Determination of foodborne pathogens in minced beef by real-time PCR without culture enrichment

Meat provides the necessary environment for the growth of foodborne pathogens due to its features such as being rich in protein and having sufficient water activity. Listeria monocytogenes, Salmonella enterica, and Escherichia coli O157:H7, which can be transmitted through many foods, including water, and cause serious diseases, are among the significant pathogens. In the current study. Detection of Listeria monocytogenes, Escherichia coli and Salmonella enterica in 100 minced beef samples collected from different butchers and markets situated in the central districts of Erzurum province was performed by Real-Time PCR without pre-enrichment and DNA isolation. Linear regression equations of Ct values of standard pathogenic bacteria were created. Ct values of minced beef samples obtained as a result of Real-Time PCR analysis were substituted in the equations, and the amounts of pathogenic bacteria in the samples were determined. Listeria monocytogenes, Escherichia coli, and Salmonella enterica were detected in 45, 30, and 29 of 100 minced beef samples, respectively. It is known that the Real-Time PCR method, which is used to detect pathogenic bacteria, is more specific, fast, and reliable than conventional methods. According to the results obtained, it has been clearly observed that with our new approach, pathogenic bacteria growing on foods can be detected sensitively with less cost, shorter amount of time, and minimized workload without pre-enrichment and DNA isolation.

Nitroso-hemoglobin-ginger conjugates effects on bacterial growth and color stability in a minced beef model

This study aims to enhance the color and microbiological qualities of a raw beef using natural ingredients. Nitroso-hemoglobin (NO-Hb) integrated with vitamin C (VC), calcium lactate, and ginger complexation were used as natural inhibitors against the growth of aerobic and pathogenic bacteria, namely (Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Salmonella. NO-Hb inhibited E. coli, S. aureus, and Salmonella, and enhanced the color stability more than nitrite in the minced beef model. After the multiexponential analysis of relaxation decays, the water component (T2b) was analyzed using the low-field NMR. The results indicated that, at the 7th d of cold-storage the third component (T2) was detected. Significant correlations were observed between T21 and T22 relaxation times and water-holding capacity in minced beef, implying that the LF-NMR measurements could be an efficient method for the determination and prediction of beef freshness. NO-Hb- ginger mixture, as a novel ingredient, could be used instead of nitrite in terms of meat safety.

coli O157:H7 in minced beef and river water

Considering the health risks of E. coli O157:H7 presence in food and water, an affordable and highly sensitive detection method is crucial. Herein, we report the first use of a single antibody-based fluorescent lateral flow immunoassay (FLFIA) depending on non-radiative energy transfer between graphene oxide and quantum dots for determination of E. coli O157:H7 in beef and river water. FLFIA showed a high sensitivity rate thousand-fold better than the conventional lateral flow (LF). In inoculated minced beef and river water samples, the limits of detection were 178 and 133 CFU g^-1 or mL^-1, respectively. Besides, it presented a high selectivity in the presence of other possible interfering bacteria. The single antibody approach reduced the assay cost to 60% less than the conventional LF. Alongside, the results could be read by portable LF readers or smartphones. These advantages offer FLFIA as a promising technology for pathogen detection in food and water.

Changes in the faecal bile acid profile in dogs fed dry food vs high content of beef: a pilot study

Background

Dogs are fed various diets, which also include components of animal origin. In humans, a high-fat/low-fibre diet is associated with higher faecal levels of bile acids, which can influence intestinal health. It is unknown how an animal-based diet high in fat and low in fibre influences the faecal bile acid levels and intestinal health in dogs. This study investigated the effects of high intake of minced beef on the faecal bile acid profile in healthy, adult, client-owned dogs (n = 8) in a 7-week trial. Dogs were initially adapted to the same commercial dry food. Thereafter, incremental substitution of the dry food by boiled minced beef over 3 weeks resulted in a diet in which 75% of each dog’s total energy requirement was provided as minced beef during week 5. Dogs were subsequently reintroduced to the dry food for the last 2 weeks of the study. The total taurine and glycine-conjugated bile acids, the primary bile acids chenodeoxycholic acid and cholic acid, and the secondary bile acids lithocholic acid, deoxycholic acid (DCA) and ursodeoxycholic acid (UDCA) were analysed, using liquid chromatography–tandem mass spectrometry.

Results

The faecal quantities of DCA were significantly higher in dogs fed the high minced beef diet. These levels reversed when dogs were reintroduced to the dry food diet. The faecal levels of UDCA and taurine-conjugated bile acids had also increased in response to the beef diet, but this was only significant when compared to the last dry food period.

Conclusions

These results suggest that an animal-based diet with high-fat/low-fibre content can influence the faecal bile acids levels. The consequences of this for canine colonic health will require further investigation.

