age of 7.0 ± 1.2 years and body condition score (BCS) of 5/9 ± 1 and group 2, consisting of six horses without crib-biting (3 females and 3 males), average body weight of 335 ± 5 kg, age 6.5 ± 1 years and BCS of 6/9 ± 1. From each horse in both groups fecal total DNA was obtained and 16S ribosomal RNA gene amplicons were sequenced to characterize the bacterial community structure. Community structure and differential abundance analyses revealed significant differences between the two conditions (p < 0.05). Specifically, the fecal microbiota at the family level in crib-biting horses, showing a decrease in Bacteroidales and an increase in Bacillota and Clostridia, differed from that of healthy horses without crib-biting, consistent with findings from previous studies. Furthermore, metagenome prediction suggests metabolic profile changes in bacterial communities between both conditions in horses. Further studies are required to validate the role of the microbiota-gut-brain axis in the etiology of crib-biting and other abnormal and stereotyped behaviors.

Different halophytes orchestrate microbial diversity in the rhizosphere of salinity-impacted soils

Investigating rhizosphere communities in saline soils is crucial for identifying the taxonomic groups that play significant roles in halophyte adaptation. However, how the microbiome is structured under different saline conditions remains unclear. This study aimed to analyze bacterial communities in the rhizospheres of halophyte species in different saline environments. Five rhizospheres were analyzed using high-throughput sequencing of the 16S rRNA gene: S1, Salicornia fruticosa from a hypersaline tidal plain; S2, Sporobolus virginicus; S3, Cyperus ligularis from a hypersaline lagoon; S4, Salicornia fruticosa and S5, Blutaparon portulacoides from an abandoned salt pan. Bacterial communities in the S4 and S5 rhizospheres were influenced by P and K content, suggesting that specific nutrients can foster unique microbial structures, potentially assisting in adaptation to saline soils. The unique ASV (Amplicon Sequence Variant), richness, diversity, and microbial core of the S1 system, along with its similarities to S2 and S3, suggest common halophyte adaptation strategies across different saline environments, aiding targeted survival efforts. Identifying keystone species such as Thermoleophilia in S1, Alphaproteobacteria in S2 and S3, multiple species in S4, and the presence of Clostridia and Bacilli in S5 shed light on the roles these bacteria play in halophyte survival. Metagenomic prediction analysis demonstrated that chemoheterotrophy and aerobic chemoheterotrophy were the main prediction functions. In summary, this study revealed the intricate microbial structures in halophyte rhizospheres, enriching our understanding of saline ecosystems.

The impact of lactic acid bacteria inoculation on the fermentation and metabolomic dynamics of indigenous Beijing douzhi microbial communities.

Douzhi, a traditional Chinese fermented beverage, features microbial communities primarily composed of lactic acid bacteria (LAB). As fermented foods continue to gain recognition and popularity, douzhi is attracting growing interest. However, investigation of the critical aspects of douzhi's fermentation processes, including fermentation characteristics and microbial community dynamics, remains vital for enhancing food safety and quality for douzhi, as well as for similar fermented food products. In this study, we collected douzhi microbial communities from four chain stores, using them as fermentation starter cultures. The microbial dynamics of the fermentation were analyzed, focusing on the inoculation of LAB strains and the transition from a mung bean-based matrix to skimmed milk. The metabolomic profiles of the fermented mung bean matrices were also studied. Douzhi samples obtained from representative chain stores were found to be overwhelmingly dominated by LAB. When inoculated along with the douzhi community, both LAB strains exhibited notable and substantial reductions in the pH value of the designated mung bean matrices compared to those inoculated indigenous microbiota. Specifically, Lactiplantibacillus plantarum CGMCC 1.1856 retained its population, whereas Pediococcus pentosaceus CGMCC 1.2695 exhibited a decrease in relative abundance. Using skimmed milk as a fermentation substrate instead of the mung bean matrix resulted in significant shifts in microbial communities, particularly leading to an increase in Escherichia sp. The metagenomic analyses and functional predictions illustrated that various metabolic functions were enhanced during the fermentation process due to LAB inoculation. The liquid chromatography-mass spectrometry based metabolomic analysis revealed that the inoculation of Lactiplantibacillus plantarum and Pediococcus pentosaceus in mung bean matrix did not introduce new metabolites but significantly altered the concentration and profile of existing metabolites, especially increased low molecular carbohydrates, which may enhance the nutritional potential of the fermented product. This study examines the microbial dynamics of douzhi microbiota fermentation, emphasizing the role of lactic acid bacteria in enhancing fermentation activity and metabolite profiles. These insights contribute to improving manufacturing processes and ensuring the safety and quality of douzhi and similar fermented foods.

