Viable and Total Bacterial Populations Undergo Equipment- and Time-Dependent Shifts during Milk Processing.

We set out to identify the viable and total bacterial content in milk as it passes through a large-scale, dairy product manufacturing plant for pasteurization, concentration, separation, blending, and storage prior to cheese manufacture. A total of 142 milk samples were collected from up to 10 pieces of equipment for a period spanning 21 h on two collection dates in the spring and late summer of 2014. Bacterial composition in the milk was determined by 16S rRNA marker gene, high-throughput DNA sequencing. Milk samples from the late summer were paired such that half were treated with propidium monoazide (PMA) to enrich for viable cells prior to quantification by PCR and identification by DNA sequence analysis. Streptococcus had the highest median relative abundance across all sampling sites within the facility on both sampling dates. The proportions of Anoxybacillus, Thermus, Lactococcus, Lactobacillus, Micrococcaceae, and Pseudomonas were also elevated in some samples. Viable cells detected by PMA treatment showed that Turicibacter was enriched after high-temperature short-time pasteurization, whereas proportions of Staphylococcus were significantly reduced. Using clean-in-place (CIP) times as a reference point, Bacillus, Pseudomonas, and Anoxybacillus were found in high relative proportions in several recently cleaned silos (<19 h since CIP). At later times (>19 h after CIP), 10 of 11 silos containing elevated viable cell numbers were enriched in Acinetobacter and/or Lactococcus These results show the tremendous point-to-point and sample-dependent variations in bacterial composition in milk during processing.IMPORTANCE Milk undergoes sustained contact with the built environment during processing into finished dairy products. This contact has the potential to influence the introduction, viability, and growth of microorganisms within the milk. Currently, the population dynamics of bacteria in milk undergoing processing are not well understood. Therefore, we measured for total and viable bacterial composition and cell numbers in milk over time and at different processing points in a cheese manufacturing facility in California. Our results provide new perspectives on the dramatic variations in microbial populations in milk during processing even over short amounts of time. Although some of the changes in the milk microbiota were predictable (e.g., reduced viable cell numbers after pasteurization), other findings could not be easily foreseen based on knowledge of bacteria contained in raw milk or when the equipment was last cleaned. This information is important for predicting and controlling microbial spoilage contaminants in dairy products

Sucrose metabolism alters Lactobacillus plantarum survival and interactions with the microbiota in the digestive tract.

We investigated whether sucrose metabolism by probiotic Lactobacillus plantarum influences the intestinal survival and microbial responses to this organism when administered to mice fed a sucrose-rich, Western diet. A L. plantarum mutant unable to metabolize sucrose was constructed by deleting scrB, coding for beta-fructofuranosidase, in a rifampicin-resistant strain of L. plantarum NCIMB8826. The ScrB deficient mutant survived in 8-fold higher numbers compared to the wild-type strain when measured 24 h after administration on two consecutive days. According to 16S rRNA marker gene sequencing, proportions of Faecalibacterium and Streptococcus were elevated in mice fed the L. plantarum ΔscrB mutant. Metagenome predictions also indicated those mice contained a higher abundance of lactate dehydrogenases. This was further supported by a trend in elevated fecal lactate concentrations among mice fed the ΔscrB mutant. L. plantarum also caused other changes to the fecal metabolomes including higher concentrations of glycerol in mice fed the ΔscrB mutant and increased uracil, acetate and propionate levels among mice fed the wild-type strain. Taken together, these results suggest that sucrose metabolism alters the properties of L. plantarum in the digestive tract and that probiotics can differentially influence intestinal metabolomes via their carbohydrate consumption capabilities

Evaluating the Associations Between the Liver Frailty Index and Karnofsky Performance Status With Waitlist Mortality.

Frailty has emerged as a critical determinant of mortality in patients with cirrhosis. Currently, the United Network for Organ Sharing registry only includes the Karnofsky Performance Status (KPS) scale, which captures a single component of frailty. We determined the associations between frailty, as measured by the Liver Frailty Index (LFI), and KPS with waitlist mortality.MethodsIncluded were 247 adult patients with cirrhosis listed for liver transplantation without hepatocellular carcinoma from February 2014 to June 2019, who underwent outpatient assessments using the LFI and KPS within 30 days of listing. "Frail" was defined using the established LFI cutoff of ≥4.4. Competing risk models assessed associations between the LFI and KPS with waitlist mortality (death/delisting for sickness).ResultsAt a median 8 months follow-up, 25 (10%) patients died/were delisted. In this cohort, median Model for End-Stage Liver Disease-Sodium was 17, LFI was 3.9 (interquartile range 3.4-4.5), and KPS was 80 (interquartile range 70-90). In multivariable analysis, LFI (sub-hazard ratio 1.07, per 0.1 unit; 95% confidence interval, 1.01-1.12) was associated with waitlist mortality while KPS was not (sub-hazard ratio 1.00, per 10 units; 95% confidence interval, 0.78-1.29).ConclusionsOur data suggest that frailty, as measured by the LFI, may be more appropriate at capturing mortality risk than KPS and provide evidence in support of using the LFI more broadly in clinical transplant practice in the outpatient setting

The Core and Seasonal Microbiota of Raw Bovine Milk in Tanker Trucks and the Impact of Transfer to a Milk Processing Facility.

