Applications of Data Characteristic AI-Assisted Raman Spectroscopy in Pathological Classification.

Raman spectroscopy has been widely used for label-free biomolecular analysis of cells and tissues for pathological diagnosis in vitro and in vivo. AI technology facilitates disease diagnosis based on Raman spectroscopy, including machine learning (PCA and SVM), manifold learning (UMAP), and deep learning (ResNet and AlexNet). However, it is not clear how to optimize the appropriate AI classification model for different types of Raman spectral data. Here, we selected five representative Raman spectral data sets, including endometrial carcinoma, hepatoma extracellular vesicles, bacteria, melanoma cell, diabetic skin, with different characteristics regarding sample size, spectral data size, Raman shift range, tissue sites, Kullback-Leibler (KL) divergence, and significant Raman shifts (i.e., wavenumbers with significant differences between groups), to explore the performance of different AI models (e.g., PCA-SVM, SVM, UMAP-SVM, ResNet or AlexNet). For data set of large spectral data size, Resnet performed better than PCA-SVM and UMAP. By building data characteristic-assisted AI classification model, we optimized the network parameters (e.g., principal components, activation function, and loss function) of AI model based on data size and KL divergence etc. The accuracy improved from 85.1 to 94.6% for endometrial carcinoma grading, from 77.1 to 90.7% for hepatoma extracellular vesicles detection, from 89.3 to 99.7% for melanoma cell detection, from 88.1 to 97.9% for bacterial identification, from 53.7 to 85.5% for diabetic skin screening, and mean time expense of 5 s.

Forest management positively reshapes the phyllosphere bacterial community and improves community stability.

Research has shown that forest management can improve the post-drought growth and resilience of Qinghai spruce in the eastern Qilian Mountains, located on the northeastern Tibetan Plateau. However, the impact of such management on the tree-associated phyllosphere microbiome is not yet fully understood. This study provides new evidence of positive forest management effects on the phyllosphere microbiome after extreme drought, from the perspectives of community diversity, structure, network inference, keystone species, and assembly processes. In managed Qinghai spruce forest, the α-diversity of the phyllosphere bacterial communities increased, whereas the ß-diversity decreased. In addition, the phyllosphere bacterial community became more stable and resistant, yet less complex, following forest management. Keystone species inferred from a bacterial network also changed under forest management. Furthermore, forest management mediated changes in community assembly processes, intensifying the influence of determinacy, while diminishing that of stochasticity. These findings support the hypothesis that management can re-assemble the phyllosphere bacterial community, enhance community stability, and ultimately improve tree growth. Overall, the study highlights the importance of forest management on the phyllosphere microbiome and furnishes new insights into forest conservation from the perspective of managing microbial processes and effects.

Asymmetries among soil fungicide residues, nitrous oxide emissions and microbiomes regulated by nitrification inhibitor at different moistures.

Carbendazim residue has been widely concerned, and nitrous oxide (N2O) is one of the dominant greenhouse gases. Microbial metabolisms are fundamental processes of removing organic pollutant and producing N2O. Nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) can change soil abiotic properties and microbial communities and simultaneously affect carbendazim degradation and N2O emission. In this study, the comprehensive linkages among carbendazim residue, N2O emission and microbial community after the DMPP application were quantified under different soil moistures. Under 90% WHC, the DMPP application significantly reduced carbendazim residue by 54.82% and reduced soil N2O emission by 98.68%. The carbendazim residue was negatively related to soil ammonium nitrogen (NH4+-N), urease activity, and ratios of Bacteroidetes, Thaumarchaeota and Nitrospirae under 90% WHC, and the N2O emission was negatively related to NH4+-N content and relative abundance of Acidobacteria under the 60% WHC condition. In the whole (60% and 90% WHC together), the carbendazim residue was negatively related to the abundances of nrfA (correlation coefficient = -0.623) and nrfH (correlation coefficient = -0.468) genes. The hao gene was negatively related to the carbendazim residue but was positively related to the N2O emission rate. The DMPP application had the promising potential to simultaneously reduce ecological risks of fungicide residue and N2O emission via altering soil abiotic properties, microbial activities and communities and functional genes. ENVIRONMENTAL IMPLICATION: Carbendazim was a high-efficiency fungicide that was widely used in agricultural production. Nitrous oxide (N2O) is the third most important greenhouse gas responsible for global warming. The 3, 4-dimethylpyrazole phosphate (DMPP) is an effective nitrification inhibitor widely used in agricultural production. This study indicated that the DMPP application reduced soil carbendazim residues and N2O emission. The asymmetric linkages among the carbendazim residue, N2O emission, microbial community and functional gene abundance were regulated by the DMPP application and soil moisture. The results could broaden our horizons on the utilizations DMPP in decreasing fungicide risks and N2O emission.