Environmental and structural factors associated with bacterial diversity in household dust across the Arizona-Sonora border

We previously reported that asthma prevalence was higher in the United States (US) compared to Mexico (MX) (25.8% vs. 8.4%). This investigation assessed differences in microbial dust composition in relation to demographic and housing characteristics on both sides of the US–MX Border. Forty homes were recruited in the US and MX. Home visits collected floor dust and documented occupants’ demographics, asthma prevalence, housing structure, and use characteristics. US households were more likely to have inhabitants who reported asthma when compared with MX households (30% vs. 5%) and had significantly different flooring types. The percentage of households on paved roads, with flushing toilets, with piped water and with air conditioning was higher in the US, while dust load was higher in MX. Significant differences exist between countries in the microbial composition of the floor dust. Dust from Mexican homes was enriched with Alishewanella, Paracoccus, Rheinheimera genera and Intrasporangiaceae family. A predictive metagenomics analysis identified 68 significantly differentially abundant functional pathways between US and MX. This study documented multiple structural, environmental, and demographic differences between homes in the US and MX that may contribute to significantly different microbial composition of dust observed in these two countries.

Gut metagenomic analysis of gastric cancer patients reveals Akkermansia, Gammaproteobacteria, and Veillonella microbiota as potential non-invasive biomarkers

The goal of the study was to investigate the changes in the gut microbiota during the advancement of gastric cancer (GC) and identify pertinent taxa associated with the disease. We used a public fecal amplicon gastric cancer dataset from the Sequence Retrieval Archive (SRA), of patients with GC, gastritis, and healthy individuals. We did sequence pre-processing, including quality filtering of the sequences. Then, we performed a diversity analysis, evaluating α- and β-diversity. Next, taxonomic composition analysis was performed and the relative abundances of different taxa at the phylum and genus levels were compared between GC, gastritis, and healthy controls. The obtained results were subsequently subjected to statistical validation. To conclude, metagenomic function prediction was carried out, followed by correlation analysis between the microbiota and KEGG pathways. α analysis revealed a significant difference between male and female categories, while β analysis demonstrated significant distinctions between GC, gastritis, and healthy controls, as well as between sexes within the GC and gastritis groups. The statistically confirmed taxonomic composition analysis highlighted the presence of the microbes Bacteroides and Veillonella. Furthermore, through metagenomic prediction analysis and correlation analysis with pathways, three taxa, namely Akkermansia, Gammaproteobacteria, and Veillonella, were identified as potential biomarkers for GC. Additionally, this study reports, for the first time, the presence of two bacteria, Desulfobacteriota and Synergistota, in GC, necessitating further investigation. Overall, this research sheds light on the potential involvement of gut microbiota in GC pathophysiology; however, additional studies are warranted to explore its functional significance.

Diet and the gut microbiome in patients with Parkinson’s disease

It has been suggested that gut microbiota influence Parkinson’s disease (PD) via the gut–brain axis. Here, we examine associations between diet and gut microbiome composition and its predicted functional pathways in patients with PD. We assessed gut microbiota in fecal samples from 85 PD patients in central California using 16S rRNA gene sequencing. Diet quality was assessed by calculating the Healthy Eating Index 2015 (HEI-2015) based on the Diet History Questionnaire II. We examined associations of diet quality, fiber, and added sugar intake with microbial diversity, composition, taxon abundance, and predicted metagenomic profiles, adjusting for age, sex, race/ethnicity, and sequencing platform. Higher HEI scores and fiber intake were associated with an increase in putative anti-inflammatory butyrate-producing bacteria, such as the genera Butyricicoccus and Coprococcus 1. Conversely, higher added sugar intake was associated with an increase in putative pro-inflammatory bacteria, such as the genera Klebsiella. Predictive metagenomics suggested that bacterial genes involved in the biosynthesis of lipopolysaccharide decreased with higher HEI scores, whereas a simultaneous decrease in genes involved in taurine degradation indicates less neuroinflammation. We found that a healthy diet, fiber, and added sugar intake affect the gut microbiome composition and its predicted metagenomic function in PD patients. This suggests that a healthy diet may support gut microbiome that has a positive influence on PD risk and progression.

