Honeybees and bumblebees play a crucial role as essential pollinators. The special gut microbiome of social bees is a key factor in determining the overall fitness and health of the host. Although bees harbor relatively simple microbial communities at the genus level, recent studies have unveiled significant genetic divergence and variations in gene content within each bacterial genus. However, a comprehensive and refined genomics-based taxonomic database specific to social bee gut microbiomes remains lacking. Here, we first provided an overview of the current knowledge on the distribution and function of social bee gut bacteria, as well as the factors that influence the gut population dynamics. We then consolidated all available genomes of the gut bacteria of social bees and refined the species-level taxonomy, by constructing a maximum-likelihood core genome phylogeny and calculating genome-wide pairwise average nucleotide identity. On the basis of the refined species taxonomy, we constructed a curated genomic reference database, named the bee gut microbe genome sequence database (BGM-GDb). To evaluate the species-profiling performance of the curated BGM-GDb, we retrieved a series of bee gut metagenomic data and inferred the species-level composition using metagenomic intra-species diversity analysis system (MIDAS), and then compared the results with those obtained from a prebuilt MIDAS database. We found that compared with the default database, the BGM-GDb excelled in aligned read counts and bacterial richness. Overall, this high-resolution and precise genomic reference database will facilitate research in understanding the gut community structure of social bees.

The accurate quantification of viable pathogens in food is crucial for ensuring food safety. This study mainly aimed to investigate the quantification of viable pathogens using PMA-qPCR and RT-qPCR, taking into account bacterial species, food matrices, and inactivation methods. The detection limit of PMA-qPCR for Salmonella serovars in simple matrices, such as culture broth, lake, or tap water, was found to be 102 cells per ml. Regarding the detection of Staphylococcus aureus and Escherichia coli in culture broth, as well as Salmonella in more complex matrices, such as juices and lab-made broth, both methods exhibited a detection limit of 103 cells per ml. Besides that, in adverse situations, there was a risk of overestimating the number of viable pathogens using PMA-qPCR. In addition, a conspicuous discrepancy between the results of PMA-qPCR/RT-qPCR and those of the plate counting assay was observed when Salmonella was exposed to isopropanol, H2O2, NaClO, sonication, or thermosonication. This suggests that it may survive in a viable but non-culturable state and poses a challenge for accurate quantification of viable cells using plate counting assay. Therefore, the results obtained by RT-qPCR were more objective compared to PMA-qPCR due to potential influences from bacteria species, surrounding media, and inactivation methods.

Quercetin has a wide range of biological properties that can be used to prevent or decrease particular inflammatory diseases. In this study, we aimed to investigate the gene expression profile and metabolic pathway of the gut microbiota of an antibiotic-treated mouse model administered quercetin. Blood, feces, and intestinal tissue samples were collected and metagenomic sequencing, enzyme-linked immunosorbent assay, and western blot analysis were used to detect variations. The results showed that the quercetin-treated group exhibited increased levels of health beneficial bacterial species, including Faecalibaculum rodentium (103.13%), Enterorhabdus caecimuris (4.13%), Eggerthella lenta (4%), Roseburia hominis (1.33%), and Enterorhabdus mucosicola (1.79%), compared with the model group. These bacterial species were positively related to butyrate, propionate, and intestinal tight junction proteins (zonula occludens-1 and occludin) expression, but negatively related to serum lipopolysaccharide and tumor necrosis factor-α level. In addition, the metabolic pathway analysis showed that dietary quercetin significantly enhanced spliceosomes (111.11%), tight junctions (62.96%), the citrate cycle (10.41%), pyruvate metabolism (6.95%), and lysine biosynthesis (5.06%), but decreasing fatty acid biosynthesis (23.91%) and N-glycan (7.37%) biosynthesis. Furthermore, these metabolic pathway changes were related to relative changes in the abundance of 10 Kyoto Encyclopedia of Genes and Genomes genes (K00244, K00341, K02946, K03737, K01885, k10352, k11717, k10532, K02078, K01191). In conclusion, dietary quercetin increased butyrate-producing bacterial species, and the acetyl-CoA-mediated increased butyrate accelerated carbohydrate, energy metabolism, reduced cell motility and endotoxemia, and increased the gut barrier function, thereby leading to healthy colonic conditions for the host.

Gestational diabetes mellitus (GDM), a common endocrine disorder with rising prevalence in pregnancy, has been reported to be associated with alteration of gut microbiota in recent years. However, the role of gut microbiome in GDM physiopathology remains unclear. This pilot study aims to characterize the alteration of gut microbiota in GDM on species-level resolution and evaluate the relationship with occurrence of GDM.
An analysis based on 16S rRNA microarray was performed on fecal samples obtained from 30 women with GDM and 28 healthy pregnant women.
We found 54 and 141 differentially abundant taxa between GDM and control group at the genus and the species level respectively. Among GDM patients, Peptostreptococcus anaerobius was inversely correlated with fasting glucose while certain species (e.g., Aureimonas altamirensis, Kosakonia cowanii) were positively correlated with fasting glucose.
This study suggests that there are large amounts of differentially abundant taxa between GDM and control group at the genus and the species level. Some of these taxa were correlated with blood glucose level and might be used as biomarkers for diagnoses and therapeutic targets for probiotics or synbiotics.

