The Difference Analysis Of Pseudomonas Spp. In Milk Deterioration And The Development Of Pseudomonas Species-level Detection Technology

Microbial contamination of raw milk is a significant issue causing the deterioration of dairy products.Before transported to dairy factory,raw milk gathered from pastures will be stored at 4~oC to limit the microbes growing.Pseudomonas is psychrophilic bacteria with high genetic and metabolic diversity,frequently damages milk quality because of low temperature growth capacity and high hydrolase activity.Noticeably,the structure of its community varied by many environmental factors,leading to the difference of spoilage threaten.Therefore,the analysis of the spoilage ability and the detection of pseudomonas in more precise level is essential to reduce spoilage risk.In the past studies of spoilage,Pseudomonas spp.was always researched as a whole genus or single strains,lacking the comparison of physiological properties,milk quality damage and related pathways between species.In addition,the detection tools of pseudomonas were not able to cover all species because of the limitation of accuracy.Based on research status,we explored the interspecific differences of representative pseudomonas in the process of milk spoilage,analyzing the change of the structure of pseudomonas microbiota during the processing of raw milk,aiming to prevent the harm of pseudomonas in source and guarantee milk quality.The main contents and results of the study are as follows.Using related bacteria isolated from raw milk,we measured the growth ability,enzyme activity,p H value,grain size and Zeta potential in 4~oC storage conditions.The results of the physicochemical properties analysis showed that species showed better low-temperature growth ability in the milk environment.In the aspect of enzymes,the low temperature enzymes activity,the retention of activity after pasteurization and UHT sterilization varied between species.The effects of pseudomonas on p H and system stability increased became remarkable after 48 h of low-temperature storage.The changes of free amino acids and volatile substances of representative strains in milk low-temperature fermentation showed that tyrosine,arginine,valine,and benzoindaldehyde and 3-methylindole may be target substances in pseudomonas fluorescens spoilage and cysteine and2,4-di-tert-butylphenol can be used as target substances for pseudomonas fragi.Finally,we analyzed the metabolic mechanisms and potential pathways during spoilage caused by these two species using the tools of proteome and metabolome.The result showed that ethylmalonic acid,L-phenylalanine,stearylamide,and serotonin is the mean distinctive metabolites.The study further explored that the pollution of the former may raise health risks of milk.On the other hand,using the community genomics and bioinformatics,the target gene which can distinguish different species were screened.Based on mre B gene,we designed the Illumina sequencing method for better sequencing at species level in dairy samples.The estimation of the accuracy and LOD using artificial mixed sample showed that this method enables high-throughput analysis of the composition of pseudomonas at the species level in complex samples.The test results further determined by the simulated mixed sample experiment are well consistent with the actual results(y=1.022x-0.088,R~2=0.9957).The limit of detection is 2.45 log CFU/m L.We further applied this method in the analysis of raw milk with different treatments,combining with 16S r DNA analysis.The structural differences of pseudomonas in different temperatures,storage times,processing sites and pasture environments.The species,p.fluorescens,p.putida and p.monteilli dominant at 4~oC.The species,p.fluorescens,p.psychrophilic and p.lurida kept dominance at 7~oC.In the analysis of samples from different pasture points,p.lundensis exhibited the dominant strains after disinfectant treatment and low temperature storage.The structure of different pastures in the neighboring areas also excites interspecific difference.In the final study,by transfer a machine learning method for microflora structure prediction based on environmental factors,we successfully predicted the microbial community depend on studied environmental factors.The study provides a new perspective and technical mean for preventing the harm of Pseudomonas spp.to some foods such as raw milk.