In recent years, the spread of antibiotic-resistant bacteria and efforts to preserve food microbiota have induced renewed interest in phage therapy. Phage cocktails, instead of a single phage, are commonly used as antibacterial agents since the hosts are unlikely to become resistant to several phages simultaneously. While the spectrum of activity might increase with cocktail complexity, excessive phages could produce side effects, such as the horizontal transfer of genes that augment the fitness of host strains, dysbiosis or high manufacturing costs. Therefore, cocktail formulation represents a compromise between achieving substantial reduction in the bacterial loads and restricting its complexity. Despite the abovementioned points, the observed bacterial load reduction does not increase significantly with the size of phage cocktails, indicating the requirement for a systematic approach to their design. In this work, the information provided by host range matrices was analyzed after building phage-bacteria infection networks (PBINs). To this end, we conducted a meta-analysis of 35 host range matrices, including recently published studies and new datasets comprising Escherichia coli strains isolated during ripening of artisanal raw milk cheese and virulent coliphages from ewes’ feces. The nestedness temperature, which reflects the host range hierarchy of the phages, was determined from bipartite host range matrices using heuristic (Nestedness Temperature Calculator) and genetic (BinMatNest) algorithms. The latter optimizes matrix packing, leading to lower temperatures, i.e., it simplifies the identification of the phages with the broadest host range. The structure of infection networks suggests that generalist phages (and not specialist phages) tend to succeed in infecting less susceptible bacteria. A new metric (Φ), which considers some properties of the host range matrices (fill, temperature, and number of bacteria), is proposed as an estimator of phage cocktail size. To identify the best candidates, agglomerative hierarchical clustering using Ward’s method was implemented. Finally, a cocktail was formulated for the biocontrol of cheese-isolated E. coli, reducing bacterial counts by five orders of magnitude.

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Bacteriophages are highly specific predators that drive bacterial diversity through coevolution while striking tradeoffs among preserving host populations for long-term exploitation and increasing their virulence, structural stability, or host range. Escherichia coli and other coliform bacteria present in the microbiota of milk and during early ripening of raw milk cheeses have been linked to the production of gas, manifested by the appearance of eyes, and the development of off-flavors; thus, they might cause early blowing and cheese spoilage. Here, we report the characterization of coliphages isolated from manure from small ruminant farms and E. coli strains isolated from goat and sheep raw milk cheese. Additionally, the virulence and host range of locally isolated and laboratory collection phages were determined by comparing the susceptibility of E. coli strains from different sources. In agreement with the high genetic diversity found within the species E. coli, clustering analysis of whole-cell protein revealed a total of 13 distinct profiles but none of the raw milk cheese isolates showed inhibition of growth by reference or water-isolated coliphages. Conversely, 10 newly isolated phages had a broad host range (i.e., able to lyse ≥50% of bacterial hosts tested), thus exhibiting utility for biocontrol and only one cheese-isolated E. coli strain was resistant to all the phages. Whereas there was a high positive correlation between bacterial susceptibility range and lysis intensity, the phages virulence decreased as range increased until reaching a plateau. These results suggest local gene-for-gene coevolution between hosts and phages with selective tradeoffs for both resistance and competitive ability of the bacteria and host-range extension and virulence of the phage populations. Hence, different phage cocktail formulations might be required when devising long-term and short-term biocontrol strategies.

The aim of this study was to identify the main Enterobacteriaceae species responsible for early gas blowing during curdling and the first week of ripening in raw goats' milk cheese. Two batches of raw goats' milk cheese were selected. One of them showed early blowing within the first 24 h of cheese ripening while the other showed no alteration. Although initial levels of Enterobacteriaceae were similar in defective and non-defective cheese, their dynamics (growth and disappearance rates of the species detected) were different. Klebsiella oxytoca and Enterobacter cloacae were the main species in the defective curd, whereas Buttiauxela spp. was predominant in normal curd. Hafnia alvei was the prevailing isolated species for both normal and defective cheese throughout the ripening process. The highest gas production was rendered by K. oxytoca and H. alvei, mainly isolated from curd and cheese. However, other species relevant in milk or curd, like Pantoea ssp. or Buttiauxela spp. were considered as low gas producers. The analysis of digitalized images of cheese showed that most of the cheese eyes were formed before the first week of ripening, although this process continued during maturation.According to the species found in the defective and non-defective cheese, their proportions at different ripening stages, their ability to produce gas and eye formation, K. oxytoca might be considered the most likely responsible for early blowing in raw goats' milk cheeses; while H. alvei increased the eyes number in the later stages of the ripening period.

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