Comparison of predicted and impedance determined growth of Listeria innocua in complex food matrices

Automatically showing microbial growth kinetics with a high-performance microbial growth analyzer

It is difficult to show microbial growth kinetics online when they grow in complex matrices. We presented a novel strategy to address this challenge by developing a high-performance microbial growth analyzer (HPMGA), which employed a unique 32-channel capacitively coupled contactless conductivity detector as a sensing element and fixed with a CellStatz software. It was capable of online showing accurate and repeatable growth curves of well-dispersed and bad-dispersed microbes, whether they grew in homogeneous simple culture broth or heterogeneous complex matrices. Moreover, it could automatically report key growth kinetics parameters. In comparison to optical density (OD), plate counting and broth microdilution (BMD) methods, we demonstrated its practicability in five scenarios: 1) the illustration of the growth, growth rate, and acceleration curves of Escherichia coli (E. coli); 2) the antimicrobial susceptibility testing (AST) of Oxacillin against Staphylococcus aureus (S. aureus); 3) the determination of Ag nanoparticle toxicity on Providencia rettgeri (P. rettgeri); 4) the characterization of milk fermentation; and 5) the enumeration of viable pathogenic Vibrio in shrimp body. Results highlighted that the HPMGA method had the advantages of universality and effectivity. This technology would significantly facilitate the routine analysis of microbial growth in many fields (biology, medicine, clinic, life, food, environment, and ecology), paving an avenue for microbiologists to achieve research goals that have been inhibited for years due to a lack of practical analytical methods.

Analytical methods for assessing antimicrobial activity of nanomaterials in complex media: advances, challenges, and perspectives

Assessing the antimicrobial activity of engineered nanomaterials (ENMs), especially in realistic scenarios, is of great significance for both basic research and applications. Multiple analytical methods are available for analysis via off-line or on-line measurements. Real-world samples are often complex with inorganic and organic components, which complicates the measurements of microbial viability and/or metabolic activity. This article highlights the recent advances achieved in analytical methods including typical applications and specifics regarding their accuracy, cost, efficiency, and user-friendliness. Methodological drawbacks, technique gaps, and future perspectives are also discussed. This review aims to help researchers select suitable methods for gaining insight into antimicrobial activities of targeted ENMs in artificial and natural complex matrices.

Identification of Listeria species and Multilocus Variable-Number Tandem Repeat Analysis (MLVA) Typing of Listeria innocua and Listeria monocytogenes Isolates from Cattle Farms and Beef and Beef-Based Products from Retail Outlets in Mpumalanga and North West Provinces, South Africa

In this study, Listeria isolates (214) were characterized as follows: L. innocua (77.10%), L. monocytogenes (11.21%), L. welshimeri (5.61%), L. grayi (1.40%), L. seeligeri (0.93%), and L. species (3.73%) that were not identified at the species level, from beef and beef based products from retail and farms in Mpumalanga and North West provinces of South Africa. MLVA was further used to type Listeria innocua isolates (165) and Listeria monocytogenes isolates (24). The L. monocytogenes isolates were also serogrouped using PCR. The MLVA protocol for L. monocytogenes typing included six tandem repeat primer sets, and the MLVA protocol for L. innocua included the use of three tandem repeats primer sets. The L. monocytogenes serogroups were determined as follows: 4b-4d-4e (IVb) (37.50%), 1/2a-3a (IIa) (29.16%), 1/2b-3b (IIb) (12.50%), 1/2c-3c (IIc) (8.33%), and IVb-1 (4.16%). MLVA could cluster isolates belonging to each specie, L. monocytogenes, and L. innocua isolates, into MLVA-related strains. There were 34 and 10 MLVA types obtained from the MLVA typing of L. innocua and L. monocytogenes, respectively. MLVA clustered the L. monocytogenes isolates irrespective of sample category, serogroups, and geographical origin. Similarly, the L. innocua isolates clustered irrespective of meat category and geographical origin. MLVA was able to cluster isolates based on MLVA relatedness. The clustering of isolates from farms and retailers indicates transmission of Listeria spp. MLVA is an affordable, simple, and discriminatory method that can be used routinely to type L. monocytogenes and L. innocua isolates.