UNASSIGNED: In the field of forensic science, accurately determining occupation of an individual can greatly assist in resolving cases such as criminal investigations or disaster victim identifications. However, estimating occupation can be challenging due to the intricate relationship between occupation and various factors, including gender, age, living environment, health status, medication use, and lifestyle habits such as alcohol consumption and smoking. All of these factors can impact the composition of oral or gut microbial community of an individual.
UNASSIGNED: In this study, we collected saliva and feces samples from individuals representing different occupational sectors, specifically students and manual laborers. We then performed metagenomic sequencing on the DNA extracted from these samples to obtain data that could be analyzed for taxonomic and functional annotations in five different databases. The correlation between occupation with microbial information was assisted from the perspective of α and β diversity, showing that individuals belonging to the two occupations hold significantly different oral and gut microbial communities, and that this correlation is basically not affected by gender, drinking, and smoking in our datasets. Finally, random forest (RF) models were built with recursive feature elimination (RFE) processes. Models with 100% accuracy in both training and testing sets were constructed based on three species in saliva samples or on a single pathway annotated by the KEGG database in fecal samples, namely, \"ko04145\" or Phagosome.
UNASSIGNED: Although this study may have limited representativeness due to its small sample size, it provides preliminary evidence of the potential of using microbiome information for occupational inference.

UNASSIGNED: The gut microbiota is a complex ecosystem that plays a critical role in human health and disease. However, the relationship between gut microbiota and intestinal damage caused by burns is not well understood. The intestinal mucus layer is crucial for maintaining intestinal homeostasis and providing a physiological barrier against bacterial invasion. This study aims to investigate the impact of gut microbiota on the synthesis and degradation of intestinal mucus after burns and explore potential therapeutic targets for burn injury.
UNASSIGNED: A modified histopathological grading system was employed to investigate the effects of burn injury on colon tissue and the intestinal mucus barrier in mice. Subsequently, 16S ribosomal RNA sequencing was used to analyze alterations in the gut microbiota at days 1-10 post-burn. Based on this, metagenomic sequencing was conducted on samples collected at days 1, 5 and 10 to investigate changes in mucus-related microbiota and explore potential underlying mechanisms.
UNASSIGNED: Our findings showed that the mucus barrier was disrupted and that bacterial translocation occurred on day 3 following burn injury in mice. Moreover, the gut microbiota in mice was significantly disrupted from days 1 to 3 following burn injury, but gradually recovered to normal as the disease progressed. Specifically, there was a marked increase in the abundance of symbiotic and pathogenic bacteria associated with mucin degradation on day 1 after burns, but the abundance returned to normal on day 5. Conversely, the abundance of probiotic bacteria associated with mucin synthesis changed in the opposite direction. Further analysis revealed that after a burn injury, bacteria capable of degrading mucus may utilize glycoside hydrolases, flagella and internalins to break down the mucus layer, while bacteria that synthesize mucus may help restore the mucus layer by promoting the production of short-chain fatty acids.
UNASSIGNED: Burn injury leads to disruption of colonic mucus barrier and dysbiosis of gut microbiota. Some commensal and pathogenic bacteria may participate in mucin degradation via glycoside hydrolases, flagella, internalins, etc. Probiotics may provide short-chain fatty acids (particularly butyrate) as an energy source for stressed intestinal epithelial cells, promote mucin synthesis and accelerate repair of mucus layer.

Oral squamous cell carcinoma (OSCC) is one of the most common malignant tumours with increasing incidence, and oral leukoplakia (OLK) has a strong tendency to undergo malignant transformation. The oral microbiota may influence oral cancer progression, but the salivary bacterial composition and functional changes in OSCC and OLK have not been comprehensively elucidated. Therefore, we compared salivary bacteria in OLK and OSCC patients with healthy controls (HC).
Metagenomic sequencing was used to compare the bacterial composition and functional changes of 18 OSCC patients, 21 OLK patients and 21 HC. Spearman correlation was used to identify possible associations between functions and bacteria.
Gemella was the most differentially enriched genus in OSCC. At the species level, Streptococcus sp. NPS 308, Streptococcus agalactiae, Gemella haemolysans and Gemella morbillorum were slightly increased in OLK and OSCC. Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that OSCC was mainly associated with metabolism functions, including lipid metabolism, carbohydrate metabolism and glycan biosynthesis and metabolism. The synthesis and degradation of ketone bodies, cysteine and methionine metabolism and glycerolipid metabolism differed significantly among the three groups, and were highest in OSCC and lowest in HC. And G. haemolysans was significantly associated with these selected metabolic pathways.
Metagenomic analysis revealed significant differences in the salivary microbiota among OSCC, OLK and HC. Thus, salivary microbiota composition and functional changes may be associated with OSCC progression. Metabolism of nonessential amino acids such as cysteine and methionine in bacteria may play an important role in oral oncogenesis, and more studies of the mechanism between metabolisms of bacteria and oral oncogenesis are needed in the future.