Using Network Analysis and Predictive Functional Analysis to Explore the Fluorotelomer Biotransformation Potential of Soil Microbial Communities.

Microbial transformation of per- and polyfluoroalkyl substances (PFAS), including fluorotelomer-derived PFAS, by native microbial communities in the environment has been widely documented. However, few studies have identified the key microorganisms and their roles during the PFAS biotransformation processes. This study was undertaken to gain more insight into the structure and function of soil microbial communities that are relevant to PFAS biotransformation. We collected 16S rRNA gene sequencing data from 8:2 fluorotelomer alcohol and 6:2 fluorotelomer sulfonate biotransformation studies conducted in soil microcosms under various redox conditions. Through co-occurrence network analysis, several genera, including Variovorax, Rhodococcus, and Cupriavidus, were found to likely play important roles in the biotransformation of fluorotelomers. Additionally, a metagenomic prediction approach (PICRUSt2) identified functional genes, including 6-oxocyclohex-1-ene-carbonyl-CoA hydrolase, cyclohexa-1,5-dienecarbonyl-CoA hydratase, and a fluoride-proton antiporter gene, that may be involved in defluorination. This study pioneers the application of these bioinformatics tools in the analysis of PFAS biotransformation-related sequencing data. Our findings serve as a foundational reference for investigating enzymatic mechanisms of microbial defluorination that may facilitate the development of efficient microbial consortia and/or pure microbial strains for PFAS biotransformation.

Porcine Brain Enzyme Hydrolysate Enhances Immune Function and Antioxidant Defense via Modulation of Gut Microbiota in a Cyclophosphamide-Induced Immunodeficiency Model.

This study examined how consuming porcine brain enzyme hydrolysate (PBEH) affects the immune function and composition of the gut microbiota in an immunodeficient animal model. Male Wistar rats aged 6 weeks were fed casein (control), 100 mg/kg body weight (BW), red ginseng extract (positive-control), and 6, 13, and 26 mg PBEH per kg BW (PBEH-L, PBEH-M, and PBEH-H, respectively) daily for 4 weeks. At 30 min after consuming assigned compounds, they were orally administered cyclophosphamide (CTX; 5 mg/kg BW), an immunosuppressive agent, to suppress the immune system by inhibiting the proliferation of lymphocytes. The normal-control rats were fed casein and water instead of CTX. Natural killer cell activity and splenocyte proliferation induced by 1 μg/mL lipopolysaccharide were lower in the control group than the normal-control group, and they significantly increased with PBEH consumption, particularly at high doses. The PBEH consumption increased dose-dependently in the Th1/Th2 ratio compared to the control. The lipid peroxide contents were lower in the PBEH group than in the control group. Moreover, PBEH m and PBEH-H consumption mitigated white pulp cell damage, reduced red pulp congestion, and increased spleen mast cells in the histological analysis. Intestinal microbiota composition demonstrated differences between the groups at the genus levels, with Akkermansia being more abundant in the control group than the normal-control group and the PBEH-H group showing a decrease. However, Bifidobacterium decreased in the control group but increased in the PBEH-H group. The β-diversity revealed distinct microbial communities of PBEH and positive-control groups compared to the control group (p < 0.05). The metagenome predictions revealed that PBEH-H influenced amino acid metabolism, antioxidant defense, insulin sensitivity, and longevity pathways. In conclusion, PBEH-H intake boosted immune responses and reduced lipid peroxides by modulating gut microbiota composition. These findings suggest that PBEH-H has the potential as a dietary supplement for improving immune function and gut health in individuals with immunodeficiency.

Integration of polygenic and gut metagenomic risk prediction for common diseases

Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.