Heavy metal induced shifts in microbial community composition and interactions with dissolved organic matter in coastal sediments.

Heavy metals can impact the structure and function of coastal sediment. The dissolved organic matter (DOM) pool plays an important role in determining both the heavy metal toxicity and microbial community composition in coastal sediments. However, how heavy metals affect the interactions between microbial communities and DOM remains unclear. Here, we investigated the influence of heavy metals on the microbial community structure (including bacteria and archaea) and DOM composition in surface sediments of Beibu Gulf, China. Our results revealed firstly that chromium, zinc, cadmium, and lead were the heavy metals contributing to pollution in our studied area. Furthermore, the DOM chemical composition was distinctly different in the contaminated area from the uncontaminated area, characterized by a higher average O/C ratio and increased prevalence of carboxyl-rich alicyclic molecules (CRAM) and highly unsaturated compounds (HUC). This indicates that DOM in the contaminated area was more recalcitrant compared to the uncontaminated area. Except for differences in archaeal diversity between the two areas, there were no significant variations observed in the structure of archaea and bacteria, as well as the diversity of bacteria, across the two areas. Nevertheless, our co-occurrence network analysis revealed that the B2M28 and Euryarchaeota, dominating bacterial and archaeal groups in the contaminated area were strongly related to CRAM. The network analysis also unveiled correlations between active bacteria and elevated proportions of nitrogen-containing DOM molecules. In contrast, the archaea-DOM network exhibited strong associations with nitrogen- and sulfur-containing molecules. Collectively, these findings suggest that heavy metals indeed influence the interaction between microbial communities and DOM, potentially affecting the accumulation of recalcitrant compounds in coastal sediments.

Childcare centre soil microbiomes are influenced by substrate type and surrounding vegetation condition.

Urban development has profoundly reduced human exposure to biodiverse environments, which is linked to a rise in human disease. The 'biodiversity hypothesis' proposes that contact with diverse microbial communities (microbiota) benefits human health, as exposure to microbial diversity promotes immune training and regulates immune function. Soils and sandpits in urban childcare centres may provide exposure to diverse microbiota that support immunoregulation at a critical developmental stage in a child's life. However, the influence of outdoor substrate (i.e., sand vs. soil) and surrounding vegetation on these environmental microbiota in urban childcare centres remains poorly understood. Here, we used 16S rRNA amplicon sequencing to examine the variation in bacterial communities in sandpits and soils across 22 childcare centres in Adelaide, Australia, plus the impact of plant species richness and habitat condition on these bacterial communities. We show that sandpits had distinct bacterial communities and lower alpha diversity than soils. In addition, we found that plant species richness in the centres' yards and habitat condition surrounding the centres influenced the bacterial communities in soils but not sandpits. These results demonstrate that the diversity and composition of childcare centre sandpit and soil bacterial communities are shaped by substrate type, and that the soils are also shaped by the vegetation within and surrounding the centres. Accordingly, there is potential to modulate the exposure of children to health-associated bacterial communities by managing substrates and vegetation in and around childcare centres.