Currently, the bacterial composition of raw milk in tanker trucks and the outcomes of transfer and storage of that milk at commercial processing facilities are not well understood. We set out to identify the bacteria in raw milk collected for large-scale dairy product manufacturing. Raw bovine milk samples from 899 tanker trucks arriving at two dairy processors in San Joaquin Valley of California during three seasons (spring, summer, and fall) were analyzed by community 16S rRNA gene sequencing. This analysis revealed highly diverse bacterial populations, which exhibited seasonal differences. Raw milk collected in the spring contained the most diverse bacterial communities, with the highest total cell numbers and highest proportions being those of Actinobacteria Even with this complexity, a core microbiota was present, consisting of 29 taxonomic groups and high proportions of Streptococcus and Staphylococcus and unidentified members of Clostridiales Milk samples were also collected from five large-volume silos and from 13 to 25 tankers whose contents were unloaded into each of them during 2 days in the summer. Transfer of the milk to storage silos resulted in two community types. One group of silos contained a high proportion of Streptococcus spp. and was similar in that respect to the tankers that filled them. The community found in the other group of silos was distinct and dominated by Acinetobacter Overall, despite highly diverse tanker milk community structures, distinct milk bacterial communities were selected within the processing facility environment. This knowledge can inform the development of new sanitation procedures and process controls to ensure the consistent production of safe and high-quality dairy products on a global scale. Raw milk harbors diverse bacteria that are crucial determinants of the quality and safety of fluid milk and (fermented) dairy products. These bacteria enter farm milk during transport, storage, and processing. Although pathogens are destroyed by pasteurization, not all bacteria and their associated enzymes are eliminated. Our comprehensive analyses of the bacterial composition of raw milk upon arrival and shortly after storage at major dairy processors showed that the communities of milk microbiota are highly diverse. Even with these differences, there was a core microbiota that exhibited distinct seasonal trends. Remarkably, the effects of the processing facility outweighed those of the raw milk microbiome and the microbial composition changed distinctly within some but not all silos within a short time after transfer. This knowledge can be used to inform cleaning and sanitation procedures as well as to enable predictions of the microbial communities in raw milk that result in either high-quality or defective products

The Core and Seasonal Microbiota of Raw Bovine Milk in Tanker Trucks and the Impact of Transfer to a Milk Processing Facility

Currently, the bacterial composition of raw milk in tanker trucks and the outcomes of transfer and storage of that milk at commercial processing facilities are not well understood. We set out to identify the bacteria in raw milk collected for large-scale dairy product manufacturing. Raw bovine milk samples from 899 tanker trucks arriving at two dairy processors in San Joaquin Valley of California during three seasons (spring, summer, and fall) were analyzed by community 16S rRNA gene sequencing. This analysis revealed highly diverse bacterial populations, which exhibited seasonal differences. Raw milk collected in the spring contained the most diverse bacterial communities, with the highest total cell numbers and highest proportions being those of Actinobacteria. Even with this complexity, a core microbiota was present, consisting of 29 taxonomic groups and high proportions of Streptococcus and Staphylococcus and unidentified members of Clostridiales. Milk samples were also collected from five large-volume silos and from 13 to 25 tankers whose contents were unloaded into each of them during 2 days in the summer. Transfer of the milk to storage silos resulted in two community types. One group of silos contained a high proportion of Streptococcus spp. and was similar in that respect to the tankers that filled them. The community found in the other group of silos was distinct and dominated by Acinetobacter. Overall, despite highly diverse tanker milk community structures, distinct milk bacterial communities were selected within the processing facility environment. This knowledge can inform the development of new sanitation procedures and process controls to ensure the consistent production of safe and high-quality dairy products on a global scale

Evaluating the Associations Between the Liver Frailty Index and Karnofsky Performance Status With Waitlist Mortality.

Frailty has emerged as a critical determinant of mortality in patients with cirrhosis. Currently, the United Network for Organ Sharing registry only includes the Karnofsky Performance Status (KPS) scale, which captures a single component of frailty. We determined the associations between frailty, as measured by the Liver Frailty Index (LFI), and KPS with waitlist mortality.MethodsIncluded were 247 adult patients with cirrhosis listed for liver transplantation without hepatocellular carcinoma from February 2014 to June 2019, who underwent outpatient assessments using the LFI and KPS within 30 days of listing. "Frail" was defined using the established LFI cutoff of ≥4.4. Competing risk models assessed associations between the LFI and KPS with waitlist mortality (death/delisting for sickness).ResultsAt a median 8 months follow-up, 25 (10%) patients died/were delisted. In this cohort, median Model for End-Stage Liver Disease-Sodium was 17, LFI was 3.9 (interquartile range 3.4-4.5), and KPS was 80 (interquartile range 70-90). In multivariable analysis, LFI (sub-hazard ratio 1.07, per 0.1 unit; 95% confidence interval, 1.01-1.12) was associated with waitlist mortality while KPS was not (sub-hazard ratio 1.00, per 10 units; 95% confidence interval, 0.78-1.29).ConclusionsOur data suggest that frailty, as measured by the LFI, may be more appropriate at capturing mortality risk than KPS and provide evidence in support of using the LFI more broadly in clinical transplant practice in the outpatient setting

Hospitalized Women With Cirrhosis Have More Nonhepatic Comorbidities and Associated Complications Than Men

Gender differences in the natural history of chronic liver disease have been well-described. Women have lower rates of chronic liver disease and slower fibrosis progression, yet higher rates of waitlist mortality.1,2 Although previous studies have identified several clinical factors including height and creatinine that explain some of this transplant disparity, most have used data from administrative records, which are limited in their ability to identify clinically relevant differences and opportunities for intervention to reduce disparities.3-5 Additionally, most studies have focused on the period between waitlist and transplant, failing to capture gender differences in access to transplant.3,6 In the present study, we took advantage of a multicenter inpatient cohort with granular clinical data to characterize how women and men with cirrhosis differ, to stimulate future research aimed at reducing the well-established gender disparity in liver transplantation