Identification Of Bacteria Research Articles

Comparison of a Sepsityper® kit and in-house membrane filtration methods for rapidly diagnosing positive blood cultures via MALDI‒TOF MS

BackgroundRapidly identifying pathogens and determining their antimicrobial susceptibilities using samples directly from flagged blood culture bottles pose significant challenges for clinical laboratories. Thus, a cost-effective and efficient sample-processing method is urgently needed to address this issue. To fulfill this need, we developed a novel protocol to rapidly identify pathogens and determine their antimicrobial susceptibilities using samples directly from blood culture bottles. MethodsSamples were either processed by the Sepsityper kit or our in-house methods. In our approach, we processed the samples using either a nonionic surfactant (Triton X-100) or a NaOH-sodium dodecyl sulfate (SDS) solution, followed by membrane filtration (MF) and centrifugation. Subsequently, the samples were analyzed using MALDI-TOF mass spectrometry (MS) for identification and the Vitek® 2 for antimicrobial susceptibility determination. ResultsIn this study, 122 clinical blood culture samples were analyzed, and our MF protocol displayed enhanced accuracy in identifying gram-positive organisms (n = 58) and gram-negative bacilli (n = 64) compared to the Sepsityper method. In particular, the Triton-MF and SDS-MF techniques outperformed Sepsityper in identifying gram-negative bacilli, with accuracy rates of 92.2 %, 85.9 %, and 78.1 %, respectively. Notably, both the Triton-MF and SDS-MF methods exhibited high categorical agreement (CA) for antimicrobial susceptibility testing (AST) for carbapenem against Enterobacterales, with CAs of 100 % and 98.7 %, respectively. Additionally, both methods exhibited a perfect CA and essential agreement of 100 % for Enterococcus faecium AST for vancomycin. ConclusionThese findings strongly indicate that our MF methods have the potential to streamline the identification and AST of bacteria in positive blood cultures.

Molecular detection and identification of Enterobacter cloacae bacteria that cause urinary tract infection by PCR sequence technique

Molecular detection and identification of Enterobacter cloacae bacteria that cause urinary tract infection by PCR sequence technique

Identification of Staphylococcus aureus, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii from Raman spectra by Artificial Intelligent Raman Detection and Identification System (AIRDIS) with machine learning

BackgroundRapid and accurate identification of bacteria is required in order to develop effective treatment strategies. Traditional culture-based methods are time-consuming, while MALDI-TOF MS is expensive. The Raman spectroscopy, due to its relatively cost-effectiveness, offers a promising alternative for bacterial identification. However, its clinical utility still requires further validation. MethodsIn this study, the artificial intelligent Raman detection and identification system (AIRDIS) was implemented to identify bacterial species, including Staphylococcus aureus (n = 1290), Enterococcus faecium (n = 1020), Klebsiella pneumoniae (n = 1366), Pseudomonas aeruginosa (n = 1067), and Acinetobacter baumannii (n = 811). Raman spectra were collected, preprocessed, and analyzed by machine learning (ML). ResultsAfter training on 24,420 Raman spectra from 1221 isolates and testing on 4333 isolates, the AIRDIS demonstrated an area under the curve (AUC) of 0.99 for Gram classification, with accuracies of 97.64 % for Gram-positive bacteria and 98.86 % for Gram-negative bacteria. Spectral differences between Gram-positive and Gram-negative bacteria were linked to structural variations in their cell walls, such as peptidoglycan and lipopolysaccharides. At the species level, S. aureus, E. faecium, K. pneumoniae, P. aeruginosa, and A. baumannii were identified with high accuracy, ranging from 94.76 % to 96.88 %, with all species achieving an AUC of 0.99. ConclusionsValidation with a large number of clinical isolates demonstrated Raman spectroscopy combined with ML excels in identification of five bacterial species associated with multidrug resistance. This finding confirms the clinical utility of the system while laying a solid foundation for the future development of antimicrobial resistance prediction models.