Promising probiotic-fermented soymilk for alleviating acute diarrhea: insights into the microbiome and metabolomics.

Fermented soymilk (FSM4) has attracted much attention due to its nutritional and health characteristics. Exploring FSM4 products to alleviate diarrhea can ensure their effectiveness as a therapeutic food for alleviating gastrointestinal disorders. However, the relationship between gut microbiota and gut metabolite production remains unknown during diarrheal episodes. Therefore, the diarrhea-alleviating role and mechanisms of FSM4 in diarrhea rats were investigated via biochemical, gut microbiota, and serum metabolite analyses. The findings showed that consuming FSM4 improved diarrhea symptoms and reduced systemic inflammation better than non-fermented soymilk (NFSM). It is worth noting that FSM4 promoted the diversity, richness, structure, and composition of gut microbiota. It increased the ability to reduce inflammation associated with harmful bacteria (Anaerofilum, Flavonifractor, Bilophila, Anaerostipes, [Ruminococcus]_torques_group, Clostridium_sensu_stricto_1, Turicibacter, Ruminococcus_1, Ruminiclostridium_6, Prevotellaceae_NK3B31_group and Fusicatenibacter), while stimulating the growth of healthy species (Lactobacillus, Ruminococcaceae_UCG-014, Oscillibacter, [Eubacterium]_coprostanoligenes_group, Negativibacillus, and Erysipelotrichaceae_UCG-003). Moreover, metabolomics analysis showed that lipid metabolites such as lysophosphatidylethanolamine (LysoPE) and sphingolipids were upregulated in the NG group, closely related to pro-inflammatory cytokines (IL-6, IL-1ß, TNF-α, and IFN-γ) and the aforementioned pathogenic bacteria. Notably, in treatment groups, especially FSM4, the accumulation of L-ornithine, aspartic acid, ursocholic acid, 18-oxooleate, and cyclopentanethiol was increased, which was robustly associated with the anti-inflammatory factor IL-10 and beneficial bacteria mentioned above. Therefore, it can be inferred that the amino acids, bile acid, 18-oxooleate, and cyclopentanethiol produced in the FSM4 group can serve as metabolic biomarkers, which synergistically act with the gut microbiota to help alleviate inflammation for diarrhea remission. Overall, FSM4 may provide a new alternative, as an anti-inflammatory diet, to alleviate diarrhea.

Microbiological exploration of the Cueva del Viento lava tube system in Tenerife, Canary Islands.

Cueva del Viento, located in the Canary Islands, Spain, is the Earth's sixth-longest lava tube, spanning 18,500 m, and was formed approximately 27,000 years ago. This complex volcanic cave system is characterized by a unique geomorphology, featuring an intricate network of galleries. Despite its geological significance, the geomicrobiology of Cueva del Viento remains largely unexplored. This study employed a combination of culture-dependent techniques and metabarcoding data analysis to gain a comprehensive understanding of the cave's microbial diversity. The 16S rRNA gene metabarcoding approach revealed that the coloured microbial mats (yellow, red and white) coating the cave walls are dominated by the phyla Actinomycetota, Pseudomonadota and Acidobacteriota. Of particular interest is the high relative abundance of the genus Crossiella, which is involved in urease-mediated biomineralization processes, along with the presence of genera associated with nitrogen cycling, such as Nitrospira. Culture-dependent techniques provided insights into the morphological characteristics of the isolated species and their potential metabolic activities, particularly for the strains Streptomyces spp., Paenarthrobacter sp. and Pseudomonas spp. Our findings underscore the potential of Cueva del Viento as an ideal environment for studying microbial diversity and for the isolation and characterization of novel bacterial species of biotechnological interest.

Cereal leaf beetle-associated bacteria enhance the survival of their host upon insecticide treatments and respond differently to insecticides with different modes of action.