BACKGROUND: In this study, recent trends in the distribution and drug resistance of pathogenic bacteria isolated from patients treated at a burn ward between 2006 and 2019 were investigated.
OBJECTIVE: To develop more effective clinical strategies and techniques for the prevention and treatment of bacterial infections in burn patients.
METHODS: Clinical samples with positive bacteria were collected from patients at the burn ward in Beijing Jishuitan Hospital in China between January 2006 and December 2019. The samples were retrospectively analyzed, the distribution of pathogenic bacteria was determined, and the trends and changes in bacterial drug resistance during different period were assessed. Drug resistance in several main pathogenic bacteria from 2006 to 2011 and from 2012 to 2019 was comparatively summarized and analyzed.
RESULTS: Samples from 17119 patients were collected and analyzed from 2006 to 2019. Surprisingly, a total of 7960 strains of different pathogenic bacteria were isolated at this hospital. Among these bacteria, 87.98% (7003/7960) of the strains were isolated from burn wounds, and only 1.34% (107/7960) were isolated from the blood of patients. In addition, 49.70% (3956/7960) were identified as Gram-positive bacteria, 48.13% (3831/7960) were Gram-negative bacteria, and the remaining 2.17% (173/7960) were classified as fungi or other pathogens. Importantly, Staphylococcus aureus (21.68%), Pseudomonas aeruginosa (14.23%), and Staphylococcus epidermidis (9.61%) were the top three pathogens most frequently isolated from patients.
CONCLUSIONS: In patients treated at the burn ward in this hospital from 2006 to 2019, Staphylococcus aureus and Pseudomonas aeruginosa were the predominant clinical pathogens responsible for bacterial infections. The circumstantial detection and detailed monitoring of the intensity and growth of different pathogenic bacteria in clinical patients as well as tests of drug sensitivity during burn recovery are particularly important to provide guidelines for the application of antibiotics and other related drugs. Careful collection and correct, standard culture of bacterial specimens are also crucial to improve the efficiency of bacterial infection detection. Effective monitoring and timely clinical treatment in patients may help reduce the possibility and rate of infection as well as alleviate the effects of drug resistance among patients in burn centers.

Present research is focused on the rapid and accurate identification of bacterial species based on artificial neural networks combined with spectral data processing technology. The spectra of different bacterial species in the logarithmic growth phase were obtained. Model input features were extracted from the raw spectra using signal processing techniques, including normalization, principal component analysis (PCA) and area-based feature value extraction. The identification models based on artificial neural network of back propagation neural networks (BPNN), generalized regression neural networks (GRNN) and probabilistic neural networks (PNN) were developed using the extracted features in order to ascertain whether the different species of bacteria could be differentiated. The performance of developed models and its corresponding signal processing techniques is tested by the recognition accuracy of validation set and test set, and model error. The maximum recognition accuracy of normalized spectrum combined with BPNN was 95.5% (error: 10%, test accuracy: 100%). The total recognition accuracy of PCA-reduced features (200-400 nm) combined with GRNN resulted in 96.3%~96.8% (error: 3.3%~6.7%, test accuracy: 97.5%~100%). While the overall recognition accuracy of area-based features combined with GRNN reached 97.3% with test accuracy of 100% (model error: 5.0%). Choosing of model and signal processing techniques has a positive influence on improving classification accuracy, so as to make it possible to realize the rapid detection and online monitoring of waterborne microbial contamination.

For the first time, full-length 16S rRNA sequencing method was applied to disclose the bacterial species and communities of a full-scale wastewater treatment plant using an anaerobic/anoxic/oxic (A/A/O) process in Wuhan, China. The compositions of the bacteria at phylum and class levels in the activated sludge were similar to which revealed by Illumina Miseq sequencing. At genus and species levels, third-generation sequencing showed great merits and accuracy. Typical functional taxa classified to ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB), denitrifying bacteria (DB), anaerobic ammonium oxidation bacteria (ANAMMOXB) and polyphosphate-accumulating organisms (PAOs) were presented, which were Nitrosomonas (1.11%), Nitrospira (3.56%), Pseudomonas (3.88%), Planctomycetes (13.80%), Comamonadaceae (1.83%), respectively. Pseudomonas (3.88%) and Nitrospira (3.56%) were the most predominating two genera, mainly containing Pseudomonas extremaustralis (1.69%), Nitrospira defluvii (3.13%), respectively. Bacteria regarding to nitrogen and phosphorus removal at species level were put forward. The predicted functions proved that the A/A/O process was efficient regarding nitrogen and organics removal.