Molecular Diagnosis of Vaginal Microbiota Associated with Spontaneous Abortion in Women

Spontaneous abortion (SA) is a sever disease in which a women losses her foetus usually before 24 weeks of the pregnancy. About 10% -50% of pregnancy cases are run out with SA for reasons related with women's age and health. This condition occurrence may increases if the patient has a history of bacterial vaginosis. This study aimed at the characterization and isolation of vaginal microbiota generally and highlight on commensal bacteria becoming opportunistic when circumstances are favourable. From October to December 2022, about 100 samples were collected, 50 specimens from women with SA and 50 specimens from healthy pregnant outcomes (control). The high vaginal swabs samples were collected from Babylon Teaching Hospital for Maternity and Children and Imam Sadiq Teaching Hospital in Babylon, Iraq. To culture the samples, they were transported by media swab to laboratory. The culture of bacteria was done on 4 types of agar media: UTI chromogenic agar, MRS agar, MacConkey agar and blood agar. The first identification of bacteria was based on phenotypic traits of colonies, using manual biochemical tests and gram stain. Finally, the diagnosis was confirmed genetically by extracting bacterial genomic DNA for 20 of bacterial isolates under study and using PCR technique for 16S rRNA Loci gene and sequencing. The current study results showed difference in bacterial genera in women with SA compared with healthy women. It was also noted that embroilment of Enterococcus faecalis occurred in most cases of SA with an estimated percentage of 56% (28/50), thus defeating Escherichia coli by 32% (16/50) and 4% (2/50) for Klebsiella pneumonia and 4% (2/50) for Enterococcus gallinarum. In this study, some very rare bacteria species were identified including Acinetobacter junii at 2% (1/50) and Corynebacterium coyleae at 2% (1/50). While the percentage of bacteria associated with healthy women was: 30% (15/50) for E. faecalis, 26% (13/50) for E. coli, 18% (9/50) for K. pneumonia, 24% (12/50) for Staphylococcus epidermidis, and 2% (1/50) for Metabacillus niabensis (which was diagnosed for the first time in Iraq as well as the rest of the world in a clinical sample).

Antibacterial activity of lactic acid bacteria isolated from traditionally fermented food against food pathogen

Aim: To evaluate the antibacterial activity of lactic acid bacteria against selected food pathogens (Escherichia coli and Staphylococcus aureus). Method: A total of twenty (20) traditionally fermented food samples were purchased from a market in Owerri metropolis. Isolation and identification of lactic acid bacteria (LAB) were conducted using standard microbiological techniques. LAB was identified using standard morphological and biochemical tests. They were tested against food pathogens using the Agar well diffusion method. Results: The isolated lactic acid bacteria include Lactobacillus fermentum, Lactobacillus acidophilus, Lactobacillus casei and Lactobacillus plantarum and were label as SP1, SP2, SP3, and SP4 respectively. The isolated LAB species had a considerable inhibitory effect on food borne pathogens. Cell free supernatant of four species were tested for antagonistic activity at 24hrs and 48hrs incubation time. Cell free supernatant from 48hrs broth of SP1 showed the highest zone of inhibition on Escherichia coli (28mm) while the cell free supernatant from 24hrs broth of SP4 showed the lowest zone of inhibition on Staphylococcus aureus (13 mm). Conclusion: The antimicrobial activity increases with time. LAB demonstrated high antimicrobial properties against food borne pathogens. This potential can be employed as starters in food industry to inhibit food spoilage microbes and contaminants.

Rapid and accurate bacteria identification through deep-learning-based two-dimensional Raman spectroscopy