Microbiota composition is fundamental to human health with the intestinal microbiota undergoing critical changes within the first two years of life. The developing intestinal microbiota is shaped by maternal seeding, breast milk and its complex constituents, other nutrients, and the environment. Understanding microbiota-dependent pathologies requires a profound understanding of the early development of the healthy infant microbiota.
Two hundred and fifty healthy pregnant women (≥20 weeks of gestation) from the greater Bern area will be enrolled at Bern University hospital\'s maternity department. Participants will be followed as mother-baby pairs at delivery, week(s) 1, 2, 6, 10, 14, 24, 36, 48, 96, and at years 5 and 10 after birth. Clinical parameters describing infant growth and development, morbidity, and allergic conditions as well as socio-economic, nutritional, and epidemiological data will be documented. Neuro-developmental outcomes and behavior will be assessed by child behavior checklists at and beyond 2 years of age. Maternal stool, milk, skin and vaginal swabs, infant stool, and skin swabs will be collected at enrolment and at follow-up visits. For the primary outcome, the trajectory of the infant intestinal microbiota will be characterized by 16S and metagenomic sequencing regarding composition, metabolic potential, and stability during the first 2 years of life. Secondary outcomes will assess the cellular and chemical composition of maternal milk, the impact of nutrition and environment on microbiota development, the maternal microbiome transfer at vaginal or caesarean birth and thereafter on the infant, and correlate parameters of microbiota and maternal milk on infant growth, development, health, and mental well-being.
The Bern birth cohort study will provide a detailed description and normal ranges of the trajectory of microbiota maturation in a high-resource setting. These data will be compared to data from low-resource settings such as from the Zimbabwe-College of Health-Sciences-Birth-Cohort study. Prospective bio-sampling and data collection will allow studying the association of the microbiota with common childhood conditions concerning allergies, obesity, neuro-developmental outcomes , and behaviour. Trial registration The trial has been registered at www.
gov , Identifier: NCT04447742.

Low microbial biomass in the lungs, high host-DNA contamination and sampling difficulty limit the study on lung microbiome. Therefore, little is still known about lung microbial communities and their functions. Here, we perform a preliminary exploratory study to investigate the composition of swine lung microbial community using shotgun metagenomic sequencing and compare the microbial communities between healthy and severe-lesion lungs. We collected ten lavage-fluid samples from swine lungs (five from healthy lungs and five from severe-lesion lungs), and obtained their metagenomes by shotgun metagenomic sequencing. After filtering host genomic DNA contamination (93.5% ± 1.2%) in the lung metagenomic data, we annotated swine lung microbial communities ranging from four domains to 645 species. Compared with previous taxonomic annotation of the same samples by the 16S rRNA gene amplicon sequencing, it annotated the same number of family taxa but more genera and species. We next performed an association analysis between lung microbiome and host lung-lesion phenotype. We found three species (Mycoplasma hyopneumoniae, Ureaplasma diversum, and Mycoplasma hyorhinis) were associated with lung lesions, suggesting they might be the key species causing swine lung lesions. Furthermore, we successfully reconstructed the metagenome-assembled genomes (MAGs) of these three species using metagenomic binning. This pilot study showed us the feasibility and relevant limitations of shotgun metagenomic sequencing for the characterization of swine lung microbiome using lung lavage-fluid samples. The findings provided an enhanced understanding of the swine lung microbiome and its role in maintaining lung health and/or causing lung lesions.

(1) Background: Pregnancy-induced hypertension (PIH) is associated with obvious microbiota dysbiosis in the third trimester of pregnancy. However, the mechanisms behind these changes remain unknown. Therefore, this study aimed to explore the relationship between the gut microbiome in early pregnancy and PIH occurrence. (2) Methods: A nested case-control study design was used based on the follow-up cohort. Thirty-five PIH patients and thirty-five matched healthy pregnant women were selected as controls. The gut microbiome profiles were assessed in the first trimester using metagenomic sequencing. (3) Results: Diversity analyses showed that microbiota diversity was altered in early pregnancy. At the species level, eight bacterial species were enriched in healthy controls: Alistipes putredinis, Bacteroides vulgatus, Ruminococcus torques, Oscillibacter unclassified, Akkermansia muciniphila, Clostridium citroniae, Parasutterella excrementihominis and Burkholderiales bacterium_1_1_47. Conversely, Eubacterium rectale, and Ruminococcus bromii were enriched in PIH patients. The results of functional analysis showed that the changes in these different microorganisms may affect the blood pressure of pregnant women by affecting the metabolism of vitamin K2, sphingolipid, lipid acid and glycine. (4) Conclusion: Microbiota dysbiosis in PIH patients begins in the first trimester of pregnancy, and this may be associated with the occurrence of PIH. Bacterial pathway analyses suggest that the gut microbiome might lead to the development of PIH through the alterations of function modules.