Comparison of the effectiveness of different normalization methods for metagenomic cross-study phenotype prediction under heterogeneity

The human microbiome, comprising microorganisms residing within and on the human body, plays a crucial role in various physiological processes and has been linked to numerous diseases. To analyze microbiome data, it is essential to account for inherent heterogeneity and variability across samples. Normalization methods have been proposed to mitigate these variations and enhance comparability. However, the performance of these methods in predicting binary phenotypes remains understudied. This study systematically evaluates different normalization methods in microbiome data analysis and their impact on disease prediction. Our findings highlight the strengths and limitations of scaling, compositional data analysis, transformation, and batch correction methods. Scaling methods like TMM show consistent performance, while compositional data analysis methods exhibit mixed results. Transformation methods, such as Blom and NPN, demonstrate promise in capturing complex associations. Batch correction methods, including BMC and Limma, consistently outperform other approaches. However, the influence of normalization methods is constrained by population effects, disease effects, and batch effects. These results provide insights for selecting appropriate normalization approaches in microbiome research, improving predictive models, and advancing personalized medicine. Future research should explore larger and more diverse datasets and develop tailored normalization strategies for microbiome data analysis.

Dose-Responsive Effects of Iron Supplementation on the Gut Microbiota in Middle-Aged Women.

Oral iron supplementation is the first-line treatment for addressing iron deficiency, a concern particularly relevant to women who are susceptible to sub-optimal iron levels. Nevertheless, the impact of iron supplementation on the gut microbiota of middle-aged women remains unclear. To investigate the association between iron supplementation and the gut microbiota, healthy females aged 40-65 years (n = 56, BMI = 23 ± 2.6 kg/m2) were retrospectively analyzed from the Alberta's Tomorrow Project. Fecal samples along with various lifestyle, diet, and health questionnaires were obtained. The gut microbiota was assessed by 16S rRNA sequencing. Individuals were matched by age and BMI and classified as either taking no iron supplement, a low-dose iron supplement (6-10 mg iron/day), or high-dose iron (>100 mg/day). Compositional and functional analyses of microbiome data in relation to iron supplementation were investigated using various bioinformatics tools. Results revealed that iron supplementation had a dose-dependent effect on microbial communities. Elevated iron intake (>100 mg) was associated with an augmentation of Proteobacteria and a reduction in various taxa, including Akkermansia, Butyricicoccus, Verrucomicrobia, Ruminococcus, Alistipes, and Faecalibacterium. Metagenomic prediction further suggested the upregulation of iron acquisition and siderophore biosynthesis following high iron intake. In conclusion, adequate iron levels are essential for the overall health and wellbeing of women through their various life stages. Our findings offer insights into the complex relationships between iron supplementation and the gut microbiota in middle-aged women and underscore the significance of iron dosage in maintaining optimal gut health.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling.

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

(260) Functional and Taxonomic Urine Microbiome Differences in Men with Abnormal Semen Analysis Parameters

Abstract Introduction Male factors contribute to nearly half of all cases of infertility. Next-generation sequencing technologies have allowed for a more nuanced understanding of the widespread influence of the microbiome on health and human disease. Recent evidence has emerged revealing a potential role for the urinary microbiome in impacting male fertility and subfertility, though studies on this topic are sparse. Objective Here, we explore the complex relationship between the urine microbiome and alterations of SA parameters. Methods Men presenting for fertility evaluation or men presenting for vasectomy consultation with proven biological paternity were recruited. Clinical data and urine samples were collected from the patients and SA was performed. Patients were then stratified according to alterations in SA parameters. Urine samples underwent DNA extraction, PCR amplification and 16S rRNA sequencing. Taxonomic microbiome community profiling was performed. Predictive metagenomics was performed using Tax4Fun2 with reference to the KEGG database. Results N = 73 participants were included in the study and were stratified based on alterations, or lack thereof, in SA parameters. Men with abnormal sperm motility (N = 27) showed a higher abundance of urine Dialister micraerophilus (p = 0.0322) compared to those with normal sperm motility (N = 46). This relationship persisted on canonical correlational analysis (r = 0.439, p = 0.0114). Furthermore, when stratifying by sperm motility, nine differentially abundant pathways emerged from predictive metagenomic analysis including pathways critical for basic microbial cell functioning (intermediary metabolism pathways, FoxO signaling, longevity regulating pathways) in addition to pathways synthesizing and breaking down potentially bioactive metabolites (notably long- and short-chain fatty acid metabolism). Men with abnormal sperm concentration (N = 20) showed a lower abundance of urine Enterococcus faecalis (p = 0.0121) and urine Staphylococcus aureus (p = 0.0375), compared to those with normal sperm concentration (N = 53). These findings are outlined in the differential abundance box plots generated from the Analysis of composition of Microbiota with Bias Correction (ANCOM-BC) in Figure 1 and the differential abundance box plots from the predictive functional analysis in Figure 2. Conclusions Our exploratory analysis suggests a role for not just an altered microbial taxonomic profile but also an altered functional profile in men with abnormal SA parameters. These changes in SA parameters may come about through differences in urine microbial metabolite production including short-chain fatty acids or byproducts of intermediary metabolic processes such as those that may contribute to a pro-inflammatory microenvironment. These findings appear to be aligned with the very limited number of studies exploring similar lines of inquiry. These pathways and microbial communities may represent potential therapeutic targets. Further, more mechanistic, investigations are necessary. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: MicrogenDx, Metuchen Pharmaceuticals, Antares Pharma, Boston Scientific, and Endo Pharmaceuticals.