Surface-enhanced Raman spectroscopy (SERS) offers a distinctive vibrational fingerprint of the molecules and has led to widespread applications in medical diagnosis, biochemistry, and virology. With the rapid development of artificial intelligence (AI) technology, AI-enabled Raman spectroscopic techniques, as a promising avenue for biosensing applications, have significantly boosted bacteria identification. By converting spectra into images, the dataset is enriched with more detailed information, allowing AI to identify bacterial isolates with enhanced precision. However, previous studies usually suffer from a trade-off between high-resolution spectrograms for high-accuracy identification and short training time for data processing. Here, we present an efficient bacteria identification strategy that combines deep learning models with a spectrogram encoding algorithm based on wavelet packet transform and Gramian angular field techniques. In contrast to the direct analysis of raw Raman spectra, our approach utilizes wavelet packet transform techniques to compress the spectra by a factor of 1/15, while concurrently maintaining state-of-the-art accuracy by amplifying the subtle differences via Gramian angular field techniques. The results demonstrate that our approach can achieve a 99.64 % and a 90.55 % identification accuracy for two types of bacterial isolates and thirty types of bacterial isolates, respectively, while a 90 % reduction in training time compared to the conventional methods. To verify the model's stability, Gaussian noises were superimposed on the testing dataset, showing a specific generalization ability and superior performance. This algorithm has the potential for integration into on-site testing protocols and is readily updatable with new bacterial isolates. This study provides profound insights and contributes to the current understanding of spectroscopy, paving the way for accurate and rapid bacteria identification in diverse applications of environment monitoring, food safety, microbiology, and public health.

Rapid identification of antibiotic resistance gene hosts by prescreening ARG-like reads

Effective risk assessment and control of environmental antibiotic resistance depend on comprehensive information about antibiotic resistance genes (ARGs) and their microbial hosts. Advances in sequencing technologies and bioinformatics have enabled the identification of ARG hosts using metagenome-assembled contigs and genomes. However, these approaches often suffer from information loss and require extensive computational resources. Here we introduce a bioinformatic strategy that identifies ARG hosts by prescreening ARG-like reads (ALRs) directly from total metagenomic datasets. This ALR-based method offers several advantages: (1) it enables the detection of low-abundance ARG hosts with higher accuracy in complex environments; (2) it establishes a direct relationship between the abundance of ARGs and their hosts; and (3) it reduces computation time by approximately 44–96% compared to strategies relying on assembled contigs and genomes. We applied our ALR-based strategy alongside two traditional methods to investigate a typical human-impacted environment. The results were consistent across all methods, revealing that ARGs are predominantly carried by Gammaproteobacteria and Bacilli, and their distribution patterns may indicate the impact of wastewater discharge on coastal resistome. Our strategy provides rapid and accurate identification of antibiotic-resistant bacteria, offering valuable insights for the high-throughput surveillance of environmental antibiotic resistance. This study further expands our knowledge of ARG-related risk management in future.

Accuracy of various matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)-based rapid identification methods—As a tool to augment diagnostic stewardship in blood culture laboratory, South India

BackgroundBlood stream infection is a medical emergency associated with high morbidity and mortality. Prompt identification of bloodstream infection-causing microorganisms directly from positive blood culture will significantly enhance patient care by reducing the turnaround time of pathogen recognition. MethodsA total of 256 freshly flagged positive blood culture bottles were subjected to Gram staining. Direct MALDI-TOF MS analysis was performed following sample preparation techniques such as lysis centrifugation, lysis filtration and VITEK® MS BC kit to directly identify microorganisms from positive blood cultures. Along with these short-term incubation methods of Choco spot and minute colony(8–10h) were also performed. All those positive bottles were identified by the routine (reference) laboratory method. Results177 isolates (69.14 %) were correctly identified by Lysis centrifugation, 163 isolates (63.67 %) were correctly identified by Lysis filtration, 206 isolates (80.47 %) were correctly identified by Choco spot,250 isolates (97.65 %) were correctly identified from minute colony (8–10h) of incubation. Of 162 isolates,115 isolates (70.99 %) were correctly identified by VITEK® MS Blood culture kit, (BioMérieux). VITEK® MS BC kit method revealed higher agreement with the kappa value of 0.697 than lysis centrifugation (0.672) followed by lysis filtration (0.611). ConclusionsIn house method of lysis centrifugation is found to be equivalent to VITEK® MS BC kit method and superior to lysis filtration method in correct direct identification of bacteria from positive blood cultures by MALDI-TOF MS analysis. As lysis centrifugation requires only 10 min of processing time as compared to overnight incubation, thus it offers a less expensive substitute for the VITEK® MS BC kit in the clinical laboratory. As a consequence of this study, we have implemented direct MALDI-TOF-based identification from positive BCs in our daily routine diagnostic management.