The cereal leaf beetle (CLB, Oulema melanopus) is one of the major cereal pests. The effect of insecticides belonging to different chemical classes, with different mechanisms of action and the active substances' concentrations on the CLB bacterial microbiome, was investigated. Targeted metagenomic analysis of the V3-V4 regions of the 16S ribosomal gene was used to determine the composition of the CLB bacterial microbiome. Each of the insecticides caused a decrease in the abundance of bacteria of the genus Pantoea, and an increase in the abundance of bacteria of the genus Stenotrophomonas, Acinetobacter, compared to untreated insects. After cypermethrin application, a decrease in the relative abundance of bacteria of the genus Pseudomonas was noted. The dominant bacterial genera in cypermethrin-treated larvae were Lactococcus, Pantoea, while in insects exposed to chlorpyrifos or flonicamid it was Pseudomonas. Insecticide-treated larvae were characterized, on average, by higher biodiversity and richness of bacterial genera, compared to untreated insects. The depletion of CLB-associated bacteria resulted in a decrease in larval survival, especially after cypermethrin and chlorpyrifos treatments. The use of a metagenome-based functional prediction approach revealed a higher predicted function of bacterial acetyl-CoA C-acetyltransferase in flonicamid and chlorpyrifos-treated larvae and tRNA dimethyltransferase in cypermethrin-treated insects than in untreated insects.

Endometrial microbiota alteration in female patients with endometrial polyps based on 16S rRNA gene sequencing analysis.

Introduction: The potential role of the endometrial microbiota in the pathogenesis of endometrial polyps (EPs) warrants further investigation, given the current landscape of limited and inconclusive research findings. We aimed to explore the microecological characteristics of the uterine cavity in patients with EPs and investigate the potential of endometrial microbiota species as novel biomarkers for identifying EPs. Methods: Endometrial samples were collected from 225 patients who underwent hysteroscopies, of whom 167 had EPs, whereas 58 had non- hyperproliferative endometrium status. The endometrial microbiota was assessed using 16S rRNA gene sequencing. We characterized the endometrial microbiota and identified microbial biomarkers for predicting EPs. Results: The endometrial microbial diversity and composition were significantly different between the EP and control groups. Predictive functional analyses of the endometrial microbiota demonstrated significant alterations in pathways involved in sphingolipid metabolism, steroid hormone biosynthesis, and apoptosis between the two groups. Moreover, a classification model based on endometrial microbial ASV-based biomarkers along with the presence of abnormal uterine bleeding symptoms achieved powerful classification potential in identifying EPs in both the discovery and validation cohorts. Conclusion: Our study indicates a potential association between altered endometrial microbiota and EPs. Endometrial microbiota-based biomarkers may prove valuable for the diagnosis of EPs. Clinical trial registration: Chinese Clinical Trial Registry (ChiCTR2100052746).

pyPGCF: A Python Software for Phylogenomic Analysis, Species Demarcation, Identification of Core, and Fingerprint Proteins of Bacterial Genomes That Are Important for Plants.

This computational protocol describes how to use pyPGCF, a python software package that runs in the linux environment, in order to analyze bacterial genomes and perform: (i) phylogenomic analysis, (ii) species demarcation, (iii) identification of the core proteins of a bacterial genus and its individual species, (iv) identification of species-specific fingerprint proteins that are found in all strains of a species and, at the same time, are absent from all other species of the genus, (v) functional annotation of the core and fingerprint proteins with eggNOG, and (vi) identification of secondary metabolite biosynthetic gene clusters (smBGCs) with antiSMASH. This software has already been implemented to analyze bacterial genera and species that are important for plants (e.g., Pseudomonas, Bacillus, Streptomyces). In addition, we provide a test dataset and example commands showing how to analyze 165 genomes from 55 species of the genus Bacillus. The main advantages of pyPGCF are that: (i) it uses adjustable orthology cut-offs, (ii) it identifies species-specific fingerprints, and (iii) its computational cost scales linearly with the number of genomes being analyzed. Therefore, pyPGCF is able to deal with a very large number of bacterial genomes, in reasonable timescales, using widely available levels of computing power.