Biofouling represents the \"Achilles\' heel\" for reverse osmosis (RO) processes due to the growth of bacteria and their production of extracellular polymeric substances (EPSs). Although the microbial community structure on the RO membrane has been analysed previously, the bacterial species with a high potential of causing RO membrane fouling have not yet been identified clearly. The key components in EPSs causing RO membrane fouling have not been revealed either. In this study, seven different bacterial species were isolated from fouled RO membranes, and their EPSs were analysed in terms of the content of polysaccharides and proteins, fluorescence characteristics and molecular weight (MW) distributions. The membrane fouling potentials of these bacterial species and EPSs were evaluated based on normalized flux decline. Generally, under the same growth conditions, bacterial species with higher EPS concentrations, rather than higher cell numbers, resulted in more severe flux decline. The flux decline showed an apparent positive correlation with the EPS concentration, indicating that the concentration of EPS rather than the bacterial number mainly contributed to biofouling. Furthermore, it was found that the MW distribution was the key factor affecting the RO membrane fouling potential of EPSs from different bacterial species. With the increase in the percentage of the high-MW fraction (>10 kDa) in the EPSs from 12.6% to 74.4%, the normalized flux decline increased from 0.4 to 0.59. The components in EPSs with a MW over 10 kDa were also separated by the ultrafiltration membrane and were proven to have a higher membrane fouling potential.

Fermented soybean foods contain nutritional components including easily digestible peptides, cholesterol-free oils, minerals, and vitamins. Various fermented soybean foods have been developed and are consumed as flavoring condiments in Asian regions. While the quality of fermented soybean foods is largely affected by microorganisms that participate in the fermentation process, our knowledge about the microorganisms in soybean pastes manufactured in Northeast China is limited. The current study used a culture-independent barcoded pyrosequencing method targeting hypervariable V1/V2 regions of the 16S rRNA gene to evaluate Korean doenjang and soybean pastes prepared by the Hun Chinese (SPHC) and Korean minority (SPKM) populations in Northeast China. In total, 63399 high-quality sequences were derived from 16 soybean paste samples collected in Northeast China. Each bacterial species-level taxon of SPHC, SPKM, and Korean doenjang was clustered separately. Each paste contained representative bacterial species that could be distinguished from each other: Bacillus subtilis in SPKM, Tetragenococcus halophilus in SPHC, and Enterococcus durans in Korean doenjang. This is the 1st massive sequencing-based study analyzing microbial communities in soybean pastes manufactured in Northeast China, compared to Korean doenjang. Our results clearly showed that each soybean paste contained unique microbial communities that varied depending on the manufacturing process and location.

OBJECTIVE: The aim of this study was to evaluate procalcitonin (PCT) diagnostic accuracy in discriminating gram-negative (GN) from gram-positive (GP) bloodstream infections and determining the relationship between PCT levels, infection sites, and pathogen types.
METHODS: Clinical and laboratory data were collected from patients with blood culture (BC)-positive sepsis between January 2014 and December 2015. PCT levels at different infection sites were compared, as was the presence of GN and GP bloodstream infection. A receiver operating characteristic (ROC) curve was generated to assess diagnostic accuracy.
RESULTS: Of the 486 monomicrobial BCs, 254 (52.26%) were positive for GN bacteria (GNB), and 202 (42.18%) for GP bacteria (GPB). Median PCT levels were higher in BCs positive for GN (2.42ng/ml, IQR: 0.38-15.52) than in those positive for GPB (0.49ng/ml, IQR: 0.13-5.89) (P<0.001). In the ROC analysis to differentiate between GNB and GPB, the area under the curve was 0.628 (95% CI: 0.576-0.679). When the cutoffs for PCT were 10.335 and 15.000ng/ml, the specificity of GNB infection was 80.2% and 84.2%, respectively. PCT levels caused by GNB differed between Escherichia coli and Acinetobacter baumanni/Burkholderia cepacia, Klebsiella pneumonia and Acinetobacter baumanni. PCT levels caused by GPB differed between Staphylococcus epidermidis/Staphylococcus aureus and Staphylococcus hominis/Staphylococcus haemolyticus, Enterococcus faecium and Enterococcus faecalis/S.hominis/S. haemolyticus. Among patients with known infection sites, there were statistical differences in PCT levels between abdominal infection and pneumonia/infective endocarditis, urinary tract infection and pneumonia/catheter-related infection/infective endocarditis.
CONCLUSIONS: PCT can distinguish between GNB and GPB infection, as well as between different bacterial species and infection sites.