Gut microbiota analyses of cutaneous T-cell lymphoma patients undergoing narrowband ultraviolet B therapy reveal alterations associated with disease treatment.

Recent studies have shown a close relationship between cutaneous T-cell lymphoma (CTCL) and its microbiome. CTCL disease progression is associated with gut dysbiosis and alterations in bacterial taxa parallel those observed in immunologically similar atopic dermatitis. Moreover, the microbial profile of lesional skin may predict response to narrowband ultraviolet B (nbUVB), a common skin-directed therapy. However, the relationship between the gut microbiome, an immunologically vital niche, and nbUVB remains unexplored in CTCL. Herein, we performed 16S rRNA sequencing and PICRUSt2 predictive metagenomics on DNA extracted from stool swabs of 13 CTCL patients treated with nbUVB, 8 non-treated patients, and 13 healthy controls. Disease response was assessed with modified Severity Weighted Assessment Tool (mSWAT); of nbUVB-treated patients, 6 improved (decreased mSWAT), 2 remained stable, and 5 worsened (increased mSWAT). Protective commensal bacteria including Lactobacillaceae and Erysipelatoclostridiaceae were significantly less abundant in CTCL patients compared to controls. With treatment, the CTCL gut microbiome exhibited decreased phylogenetic diversity and lower relative abundance of pro-inflammatory Sutterellaceae. Sutterellaceae was also significantly more abundant in patients who worsened, and Eggerthellaceae and Erysipelotrichaceae trended higher in patients who improved. Finally, PICRUSt2 functional predictions based on shifts in abundance of bacterial sequences repeatedly identified alterations in inositol degradation, which plays a key role in host immunomodulation, including inositol phospholipid signaling relevant to T-cell survival and proliferation. Our results bolster the paradigm of gut dysbiosis in CTCL and its functional implications in disease pathogenesis, and further delineate bacterial taxa associated with nbUVB response and with nbUVB treatment itself.

Mining and rational design of psychrophilic catalases using metagenomics and deep learning models.

A complete catalase-encoding gene, designated soiCat1, was obtained from soil samples via metagenomic sequencing, assembly, and gene prediction. soiCat1 showed 73% identity to a catalase-encoding gene of Mucilaginibacter rubeus strain P1, and the amino acid sequence of soiCAT1 showed 99% similarity to the catalase of a psychrophilic bacterium, Pedobacter cryoconitis. soiCAT1 was identified as a psychrophilic enzyme due to the low optimum temperature predicted by the deep learning model Preoptem, which was subsequently validated through analysis of enzymatic properties. Experimental results showed that soiCAT1 has a very narrow range of optimum temperature, with maximal specific activity occurring at the lowest test temperature (4°C) and decreasing with increasing reaction temperature from 4 to 50°C. To rationally design soiCAT1 with an improved temperature range, soiCAT1 was engineered through site-directed mutagenesis based on molecular evolution data analyzed through position-specific amino acid possibility calculation. Compared with the wild type, one mutant, soiCAT1S205K, exhibited an extended range of optimum temperature ranging from 4 to 20°C. The strategies used in this study may shed light on the mining of genes of interest and rational design of desirable proteins. KEY POINTS: • Numerous putative catalases were mined from soil samples via metagenomics. • A complete sequence encoding a psychrophilic catalase was obtained. • A mutant psychrophilic catalase with an extended range of optimum temperature was engineered through site-directed mutagenesis.