Cold-active microbial enzymes and their biotechnological applications.

Microorganisms known as psychrophiles/psychrotrophs, which survive in cold climates, constitute majority of the biosphere on Earth. Their capability to produce cold-active enzymes along with other distinguishing characteristics allows them to survive in the cold environments. Due to the relative ease of large-scale production compared to enzymes from plants and animals, commercial uses of microbial enzyme are alluring. The ocean depths, polar, and alpine regions, which make up over 85% of the planet, are inhabited to cold ecosystems. Microbes living in these regions are important for their metabolic contribution to the ecosphere as well as for their enzymes, which may have potential industrial applications. Cold-adapted microorganisms are a possible source of cold-active enzymes that have high catalytic efficacy at low and moderate temperatures at which homologous mesophilic enzymes are not active. Cold-active enzymes can be used in a variety of biotechnological processes, including food processing, additives in the detergent and food industries, textile industry, waste-water treatment, biopulping, environmental bioremediation in cold climates, biotransformation, and molecular biology applications with great potential for energy savings. Genetically manipulated strains that are suitable for producing a particular cold-active enzyme would be crucial in a variety of industrial and biotechnological applications. The potential advantage of cold-adapted enzymes will probably lead to a greater annual market than for thermo-stable enzymes in the near future. This review includes latest updates on various microbial source of cold-active enzymes and their biotechnological applications.

Gut microbiota composition in patients with Crohn's disease in Saudi Arabia.

Crohn's disease (CD) entails intricate interactions with gut microbiome diversity, richness, and composition. The relationship between CD and gut microbiome is not clearly understood and has not been previously characterized in Saudi Arabia. We performed statistical analysis about various factors influencing CD activity and microbiota dysbiosis, including diagnosis, treatment, and its impact on their quality of life as well as high-throughput metagenomic V3-V4 16S rRNA encoding gene hypervariable region of a total of eighty patients with CD, both in its active and inactive state with healthy controls. The results were correlated with the demographic and lifestyle information, which the participants provided via a questionnaire. α-diversity measures indicated lower bacterial diversity and richness in the active and inactive CD groups compared to the control group. Greater dysbiosis was observed in the active CD patients compared to the inactive form of the disease, showed by a reduction in microbial diversity. Specific pathogenic bacteria such as Filifactor, Peptoniphilus, and Sellimonas were identified as characteristic of CD groups. In contrast, anti-inflammatory bacteria like Defluviitalea, Papillibacter, and Petroclostridium were associated with the control group. Among the various factors influencing disease activity and microbiota dysbiosis, smoking emerged as the most significant, with reduced α-diversity and richness for the smokers in all groups, and proinflammatory Fusobacteria was more present (p<0.05). Opposite to the control group, microbial diversity and richness were lower in CD participants of older age compared to younger ones, and male CD participants showed less diversity compared to women participants from the same groups. Our results describe the first report on the relationship between microbiota and Crohn's disease progress in Saudi Arabia, which may provide a theoretical basis for the application of therapeutic methods to regulate gut microbes in CD.

Evolution of homologous recombination rates across bacteria.

Bacteria are nonsexual organisms but are capable of exchanging DNA at diverse degrees through homologous recombination. Intriguingly, the rates of recombination vary immensely across lineages where some species have been described as purely clonal and others as "quasi-sexual." However, estimating recombination rates has proven a difficult endeavor and estimates often vary substantially across studies. It is unclear whether these variations reflect natural variations across populations or are due to differences in methodologies. Consequently, the impact of recombination on bacterial evolution has not been extensively evaluated and the evolution of recombination rate-as a trait-remains to be accurately described. Here, we developed an approach based on Approximate Bayesian Computation that integrates multiple signals of recombination to estimate recombination rates. We inferred the rate of recombination of 162 bacterial species and one archaeon and tested the robustness of our approach. Our results confirm that recombination rates vary drastically across bacteria; however, we found that recombination rate-as a trait-is conserved in several lineages but evolves rapidly in others. Although some traits are thought to be associated with recombination rate (e.g., GC-content), we found no clear association between genomic or phenotypic traits and recombination rate. Overall, our results provide an overview of recombination rate, its evolution, and its impact on bacterial evolution.