Biofertilizer based on <i>Agrobacterium </i>as a key to food security

Background: The concept of food security is contingent upon the fulfillment of two fundamental requirements: physiological and socioeconomic. The former comprises providing sustenance that is both safeguarded and enhanced in line with people’s nutritional needs and priorities, whereas the latter includes the mechanisms by which these needs are supplied. The objective is to ensure a state of robust and healthy well-being. As a sustainable solution, biofertilizers play a pivotal role in addressing the challenges of food security. Biofertilizers represent a cost-effective and environmentally friendly solution, with the potential to enhance soil productivity through nitrogen fixation. They also enhance crop yield by increasing the concentration of nutrients. Access to functional foods derived from biofertilizer-enhanced yields may contribute to improved dietary diversification and overall well-being. Objective: The objective is to isolate and screen the most active nitrogen-fixing bacterium as a basis to a new biofertilizer. Methods: The isolation of nitrogen-fixing bacteria was conducted using the soil sowing technique. The selection of nitrogen-fixing bacteria was based on their morphophysiological characteristics. Bacterial growth was evaluated by viable cell count. Cultivation of the selected bacterium occurred in both flasks (on a shaker) and a bioreactor to compare growth conditions. The stimulatory effect of the selected bacterium on seed germination was assessed based on the final germination rate. The selected bacterium identified through molecular taxonomy. Results: A total of 100 pure cultures were isolated, from which nitrogen-fixing bacteria were selected. The cultivation conditions for these bacteria were optimized regarding pH, temperature and process duration in a flask on a shaker. Strain NB4 exhibited the most favorable development under optimal settings. Additionally, cultivation parameters for this strain were optimized in a laboratory bioreactor. Notably, a bacterial liquid culture water solution comprising 1.5% strain NB4 facilitated complete germination of wheat (Triticum aestivum L.), seeds and produced high-quality sprouts. The 16S rRNA gene sequence of strain NB4 was submitted to the GenBank database under accession number MT670424.1, identifying it as Agrobacterium Pusense RP 1. Conclusion: This research aimed to develop an effective biofertilizer to tackle the pressing issue of food security. The project’s cornerstone was Agrobacterium pusense RP 1, nitrogen-fixing strain isolated and identified through rigorous research. Keywords: Isolation and identification of nitrogen-fixing bacteria, cultivation in bioreactor, germination of wheat seeds, Agrobacterium pusense.

Isolation and purification of lactic acid bacteria and yeasts based on a multi-channel magnetic flow device and rapid qualitative and quantitative detection

Rapid isolation and identification of lactic acid bacteria and yeasts during fermentation is of great significance for quality control and regulation of fermented foods. In this study, we prepared a multi-channel magnetic flow device for rapid separation and purification of lactic acid bacteria and yeast, and based on SERS spectrum, we made rapid qualitative and quantitative analysis of Lactobacillus plantarum, Lactococcus lactis and Saccharomyces cerevisiae. The results showed that the synthesized Synthesized Fe3O4-Van antibiotic magnetic beads are paramagnetic; Fe3O4-Van antibiotic magnetic beads achieved capture efficiencies of more than 98.5 % for both L. plantarum and L. lactis at 102–104 CFU/mL, respectively. Separation and purification efficiency of single S. cerevisiae, L. plantarum and L. lactis by multi-channel magnetic flow device all reached more than 98 % with good isolation and purification results. The SERS spectra of the three microorganisms were classified and analyzed using linear discriminant analysis (LDA), and the accuracy of the established LDA model was 100 %, which completely differentiated the SERS spectra of the three microorganisms,and realized the qualitative identification of L. plantarum, L. lactis, and S. cerevisiae, and finally, quantitative model was established with the logarithmic values (lg C) of different concentrations of L. plantarum, L. lactis, and S. cerevisiae as the horizontal coordinates, and the Raman intensities at their strongest characteristic peaks of 512 cm−1, 1669 cm−1, and 1125 cm−1, respectively, were used as vertical coordinates to establish a quantitative model, with the lowest detection limit of 10 CFU/mL, and the digital quantification of lactic acid bacteria and yeast were achieved. It provided an effective means for real-time monitoring and tracking of the dynamics of lactic acid bacteria and yeast in the fermentation process and the quality control of fermented foods.