Blue Light-Emitting Diode Irradiation Without a Photosensitizer Alters Oral Microbiome Composition of Ligature-Induced Periodontitis in Mice.

Objective: This study investigated the suppressive effects of blue light-emitting diode (LED) irradiation on bone resorption and changes in the oral microbiome of mice with ligature-induced periodontitis. Background: Wavelength of blue light has antimicrobial effects; however, whether blue LED irradiation alone inhibits the progression of periodontitis remains unclear. Methods: Nine-week-old male mice ligated ligature around the right maxillary second molar was divided into ligation alone (Li) and ligation with blue LED irradiation (LiBL) groups. The LiBL group underwent blue LED (wavelength, 455 nm) irradiation four times in a week at 150 mW/cm2 without a photosensitizer on the gingival tissue around the ligated tooth at a distance of 5 mm for 5 min. The total energy density per day was 45 J/cm2. Bone resorption was evaluated using micro-computed tomography at 8 days. Differences in the oral microbiome composition of the collected ligatures between the Li and LiBL groups were analyzed using next-generation sequencing based on the 16S rRNA gene from the ligatures. Results: Blue LED irradiation did not suppress bone resorption caused by ligature-induced periodontitis. However, in the LiBL group, the α-diversity, number of observed features, and Chao1 were significantly decreased. The relative abundances in phylum Myxococcota and Bacteroidota were underrepresented, and the genera Staphylococcus, Lactococcus, and Lactobacillus were significantly overrepresented by blue LED exposure. Metagenomic function prediction indicated an increase in the downregulated pathways related to microbial energy metabolism after irradiation. The co-occurrence network was altered to a simpler structure in the LiBL group, and the number of core genera decreased. Conclusions: Blue LED irradiation altered the composition and network of the oral microbiome of ligature-induced periodontitis in mice.

Coping with extremes: Alternations in diet, gut microbiota, and hepatic metabolic functions in a highland passerine

In wild animals, diet and gut microbiota interactions are critical moderators of metabolic functions and are highly contingent on habitat conditions. Challenged by the extreme conditions of high-altitude environments, the strategies implemented by highland animals to adjust their diet and gut microbial composition and modulate their metabolic substrates remain largely unexplored. By employing a typical human commensal species, the Eurasian tree sparrow (Passer montanus, ETS), as a model species, we studied the differences in diet, digestive tract morphology and enzyme activity, gut microbiota, and metabolic energy profiling between highland (the Qinghai-Tibet Plateau, QTP; 3230 m) and lowland (Shijiazhuang, Hebei; 80 m) populations. Our results showed that highland ETSs had enlarged digestive organs and longer small intestinal villi, while no differences in key digestive enzyme activities were observed between the two populations. The 18S rRNA sequencing results revealed that the dietary composition of highland ETSs were more animal-based and less plant-based than those of the lowland ones. Furthermore, 16S rRNA sequencing results suggested that the intestinal microbial communities were structurally segregated between populations. PICRUSt metagenome predictions further indicated that the expression patterns of microbial genes involved in material and energy metabolism, immune system and infection, and xenobiotic biodegradation were strikingly different between the two populations. Analysis of liver metabolomics revealed significant metabolic differences between highland and lowland ETSs in terms of substrate utilization, as well as distinct sex-specific alterations in glycerophospholipids. Furthermore, the interplay between diet, liver metabolism, and gut microbiota suggests a dietary shift resulting in corresponding changes in gut microbiota and metabolic functions. Our findings indicate that highland ETSs have evolved to optimize digestion and absorption, rely on more protein-rich foods, and possess gut microbiota tailored to their dietary composition, likely adaptive physiological and ecological strategies adopted to cope with extreme highland environments.