Metabolic coupling between soil aerobic methanotrophs and denitrifiers in rice paddy fields.

Paddy fields are hotspots of microbial denitrification, which is typically linked to the oxidation of electron donors such as methane (CH4) under anoxic and hypoxic conditions. While several anaerobic methanotrophs can facilitate denitrification intracellularly, whether and how aerobic CH4 oxidation couples with denitrification in hypoxic paddy fields remains virtually unknown. Here we combine a ~3300 km field study across main rice-producing areas of China and 13CH4-DNA-stable isotope probing (SIP) experiments to investigate the role of soil aerobic CH4 oxidation in supporting denitrification. Our results reveal positive relationships between CH4 oxidation and denitrification activities and genes across various climatic regions. Microcosm experiments confirm that CH4 and methanotroph addition promote gene expression involved in denitrification and increase nitrous oxide emissions. Moreover, 13CH4-DNA-SIP analyses identify over 70 phylotypes harboring genes associated with denitrification and assimilating 13C, which are mostly belonged to Rubrivivax, Magnetospirillum, and Bradyrhizobium. Combined analyses of 13C-metagenome-assembled genomes and 13C-metabolomics highlight the importance of intermediates such as acetate, propionate and lactate, released during aerobic CH4 oxidation, for the coupling of CH4 oxidation with denitrification. Our work identifies key microbial taxa and pathways driving coupled aerobic CH4 oxidation and denitrification, with important implications for nitrogen management and greenhouse gas regulation in agroecosystems.

Vertical differences in carbon metabolic diversity and dominant flora of soil bacterial communities in farmlands.

The carbon cycle in soil is significantly influenced by soil microbes. To investigate the vertical distribution of the dominant groups in agricultural soil and the carbon metabolic diversity of soil bacteria, 45 soil samples from the 0 ~ 50 cm soil layer in Hunan tobacco-rice multiple cropping farmland were collected in November 2017, and the carbon diversity of the soil bacterial community, bacterial community composition and soil physical and chemical properties were determined. The results showed that the carbon metabolic capabilities and functional diversity of the soil bacterial community decreased with depth. The three most widely used carbon sources for soil bacteria were carbohydrates, amino acids, and polymers. The dominant bacterial groups in surface soil (such as Chloroflexi, Acidobacteriota, and Bacteroidota) were significantly positively correlated with the carbon metabolism intensity. The alkali-hydrolysable nitrogen content, soil bulk density and carbon-nitrogen ratio were the key soil factors driving the differences in carbon metabolism of the soil bacterial communities in the different soil layers.

Production of kojic acid by Aspergillus flavus OL314748 using box-Behnken statistical design and its antibacterial and anticancer applications using molecular docking technique.