Principal Component Analysis (PCA) of MALDI-TOF for the Identification of Waterborne Pathogenic Bacteria

The study focuses on the application of Principal Component Analysis (PCA) combined with MALDI-TOF MS (Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry) for the identification of waterborne pathogenic bacteria in urban water networks. In this comprehensive research, 168 bacterial strains were meticulously isolated from the water networks of Abidjan, Côte d'Ivoire, a region known for its inadequate wastewater treatment infrastructure. The analysis aimed to rapidly and precisely identify these bacterial pathogens, leveraging the power of MALDI-TOF MS and the sophisticated data reduction capabilities of PCA. This approach not only accelerates the identification process but also enhances the accuracy of detecting various pathogens. The study identified a diverse range of pathogens, including Pseudomonas aeruginosa, Escherichia coli, Salmonella, Shigella, Vibrio cholerae, Morganella morganii, Proteus mirabilis, Acinetobacter baumannii, Klebsiella pneumoniae, Providencia rettgeri, Providencia stuartii, Aeromonas hydrophila, Bacillus cereus, Lysinibacillus fusiformis, Lysinibacillus sphaericus, and Staphylococcus aureus. These findings underscore the critical public health risks posed by microbial contamination in water networks, particularly in areas with deficient waste management systems. This study highlights the necessity for improved wastewater management practices, robust public health strategies, and regular monitoring to mitigate the risks associated with waterborne pathogens. Moreover, the integration of PCA with MALDI-TOF MS proves to be a powerful tool for enhancing the efficiency and accuracy of pathogen identification in environmental water samples, offering a promising solution for better public health protection and water quality management in urban settings.

Identification and antibiotic susceptibility pattern of bacteria isolated in Laboratory (ART)

Identification and antibiotic susceptibility pattern of bacteria isolated in Laboratory (ART)

Identification of pathogenic bacteria from eggshell of leatherback sea turtle (Dermochelys coriacea) in Lampuuk Beach, Aceh Besar using 16S rRNA gene

Currently, the leatherback turtle population in Indonesia tends to decline. One of the factors that cause turtles' existence is the turtle eggs that fail to hatch because bacteria contaminate them, 80% of the reasons turtle eggs fail to hatch are due to infection by microorganisms found on the eggshell. Turtle eggs have a soft structure and there are pores that function for gas exchange and water absorption. Microorganisms in sand can infect turtle eggs through the pores and cause hatching failure. This study aims to isolate and identify pathogenic bacteria found in leatherback turtle eggshell (Dermochelys coriacea) from Lampuuk Beach, Aceh Besar, based on the 16S rRNA gene analysis. Eight eggshell samples from leatherback turtle eggs that failed and hatched were cultured on Nutrient Agar (NA) medium. Then, the samples were inoculated on a blood agar medium for haemolysis test. Molecular identification of the 16S rRNA gene was also carried out to determine bacterial species. A total of five bacterial colonies from leatherback turtle eggshells were successfully isolated consisting of two Gram-negative bacteria (Penyu Belimbing Aceh (PBA) = PBA-1 and PBA-2 and three Gram-positive bacteria (PBA-3, PBA-4, and PBA-5). Based on the haemolysis test, the five bacterial isolates were unable to haemolyze blood. Bacterial DNA of PBA-1 and PBA-2 were successfully isolated and amplified using polymerase chain reaction (PCR) with a DNA target of ~1500 bp. Analysis using BLASTN and phylogenetic tree construction showed that PBA-1 isolate had 98.64% similarity with Acinetobacter baumannii, while PBA-2 isolate had 97.82% similarity with Enterobacter kobei. Both bacteria are members of the Enterobacteriaceae family. It can be concluded that, there were two pathogenic bacteria can potentially be opportunistic pathogens found in leatherback turtle eggshells that failed or succeeded in hatching, namely A. baumannii and E. Kobei