Electronic supplementary material

The online version of this article (10.1186/s13028-018-0383-7) contains supplementary material, which is available to authorized users.

Assessing different processed meats for adulterants using visible-near-infrared spectroscopy

The main objective of this study was to investigate the use of spectroscopic systems in the range of 400-1000nm (visible/near-infrared or Vis-NIR) and 900-1700nm (NIR) to assess and estimate plant and animal proteins as potential adulterants in minced beef and pork. Multiple machine learning techniques were used for classification, adulterant prediction, and wavelength selection. Samples were first evaluated for the presence or absence of adulterants (6 classes), and secondly for adulterant type (6 classes) and level. Selected wavelengths models generally resulted in better classification and prediction outputs than full wavelengths. The first stage classification rates were 96% and 100% for pure/unadulterated and adulterated samples, respectively. Whereas, the second stage had classification rates of 69-100%. The optimal models for predicting adulterant levels yielded correlation coefficient, r of 0.78-0.86 and ratio of performance to deviation, RPD, of 1.19-1.98. The results from this study illustrate potential application of spectroscopic technology to rapidly and accurately detect adulterants in minced beef and pork.

Rapid detection of frozen-then-thawed minced beef using multispectral imaging and Fourier transform infrared spectroscopy

In recent years, fraud detection has become a major priority for food authorities, as fraudulent practices can have various economic and safety consequences. This work explores ways of identifying frozen-then-thawed minced beef labeled as fresh in a rapid, large-scale and cost-effective way. For this reason, freshly-ground beef was purchased from seven separate shops at different times, divided in fifteen portions and placed in Petri dishes. Multi-spectral images and FTIR spectra of the first five were immediately acquired while the remaining were frozen (-20°C) and stored for 7 and 32days (5 samples for each time interval). Samples were thawed and subsequently subjected to similar data acquisition. In total, 105 multispectral images and FTIR spectra were collected which were further analyzed using partial least-squares discriminant analysis and support vector machines. Two meat batches (30 samples) were reserved for independent validation and the remaining five batches were divided in training and test set (75 samples). Results showed 100% overall correct classification for test and external validation MSI data, while FTIR data yielded 93.3 and 96.7% overall correct classification for FTIR test set and external validation set respectively.

A diet change from dry food to beef induces reversible changes on the faecal microbiota in healthy, adult client-owned dogs

BACKGROUND

Diet has a major influence on the composition of the gut microbiota, whose importance for gut health and overall well-being is increasingly recognized. Knowledge is limited regarding health implications, including effects on the faecal microbiota, of feeding a diet with high content of red meat to dogs, despite some owners' apparent preference to do so. The aim of this study was to evaluate how a diet change from commercial dry food to one with a high content of boiled minced beef and vice versa influenced the faecal microbiota, and short chain fatty acid profile in healthy, adult, client-owned dogs.

RESULTS

The diet change influenced the faecal microbiota composition and diversity (Shannon diversity index). The most abundant OTUs in samples of dogs fed the dry food and high minced beef were affiliated with the species Faecalibacterium prausnitzii and Clostridia hiranonis respectively. The high minced beef diet apparently also influenced the short chain fatty acid profile, with increased isovaleric acid, as well as an increase in faecal pH. These effects were reversed when the commercial dry food was reintroduced in weeks 6 and 7.

CONCLUSIONS

Results of this study can aid in the understanding of how diet changes influence the faecal microbiota and metabolite content on a short-term basis. Long-term studies are required to investigate potential implications for canine gut and general health.

Arcobacter Isolation from Minced Beef Samples in Costa Rica

The presence of Arcobacter spp. in minced meat (including beef) samples has been well documented in different countries, with varying frequencies. Nevertheless, the only Latin American country reporting this bacterium in minced beef samples is Mexico, with a 28.8% frequency in 2003. Previous studies in Costa Rica have demonstrated the presence of Arcobacter species in samples taken from the poultry production chain, but still there are no studies performed in bovine meat. The aim of this study was to determine the frequency of this bacterium in 120 samples of minced beef acquired from the Central Valley region of Costa Rica and to describe the antibiotic sensitivity pattern of the isolates obtained. A total of 75 different Arcobacter strains were isolated from minced beef samples, for a final frequency of 48.3%. After species PCR identification, the strains were classified as A. butzleri (37.3%), A. cibarius (14.7%), A. thereius (12%), and Arcobacter spp. (36%). All samples were sensitive to gentamicin but were resistant to ampicillin, levofloxacin, nalidixic acid, and ciprofloxacin. The results obtained in this study show that the frequency of isolation of Arcobacter in minced beef samples is high and that there is a high resistance rate for antibiotics in common use. This suggests that Arcobacter represents a health risk for Costa Rica and that control measures should be developed to decrease its potential impact.