Antibiotic resistance has become a comprehensive and complicated environmental problem. It is of great importance to effectively determine the abundance of various antibiotic resistance genes (ARGs) in the environment. Here, we attempted to find a practical method for monitoring environmental antibiotic resistance. The results of culture-based analysis of antibiotic resistance and metagenomic sequencing indicate that egrets inhabiting along the urban river (Jinjiang River) can be used as the sentinel of environmental antibiotic resistance. The antibiotic resistance in the environment fluctuated with time, while that in the wild bird was relatively stable. The network analysis based on metagenomic sequencing data gave the co-occurrence pattern of ARGs. The overall situation of the antibiotic resistance in the river was determined by quantifying several module hub genes of the co-occurrence network in river sediments. The temporal and spatial distribution of ARGs in Jinjiang River is highly correlated with that of human gut-specific bacteriophage (crAssphage), which indicates that one main source of the antibiotic resistance in the river is likely to be municipal sewage. The mobility potential of ARGs varying among different niches suggests the transmission direction of antibiotic resistance in the environment.

BACKGROUND: Acute pancreatitis (AP) is an inflammatory disorder that causes a considerable economic health burden. While the overall mortality is low, around 20% of patients have a complicated course of disease resulting in increased morbidity and mortality. There is an emerging body of evidence that the microbiome exerts a crucial impact on the pathophysiology and course of AP. For several decades multiple clinical and laboratory parameters have been evaluated, and complex scoring systems were developed to predict the clinical course of AP upon admission. However, the majority of scoring systems are determined after several days and achieve a sensitivity around 70% for early prediction of severe AP. Thus, continued efforts are required to investigate reliable biomarkers for the early prediction of severity in order to guide early clinical management of AP patients.
METHODS: We designed a multi-center, prospective clinical-translational study to test whether the orointestinal microbiome may serve as novel early predictor of the course, severity and outcome of patients with AP. We will recruit 400 AP patients and obtain buccal and rectal swabs within 72 h of admission to the hospital. Following DNA extraction, microbiome analysis will be performed using 3rd generation sequencing Oxford Nanopore Technologies (ONT) for 16S rRNA and metagenomic sequencing. Alpha- and beta-diversity will be determined and correlated to the revised Atlanta classification and additional clinical outcome parameters such as the length of hospital stay, number and type of complications, number of interventions and 30-day mortality.
CONCLUSIONS: If AP patients show a distinct orointestinal microbiome dependent on the severity and course of the disease, microbiome sequencing could rapidly be implemented in the early clinical management of AP patients in the future.
BACKGROUND: ClinicalTrials.gov Identifier: NCT04777812.

Huangjiu (Chinese rice wine) is brewed in an open environment, where bacteria play an important role during the fermentation process. In this study, bacterial community structure and composition changes in the fermented mash liquid of mechanized Huangjiu, well-fermented manual Huangjiu (wines of good qualities), and poorly fermented manual Huangjiu (wines of poor qualities: spoilage, high acidity, low alcohol content) in different fermentation stages from Guyuelongshan Shaoxing Huangjiu company were analyzed via metagenomic sequencing. And bacterial metabolic difference was analyzed via gene prediction of metabolic pathway enzymes. The results showed that the bacterial diversity degree was abundant, and the number of bacterial species in every sample was approximately 200-400. Lactic acid bacteria (LAB) dominated the bacterial community of Huangjiu fermentation, and lactobacillus was predominant species in well-fermented Huangjiu while Lactobacillus brevis had an absolute dominance in spoilage Huangjiu. Further, gene prediction revealed that transformation of malate to pyruvate and lactate anabolism was more active in mash liquid of well-fermented manual Huangjiu, while acetate accumulation was stronger in mash liquid of poorly fermented manual Huangjiu, which explained acidity excess reason in poorly fermented Huangjiu at gene level.

BACKGROUND: In COVID-19 patients, information regarding superinfection, antimicrobial assessment, and the value of metagenomic sequencing (MS) could help develop antimicrobial stewardship.
METHODS: This retrospective study analyzed 323 laboratory-confirmed COVID-19 patients for co-infection rate and antimicrobial usage in the Shanghai Public Health Clinical Center (SPHCC) from January 23rd to March 14th 2020. The microbiota composition was also investigated in patients with critically severe COVID-19.
RESULTS: The total population co-infection rate was 17/323 (5.3%) and 0/229 (0), 4/78 (5.1%), and 13/16 (81.3%) for the mild, severe, and critically severe subgroups, respectively. Proven fungal infection was significantly associated with a higher mortality rate (p = 0.029). In critically severe patients, the rate of antimicrobials and carbapenem usage were 16/16 (100%) and 13/16 (81.3%), respectively, in which the preemptive and empiric antimicrobial days accounted for 51.6% and 30.1%, respectively. Targeted therapy only accounted for 18.3%. MS was implemented to detect non-COVID-19 virus co-existence and the semi-quantitative surveillance of bacteremia, with clear clinical benefit seen in cases with MS-based precision antimicrobial management. Airway microbiome analysis suggested that the microbiota compositions in critically severe COVID-19 patients were likely due to intubation and mechanical ventilation.
CONCLUSIONS: In the SPHCC cohort, we observed a non-negligible rate of super-infection, especially for the critically ill COVID-19 patients. Fungal co-infection requires intensive attention due to the high risk of mortality, and the clinical benefit of MS in guiding antimicrobial management warrants further investigation.