Isolation and molecular identification of cellulose-degrading bacteria from rumen sheep ''Ovis aries'' and evaluation of their cellulase production

This study focuses on the isolation and identification of cellulose-degrading bacteria from the digestive tract of sheep (Ovis aries) and to determine the cellulase capacity of different isolates for ulterior application. The bacterial strains were screened firstly using Congo red, where cellulase activity is indicated by the appearance of a hydrolysis zone on the Carboxymethylcellulose medium (CMC), the clearance zone value ranged between 8 and 15 mm for all isolates and the hydrolytic capacity was between 1.6 to 2.5 mm. The cellulolytic strain isolates were identified using MALDI-TOF Mass Spectrometry and 16S ribosomal RNA gene sequencing. MALDI-TOF MS test indicated that all strains belonged to Bacillaceae family. The strains Isolate2, Isolate3, and Isolate8 were reliable to B. tequilensis species with a score value 2.0. Whereas, the Isolate1, Isolate4, Isolate5, and Isolate6 were reliably identified to the genus level (Score value 1.7–1.99). The molecular identification results revealed that the strains indicate a high sequence similarity with 16S rRNA gene sequences accessible in GenBank database and belong to Priestia megaterium, Lysinibacillus capsici, Bacillus tequilensis, and Bacillus paralicheniformis. The highest Carboxymethylcellulase activity (CMCase) was obtained by B. tequilensis (0.827 ± 0.035 U/ml) at a pH of 7.0 and temperature of 30 °C at 100 g. The carbon source utilized was CMC (1 %), while peptone (1 %) and ammonium sulfate (0.24 %) served as the nitrogen sources. Further research in optimizing and purifying of cellulase, could be useful for the future hydrolyzation of some green biomass for various biotechnological applications such as biofuel production.

Isolation, Screening, and Molecular Identification of Cellulolytic Bacteria From Supit Urang Municipal Landfill, Malang City

The municipal landfills contain substantial amounts of lignocellulosic waste that have not been adequately utilized. This waste can be processed using cellulolytic bacteria. Cellulolytic bacteria play an important role in the degradation of cellulose-based materials. This study aimed to isolate and identify cellulolytic bacteria based on 16S rDNA sequence obtained from the Supit Urang municipal landfill, Malang City. Bacteria were isolated from soil by cultivating on 1% carboxyl methyl cellulose (CMC) agar media. The cellulolytic activity was analyzed semi-quantitatively with flooded 1% Congo red and then washed with 1 M NaCl three times. Cellulase activity assay was measured using the 3.5-Dinitrosalicylic Acid (DNS) method. The most potential isolate in cellulose decomposition was identified. The most potential isolate in cellulose decomposition was identified. Twenty isolates of cellulolytic bacteria were obtained from the sample and sixteen isolates formed the clear zone. The cellulolytic index ranged between 0.26 and 1.52. Five isolates, SL1, SL2, SL10, SL16, and SL19 had the highest cellulolytic index. Isolate SL2 had the highest cellulase activity at 0.071 U/mL. Based on the 16S rDNA sequence, SL2 was identified as Bacillus amyloliquefaciens F98 with a similarity of 99.02%. This potential isolate has prospects for the biodegradation process from agricultural waste, which can be processed into valuable products.

Rapid Detection of Single Bacteria Using Filter-Array-Based Hyperspectral Imaging Technology.

Rapid and accurate detection of bacterial pathogens is crucial for preventing widespread public health crises, particularly in the food industry. Traditional methods are often slow and require extensive labeling, which hampers timely responses to potential threats. In response, we introduce a groundbreaking approach using filter-array-based hyperspectral imaging technology, enhanced by a super-resolution demosaicking technique. This innovative technology streamlines the detection process and significantly enhances the resolution of mosaic hyperspectral imaging. By utilizing a snapshot hyperspectral camera with a 15 ms integration time, it facilitates the identification of bacteria at the single-cell level without requiring chemical labels. The integration of a 3D convolutional neural network optimizes the recognition of pathogenic bacteria, achieving an impressive accuracy of 91.7%. Our approach dramatically improves the efficiency and effectiveness of bacterial detection, providing a promising solution for critical applications in public health and the food industry.