Quantification of rubidium as a trace element in beef using laser induced breakdown spectroscopy

This study evaluates the potential of laser induced breakdown spectroscopy (LIBS) coupled with chemometrics to develop a quantification model for rubidium (Rb) in minced beef. A LIBSCAN 150 system was used to collect LIBS spectra of minced beef samples. Beef liver was used to spike the Rb levels in minced beef. All samples were dried, powdered and pelleted using a hydraulic press. Measurements were conducted by scanning 100 different locations with an automated XYZ sample chamber. Partial least squares regression (PLSR) was used to develop the calibration model, yielding a calibration coefficient of determination (R_c²) of 0.99 and a root mean square error of calibration (RMSEC) of 0.05ppm. The model also showed good results with leave-one-out cross validation, yielding a cross-validation coefficient of determination (R_cv²) of 0.90 and a root mean square error of cross-validation (RMSECV) of 0.22ppm. The current study shows the potential of LIBS as a rapid analysis tool for the meat processing industry.

Prevalence and antimicrobial susceptibility of Escherichia coli O157 in beef at butcher shops and restaurants in central Ethiopia

BACKGROUND

Ethiopia bears the largest burden of foodborne diseases in Africa, and diarrheal diseases are the second leading causes of premature deaths. Enterohemorrhagic Escherichia coli O157 causes an asymptomatic infection to severe diarrhea and/or hemolytic-uremic syndrome in humans.

METHODS

A total of 440 beef carcass and in-contact surface swabs from 55 butcher shops and 85 minced beef samples from 40 restaurants in central Ethiopia were collected and examined for the presence of E. coli O157. Standard microbiological methods were used to isolate and identify E. coli O157 and to characterize the antimicrobial resistance of the isolates.

RESULTS

E. coli O157 was detected in 4.5% carcass swabs (n = 5) and 3.6% cutting board swabs (n = 4) samples from butcher shops. E. coli O157 was not detected in any of the minced beef samples obtained from restaurants. All isolates (n = 9) were 100% susceptible to five drugs, but five isolates were resistant to amoxicillin, two isolates to streptomycin and three isolates to chloramphenicol. One isolate was resistant to two drugs and another to three drugs.

CONCLUSIONS

The present study shows a low prevalence of E. coli O157 in beef sold at butcher shops. Nevertheless, given the low infective dose of this pathogen and the deep-rooted tradition of consuming raw or undercooked beef, the current prevalence should not be considered lightly from a public health perspective.

Effect of PLA films containing propolis ethanolic extract, cellulose nanoparticle and Ziziphora clinopodioides essential oil on chemical, microbial and sensory properties of minced beef

This study was conducted to examine the effects of polylactic acid (PLA) film containing propolis ethanolic extract (PE), cellulose nanoparticle (CN) and Ziziphora clinopodioides essential oil (ZEO) on chemical, microbial and sensory properties of minced beef during storage at refrigerated temperature for 11days. The initial total volatile base nitrogen (TVB-N) was 8.2mg/100g and after 7days reached to 29.1mg/100g in control, while it was lower than 25mg/100g for treated samples. At the end of storage time in control samples peroxide value (PV) reached to 2.01meqperoxide/1000g lipid, while the values for the treated samples remained lower than 2meqperoxide/1000g lipid. Final microbial population decreased approximately 1-3logCFU/g in treated samples compared to control (P<0.05). Films containing 2% ZEO alone and in combination with different concentrations of PE and CN extended the shelf life of minced beef during storage in refrigerated condition for at least 11days without any unfavorable organoleptic properties.

Identification of meat-associated pathogens via Raman microspectroscopy

The development of fast and reliable sensing techniques to detect food-borne microorganisms is a permanent concern in food industry and health care. For this reason, Raman microspectroscopy was applied to rapidly detect pathogens in meat, which could be a promising supplement to currently established methods. In this context, a spectral database of 19 species of the most important harmful and non-pathogenic bacteria associated with meat and poultry was established. To create a meat-like environment the microbial species were prepared on three different agar types. The whole amount of Raman data was taken as a basis to build up a three level classification model by means of support vector machines. Subsequent to a first classifier that differentiates between Raman spectra of Gram-positive and Gram-negative bacteria, two decision knots regarding bacterial genus and species follow. The different steps of the classification model achieved accuracies in the range of 90.6%-99.5%. This database was then challenged with independently prepared test samples. By doing so, beef and poultry samples were spiked with different pathogens associated with food-borne diseases and then identified. The test samples were correctly assigned to their genus and for the most part down to the species-level i.e. a differentiation from closely-related non-pathogenic members was achieved.