Kojic acid is a wonderful fungal secondary metabolite that has several applications in the food, medical, and agriculture sectors. Many human diseases become resistant to normal antibiotics and normal treatments. We need to search for alternative treatment sources and understand their mode of action. Aspergillus flavus ASU45 (OL314748) was isolated from the caraway rhizosphere as a non-aflatoxin producer and identified genetically using 18S rRNA gene sequencing. After applying the Box-Behnken statistical design to maximize KA production, the production raised from 39.96 to 81.59 g/l utilizing (g/l) glucose 150, yeast extract 5, KH2PO4 1, MgSO4.7H2O 2, and medium pH 3 with a coefficient (R2) of 98.45%. Extracted KA was characterized using FTIR, XRD, and a scanning electron microscope. Crystalized KA was an effective antibacterial agent against six human pathogenic bacteria (Bacillus cereus, Staphylococcus aureus, Escherichia coli, Klebsiella pneumonia, Serratia marcescens, and Serratia plymuthica). KA achieves high inhibition activity against Bacillus cereus, K. pneumonia, and S. plymuthica at 100 µg/ml concentration by 2.75, 2.85, and 2.85 compared with chloramphenicol which gives inhibition zones 1, 1.1, and 1.6, respectively. Crystalized KA had anticancer activity versus three types of cancer cell lines (Mcf-7, HepG2, and Huh7) and demonstrated high cytotoxic capabilities on HepG-2 cells that propose strong antitumor potent of KA versus hepatocellular carcinoma. The antibacterial and anticancer modes of action were illustrated using the molecular docking technique. Crystalized kojic acid from a biological source represented a promising microbial metabolite that could be utilized as an alternative antibacterial and anticancer agent effectively.

Pathogenic spectrum and risk factors of peritoneal dialysis-associated peritonitis: a single-center retrospective study.

The present study aimed to explore the pathogenic spectrum and risk factors of peritoneal dialysis-associated peritonitis (Peritoneal dialysis associated peritonitis, PDAP) in Yongzhou, Hunan, China. The clinical and epidemiological data on regular peritoneal dialysis (Peritoneal dialysis, PD) between January 2016 and December 2020 in Yongzhou were collected for retrospective analysis. The related factors of peritonitis were evaluated by single-factor analysis, while risk factors of refractory PDAP were evaluated by multivariate logistic regression analysis.172/331 172 (51.9%) patients developed peritonitis. The risk factors of PDAP in PD patients included high C-reactive protein (C-reactive protein, CRP), low albumin(Albumin, ALB), low hemoglobin (Hemoglobin, Hb), low educational level (junior high school or lower), preference of spicy food, irregular diet, low annual household income, unfavorable fluid exchange conditions, unstable employment (including working as a farmer), and unfavorable humidity conditions (P < 0.05). 63/172 (36.6%) PDAP patients were intractable cases with a pathogenic bacteria positive rate of 74.60% in the peritoneal dialysate cultures, and 109/172 patients were non-intractable cases with a pathogenic bacteria positive rate of 53.21%. Gram-positive bacteria (G+) were detected in most of the dialysate cultures, with Staphylococcus epidermidis (S. epidermidis) as the most common type, while Escherichia coli (E. coli) was the most common Gram-negative bacteria (G-). Gram-positive bacteria were sensitive to vancomycin and linezolid, while G- bacteria were sensitive to imipenem and amikacin. Lifestyle, educational level, and environmental factors are the major contributors to PDAP in PD patients. Fungal and multi-bacterial infections are the major causes of death; PD is stopped for such patients.

The characteristics of microbiome in the upper respiratory tract of COVID-19 patients.

BACKGROUND: Co-infection with other pathogens in coronavirus disease 2019 (COVID-19) patients exacerbates disease severity and impacts patient prognosis. Clarifying the exact pathogens co-infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is premise of the precise treatment for COVID-19 patients. METHODS: Sputum samples were collected from 17 patients in the COVID-19 positive group and 18 patients in the COVID-19 negative group. DNA extraction was performed to obtain the total DNA. Sequencing analysis using 16S and ITS rRNA gene was carried out to analyze the composition of bacterial and fungal communities. Meanwhile, all the samples were inoculated for culture. RESULTS: We did not observe significant differences in bacterial composition between the COVID-19 positive and negative groups. However, a significantly higher abundance of Candida albicans was observed in the upper respiratory tract samples from the COVID-19 positive group compared to the COVID-19 negative group. Moreover, the Candida albicans strains isolated from COVID-19 positive group exhibited impaired secretion of aspartyl proteinases. CONCLUSION: COVID-19 positive patients demonstrate a notable increase in the abundance of Candida albicans, along with a decrease in the levels of aspartyl proteinases, indicating the alteration of microbiota composition of upper respiratory tract.