Isolation and Identification of Lactic Acid Bacteria from Naturally Fermented Goat Milk as Potential Goat Milk Yogurt Starter

Isolation and Identification of Lactic Acid Bacteria from Naturally Fermented Goat Milk as Potential Goat Milk Yogurt Starter

Colchicine can keep the viability of bacteria in mastitic milk by preventing leukocyte phagocytosis in dairy cow and goat.

Despite the occurrence of mastitis, no bacteria were detected in any of the milk samples after culture. This is partially because the neutrophils present in milk phagocytose bacteria during milk preservation. In this study, we investigated whether colchicine inhibited the decrease in viable bacteria in milk by suppressing phagocytosis during preservation. The number of viable bacteria decreased when cow milk was preserved for 5 h. However, the addition of 0.1 and 1% colchicine significantly increased the number of viable bacteria (p < 0.05). The percentage of culture-negative cow's milk increased more than two-fold after 5 h compared to that at 0 h of preservation, however this percentage was significantly reduced by the addition of colchicine (p < 0.05). When goat milk with mastitis was incubated with bacteria (Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus), the percentage of phagocytosed neutrophils decreased significantly with the addition of colchicine (p < 0.05). These results indicate that colchicine suppressed the decrease in the number of viable bacteria by preventing neutrophil phagocytosis during milk preservation. These findings may help in the identification of mastitis-causing bacteria and the selection of antibiotics for the treatment of mastitis.

Isolation, identification and antibiotic susceptibility patterns of bacteria associated with wound of patients attending Ahmadu Bello University Teaching Hospital, Shika, Zaria-Nigeria

Isolation, identification and antibiotic susceptibility patterns of bacteria associated with wound of patients attending Ahmadu Bello University Teaching Hospital, Shika, Zaria-Nigeria

Widespread presence of gut bacterium Glutamicibacter ectropisis sp. nov. confers enhanced resistance to the pesticide bifenthrin in tea pests

The gut microbiota in Lepidopterans demonstrates variability and susceptibility to environmental influences, thereby presenting opportunities for the acquisition of novel bacterial strains. Ectropis grisescens (Warren), a notorious Lepidopteran pest, causes substantial damage to tea crops. Prolonged application usage of bifenthrin for the management of this pest has led to increased resistance. This study aims to investigate the relationship between the gut microbiota, as shaped by long-term pesticide use and the resistance of E. grisescenes. We employed high-throughput sequencing of the 16S rRNA gene to analyze the gut microbiota compositions in bifenthrin-resistant (BIF-R) and bifenthrin-sensitive (BIF-S) strains. Bifenthrin-degrading strains were isolated from the gut of BIF-R using selective media. The degradation efficiency and products of bifenthrin by the key strain were detected using gas chromatography (GC) and gas chromatography–mass spectrometry (GC–MS). The effect of the key strain on host resistance was verified in vivo. Finally, the distribution and abundance of the degrading bacterium, in conjunction with insect's pesticide resistance, were assessed in 22 distinct E. grisescens populations. Bifenthrin resistance was diminished in BIF-R following the removal of gut bacteria, a phenomenon not observed in BIF-S. Subsequent high-throughput amplicon sequencing revealed distinct structural differences in the gut microbiota between the two groups, notably an increased abundance of Glutamicibacter in BIF-R. A newly identified bacterial strain from BIF-R larvae, Glutamicibacter ectropisis (B1), demonstrated bifenthrin degradation efficiency and the main metabolite was 2,4-di-tert-butylphenol. Inoculation of B1 into BIF-S larvae conferred increased resistance to bifenthrin. Furthermore, we confirmed the prevalence of B1 in the gut of E. grisescens across 22 tea-growing areas in China. A positive correlation was observed between the absolute abundance of B1 and bifenthrin resistance in E. grisescens. This study represents the first identification of a novel gut bacterium, G. ectropisis, which mediates host resistance through the direct degradation of bifenthrin. This mechanism has been widely validated across 22 distinct populations.