Gut bacterial and fungal dysbiosis in tuberculosis patients.

BACKGROUND: Recent studies have more focused on gut microbial alteration in tuberculosis (TB) patients. However, no detailed study on gut fungi modification has been reported till now. So, current research explores the characteristics of gut microbiota (bacteria)- and mycobiota (fungi)-dysbiosis in TB patients and also assesses the correlation between the gut microbiome and serum cytokines. It may help to screen the potential diagnostic biomarker for TB. RESULTS: The results show that the alpha diversity of the gut microbiome (including bacteria and fungi) decreased and altered the gut microbiome composition of TB patients. The bacterial genera Bacteroides and Prevotella were significantly increased, and Blautia and Bifidobacterium decreased in the TB patients group. The fungi genus Saccharomyces was increased while decreased levels of Aspergillus in TB patients. It indicates that gut microbial equilibrium between bacteria and fungi has been altered in TB patients. The fungal-to-bacterial species ratio was significantly decreased, and the bacterial-fungal trans-kingdom interactions have been reduced in TB patients. A set model including Bacteroides, Blautia, Eubacterium_hallii_group, Apiotrichum, Penicillium, and Saccharomyces may provide a better TB diagnostics option than using single bacterial or fungi sets. Also, gut microbial dysbiosis has a strong correlation with the alteration of IL-17 and IFN-γ. CONCLUSIONS: Our results demonstrate that TB patients exhibit the gut bacterial and fungal dysbiosis. In the clinics, some gut microbes may be considered as potential biomarkers for auxiliary TB diagnosis.

Microbiome signatures associated with clinical stages of gastric Cancer: whole metagenome shotgun sequencing study.

BACKGROUND: Gastric cancer is one of the global health concerns. A series of studies on the stomach have confirmed the role of the microbiome in shaping gastrointestinal diseases. Delineation of microbiome signatures to distinguish chronic gastritis from gastric cancer will provide a non-invasive preventative and treatment strategy. In this study, we performed whole metagenome shotgun sequencing of fecal samples to enhance the detection of rare bacterial species and increase genome sequence coverage. Additionally, we employed multiple bioinformatics approaches to investigate the potential targets of the microbiome as an indicator of differentiating gastric cancer from chronic gastritis. RESULTS: A total of 65 patients were enrolled, comprising 33 individuals with chronic gastritis and 32 with gastric cancer. Within each group, the chronic gastritis group was sub-grouped into intestinal metaplasia (n = 15) and non-intestinal metaplasia (n = 18); the gastric cancer group, early stage (stages 1 and 2, n = 13) and late stage (stages 3 and 4, n = 19) cancer. No significant differences in alpha and beta diversities were detected among the patient groups. However, in a two-group univariate comparison, higher Fusobacteria abundance was identified in phylum; Fusobacteria presented higher abundance in gastric cancer (LDA scored 4.27, q = 0.041 in LEfSe). Age and sex-adjusted MaAsLin and Random Forest variable of importance (VIMP) analysis in species provided meaningful features; Bacteria_caccae was the most contributing species toward gastric cancer and late-stage cancer (beta:2.43, se:0.891, p:0.008, VIMP score:2.543). In contrast, Bifidobacterium_longum significantly contributed to chronic gastritis (beta:-1.8, se:0.699, p:0.009, VIMP score:1.988). Age, sex, and BMI-adjusted MasAsLin on metabolic pathway analysis showed that GLCMANNANAUT-PWY degradation was higher in gastric cancer and one of the contributing species was Fusobacterium_varium. CONCLUSION: Microbiomes belonging to the pathogenic phylum Fusobacteria and species Bacteroides_caccae and Streptococcus_anginosus can be significant targets for monitoring the progression of gastric cancer. Whereas Bifidobacterium_longum and Lachnospiraceae_bacterium_5_1_63FAA might be protection biomarkers against gastric cancer.